MOTIVATION IN SUBSTANCE ABUSE TREATMENT: ASSESSING THE
RELATIONSHIP BETWEEN THE TRANSTHEORETICAL MODEL OF
CHANGE, SELF-DETERMINATION THEORY, AND THEIR IMPACT UPON
TREATMENT OUTCOMES
DISSERTATION
Presented in Partial Fulfillment of the Requirements for
the Degree Doctor Of Philosophy in the Graduate
School of The Ohio State University
By
Kerry S. Kennedy, M.S. W.
The Ohio State University
2005
Dissertation Committee:
Dr. Thomas Gregoire, Adviser
Dr. MoYee Lee
Dr. Scottye Cash
Approved by
______________________
Adviser
Graduate program in Social Work
Copyright by
Kerry Sue Kennedy
2005
ABSTRACT
As the field of chemical dependency treatment has changed and evolved over the
past decade, so has the perception of the importance of the motivation of persons entering
into treatment. Two theories focus on motivation in substance abuse: Self-determination
theory and the Transtheoretical Model of Change. Self-determination theory provides a
theoretical basis for the source of motivation, and outlines a continuum of motivation
from amotivation to external motivation to internal motivation. The Transtheoretical
Model of Change describes stages, processes, and levels of change.
The purpose of this research was to explore the relationship between Selfdetermination theory and the Transtheoretical model of change. Specifically, Selfdetermination theory was operationalized as internal or external source of motivation, and
the Transtheoretical model was operationalized as the stages of change:
precontemplation, contemplation, and action. The second purpose of this research was to
examine the relationship between source of motivation and chemical dependency
treatment outcome, measured both as use after intake and treatment completion.
Data used for this study were from the Drug Abuse Treatment Outcome Study
(DATOS). A multinomial logistic regression analysis indicated that there was a
significant relationship between source of motivation and the stage of change at intake (n
ii
= 8719). People entering treatment with high levels of internal motivation were more
likely to be in the action stage than people with high levels of external motivation.
A logistic regression analysis from the 12-month follow-up (n = 731) indicated no
significant relationship between source of motivation and treatment completion or use
after admission to substance abuse treatment. No difference existed between people with
high levels of internal or high levels of external motivation and people with low levels of
internal or low levels of external motivation. This study supports a definition of
motivation that is dynamic and changing.
iii
Dedicated to Mom and Dad
iv
ACKNOWLEDGMENTS
I would like to thank my advisor, Tom Gregoire, for the support and interest in
my research which made this dissertation possible.
I would also like to thank my candidacy and dissertation committees, MoYee Lee,
Scottye Cash, and Tom Pepper, for helping me through this process.
To Ken Yeager - thanks for believing in me and making me complete my
application to the PhD program.
There are so many people that have been instrumental in seeing me through this
process. I am grateful to my family and friends who have supported and assisted me
through my education.
v
VITA
1997………………………………………B.A. Sociology, Mount Union College
1999………………………………………...M.S.W. The Ohio State University
2002- 2004…………………………………Graduate Teaching and Research
Associate, The Ohio State University
FIELDS OF STUDY
Major Field: Social Work
vi
TABLE OF CONTENTS
Page
Abstract……………...………………………………………………………..……….…..ii
Dedication…………………………………………………………………………….…..iv
Acknowledgements…………………………………………………..…………..……. …v
Vita………………………………………………………………...……….………...…...vi
List of Tables…………………………………………………………………..……..…..ix
List of Figures………………………………………………………….…………….......xii
Chapters:
1.
2.
Introduction……………………………………..………………...…….................1
Literature Review……………………………..……………………………..…….5
Recent thought on the concept of motivation……..………………………..……5
Motivation in substance abuse………………………..…………………..…… 10
Evolution of motivation in the field of substance abuse……...……...…..12
Readiness for treatment……………………………………….…….……13
Internal and external motivation in substance abuse………….…….…...17
Self-Determination Theory………………..……………………………....…..…21
Measures……….……………………………………………..……....….26
Transtheoretical Model of Change……………..……………………….……..…28
Stages of change………….…………………………………...........……29
Processes of change………….…….…………………...………………..33
Levels of change………….…………………………………...........……37
Other factors………….…………………………………………………..37
Critique of the model…….……………………………………..……......41
Measures……………….………………………………………….......…42
Treatment Outcomes…………………..………………………………………....45
Purpose and Rationale…………………..………………………………………..47
Relationship between Self-determination theory and Transtheoretical
Model of change…..…………………….………………………….……47
Hypothesis 1…………….…………………..………….….……………..48
Hypothesis 2…………….…………………..…………….….…………..49
vii
3.
Methods and Findings………………………………..………………..…………51
Data analysis……………………………………..………..………………..…....51
Drug Abuse Treatment Outcome Study...…………..……..………...……..…….52
Protection of human subjects………………………..……..………………..…...56
Characteristics of the sample……………………………....……………….....…56
Demographics………………………………………………………………..…..56
Drug and alcohol information……………………………....….…………..…….58
Severity indicators………………………………………..…..…………….........60
Independent variable: Self-determination theory……….……...………..………61
Dependent variable: Stage of change…………………………..…..……..……..62
Stage of change and source of motivation……………………...….……..…...…63
Bivariate analysis: Source of Motivation……………...………..…..……..…….66
Bivariate analysis: Stage of change…...……………………..…………..…..….67
Multinomial Logistic Regression…………………………………...….…..…….69
Precontemplation versus action………………………...……………..…70
Contemplation versus action……………………………..……..…..……71
Data analysis: Hypothesis 2…………………………………………..….......….73
Characteristics of the sample……………………………………….....……..…..77
Alcohol and drug indicators……………………………………….….……….…78
Severity indicators…………………………………………………..…….......…81
Dependent variable: Treatment outcomes…………………………..…..…..…..82
Independent variable: Source of motivation………………………..…...….…...82
Severity: Major life areas…………………………………………...……...…....83
Bivariate analysis: Treatment completion……….………...……………..…..…84
Bivariate analysis: Source of motivation………….……...……..………………86
Logistic Regression………………………………………………..……………..87
Hypothesis 2b……………………………………………………..……….......…90
Bivariate analysis: Use……………………………..…………..…………......…90
4.
Discussion…………………………………………………………………....….94
Relationship between stage of change and source of motivation……..…………94
Source of motivation and treatment outcomes……………...…………..………..97
Source of motivation and substance use after intake……..………………….......98
Limitations of the study………………………..……………………..……..…...99
Implications……………………...………….………………………..………....101
Future Research…………………………..……………………………..……...103
References………...………………………………………………………………....….105
Appendix A: Coding responses for source of motivation………………………......….116
Appendix B: Distribution of Key Indicators across Main Independent and Dependent
Variables………………………………………………………………....119
viii
LIST OF TABLES
Table
2.1
Transtheoretical Model Processes of Change……………………
Page
34
3.1
Rationale for Variable Included in the Analysis…………………
53
3.2
Frequencies and Percentages of Demographic Information……..
57
3.3
Frequencies and Percentages of Alcohol and Drug Indicators…..
59
3.4
Frequencies and Percentages of Severity Indicators……………..
64
3.5
Statement, Responses and Categorization for Stage of Change…
60
3.6
Frequencies and Percentages for Stage of Change and Source of
Motivation………………………………………………………..
65
3.7
Relationship between Source of Motivation and Key Indicators..
67
3.8
Relationship between Stage of Change and Key Indicators……..
68
3.9
Model Summary for Multinomial Logistic Regression………….
69
3.10
Likelihood Ratio Test for Multinomial Logistic Regression……
70
3.11
Unordered Multinomial Logistic Regression for Multiple
72
Outcomes…………………………………………………………
3.12
Percentage Distribution of Demographic Indicators of
74
Respondents at Intake and at 12-month Follow-up………………
Percentage Distribution of Alcohol and Drug Indicators of
76
Respondents at Intake and at 12-month Follow-up………………
Percentage Distribution of Severity Indicators of Respondents at 77
Intake and at 12-month Follow-up……………………………….
3.13
3.14
ix
3.15
Frequencies and Percentages of Demographics for Hypothesis
2………..........................................................................................
79
3.16
Frequencies and Percentages of Alcohol and Drug Indicators for
Hypothesis 2……………………………………………………
80
3.17
Frequencies and Percentages of Severity Indicators for
Hypothesis 2……………………………………………………..
81
3.18
Frequencies and Percentages of Treatment Outcomes and Source 83
of Motivation ………... ………………………………………….
3.19
Frequencies and Percentages of Severity in Life Areas……….…
3.20
Relationship between Treatment Outcome and Key Indicators…. 85
3.21
Relationship between Source of Motivation and Key Indicators... 86
3.22
Model Fitting Information for Logistic Regression…………
88
3.23
Logistic Regression Analysis: Treatment Outcomes Regressed
on Key Indicators………………………………………………...
89
3.24
3.25
Frequency and Percentage of Use and Source of Motivation……
Relationship between for Use and Severity Indicators…………..
90
91
3.26
Model Fitting Information for Logistic Regression……………...
92
3.27
B.1
Logistic Regression Analysis: Use Regressed on Key Indicators.
Percentage Distribution of Demographic Indicators across Stage
of Change………………………………………………………...
Percentage Distribution of Alcohol and Drug Indicators across
Stage of Change………………………………………………….
Percentage Distribution of Severity Indicators across Stage of
Change……………………………………………………………
Percentage Distribution of Demographic Indicators across
Motivation Source………………………………………………..
Percentage Distribution of Alcohol and Drug Indicators across
Motivation Source………………………………………………..
Percentage Distribution of Severity Indicators across Motivation
Source………………………………………………..
Percentage Distribution of Demographic Indicators across
Treatment Completion……………………………………………
Percentage Distribution of Alcohol and Drug Indicators across
Treatment Completion……………………………………………
93
120
B.2
B.3
B.4
B.5
B.6
B.7
B.8
x
84
121
122
123
124
125
126
127
B.9
B.10
B.11
B.12
B.13
B.14
B.15
Percentage Distribution of Severity Indicators across Treatment
Completion………………………………………………………
Percentage Distribution of Demographic Indicators across Use…
Percentage Distribution of Alcohol and Drug Indicators across
Use………………………………………………………………..
Percentage Distribution of Severity Indicators across Use………
Percentage Distribution of Demographic Indicators across
Motivation Source………………………………………………..
Percentage Distribution of Alcohol and Drug Indicators across
Motivation Source………………………………………………..
Percentage Distribution of Severity Indicators across Motivation
Source…………………………………………………………….
xi
128
129
130
131
132
133
134
LIST OF FIGURES
Figure
2.1
Self-Determination Theory………………………………………….
Page
23
2.2
Processes of Change in Relation to Stages of Change………………
36
xii
CHAPTER 1
INTRODUCTION
Chemical dependency treatment has evolved and changed over the past decade,
and the concept of motivation in treatment has been considered in many of the models
utilized in treatment. Miller and Hester (2003) describe thirteen different conceptual
models of treatment philosophies, and The Center for Substance Abuse Treatment (1999)
describes six over-arching treatment philosophies that have guided treatment from the
1960’s. Different models of chemical dependency treatment include: a moral model, in
which drug and alcohol problems are considered a “willful violation of societal rules and
norms” (Miller and Hester, 2003, p. 2); a spiritual model of which Alcoholics
Anonymous is a part; a disease model that focuses on biological determinants of
alcoholisms; and a public health model which considers not only the individual, but the
environment as well.
As chemical dependency treatment has changed, so has the perception of the
importance of motivation in treating substance abusers. In large part, this change in the
perception of motivation is a direct result of different theoretical underpinnings of
chemical dependency treatment. Motivation in substance abuse treatment was once
viewed as the sole responsibility of the individual. If an individual did not comply with
1
treatment, they were considered to be “unmotivated” (Clancy, 1961). More recent views
of motivation in treatment involve the clinician as having an impact on motivation: the
interaction of the clinician and the client “has a crucial impact on how they respond and
whether treatment is successful” (Center for Substance Abuse Treatment, 1999, p.3).
Two theories focus specifically on motivation in substance abuse: the
Transtheoretical Model of Change and Self-determination theory. The Transtheoretical
Model of Change was derived from a compilation of eighteen different psychological and
behavioral theories (Prochaska, 1979) and provides a framework for intentional behavior
change. The Transtheoretical Model is comprised of stages, processes, and levels of
change to address behavior change. The stages of change are a progression of movement
towards and through change, and each stage is delineated with a time frame and tasks
associated with movement through the stage. The five stages of change are:
precontemplation, contemplation, preparation, action, and maintenance (Prochaska,
1979). The processes of change are the specific ways that a person moves through each
stage, and each process consists of interventions appropriate to assist a person to move to
the next stage of change. The levels of change attempt to address not only the problem
with a particular behavior, but also other areas that may contribute to the problem being
addressed, from micro, interpersonal dimensions to macro, societal dimensions.
“What we are attempting to develop…is a framework applicable to all clinical
problems of psychological origin” (Prochaska and DiClemente, 1986, p. 173). While the
TTM began with research based in people who change naturally (Prochaska and
DiClemente, 1983; Mcconnaughy et al, 1983), the evolution of this model includes
addictive behaviors primarily but does not rule out the application to other behaviors.
2
Smoking cessation has historically been the main problem area researched (Prochaska
and DiClemente, 1983; Prochaska, et al, 1988; DiClemente et al, 1985; DiClemente et al,
1991). However, the TTM has been applied to various behaviors such as alcoholism
(DiClemente and Hughes, 1990), phobias (Prochaska, 1991), cocaine use, weight control,
diet, adolescent delinquent behaviors, safer sex, condom use, sunscreen use, radon gas
exposure, exercise, mammography screening and physicians’ preventative practices with
smokers (Prochaska et al, 1994; Prochaska and Velicer, 1997).
Self-determination theory (Deci and Ryan, 1985) outlines a framework for
understanding internal and external sources of motivation and the impact of the type of
motivation on treatment outcomes. The organismic integration theory (OIT), a specific
aspect of Self-determination theory, defines motivation as six categories from
amotivation to internal motivation, as an extension of internal and external motivation.
The categories allow for a combination of internal and external motivation rather than
having purely internal or external motivation.
Self-determination theory has been applied to many areas, such as medication
adherence, weight loss, and test-taking behavior in school-aged children. However, the
application of this theory specifically to substance abuse has been limited (Ryan, Plant,
and O’Malley, 1995; Zeldman, Ryan and Fiscella, 2004).
In determining the impact of motivational theories in substance abuse, it becomes
necessary to define “successful treatment”. Treatment outcomes in the field of substance
abuse have changed from a dichotomous indicator (completed treatment or not completed
treatment, used substances or abstinent) to a more comprehensive view of what
“successful” treatment is. McLellan et al (1997) describe the need for treatment
3
outcomes to be multi-dimensional to reflect the multi-dimensional nature of addiction.
Moos, Finney, and Cronkite (1990) recommend using the criteria for substance
dependence from the DSM IV when considering outcomes, reflecting the need for not
only a biological indicator, but social and psychological indicators as well.
The purpose of this research is first to explore two different theories of
motivation, the Transtheoretical Model of Change and Self-determination Theory and to
determine their relationship to each other. The second purpose of this research is to
examine the relationship between Self-determination theory and chemical dependency
treatment outcomes.
The results of this study might provide information to develop a more
comprehensive measure of motivation. Further, it may be used as a springboard to create
instruments that utilize components of Self-determination theory and the Transtheoretical
Model of Change for a more in-depth view of motivation throughout treatment.
4
CHAPTER 2
REVIEW OF THE LITERATURE
Motivation is an important factor in the substance abuse field. The literature
review that follows will examine motivation, first as an overview of recent thought about
motivation followed by motivation specifically in substance abuse. Self-determination
theory will then be described, followed by the Transtheoretical Model of change. Finally,
the importance of having multi-dimensional treatment outcomes in chemical dependency
will be presented.
Recent thought on the concept of motivation
Motivation has frequently been considered to be relevant to counseling and
psychotherapy, and a number of models have been used to explain this concept. The
field of psychology describes motivation through drives, decision making, and emotions
(Saunders et al, 1996). Drives are biological in nature and are determinants of activity.
Drive Reduction Theory (Hull, 1943) describes the need to reduce internal tension which
in turns motivates a person to take action. Using emotions as part of a definition of
motivation is using a reward / punishment model: the emotional foundation of motivation
comes from avoiding negative or unpleasant feelings and increasing positive or pleasant
feelings (Beck, 2004). Baker et al (1986) view motivation as related to urges through
psychobiological models. Appelbaum (1971) addressed motivation to change as an
5
indicator of how well psychoanalytic treatment will work. Often viewed as an
intervening variable linking a stimulus to a response (Petri, 1996), motivation is a factor
which guides behavior as a process that makes striving for goals possible (Beck, 2004).
Motivation is related to an individual’s tendency to engage in activities in which
the outcome is expected to be positive and avoid behaviors that may lead to unpleasant
outcomes (Beck, 2004). Further, motivated behavior is considered goal-directed
behavior. Uses of motivation include the ability to explain if an individual activates
behavior change, the persistence of an individual to change a behavior, and the direction
of the behavior (Petri, 1996). The level of motivation often is considered an important
predictor of outcomes: that is, the higher the motivation, the greater the likelihood that
change will occur.
Saunders et al (1996) note that an agreed upon definition of motivation is
“elusive” (p. 242). Motivation is considered to be causes, reasons, and intentions that an
individual engage in certain behaviors (DiClemente, 1999). The Center for Substance
Abuse Treatment (1999) defines motivation as “related to the probability that a person
will enter into, continue, and adhere to a specific change strategy” (p. XV). The Center
for Substance Abuse Treatment (1999) also makes the following assumptions about the
nature of motivation: it is a dynamic, multidimensional, interactive, modifiable state
which is the key to change. This definition of motivation takes into consideration not
only what is going on within the individual but also considers the environment and what
is happening to the individual. Because of its comprehensive approach to motivation, it
is the Center for Substance Abuse Treatment’s (1999) definition that will be utilized for
this paper.
6
While a definition of motivation may be difficult to pinpoint, components of the
concept of motivation are more readily available. For example, Miller and Rollnick
(2002) and Viets, Walker, and Miller (2002) describe three components of motivation as
readiness, willingness, and ability. Readiness is the importance of the action, the level of
priority of the behavior change in context of other concerns and demands (Viets et al,
2002). Willingness is both the importance of the change and the personal volition
involved with making the change. Willingness is not only deciding that the change is
important enough to undertake, but also that there is an intent to make the change (Viets
et al, 2002). Ability is confidence that one can perform that task and carry out the
behavior change. Self efficacy, the belief that one can be successful with the specific
task, is a component of ability. (Miller and Rollnick, 2000).
As the use of motivation as an integral component for individuals engaging in
behavior change evolved, constructs important in the field of motivation developed.
Locus of control is a broad construct that developed out of social learning theory (Rotter,
1975) and is primarily focused on expectancies following reinforcement. Expectancies
are determined both through specific situations, but are also based on past experiences
that an individual perceives as similar (Rotter, 1975). Rotter (1966) described locus of
control:
When a reinforcement is perceived by the subject as following
some action of his own but not being entirely contingent upon his action,
then, in our culture, it is typically perceived as the result of luck, chance,
fate, as under the control of powerful others, or as unpredictable because
of the great complexity of the forces surrounding him. When the event is
7
interpreted in this way by an individual, we have labeled this a belief in
external control. If the person perceives that the event is contingent upon
his own behavior or his own relatively permanent characteristics, we have
termed this a belief in internal control (p.1).
Internal and external motivation are similar to Rotter’s locus of control, but
differences exist between the two concepts. While a determination of locus of control
seems to be appropriately determined after the fact (this happened to me because of luck,
or this happened to me because of who I am), motivation that is internal or external
occurs simultaneously with becoming aware of a problem (my boss, an external source of
motivation, says that I need help). Internal motivation is analogous to a need, as a need
comes from within an individual and often activates behavior to alleviate the need (Petri,
1996). McMurran (2002) describes internal motivation as derived from values and
beliefs: internally motivated behavior can result from wanting to achieve a valued goal
or avoiding aversive feelings like guilt and shame. Internal motivation is not dependent
on external controls, and internal motivation is viewed as autonomous and selfdetermined (Viets et al, 2002).
External motivation is motivation derived from the social environment (Petri,
1996) and may further be associated with material and/or social rewards (McMurran,
2002). External motivation can be viewed as beyond the control of an individual (Rotter,
1990). Changes in the external environment may also activate external motivation (Petri,
1996). Viets, Walker, and Miller (2002) further describe external motivation as being
“short-lived”: if the external source is removed, the change is often not retained.
8
DeCharms (1976) uses the analogy of “pawns” and “origins” to describe the
personal causation of motivation. “Pawns” are people that are moved by others,
reflecting an external locus of causality. “Origins” reflect a person’s feeling of being in
control of his/her behavior, an internal locus of causality. Further, deCharms (1976)
describes the importance of the specific situation involved, as “situations may induce
more origin or more pawn feelings (deCharms, 1976, p. 5).
Rather than viewing internal and external motivation as two distinctly opposite
constructs, Deci and Ryan (1985) describe motivation as occurring along a continuum of
six categories defined from amotivation to extrinsic motivation to internal motivation
(Ryan and Deci, 2000). Extrinsic motivation contains four separate categories that take
into consideration “the degree to which motivation emanates from the self” (Ryan and
Deci, 2000, p. 72).
While internal motivation has been described as a more reliable predictor of
behavior change (McMurran, 2002) and is associated with greater long-term change
(Deci and Ryan, 1985), a relationship between internal and external motivation exists.
External motivation is often viewed as an opportunity for enhancing internal motivation.
For example, treatment can be suggested for a person from an outside source, and while
in treatment the person may realize that changing would be personally beneficial to
him/her, thus increasing internal motivation to change. Typically, internal motivation
does not lead to external motivation but external motivation can potentially lead to
internal motivation. Further, external motivation can be detrimental to sustained
performance without an increase in internal motivation (Deci and Ryan, 1985).
9
Curry et al (1991) evaluated intrinsic and extrinsic interventions on a group of
smokers (n = 1217). The intrinsic intervention was personalized feedback focused on
enhancing the participant’s self confidence and motivation. Participants could get up to
three sets of feedback. The extrinsic motivation was a gift and an entry into a prize
drawing for turning in their progress reports. While participants in the externally
reinforced group were more likely to turn in their materials, persons in the internally
reinforced group were more likely to have stopped smoking at both the 3 and 12 month
follow-ups.
Motivation in substance abuse
In the field of substance abuse, motivation has been identified as an important
characteristic, specifically with regards to treatment and outcomes. Sterne and Pittman
(1965) describe low motivation as an obstruction for alcoholics in treatment. Miller
(1985) parallels motivation with treatment outcomes: low motivation is equated with
relapse. According to DiClemente and Bellino (1999), motivation is a driving force
behind a patient seeking, completing, and complying with treatment. The Center for
Substance Abuse Treatment (1999) states that motivation is an important predictor of the
change of use in a substance abuser.
Motivation in the field of substance abuse has been affected by differing
prevailing models of treatment. The moral model of chemical dependency treatment is
characterized by “willful violations of societal rules and norms” (Miller and Hester, 2003,
p. 2). The view of motivation from a moral perspective is that a person is personally
responsible, and motivation necessary to change comes from inside the person. The
spiritual model of alcoholism and addiction became popular in the 1930’s with the
10
creation of Alcoholics Anonymous and was centered around the concepts of
powerlessness and turning one’s life over to a higher power. Motivation in the spiritual
model comes from the willingness (internal) to change and the need for a higher power
(external locus of control).
Fagan (1999) describes a “traditional” view of motivation in substance abuse:
“individuals who refuse, do not comply with, or fail in treatment are often said not to
have been motivated enough for treatment to be effective” (p. 254). The traditional view
of motivation is reflected in research predominately from the 1960’s and 1970’s which
describes motivation as the sole responsibility of the client’s (Clancy, 1960; Sterne and
Pittman, 1967; Holt, 1965; Arahan et al, 1965). This time frame (60’s and 70’s) and view
of motivation (as people who fail in treatment are not sufficiently motivated) corresponds
with predominating views of chemical dependency and treatment at that time. During
this time the disease model of treatment was the major paradigm in treatment, and lack of
motivation was equated with having high levels defense mechanisms that may be barriers
to treatment, such as denial (Moore and Murphy, 1960; DiCicco, 1978; Miller and
Hester, 2003). As substance abuse treatment has changed and evolved, so has the view of
motivation.
Current research identifies the importance of motivation in chemical dependency
treatment, and treatment has been designed specifically using motivational interventions
targeted at enhancing motivation. For example, the Motivational Enhancement Therapy
(MET) approach is based in both cognitive and social psychology, specifically using
principles of motivational psychology (Fuller and Hiller-Sturmhofel, 1999). As part of
the philosophy, denial and resistance are viewed not as inherent traits of a substance
11
abuser, but as induced by the conditions of the environment. For the substance abuser
having a person in the environment that enables the use to continue is an example of how
denial can be a condition of the environment. Further, if others around the substance
abuser continually deny that there is a problem, resistance to treatment can also be
provoked through the environment. The focus of therapy is on enhancing intrinsic
motivation as well as assisting a client to increase levels of motivation for change
(Moyer, 2003; Miller, 2002). Miller, Wilbourne, and Hettema (2003) describe
interventions using motivation as being highly effective.
Project MATCH (1997) has been identified as a landmark study addressing the
issues of matching clients to treatment. One of the three treatment modalities used was
MET. According to this study, readiness for treatment was the most significant predictor
of long term modification of the consumption of alcohol for outpatients. Readiness was a
significant predictor of abstinence and the number of drinks consumed per drinking day.
Evolution of motivation in substance abuse
In the field of substance abuse the concept of motivation has changed from being
embedded in defense mechanisms (Clancy, 1961) to being a stable trait (Miller, 1985) to
being a dynamic and changeable state (Center for Substance Abuse Treatment, 1999).
The trait model regards motivation as a characteristic that someone has at birth
(McMurran, 2002) and is static and unable to be changed. The trait model also implies
that there is something inherently wrong in a person, an inability to change. Miller
(1985) describes difficulty with motivation being described as a trait in that a trait implies
that that the characteristic is beyond the control of the individual.
12
Motivation as a state views the concept as more of a “rational response to
circumstances” (McMurran, 2002, p. 7) rather than an inherent trait. Also using a statemodel, motivation is seen as modifiable and interpersonal. Sterne and Pittman (1965)
state that motivation as dynamic is variable and “dependent upon a complex interaction
of internal and external influences converging upon the alcoholic at a point in time” (p.
47).
Sterne and Pittman (1965) found in their study of professionals working with
clients with alcoholism (n = 177) a division between a static trait model and a dynamic
state model of motivation. 75% of the respondents were “to some extent guided by static
orientations” (p. 48), and 25% were viewing motivation as a dynamic process. The
importance of motivation was also explored: three-quarters of the respondents indicated
“some commitment to the importance of motivation to recovery from alcoholism” (p. 44).
Over half of the respondents indicated that motivation is “absolutely essential” for clients
to want to be treated.
Readiness for treatment
Further expanding on the changing conceptualization of motivation in the field of
substance abuse, treatment readiness is a construct that has emerged out of research on
motivation to change. Joe et al (1999) consider treatment readiness a measure of the
degree of commitment to a behavior change. Broome et al (1999) defined treatment
readiness as the motivation to actively participate in order to make changes in behavior.
Broome et al (1999) go on to describe treatment readiness as an aspect of intrinsic
motivation that is “subject to intervention and enhancement” (p.229).
13
One measure of treatment readiness is the CMRS (Circumstances, Motivation,
Readiness, and Suitability) scale (DeLeon, 1994) which embodies components necessary
for sustained behavior change. Each of the four components can be conceptualized as
differing types of motivation: Circumstances refers to external reasons for seeking
treatment (legal, employer, etc.); Motivation is reflective of the internal reasons for
change; Readiness is the perceived need for treatment; and Suitability is referring to the
treatment modality as appropriate to the individual. The CMRS was originally derived to
predict early dropouts from therapeutic communities. When testing the CMRS on a
sample of 2,372 consecutive admissions to a therapeutic community treatment center in
New York City, DeLeon (1994) found that the total score of the scale was the best
predictor of 30-day retention in treatment, but that the readiness component was
consistently the better predictor among the four components.
Joe et al (1999) and Simpson and Joe (1993) describe three components of
motivational phases that use aspects of the CMRS scale as well as other motivational
models (such as the Transtheoretical Model of Change which will be described in detail
later): problem recognition, desire for help, and readiness for treatment. Problem
recognition is defined as the level of denial or acknowledgement surrounding problems
related to use. The desire for help is awareness of the need for getting help and the
interest in receiving help. Readiness for treatment is defined as the degree of
commitment to alter the behavior (Joe et al, 1999).
Specifically with regards to treatment readiness and substance abuse, Joe,
Simpson, and Broome (1998) found that motivation at intake is a predictor of
engagement and retention in long-term residential, outpatient methadone treatment, and
14
outpatient drug free treatment. Their study used the Drug Abuse Treatment Outcome data
and included 2,265 clients in long-term residential treatment (LTR), 1791 clients in
outpatient drug free (ODF), and 981 clients in methadone maintenance (MM). The
dependent variable was retention in treatment, measured with a benchmark of 90 days for
LTR and ODF and 360 days for MM. Treatment readiness was found to be a significant
predictor of increased odds of staying in treatment at least 90 days in LTR: for every one
point increase on the treatment readiness scale, the odds of staying at least 90 days
doubled. For participants in the MM program, treatment readiness was also found to be a
significant predictor of retention in treatment. For participants in ODF, treatment
readiness was not a significant predictor of 90 day retention, but problem recognition was
a significant predictor.
Further examining readiness for treatment, Broome, Simpson, and Joe (1999)
found in their study of 1141 long-term residential clients, 718 outpatient drug-free clients,
and 689 methadone maintenance clients who participated in at least three months of
treatment that treatment readiness is the “most notable and consistent predictor among
background measures” (p. 131) of both confidence and commitment. Background
measures included gender, ethnicity, use of cocaine weekly, use of heroin weekly, age
and treatment readiness.
Joe, Simpson, and Broome (1999) identified treatment readiness at intake as a
determinant of the level of therapeutic involvement that a patient would have in
treatment. Therapeutic involvement was defined as the rapport that the client had with the
counselor and the client’s confidence in treatment. This study used the Drug Abuse
Treatment Outcome data and participants were from long term residential programs (n =
15
1362), outpatient drug free programs (n=866) and methadone maintenance programs (n =
981). When looking at the effects of motivation on treatment process, results showed that
therapeutic involvement was more strongly predicted than session attributes (frequency
of attendance, number of health topics discussed, and number of other topics discussed)
as a function of treatment readiness. Treatment readiness was a significant predictor of
remaining in treatment in both long term residential treatment and methadone
maintenance.
Other studies have found no relationship between motivation and treatment
outcomes. Holt (1967) describes motivation as having “little practical value” (p. 1388) in
treatment due to the lack of a consistent definition of motivation and the lack of
consistent measures for the concept. DiCicco et al (1978) describe motivation as an
“irrelevant concept” (p. 599) and instead notes that “precipitation of crisis” (p. 599) is
more appropriate in bringing alcoholics into treatment.
Arahan, Ogilvie, and Partington (1965) measured motivation with four behavior
indicators: willingness to accept dilsulfiram therapy, being sober or intoxicated at time of
initial contact with the treatment center, the method of referral (self or other), and the
number and regularity of contacts at the clinic. They found in their study of 116 patients
in substance abuse treatment that motivation had no relationship on treatment outcomes.
Rapp et al (2003) measured motivation using scales of problem recognition,
desire for help, and treatment readiness in a sample of 263 clients from both a short-term
detoxification center and an outpatient substance abuse program. Measures also included
severity and referral source (self-referred or being involved with the legal system). At
intake, results found that high motivation was significantly related to high severity scores
16
measured with the Addiction Severity Index, and that self-referral was positively related
to motivation and criminal justice involvement was negatively related to motivation.
However, no relationship was found between motivation at intake and follow-up severity
scores, suggesting that motivation does not accurately predict treatment outcomes
measured by severity scores. Further, “neither the coercion that accompanies legal system
involvement nor self-referral were significantly related to measured levels of motivation”
(Rapp et al, 2003, p. 113). This finding suggests that referral source or involvement with
the criminal justice system may not be adequate to judge a person motivated or
unmotivated.
Internal and external motivation in substance abuse
In substance abuse treatment, factors that lead a person to get treatment may have
an impact on his/her motivation for treatment, and these factors may be viewed as either
internal or external motivators. Internal motivation for treatment is often reflected in the
Alcoholic’s Anonymous slogan ‘sick and tired of being sick and tired’.
External motivation in substance abuse historically has been defined as coercion
from the legal system (Fagan and Fagan, 1982; Watson et al, 1988; Fagan, 1999). More
recently, the definition of external motivation has been expanded to include pressure
from other outside sources including a spouse, employer, or legal system (Miller and
Flaherty, 2000; Marlowe et al, 1996).
Coercion as a motivator for treatment is considered external. A definition of
coercion is not agreed up on in the literature; instead, categories of levels of coercion
appear to be more common. In an attempt to operationally define coercion from a
17
records analysis, Monahan et al (1995) defined coercion as formal and quasi-formal.
Formal coercion is defined as legal whereas quasi-formal coercion involves some level of
pressure although the individual is not explicitly involuntary.
Marlowe et al (1996) emphasized a continuum of coercion rather than being an all
or nothing legally mandated construct. In their study of 260 clients admitted to an
outpatient clinic Marlowe et al (1996) combined four measures to create one measure of
perceived pressure to enter treatment: advantages and disadvantages of quitting drugs, a
reinforcement schedule of “escape, avoidance, or positive reinforcement” (p. 79), a
determination of items as socially mediated, and a measure of the primary psychosocial
domain that the individual is operating from (family, social, legal, medical,
psychological, financial, religious, or drug specific). The results determined that pressure
for treatment-entry as defined by subjects was from psychological, financial, social,
family, and medical domains regardless of their referral source (legal or non-legal),
suggesting that legal coercion may exert less influence than does informal, extra-legal
pressure.
Farabee, Prendergast, and Anglin (1998) reviewed eleven studies on the
relationship between legal coercion and substance abuse treatment and found mixed
results. Five of the eleven studies determined a positive relationship between legal
coercion and treatment, four studies found that coercive pressure made no difference in
treatment outcomes, and two studies reported a negative relationship. Of interest, the
authors found that the variations in the results were due to the inconsistent terminology
with regards to coercive pressures, a lack of emphasis on the elements of internal
motivation, and problems with program implementation.
18
Of the five studies that found a positive relationship between coercion and
substance abuse, two utilized the Treatment Alternative to Street Crimes (TASC)
program. Collins and Allison (1983) found a positive relationship between being referred
to drug abuse treatment either through TASC or the criminal justice system and length of
stay in treatment. In the other study utilizing the TASC program, Salmon and Salmon
(1983) found that coercion facilitated success with older, long-term heroin addicts with
regards to arrest and abstinence.
Three other studies found positive outcomes between coercion and treatment
outcomes with substance abusers. Schnoll et al (1980) found that residents admitted
directly from prison had better rates of treatment completion. Siddall and Conway (1988)
found that persons who were involuntary admissions to treatment were more likely to
successfully complete treatment. Rosenberg and Liftik (1976) found that people
mandated to treatment had better attendance patterns in outpatient treatment than did
voluntary clients.
In four studies, no difference was found between voluntary and involuntary
clients with regards to treatment outcomes. Two of the studies involved outcomes of
criminal involvement, social functioning, and drug involvement (Anglin et al,
1989; Brecht and Anglin, 1993). McLellan and Druley (1977) used the number of staff
contacts as a measure of disruptiveness, and Simpson and Friend (1988) utilized
treatment outcomes as the primary measurement. In these studies, the majority of the
client population was male opiate addicts in primarily methadone maintenance programs.
Of the two studies that found negative relationships between legal coercion and
treatment outcomes, Hartford et al (1976) found that clients admitted while on probation
19
were retained in treatment for shorter amounts of time that clients not on probation.
Howard and McCaughrin (1996) surveyed organizations and found that organizations
that had at least 75% of court-mandated clientele had a higher rate of non-compliance
with treatment plans than organizations with 25% or less court-mandated clients.
Other research has found no difference between coerced clients and voluntary
clients. Fagan and Fagan (1982) state that “there is no sound empirical evidence that
coercion is effective in treating the court- referred alcoholic” (p. 287) based on their
meta-analysis of studies on the impact of legal coercion. Fagan and Fagan (1982) discuss
the research difficulties with the studies in the analysis, from not having a control group
to using invalid measures of treatment success. While this review is helpful when
looking at methodological inadequacies of studies, it may be unrealistic to find studies
that have the most rigid definition of “good research”, meaning that random assignment
or having a control group may not be possible.
In their study of coerced versus voluntary inpatient alcoholics, Watson et al
(1988) found that there was no difference in the prognostic outcome between groups.
However, the group of coerced clients had less alcohol consumption during and after
treatment than the voluntary clients.
In summary, motivation in substance abuse treatment has become an important
indicator in treatment engagement and treatment outcomes. Internal and external sources
of motivation contribute to a better understanding of the client and assist treatment
providers to better serve clients based on their level of motivation. Sources of external
motivation include coercion, and the literature has produced mixed results of how
20
persons coerced into treatment fair in treatment. More research is needed to solidify the
definition of coercion and to determine the impact of different levels of internal and
external motivation on treatment outcomes.
Self-determination theory
Self-determination theory is based in an “organismic dialectical perspective”
(Ryan and Deci, 2004, p.3). The organismic construct refers to an individual’s psyche as
having both potential and tendency to develop more complex levels of expression and
functioning. Self-determination theory characterizes the interaction with the social
environment as dialectical, emphasizing either the facilitation of growth and integration
or a disruption or fragmentation of the psyche as a result of this interaction with the social
environment. The dialectical component further supports the organismic construct: as a
struggle with the environment occurs, new challenges and creative solutions may result
which reflect a need to reach new levels of functioning.
Self-determination theory identifies three basic psychological needs for all
individuals, a platform on which motivation is built: the need for competence,
relatedness, and autonomy. The need for competence reflects wanting to find things to
do and do them well. Autonomy is the regulation of the self by the self rather than
external forces. Relatedness refers to having a connection with others, a sense of
community. The three needs are the basis for determining an environment to be
supporting or opposing an individual’s pursuit of a more complex psyche.
“Functional significance” of an event takes into account the meaning of the
interactions prior to an individual taking action (Deci and Ryan, 1985). For example, if
an individual seeks treatment due to an external source prompting the admission, the
21
motivation may fall on the external motivation continuum. However, the external
reasons for seeking treatment may coincide with an individual’s realization of needing
treatment, which would be a more internal reason for seeking treatment.
Expectancies of an individual’s environment are developed with tendencies
toward regulations that are autonomous, controlled, or impersonal (Deci and Ryan,
1985). Autonomous regulations correspond with an individual feeling that their
behavior is caused by their own motives (internal perceived locus of causality) whereas
controlled regulations are those events that cause people to act or think in a certain way
thus an individual experiences these events as causing the behavior (external perceived
locus of causality) (Pelletier, Tuson, and Haddad, 1997). Impersonal expectances are
defined as having no perceived relationship between behavior and a source of motivation
(either internal or external).
The perceived locus of causality and expectancies in Self-determination theory
are similar to expectancies in Rotter’s (1966, 1975) construct locus of control. However,
Deci and Ryan (1987) describe the difference between locus of control and locus of
causality in Self-determination theory as two-fold: 1). “expectations of behavioroutcome dependence and of competence promote intentional behavior, but they do not
provide a basis of distinguishing between self-determined and controlled behaviors”
(Deci and Ryan, 1987, p. 1034); 2). Locus of control considers reinforcements are part of
the determination of being internal or external, and self-determination theory posits that
intrinsically motivated behavior “require no reinforcements” (p. 1034).
One aspect of self-determination theory, the organismic integration theory (OIT)
defines motivation as six categories of levels of internalization of regulation. This
22
continuum of motivation includes amotivation, four categories of extrinsic motivation,
and intrinsic motivation. This taxonomy is defined by the degree to which motivation
originates from the self (Ryan and Deci, 2000). Each type of motivation has
characteristics related to the perceived locus of causality, regulatory processes, and
regulatory styles (Ryan and Deci, 2000). See Figure 2.1.
Amotivation is defined as the absence of the intention to act and is considered to
be non-self-determined behavior. The perceived locus of control is outside of an
individual, and the lack of motivation is characterized by feelings of the inability to
achieve the desired outcomes due to lack of perceived competence or a lack of value
toward the activity and/or the outcome of the activity.
Type of
Motivation
Amotivation
Type of
Regulation
Nonregulation
Extrinsic Motivation
External
Regulation
Perceived
locus of
causality
Impersonal
Quality of
Behavior
Nonself-determined
External
Introjected
Regulation
Somewhat
External
Intrinsic
Motivation
Identified
Regulation
Integrated
Regulation
Intrinsic
Regulation
Somewhat
Internal
Internal
Internal
Self-determined
From: Ryan, R., and Deci, E. (2000). Self-determination theory and the facilitation of intrinsic motivation, social development, and
well-being. American Psychologist, 55(1), 68-78.
Figure 2.1: Self-determination theory
23
Extrinsic motivation is divided into four categories on the motivation continuum,
each reflecting the perceived locus of causality from external to internal and level of
integration from non-integrated to fully integrated (Ryan and Deci, 2000). The most
extrinsic of the four types is externally regulated. Behaviors that are performed are
usually to satisfy an outside demand, and often externally regulated behaviors are viewed
as controlled. The perceived locus of causality is external.
Introjected regulation is also characterized by an external perceived locus of
causality, although not as severe as the previous category. While the regulation may be
taken in, it is not accepted as one’s own (Ryan and Deci, 2000). The rewards and
punishments with this type of motivation come from ego involvement: behavior is
performed to avoid feelings of guilt and shame or to enhance self-worth.
When an individual accepts an action as personally important with a conscious
value placed on a behavior, the motivational category is identified regulation. In this
stage, there is a somewhat internal perceived locus of control although the regulation has
not been integrated totally with the self. Behaviors that result from identified regulation
are viewed as relatively self-determined (Ryan and Deci, 2000).
Integrated regulation shares many aspects of intrinsic motivation. Behaviors are
done to satisfy an external source rather than for purely intrinsic reasons. However, the
regulation is assimilated with the self. The perceived locus of control is considered
internal.
Intrinsic motivation is defined as doing something for the enjoyment of doing it
rather than for an external reward. The perceived locus of causality for intrinsic activities
is internal, and is characterized by satisfaction and interest.
24
Because intrinsic motivation is associated with increased performance and,
conversely, extrinsic motivation is negatively associated with sustained performance
(McBride, Curry, and Stephens, 1994), self-determination theory posits the need to move
toward more self-determined behavior. More fully integrated regulations are equated
with more intrinsically motivated behavior (Deci and Ryan, 1985).
Testing the predictions within self-determination theory has been successful in
different areas. Williams, Grow, Freedman, Ryan, and Deci (1996) found in their study
of weight loss subjects (n = 128) that the degree of autonomous motivation predicted
weekly attendance at weight loss meetings and maintenance of weight loss at a 23 month
follow-up. Williams et al (1998) found in their study of 126 adults taking prescription
medication that autonomous regulation mediates the autonomy support on prescription
medication adherence.
Applying the self-determination theory specifically to chemical dependency,
Zeldman, Ryan and Friscella (2004) found a relationship between levels of motivation
and treatment outcomes. In this study of 74 clients in a methadone maintenance
treatment program, higher levels of internal motivation were found to be predictive of
lower relapse rates. More autonomous motivations were predictive of lower relapse rates
and higher retention, whereas external motivators were negative predictors of program
adherence. External motivation predicted absence from treatment: this is not a consistent
finding with coercion literature. Coercion literature indicates that people with external
pressures stay in treatment (which may be in part to avoid other consequences).
Individuals with high external and low internal motivation reported the worst outcomes,
where as those with high internal and high external motivation had the best outcomes.
25
Ryan, Plant, and O’Malley (1995) found a relationship between initial treatment
motivations and dropout rates in alcoholism treatment. In this study of 98 outpatient
alcohol abusers, higher internalized motivation was negatively correlated with dropping
out of treatment (r = -.23, p > .05). Higher levels of internalized motivation at admission
were positively related to attendance (the number of sessions attended) and treatment
status (defined as if someone remained in treatment, dropped out, or was terminated) at 8
weeks. An interaction between internal and external motivation emerged, as persons with
both high internal and high external motivation were most likely to persist in treatment.
Of interest, external motivation was positively related to outcomes only when internal
motivation was present.
Both Ryan, Plant, and O’Malley (1995) and Zeldman, Ryan, and Friscella (2004)
relate that persons with both high internal and high external motivation have better
outcomes in treatment.
Measures
Several measures have been developed to represent specific indicators from Selfdetermination theory. The General Causality Orientations Scale (GCOS) (Deci and
Ryan, 1985) consists of 12 vignettes and 36 items to represent levels of regulations:
autonomous, controlled, or impersonal. The autonomous orientation is geared toward
intrinsic motivation, controlled orientations are geared toward rewards and more external
motivation, and impersonal orientations are represented by feelings of luck or fate. Deci
26
and Ryan (1985) tested the items with 932 undergraduate students and 193 non-students
and found a Chronbach’s alpha of .75 and test-retest of .74 over two months. The
application of this scale appears to be limited: there have been very few studies
replicating the results using the GCOS scale.
Another scale created to measure indicators of Self-determination theory is the
Treatment Motivation Questionnaire (TMQ) (Ryan, Plant and O’Malley, 1995). The
TMQ contains two factors representing motivation: internal and external motivation.
Ryan, Plant, and O’Malley (1995) tested this instrument with 100 subjects entering
treatment for outpatient alcohol abuse. They found an internal consistence of .70 to .98
of the items in the scale to represent each of the factors.
Treatment Self-regulation Questionnaires (TSRQ) were created to assess
autonomous motivation (Ryan and Connell, 1989). The TSRQ consists of five items and
asked participants to respond with a Likert-scaled response. The questionnaire was
originally tested on school-aged children, and has also been used for smoking cessation
(Williams et al, 2002).
Perhaps one difficulty with the measures described previously is that the
instruments have not become commonly used with any population. The research
supporting the use of the questionnaires comes primarily from the same source, the
people who created and continue to develop Self-determination theory. Further, the
research that has been done on each of these measures has not been replicated, which
may call reliability and validity of the measure into question.
Self-determination theory identifies three concepts on which motivation is built:
autonomy support, relatedness, and competence. This theory further defines motivation
27
though a series of categories on a continuum: from amotivation to external motivation to
entirely internal motivation. Self-determination theory accounts not only for motivation,
but also considers the context, the “functional significance”.
In substance abuse, rarely if ever does a person present to treatment without some
external consequence, which makes the Self-determination theory model appropriate for
the substance abusing population: being able to have both internal and external
motivation at varying levels allows for a more accurate representation of motivation for
substance abusers.
Transtheoretical model of change
“The Transtheoretical Model (TTM) offers an integrative framework for
understanding and intervening with human intentional behavior change,” (DiClemente
and Prochaska, 1998, p.3). TTM was developed out of a perceived need to identify the
change process in individuals with a focus on changing addictive behaviors (DiClemente,
2003; Miller, 1985). 18 different psychological and behavioral theories were analyzed
for commonalities about how change occurs, and the TTM was produced from the
common traits of these theories (Prochaska, 1979; Miller, 1998). The focus of the model
is on intentional change with an emphasis on an individual’s decision making process.
The variables originally determined through a comparative analysis of existing
theories were preconditions for therapy, processes for change, content to be changed, and
the therapeutic relationship (Prochaska and DiClemente, 1982). Out of this framework,
application began with individuals attempting to change their smoking habits without
formal treatment (Prochaska and DiClemente, 1982; McConnaughy et al, 1983).
28
DiClemente and Prochaska (1998) define the TTM with three constructs: stages
of change, processes of change, and levels of change. The stages of change are the
“central organizing construct” (Velicer et al, 1998, p. 216). Other variables included in
the model are: the pros and cons of change, self-efficacy, and temptation (Prochaska et
al, 1992).
Stages of change
Perhaps the most well-known dimension of the TTM is the stages of change.
“These stages depict the motivational and dynamic fluctuations of the processes of
change over time,” (DiClemente, 2003, p. 26). Each stage includes a time period as well
as tasks necessary to move to the next stage. The five stages are precontemplation,
contemplation, preparation, action, and maintenance (Prochaska et al, 1992).
The precontemplation stage is marked by individuals either not being aware that a
change is necessary or unwilling to make any kind of change. The specific task of the
precontemplation stage is awareness: an individual needs to become aware that a
behavior exists and that the possibility for change may exist. The goal of the
precontemplation stage is for an individual to begin to consider changing the behavior
(DiClemente, 2003).
The contemplation stage is marked by an individual being aware that there is a
need to change and serious thoughts of change. No commitment to change is made,
however. A decision balance is typically part of the contemplation stage, a weighing of
the pros and cons of change. The time period that one may be in this stage is not
specified, “it is not uncommon for individuals to remain in this stage for extended
29
periods, often for years, vacillating between wanting and not wanting to change” (Center
for Substance Abuse Treatment 1999, p. 18). The goal of the contemplation stage is for
an individual to resolve their ambivalence to move into the preparation stage.
Originally labeled decision-making, the preparation stage is marked by the
development of a plan of action and committing to follow through with the behavior
change (DiClemente, 2003; Connors et al 2001; Miller, 1998). Typically, an individual is
intending to change in the next 30 days (Miller, 1998), and the individual has attempted
to change unsuccessfully in the past year (Prochaska, DiClemente, and Norcross, 1992).
The task of the preparation stage is for an individual to develop competencies and the
self-efficacy to move to action.
An individual implementing the plan developed in the preparation stage is the
hallmark of the action stage. Connors et al (2001) denote two features of the action
stage: a commitment to change and the changes in behavior reflecting this commitment.
The time period for an individual to be in the action stage is from one day to six months
of changing and sustaining the behavior change (Prochaska et al, 1992). The task of the
action stage is to make an effort to change the behavior and to continue the change for a
period of time (DiClemente, 2003; Prochaska et al, 1992).
The final stage outlined in this model is the maintenance stage. The maintenance
stage involves integrating the behavior change into different life areas and preventing
relapse. Typically, the maintenance stage begins six months after the initial action and
can last indefinitely (Prochaska et al, 1992; Connors et al, 2001; DiClemente, 2003). To
have a ‘fully maintained’ behavior, little or no effort is necessary to continue the behavior
30
(DiClemente, 2003). Connors et al (2001) maintain that practically, individuals never
leave the stages of change cycle. Rather, individuals making a behavior change need to
be aware of possible relapse risks throughout the maintenance stage.
The stages of change may appear as a linear progression; however, Prochaska et
al (1994), Prochaska et al (1992), DiClemente (2003), and Connors et al (2001)
emphasize that a linear progression is more of an exception than a rule. Rather, the
stages of change are often referred to as a spiral model. Individuals may go through the
stages numerous times or become stuck in one stage for a long period of time (Prochaska
et al, 1994). An individual may experience problems that send him/her back to an earlier
stage; the problems may be identified as “relapse” (DiClemente, 1991, Prochaska, 1992).
Prochaska et al (1994) describe the process of going back through an earlier stage as
‘recycling’ rather than relapsing (p. 48). Rarely does a person return to the
precontemplation stage if recycling through the stages.
Based on a meta-analysis of six studies across behaviors that utilize the stages of
change, Ashworth (1997) determined that tailored, stage-based intervention led to greater
stage progression than non-tailored, non-stage based intervention. Of the six studies
included in the analysis, three were concerned with the effects of messages on smoking
cessation. In the first study, 72 people were interviewed by phone, their stage of change
was determined, and they were randomly assigned to two groups. One group got a
standardized self-help manual: the other group got a message that was computer
generated that was tailored to the individual based on the information they provided at
intake. Among light smokers, the tailored-message group had a higher quit rate but no
significant difference was seen for heavier smokers between the two interventions. The
31
second study, which utilized similar methods, excluded precontemplators. Participants
were randomly assigned to receive either a tailored message or no message (n = 296). At
the six month follow-up, light smokers in the tailored message group had significantly
higher cessation rates. No difference was found between the groups for heavy smokers.
The third study compared smoking cessation interventions. 756 participants randomly
received one of four interventions: self-help manuals that were standardized, staged selfhelp manuals, staged manuals with individualized computer feedback, or stage manuals
with individualized computer feedback and brief counseling by phone at one, three and
six months. At 18 months, the cessation rate was highest among the groups receiving
stage-based interventions as opposed to receiving the standardized manual.
In another study focused on tailored interventions (Skinner et al, 1994), 497
women at a mammography screening were randomized to receive tailored or non-tailored
letters five months after baseline and had a follow-up eight months after baseline. People
that received tailored letters were more likely to have read the letter and were more likely
to recall the letter, and recipients of the tailored letter who were black and low-income
were found to have better stage progression.
In a study of face-to-face interventions tailored to an individual’s stage, Gomel et
al (1993) found that people who received stage counseling had higher smoking cessation
rates at the 18 month follow-up than those in other groups (having a health risk
assessment or risk factor education).
32
The results of the six studies were measured at least 12 to 18 months after the
initial assessment. The results “are consistent with the prediction of the Stages of Change
model that a staged intervention brings about greater stage progression than a non-staged
intervention” (Ashworth, 1997, p. 171).
O’Hare (1996) found in his study of 374 adults in treatment for mental health
outpatient services that a relationship exists between the stages of change and referral
source. People that were referred through the court were more likely to be in the
precontemplation stage than people who were voluntary, and people who were
considered voluntary were associated with being in later stages of change (contemplation,
action, and maintenance).
Gregoire and Burke (2004) conducted a study on the relationship between legal
coercion and the stage of change in outpatient treatment programs (n = 295). This study
utilized the Readiness to Change Questionnaire which contains items with a Likert scale
response. Results showed that persons that were court-referred to treatment were more
likely to be in the action stage of change.
Processes of change
The processes of change are the experiences that allow for the movement among
the five stages of change. While the stages of change represent a time frame of when
change occurs, the processes of change represent how the change occurs. Ten processes
of change have been determined from principle component analysis (Prochaska et al,
1992).
Consciousness raising is defined as “increasing awareness of the causes,
consequences, and responses to a particular problem” (Prochaska, 2003, p.832).
33
Dramatic relief “involves emotional arousal about one’s current behavior and the relief
that can come from changing” (Prochaska, 2003, p. 832). Environmental reevaluation is
an assessment of how an individual’s problems affect the social environment as well as
how changing the behavior would affect the social environment. Self-reevaluation is the
process of determining feelings about the self in regards to the specific problem behavior.
Self-liberation defined is two-fold: it is both the belief that it is possible to change and
committing to the change.
Process
Consciousness Raising
Dramatic Relief
Environmental Reevaluation
Self Reevaluation
Social Liberation
Self Liberation
Contingency Management
Stimulus Control
Counter Conditioning
Helping Relationship
Definition
Increase awareness of
consequences: Cause and
response to behavior.
Emotional arousal
How addiction affects social
environment and impact of
changing self in environment
Assessment of how addiction
affects self and impact of self in
changes on self
Increase in social opposition
Belief that one can change,
commitment to act
Learning healthy behavior to
substitute an addictive behavior
Use of reinforcement/punishment
for taking steps
Increase cues to prompt healthy
responses: Decrease cues to
prompt addictive responses
Support, openness, caring
Example
Observation, confrontation,
feedback, education
Psycho-drama, role-players,
personal testimonies
Empathy training, family
interventions
Impact value clarification
Advocacy, empowerment
procedures
Public commitments
Assertion, desensitization
Overt & covert reinforcement.
Contingency contract
Avoidance, attendance at selfhelp groups
Rapport building, sponsor,
therapeutic alliance
From Prochaska (2003) and Prochaska, Norcross, and DiClemente (1994).
Table 2.1: The Processes of Change in the Transtheoretical Model of Change
34
Reinforcement management, also referred to as contingency management
(Prochaska, 2003) is a system of rewards and punishments for making changes. Helping
relationships involve support for changing, combining “caring, openness, trust, and
acceptance” (Prochaska, 2003, p. 833). Counterconditioning is the substitution of other
behavior for problem behaviors. Finally, stimulus control is changing or modifying the
external environment to avoid triggering stimuli (Prochaska et al, 1992).
Certain processes of change correspond more appropriately with specific stages of
change. For example, precontemplators are not actively involved with any process of
change (Prochaska et al, 1998). Consciousness raising, emotional arousal, dramatic
relief, and self- and environmental-reevaluation are more compatible within the
contemplation stage and the preparation stage. In the action stage, social liberation, self
liberation, counterconditioning, stimulus control, and contingency management are more
appropriate processes. The continuation of the processes utilized in the action stage is
necessary in the maintenance stage. See Figure 2.
Clarification of the relationship between the processes of change and the stages of
change is described by Prochaska and DiClemente (1983) in their study of smokers
determined as being in different stages of change. An interaction between the processes
and stages of change was identified. For example, individuals in the precontemplation
stage used 8 of the 10 processes of change less than individuals in any other stage.
Contemplators were more likely to respond to the processes of feedback and education
whereas those in the action stage were more engaged in counterconditioning and stimulus
35
control. The processes of counter conditioning and stimulus control were also found to
be a link between the action and maintenance stage rather than just focused in the action
stage.
Using processes of change that are congruent with a client’s stage of change may
produce less resistance on the part of the client and less frustration on the part of the
therapist (Prochaska and DiClemente, 1996). Perz, DiClemente, and Carbonari (1996)
found in their study of 388 smokers in the contemplation or preparation stage that
processes congruent to the stage of change an individual was in helped them progress
through the stage model.
Precontemplation
Contemplation
Preparation
Action
Maintenance
Consciousness raising
Dramatic Relief
Environmental reevaluation
Self-reevaluation
Self-liberation
Reinforcement Management
Helping relationships
Counterconditioning
Stimulus control
From: Prochaska, J., DiClemente, C., and Norcross, J. (1992) In search of how people change: Applications to addictive behaviors.
American Psychologist, 47(9), 1102-1114.
Figure 2.2: The Processes of Change in relation to the Stages of Change
36
Levels of change
The levels of change are perhaps the least written about aspect of the TTM
(DiClemente and Prochaska, 1998). The levels of change allow for the consideration of
other life areas that may impact the changing of one specific behavior. The levels of
change take into consideration the multi-dimensional nature of addiction and attempt to
address not only the problem with the particular substance, but also other areas that may
contribute to the addiction such as depression, domestic violence, and abuse. The five
levels of change are: symptom/situational, maladaptive cognitions, interpersonal
conflicts, family/systems problems, and intrapersonal conflicts (Prochaska et al, 1992).
DiClemente (2003) describe the levels of change as context, the individual him/herself
with environmental factors. An example of using the levels of change in substance abuse
treatment is assisting the client not only to reduce or stop using drugs and/or alcohol
(symptom/situational) but also addressing family dynamics such as working with a
spouse or family (family/systems level) as well as working with the referral source such
as an employer (intrapersonal conflicts).
Other factors
From early stages of the development of the Transtheoretical model, self-efficacy
has been identified as an important intervening variable (Prochaska and DiClemente,
1982). Bandura (1977) describes self-efficacy as the belief that a person has that he/she
can succeed in a given situation. Further, the higher the efficacy expectations, the more
likely one is to engage in the related task. The concept of self-efficacy is tied into the
stages of change: lower efficacy expectations are more indicative of a person in earlier
stages of change such as precontemplation or contemplation, and higher efficacy
37
expectations are linked to individuals in later stages of change such as action and
maintenance (DiClemente et al, 1984; DiClemente, 1986; DiClemente and Hughes,
1990). DiClemente (2003) and Miller (1985) indicate that self-efficacy is an important
predictor of successful abstinence, which is reflected by Prochaska and DiClemente’s
(1984) emphasis of the construct in the maintenance stage to predict relapse.
DiClemente, Prochaska, and Gibertini (1985) examined the relationship between
self-efficacy and the stages of change. 957 smokers or past-smokers were divided into
five groups based on the stage of change they were in with regards to smoking: longterm quitters, recent quitters, relapsers, contemplators, and immotives. Self-efficacy was
determined to be an important aspect of self-change as efficacy evaluations at assessment
were related to changes in status for recent quitters and contemplators at follow-up.
Further, different processes of change were correlated with efficacy: the higher the
efficacy expectation, the fewer change processes that were utilized. However, for
persons with high efficacy expectations, when processes were utilized, they were more
behavioral in nature than cognitive or affective.
Related to self-efficacy, temptation is another potential intervening variable in the
TTM. Temptation is the perceived strength of cues for the behavior that is being changed
(DiClemente, 1999). According to Prochaska and DiClemente (1984), self-efficacy and
temptation are used together as a tool “to assist therapists in determining areas of
vulnerability and to design relapse prevention strategies for situations in which addicted
individuals evaluate themselves as vulnerable and inefficacious” (p.100). According to
Prochaska and Velicer (1997), three factors represent the most common temptations:
“negative affect or emotional distress, positive social situations, and craving” (p. 40).
38
The relationship between self-efficacy and temptation is described by DiClemente
(1999): the level of self-efficacy rises to meet the level of temptation over the course of
the stages of change. In other words, as a person progresses through the stages of
change, higher levels of self-efficacy reflect an individual’s increasing confidence that
he/she will remain abstinent even if levels of temptation are consistently high.
DiClemente (1986) describes intensity of temptation as high throughout the initial stages
of change, but decreases substantially during the maintenance stage.
Decision balance is a third non-specific variable within the Transtheoretical
model. Janis and Mann (1977) described a decision making model that included four
categories of “pros”, and four categories of “cons”. The pros included instrumental gains
for self and others and approval for self and others. The cons were instrumental costs to
self and other and disapproval for self and others. Velicer et al (1985) tested the decision
making model of Janis and Mann (1985) and determined two principal components of the
decision balance as Pros and Cons. The relationship between the decision balance and
stages of change has become integral in the model: the balance of the pros and cons of
changing varies depending on which stage of change a person is in (Prochaska et al,
1994). For example, in the precontemplation stage, the pros of the behavior outweigh the
cons, whereas the cons outweigh the pros in the later stages of action and maintenance.
While the TTM began with research based in people who change naturally
(Prochaska and DiClemente, 1983; McConnaughy et al, 1983), the evolution of this
model includes addictive behaviors primarily but does not rule out the application to
other behaviors. Smoking cessation has historically been the main problem area
researched (Prochaska and DiClemente, 1983; Prochaska, et al, 1988; DiClemente et al,
39
1985; DiClemente et al, 1991). However, the TTM has been applied to various behaviors
such as alcoholism (DiClemente and Hughes, 1990), phobias (Prochaska, 1991), cocaine
use, weight control, diet, adolescent delinquent behaviors, safer sex, condom use,
sunscreen use, radon gas exposure, exercise, mammography screening and physicians’
preventative practices with smokers (Prochaska et al, 1994; Prochaska and Velicer,
1997).
More recent research has expanded the applicability of the TTM. Norcross et al
(2002) in their study of New Year’s resolvers and non –resolvers found that those
individuals that successfully changed used processes of change that paralleled processes
of change used with individuals attempting to quit smoking: self-liberation, stimulus
control, reinforcement management, positive thinking, and avoidance (see Prochaska and
DiClemente, 1983). The application of the TTM to those resolving to change supported
the foundation of the model, thus increasing applicability.
Extending beyond health behaviors, Xiao et al (2001) applied the TTM to
financial behavior and refers to the model as a “revolution in the science of behavior” (p.
2). A financial program, Money2000, was developed with the TTM as the theory base,
and the target behavior was avoidance of undesirable debt and the development of
healthy saving behavior. Results of the program support findings of Prochaska and
DiClemente (1983): different processes are used more in different stages of change.
Four change processes were found to have a greater effect on individuals in the action
stage: self-liberation, contingency management, self-reevaluation, and dramatic relief.
40
Critique of the model
The TTM is not without its critics. Bandura (1997) and Davidson (1992, 1998)
argue that this model is arbitrary in its division of the stages of change and the time frame
of each stage. Bandura (1997) defines the TTM as “arbitrary pseudo-stages” (p.8), as not
being a true stage theory. Genuine stage theories are sequential, and attributes are
qualitatively different in each stage. However, the TTM does not include stages that are
distinctly, qualitatively different from each other (Davidson, 1998; Bandura, 1997). For
example, maintenance may be considered an extension of the action stage with the only
distinction between the two stages being the time-frame. Connors et al (2001) refer to the
stages of change as being both continuous and discrete, “a continuous process with
important discrete steps” (p. 221).
Another difficulty with the stage conceptualization as iterated by Davidson (1998)
and Sutton (2001) is the division of the stages by length of time. Each stage is described
with a time frame. The precontemplation stage is designated by no intention to change
within the next six months. The contemplation stage is marked by an intention to change
within the next six months. The intention to change in the next 30 days is characteristic
of the preparation stage. Actually making the change and following- through for 6
months is the time frame of the action stage, and maintaining the change beyond 6
months is considered maintenance (Prochaska and Velicer, 1997). Weinstein et al (1998)
describe the specific time points of the stages as “somewhat arbitrary” (p. 293). Davidson
(1992) further questions the time dimension: why and how was the time frame created?
Who determined the specific time designations for each stage?
41
Measures
There have been several scales and tests created to address the concepts presented
in the Transtheoretical model. Two of the better known instruments are the URICA and
SOCRATES. Other measures developed include the Readiness to Change Questionnaire,
the Levels of Attribution and Change Scale, and a measure of the processes of change.
Developed in the early 1980’s, McConnaughy et al (1983) developed the Stagesof-Change Questionnaire, later to be known as the University of Rhode Island Change
Assessment Scale – URICA. The URICA has evolved into a 32 question measure of four
stages of change: precontemplation, contemplation, action and maintenance. The fifth
identified stage of preparation, then known as decision-making, did not emerge as a
distinct component in the principal component analysis. The internal consistency is
reported to be high, ranging from .88 to .89 (McConnaughy et al 1983). In a study
designed to cross-validate the results from McConnaughy et al’s original work,
McConnaughy et al (1989) found internal reliability (Cronbach’s coefficient alpha) to be
between .79 and .84. While the initial measure was designed and tested using individuals
involved in psychiatric outpatient counseling (McConnaughy, 1983), the URICA has
been found to be useful in outpatient alcoholism treatment (DiClemente and Hughes,
1990) and has been modified to be used specifically in alcoholism treatment (Center for
Substance Abuse Treatment, 1999).
Developed from the URICA, the Readiness to Change Questionnaire (RCQ)
consists of 12 items which correspond with three levels of change: precontemplation,
contemplation, and action (Center for Substance Abuse Treatment, 1999). The RCQ was
developed for heavy drinkers identified in hospital settings although not seeking
42
treatment (Rollnick, Heather, Gold, and Hall, 1992). According to Gavin, Sobell, and
Sobell (1998), Chronbach’s alpha for this scale exceeds .73 on each scale, a reflection of
internal consistency. An identified limitation of the RCQ has to do with the use of the
instrument with a different population. When applying the RCQ to drinkers in treatment,
Gavin et al (1998) found that only one section of the three addressing the stages of
change had acceptable internal reliability, a contrast to the previous results.
The SOCRATES (Stages of Change Readiness and Treatment Eagerness Scale) is
another measure applied to the TTM, developed to assess motivation to change in
problem drinkers (Miller and Tonigan, 1996). The scale consists of 19 Likert scale items
(Center for Substance Abuse Treatment, 2000). While the original instrument consisted
of questions identifying each of the stages of change, a factor analysis determined three
constructs which are independent of the stages of change: taking steps, recognition, and
ambivalence (Miller, 1996). “The scales of SOCRATES seem better understood as
continuously distributed motivational processes that may underlie the stages of change”
(Miller and Tonigan, 1996, p. 84). Regarding internal consistency, Chronbach’s alpha
ranged from .6 to .85 for the three constructs (Miller and Tonigan, 1996).
Maisto et al. (1999) applied the SOCRATES to persons identified as at risk
drinkers at community mental health centers. The results found that rather than
identifying three constructs, two factors created a better fit. The two factors were
identified as “Amrec”, a combination of ambilivance and recognition, and “taking steps”
(p. 879).
A change processes scale was developed initially to measure the differences in the
use of specific processes between self-changers and individuals in therapy (DiClemente
43
and Prochaska, 1982). The questionnaire originally contained three questions about each
of the ten processes of change. However, Prochaska et al (1988) indicated in their
research further analyzing the processes of change that the initial instrument “did not
adequately demonstrate psychometric properties” (p. 521). A revised instrument to
measure the processes of change, the Smoking Processes of Change scale (SPC), was
developed as a 40 item Likert scale questionnaire.
Scales have also been developed for the levels of change. Norcross, Prochaska,
and Hambrecht (1985) describe the Levels of Attribution and Change Scale (LAC) as a
measure consisting of 60 Likert scale questions. Norcross et al (1985) found 10
components in their analysis of the LAC falling into two dimensions: InternalDispositional and External-Situational. From the most external to the most internal, the
10 components are: spiritual determinism, biological inadequacies, bad luck,
environmental difficulties, maladaptive cognitions, familial conflicts, interpersonal
conflicts, intrapersonal conflicts, chosen lifestyle, and insufficient support (Norcross et al,
1984). The scale was developed and tested on individuals who self-selected their
problem, as opposed to a sample of people with a similar malady.
In replication studies regarding the validity and reliability of the instrument,
Norcross et al (1984) found similar factor structure results when applying the LAC to two
specific populations: psychotherapists and smokers. Reported alpha coefficients for the
two samples were .84 and .87. Further, Norcross and Magaletta (1990) demonstrated the
instrument to be valid and reliable in a sample of college students, with alpha coefficients
ranging from .87 at initial testing to .70 after four weeks.
44
The Transtheoretical model began as an integration of many different theories to
address substance abuse. It has been applied to many other areas as well, showing the
diverse utility of the model. The TTM offers a framework for substance abuse treatment
that focuses on an individual’s own process and allows treatment professionals to meet
the clients where they are and tailor treatment to an individual’s needs, rather than treat
individuals with a ‘one size fits all’ mentality.
Treatment outcomes
When considering the importance of motivation in substance abuse treatment, it
becomes necessary to consider how motivation impacts treatment outcomes. Treatment
outcomes in substance abuse have been widely debated and explored in recent years.
Outcomes traditionally have been measured as a dichotomous indicator of success.
Drinking behavior is an example of such a dichotomous indicator: either a person is
abstinent at the time of measurement or is not. Another indicator that is dualistic is
treatment completion. Emrick and Hanson (1983) indicate that treatment completion is
one component appropriate as a core index for outcome evaluation in substance abuse.
However, drinking behavior and treatment completion are not the only appropriate
measures of success in treatment. Rather, since recovery is not a fixed event but is a
dynamic experience, treatment outcomes need to reflect this multi-dimensional
phenomenon (Drummond, 1993).
A comprehensive model for considering a framework for treatment outcomes
includes components beyond abstinence or non-abstinence. McLellan et al (1992)
identify seven major areas that commonly affect substance abusers: alcohol and drug
use, employment, crime, family, medical, and psychiatric conditions. These seven areas
45
comprise the ASI (Addiction Severity Index) (McLellan et al, 1992). Each of these areas
lends itself to treatment outcomes, offering a complete picture of the individual. An
extension of the ASI, the Problem Severity Index (PSI) measures major life areas in
terms of barriers: alcohol, drug, lack of insurance, criminality, psychological, family, and
employment (Simpson et al, 1999).
Since abusing alcohol and other substances impacts many other areas of life,
outcome indicators need to reflect not only the reduction in use, but also reduction in
addiction- related problems (McLellan et al, 1993). McLellan et al (1997) describe three
components important in considering a more comprehensive view of treatment outcomes:
individual improvement in drinking behavior, improvement in other life areas
(psychological, employment, legal, etc) and improvement on a macro level with
reductions in problems affecting public health and society in general (such as spread of
AIDS and STDs). The improvement in personal and social functioning was identified as
important from a societal level and also as relating to maintenance of reduced substance
use (McLellan, 1997).
Moos, Finney, and Cronkite (1990) describe the need to use more bio-psychosocial indicators of treatment outcomes based on the DSM-IV criteria. The criteria for the
diagnosis of chemical dependency includes not only biological components (which the
outcome of abstinence may address), but also psychological and social indicators. Some
of the DSM-IV criteria include: tolerance change (biological), reducing or giving up
activities that used to be enjoyable (social), and continued use despite negative emotional
46
consequences (psychological). Because it takes three of seven criteria to diagnose
chemical dependency, alleviating only one of the indicators does not address other areas
that contribute to chemical dependency.
Purpose and rationale
Relationship between Self-determination theory and Transtheoretical Model of Change
Self-determination theory identifies the forces and factors that may influence an
individual to initiate and participate in behavior change as well as psychological
mechanisms that drive an individual to and through change. Deci and Ryan (2000)
describe self-determination theory as being able to offer an explanation about the “what”
and “why” of motivation. “What” is directed toward the psychological need of
competence which may dictate the product of the goal pursuit as well as the effort in
achieving the outcome. The “why” question is addressed through perceived autonomous
or controlled self-regulation, whether the perceived locus of causality is internal or
external.
The Transtheoretical model identifies the change processes in individuals with a
temporal dimension to motivation and a frame for moving through the different stages of
change. Each stage of change has with it a time frame and outlines processes of change
that facilitate movement through the stage. Certain processes of change correspond more
appropriately with specific stages of change: that is, the process of change used by an
individual depends on what stage of change he/she is in.
Together, the SDT and the TTM offer a more comprehensive view of motivation
than either do standing alone. Whereas self-determination theory emphasizes the
experience of the individual with regards to the perceived cause of initiating behavior
47
change, TTM provides structure to move through the behavior change. Abblett (2001)
describes self-determination theory as providing the molecular mechanisms of how
motivation is created, and the TTM as providing an infrastructure for understanding the
processes of change. A specific relationship between these two theories has yet to be
determined within the substance abusing population.
The purpose of this study is to determine the nature of the relationship between
Self-determination theory and the Transtheoretical model of change. The two theories
together may provide a more robust measure of motivation than either does individually.
Hypothesis 1
Sources of external motivation often prompt people to seek treatment to avoid
other consequences, whether or not the person feels they have a problem that needs to be
addressed. Since a characteristic of precontemplation is that a person in this stage has no
concept that there is or might be a problem, it is my hypothesis that people with high
external motivation are more likely to be in the precontemplation stage. People with
higher levels of internal motivation are aware that there is a need for a behavior change:
people with higher internal motivation are more likely to have some awareness of a
problem and may have taken steps to change their behavior, thus being in the later stages
of contemplation or action.
1.
A relationship exists between source of motivation and the stages of change.
People with higher levels of internal motivation will be in the later stages of
change (contemplation and action) than people with high external motivation.
48
Hypothesis 2
People with high external motivation and high internal motivation usually have
pressure to finish a course of treatment, whether the pressure is from an outside source
such as court, or an internal source such as wanting to have the satisfaction of completing
treatment. People with lower levels of internal and/or external motivation may not be
convinced of the importance of treatment completion, or may not have a requirement to
complete treatment (perhaps a suggestion that completing treatment would be beneficial).
Similarly, people with high levels of external motivation may have drug screen
requirements, and having an unclean urine sample would cause further consequences, and
people with high internal motivation may feel that they no longer need to use substances
purely for personal improvement. People with lower levels of internal or lower levels of
external motivation may not be convinced that they need to stop using drugs and/or
alcohol, or may not have had severe enough consequences to consider stopping drug or
alcohol use during and after treatment.
Determining the impact of the source of motivation on treatment completion and
on use of drugs and/or alcohol after the start of treatment may provide information about
the pervasiveness of motivation throughout and after treatment.
2a. Level of motivation at intake predicts retention or outcomes. People with high
external motivation or high internal motivation at intake will have higher levels of
retention: people with low intrinsic motivation or low extrinsic motivation at
intake will have lower levels of retention.
2b. Level of motivation at intake predicts drinking or using outcomes. People
with high extrinsic or high intrinsic motivation at intake will not have used
49
substances at the 12-month follow-up: people with low intrinsic motivation or
low extrinsic motivation at intake will have a higher probability of use at the 12month follow-up.
50
CHAPTER 3
METHODS AND FINDINGS
Data analysis
In order to determine a relationship between source of motivation and stage of
change, I conducted a secondary analysis of data from The Drug Abuse Treatment
Outcome Study- Adult (DATOS). The research design used in this study is a
correlational design based on a secondary analysis of survey data. The DATOS database
addresses research variables of interest in this study, specifically motivation and
treatment outcomes. One of the four major research objectives in the DATOS study was
to analyze motivation (Franey and Ashton, 2000), which is consistent with my research
objective.
To test the relationship between the stages of change and source of motivation, I
used multinomial logistic regression. Multinomial logistic regression was used because
the dependent variable has more than two categories. Covariates were determined by
their significant relationship with the dependent variable determined after conducting a
bi-variate analysis.
To test the relationship between source of motivation and treatment outcomes, I
used logistic regression. Treatment outcomes were tested using two different models:
treatment completion and use of alcohol or drugs after intake. The dependent variable for
51
each model was two categories: treatment completed or treatment not completed and use
of alcohol and/or drugs after intake or no use of alcohol and/or drugs after intake.
Covariates were determined by their significant relationship with the dependent variable
determined after conducting a bi-variate analysis.
Demographic indictors, alcohol and drug indicators, and severity indicators were
analyzed to determine if each variable was appropriate to include in the model. The
demographic indicators were: gender, ethnicity, marital status, age at admission,
educational level, and major source of income. Drug and alcohol indicators included
primary drug problem, treatment modality, number of previous treatments, and referral
source. Frequency of primary drug use and the number of drugs used weekly and overall
severity were indicators of severity. Also included in the analysis of the second
hypothesis were potential barriers to treatment: psychological barriers, employment
barriers, and severity. Table 3.1 outlines the indicator and the rationale for including the
variable in the model.
Drug Abuse Treatment Outcome Study
The Drug Abuse Treatment Outcome Study (DATOS) was conducted by
Research Triangle Institute and funded by NIDA (The National Institute of Drug Abuse).
DATOS data was derived from a longitudinal prospective cohort design: clients were
interviewed at intake and again at several points during treatment. 96 programs in 11
cities were purposively chosen and reflect typical drug treatment programs in medium
and large-sized US cities (Craddock et al, 1997). Treatment centers were both publicly
and privately funded entities. 10, 010 clients aged 18 or older were the subjects.
52
Variable
Demographic Information
Gender
Rationale
Source
Women have “complicating
factors and barriers to treatment”
(p.37)
U.S. Department of
Health and Human
Services (1995)
Ethnicity
Relationship between ethnicity
and drugs of choice and
treatment choice
Landry (1997)
Marital Status
Having never been married is a
significant predictor of retention
in treatment and of readiness to
change.
Joe, Simpson, and
Broome (1998 and
1999).
Age
Age is a significant predictor of
retention in treatment and of
readiness to change.
Joe, Simpson, and
Broome (1998 and
1999).
Educational Level
Practice experience
Major Source of Income
Active employment is associated
with positive treatment
outcomes; Poor economic
supports are negatively
associated with treatment
outcomes
Landry (1997)
Criminal Justice Status
An indirect effect on treatment
outcomes:
A significant predictor of
retention in treatment;
Ryan et al. (1995)
Joe, Simpson, and
Broome (1998 and
1999)
Continued
Table 3.1: Rational for Variables Included in the Analysis
53
Table 3.1: Continued
Alcohol and Drug Indicators
Primary Drug
History and current substance
use influences treatment
engagement and retention
Simpson (1999)
Treatment Modality
Retention rates differ among
treatment types; effectiveness of
treatment is related to type of
treatment
Mueller and Wyman
(1997);
Landry (1997)
Previous Treatment
May help a person moving
through stages towards sobriety:
May have a cumulative effect
Franey and Ashton
(1998)
Hser et al (1997)
Referral Source
Predicted treatment outcomes;
Mandated persons are more
likely to remain in treatment;
persons that were court-referred
to treatment were more likely to
be in the action stage of change
Zeldman et al
(2004);
Landry (1997);
Gregoire and Burke
(2004)
Severity
Persons with higher severity can
be difficult to maintain in
treatment:
Is an indirect predictor of
treatment outcomes
U.S. Department of
Health and Human
Services (1995);
Ryan, Plant and
O’Malley (1994)
Psychological severity as one of
the most important predictor of
response to treatment
Landry (1997);
McLellan et al
(1997)
Unemployment is negatively
associated with treatment
outcomes
Landry (1997)
Barriers to Treatment
Psychological Barrier
Employment Barrier
54
Four major treatment modalities were used: outpatient methadone maintenance
(OMT), long-term residential (LTR), outpatient drug free (ODF), and short term inpatient
(STI). Outpatient methadone maintenance expected average length of stay was 19
months, mainly implementing a long-term maintenance philosophy. Long-term
residential programs were typically therapeutic communities with an eleven month
average length of stay. Outpatient drug-free programs included non-medical services
with an average length of stay of five months. Short-term inpatient programs were
“Minnesota Model” programs with an average stay of three to four weeks (Franey and
Ashton, 2002).
The data were collected by personal interviews by trained and supervised
independent interviewers between 1991 and 1993. Two interviews were done in the first
week of treatment: an initial interview 90 minutes in length was conducted as soon as
possible after admission and a second interview was conducted about one week later.
Data collected in the first two interviews included baseline information about drug and
alcohol use, demographic characteristics, living situation, education, income, illegal
involvement, health, mental health, and treatment readiness.
In- treatment interviews were conducted at several points: one month after
admission, three months, six months, and 12 months (Flynn et al, 1997). Interviews
during treatment consisted of much of the same information from the intake interview as
well as in-treatment experiences and perceived helpfulness.
A follow-up interview was conducted at 12 months post-admission. The 12month follow-up included content similar to the in-treatment and initial interviews, as
well as information on post-treatment experiences.
55
Protection of human subjects
This study was reviewed and met exempt status by the Institutional Review Board
at The Ohio State University.
Characteristics of the sample
Of the 10, 010 participants in the total sample, 8,725 were found with both intake
one and two completed. Six of the respondents fell into the “0” category with the source
of motivation, thus were left out of the analysis. The number of participants in the final
analysis was 8, 719. Frequency distributions of the client characteristics are in Table 3.2.
Demographics
Gender, ethnicity, marital status, age at admission, educational level, major source
of income, and criminal justice status were analyzed as demographic information. See
Table 3.2. The majority of the 8, 719 participants were male (66.1%). With regards to
ethnicity, 47% of the respondents were African American, 38.3% were Caucasian, and
12.3% were Hispanic. With regards to marital status, 45.3% reported having never
married, 19.3% were married, 14.1% were divorced, and 12.2% were living as married.
The majority of the respondents were over age 30 (58.6%) with a mean age of 32.55 (sd
7.3).
About one-third of the respondents had a High School Degree (38.1%), and
another third (36.2%) had less than a high school degree. Slightly less than half of the
respondents (42.2%) identified the major source of income as legal work, and about onefifth (20.6%) stated that public assistance was the major source of income. The majority
of the respondents had no legal status (55.1%), with 31.1% on probation or parole.
56
Variable
Gender
Male
Female
Ethnicity
African American
Caucasian / white
Hispanic
Other
Marital Status at Intake
Never Married
Married
Divorced
Living as married
Separated
Widowed
Age at Admission
18-20
21-25
26-30
31-35
36-44
45+
Educational Level
High School Degree
High School
Some College
Grade School or Less
College / Associate Degree
College Degree
Advanced Degree
Major Source of Income
Legal Work
Public Assistance
Illegal Sources
Family/Friends
Social Security
No Income
Other
Blank
Frequency
Percent
5763
2956
66.1
33.9
4098
3338
1070
213
47.0
38.3
12.3
2.4
3948
1687
1226
1063
656
120
45.3
19.3
14.1
12.2
7.5
1.4
280
1235
2093
2296
2282
531
3.2
14.2
24
26.3
26.2
6.1
3325
2785
1486
371
363
322
63
38.1
31.9
17
4.3
4.2
3.7
0.7
3676
1797
1289
585
411
389
136
436
42.2
20.6
14.8
6.7
4.7
4.5
1.6
5.0
Continued
Table 3.2: Frequencies and Percentages of Demographic Information
57
Table 3.2: Continued
Criminal Justice Status
No Legal Status
Probation/Parole
In Jail/Detention
Case Pending
4803
2712
608
576
55.1
31.1
7.0
6.6
Drug and alcohol information
The following information regarding drug and alcohol history was also collected:
primary drug problem, number of prior treatments, referral source, treatment modality,
and length in treatment. See Table 3.3. The majority of respondents (51.5%) identified
crack/cocaine as the primary drug problem, followed by alcohol (21.1%), heroin (18.5%),
marijuana (3.1%), narcotics/opiates (2.2%), amphetamines (2.2%), hallucinogens (1.5%)
and sedatives (0.8%). The average number of prior treatments was 1.89 (SD 4.188) with
slightly less than half of the participants (44.9%) reporting having no previous treatment.
20.7% reported having one previous treatment, and 25.7% identified having two to six
prior treatments.
About one-third of the participants identified their primary referral source as self
(33.9%), followed by family/friends (31.2%), legal system (21.7%). Short-term inpatient
was the most common treatment (31.9%), followed by residential (28.1%), outpatient
drug free (24.7%) and methadone maintenance (15.3%).
58
Variable
Primary Drug Problem
Cocaine/crack
Heroin
Alcohol
Marijuana
Narcotics /Opiates
Amphetamines
Hallucinogen
Sedatives
Number
Percent
4489
1610
1055
270
193
190
132
73
51.5
18.5
21.1
3.1
2.2
2.2
1.5
0.8
Treatment Modality
Residential
Short-term Inpatient
Outpatient Drug Free
Methadone Maintenance
2451
2778
2156
1334
28.1
31.9
24.7
15.3
Previous Treatment
0
1
2-6
7+
3920
1811
2243
751
44.9
20.7
25.7
8.6
Referral Source
Family / Friends
Self
Legal System (including
2718
2960
1890
31.2
33.9
21.7
260
260
542
21
49
3.0
3.0
6.2
0.2
0.6
probation/parole)
School/Employer
Medical Service
Community Agency
Veteran
Other
Table 3.3: Frequencies and Percentages of Alcohol and drug indicators
59
Severity indicators
Two severity indicators were analyzed: frequency of use and multiple drug use.
With regards to frequency of use, 25.7% reported that they used their primary drug two
or more times per day, 23.4% reported using daily or almost every day, 28.2% reported
using one to six times per week, and 10.1% reported using less than once a week, and
4.7% reported no use.
The number of drugs used weekly ranged from zero to eight: 12.1% indicated
using zero drugs weekly, 28.9% reported using one drug weekly, 34.9% reported using
two drugs weekly, 17.3% used three drugs weekly, 6.8% used four to eight drugs weekly.
Slightly over half of the respondents (51.8%) fell into the moderate category with regards
to severity, 12.7% were in the low category, and 27.6% fell into the high severity
category. See Table 3.4.
60
Variable
Frequency of Primary Drug Use
2 + times per day
Daily or almost every day
1-6 times per week
Less than once per week
None
Number of Drugs Used Weekly
0
1
2
3
4 or more
Overall Severity
Low
Moderate
High
Number
Percent
2242
2040
2462
878
411
25.7
23.4
28.2
10.1
4.7
1052
2523
3040
1511
593
12.1
28.9
34.9
17.3
6.8
1108
4518
2407
12.7
51.8
27.6
Table 3.4: Frequencies and Percentages of Severity Indicators
Independent variable: Self-determination theory
To measure the independent variable of type of motivation (internal or external) I
recoded responses to the question “what is the most important reason you are in
treatment?” into three categories: internal, external, or unidentified. There were 57
possible responses for each of the questions: responses were recorded as open-ended
questions and then coded into a fixed category. Examples of external motivation include
“drug availability”, “custody issues with children”, and “court”. Examples of internal
motivation include “disgusted with lifestyle”, “fear”, and “wanting to get off drugs”.
Unidentified responses were responses that could have fallen into either internal or
external motivation, such as religious reasons. A total of 47 of the possible responses
61
were coded as external, seven of the possible responses were coded as internal, and three
of the possible responses were coded as undecided (See Appendix A).
The question “What is the most important reason you are in treatment?” was
asked three times to identify the most important reason, second most important reason,
and the third most important reason. Based on the responses to the three questions, a
respondent could have endorsed three external responses, three internal responses, or
could have fallen in the middle. Responses that were considered external were recoded
as a negative number. Responses were summed from the recoded responses for the three
questions, to create a motivation continuum, a scale ranging from –3 (totally external) to
+3 (totally internal).
Dependent variable: Stages of change
The stages of change were assessed at the three-month interview, at which time
the sample size was dramatically reduced and the vast majority of the respondents were
in the action stage. Measuring the stages of change at three-months and not at the time of
assessment does not give a good indication of where a person was when they began
treatment. The stages of change definition outlines a time frame for each stage of
change: for example, people in the preparation stage are likely to take action in the next
30 days, and people in the action stage have already taken some steps toward behavior
change. People may have progressed to a different stage of change by the three-month
interview, and there is no way to tell if a change in stage occurred or if a person is in the
same stage they were in at intake. Because the stages of change were not formally
assessed until the three-month interview, a proxy of the stages of change was created
from the initial two interviews. Four questions were used from the CMRS
62
(Circumstances, motivation, readiness, and suitability) scale (DeLeon, 1997) to determine
if a participant was in the precontemplation stage or the contemplation stage.
If a participant responded “not at all” to the statement “My drug use is a very
serious problem in my life, and responded “very much agree” to the statement “I don’t
really need treatment, I’m here because of pressure on me”, they were categorized in the
precontemplation stage. If a participant responded “agree somewhat” or “very much
agree” to “I feel that my drug use and the way I’ve been living have hurt a lot of people”,
“I am really tired of using drugs and want to change”, and “I really do need to be
completely drug free in order to live the way I want to”, and “My drug use is a very
serious problem in my life”, they were categorized in the contemplation stage.
To be classified in the action stage, participants needed to have taken some action
toward changing their drug/ alcohol use in the recent past. Participants were asked if they
had attended AA or NA in the past 30 days and/or had participated in treatment in the
past 30 days. If the response to any of these statements was “yes”, the participant was
categorized in the action stage. See Table 3.5.
Stage of change and source of motivation
Respondents were categorized into three stages of change: precontemplation,
contemplation, and action. Approximately two-thirds of the respondents (65.6%) were in
the contemplation stage, approximately one-third were in the action stage (32.9%) and
1.5% were in the precontemplation stage. See Table 3.6.
63
ƒ
Statement
My drug use is a very serious
problem in my life.
Response
Not at all
Classification
Precontemplation
ƒ
I don’t really need treatment, I’m
here because of pressure on me.
Very much agree
Precontemplation
ƒ
I feel that my drug use and the way
I’ve been living have hurt a lot of
people.
Agree somewhat
Very much agree
Contemplation
ƒ
I am really tired of using drugs and
want to change.
Agree somewhat
Very much agree
Contemplation
ƒ
I really do need to be completely
drug free in order to live the way I
want to.
Agree somewhat
Very much agree
Contemplation
ƒ
My drug use is a very serious
problem in my life.
Agree somewhat
Very much agree
Contemplation
ƒ
Did you attend AA in the past 30
days?
Yes
Action
ƒ
Did you attend NA in the past 30
days?
Yes
Action
ƒ
Did you participate in any treatment
in the past 30 days?
Yes
Action
Table 3.5: Statement, Responses and Categorization for Stages of Change
64
Variable
Frequency
Percent
Stage of Change
Precontemplation
Contemplation
Action
129
5717
2873
1.5
65.6
32.9
Source of Motivation
Totally External
Slightly External
Slightly Internal
Totally Internal
492
3260
3051
1916
5.6
37.3
34.9
22.0
Table 3.6: Frequencies and Percentages of Stage of Change and Source of
Motivation
Respondents were also categorized into seven categories based on the source of
motivation, ranging from totally extrinsic (-3) to totally intrinsic (+3). 4.6% of the
respondents were in the totally extrinsic motivation category, and 22.0% had a totally
intrinsic source of motivation. Approximately one-third of the respondents each were in
the category of slightly internal (34.9%) and slightly external (37.3%).
Because of the low number of respondents in the somewhat external and
somewhat internal categories, these respondents were classified under the lower heading:
somewhat internal respondents were included with the slightly internal respondents, and
somewhat external respondents were included with the slightly external respondents. The
final source of motivation variable contains four levels: totally external, slightly external,
totally internal, and slightly internal.
65
Bivariate analysis: Source of motivation
To analyze the relationship between demographic information and the source of
motivation, I ran a series of crosstabs. Because the p value is sensitive to a large sample
size, additional criteria was used for statistical significance: the criterion for significance
was that the p < .05 and the effect size (phi) > .10 (Cohen, 1988). For purposes of
analysis, criminal justice status was recoded into two categories: no criminal justice
involvement and criminal justice involvement. Criminal justice status was the only
demographic indicator that was significant (p< .000, phi = .122) No other demographic
(gender, age at admission, ethnicity, source of income, educational level, marital status)
met both of the criterion for significance.
With regards to specific drug and alcohol use indicators, three met the criteria for
significance both with p < .05 and phi > .10: referral source (p < .000, phi = .238),
primary drug problem (p< .000, phi = .160), treatment modality (p < .000, phi = .150).
The number of previous treatments was not significant.
With regards to severity, the number of drugs used per week was statistically
significant (p < .000 and phi = .096) and the frequency of use was not significant
(p <.000, phi = .091). These two variables were combined to create overall severity,
which was categorized as low, moderate, or high. Overall severity was not significant
(p < .000, phi = .063). See Table 3.7. The specific distribution for each of the variables
can be found in Appendix B.
66
Variable
Demographic Information
Gender
Ethnicity
Marital status
Age
Educational Level
Major source of income
Criminal justice status
Alcohol and Drug Indicators
Primary drug
Treatment modality
Referral Source
Previous Treatment
Severity Indicators
Number of Drugs
Frequency of Use
Severity
Chi-square
DF
Phi
.188
.000
.000
.049
.178
.000
.000
3
9
18
18
21
21
3
.023
.067
.073
.049
.055
.080
.114**
.000
.000
.000
.000
33
9
33
9
.160**
.150**
.238**
.062
.000
.000
.000
12
12
6
.096**
.091
.063
** Significant at p < .05 and phi > .1
Table 3.7: Relationship between Source of Motivation and Key Indicators
Bivariate analysis: Stage of change
To analyze the relationship between demographic information and the stages of
change, I ran a series of crosstabs. Criminal justice status was the only demographic
indicator that was significant (p < .000, phi = .113). No other demographic (gender, age
at admission, ethnicity, source of income, educational level, and marital status) met both
of the criterions for significance.
67
Variable
Demographic Information
Gender
Ethnicity
Marital status
Age
Educational Level
Major source of income
Criminal justice status
Alcohol and Drug Indicators
Primary drug
Treatment modality
Referral Source
Previous Treatment
Severity
Number of Drugs
Frequency of Use
Overall Severity
Chi-square
DF
Phi
.21
.000
.000
.000
.033
.409
.000
2
6
12
12
14
14
2
.030
.082
.075
.075
.054
.041
.096**
.000
.000
.000
.000
22
6
22
6
.246**
.218**
.196**
.175**
.000
.000
.000
8
8
6
.155**
.106**
.108**
** Significant at p < .05 and phi > .1
Table 3.8: Relationship between Stages of Change and Key Indicators
With regards to specific drug and alcohol use indicators, each of the four
indicators met the criteria for significance both with p < .05 and phi > .10: referral source
(p < .000, phi = .238), primary drug problem (p < .000, phi = .160), treatment modality (p
< .000, phi = .150), and previous treatment (p < .000, phi = .175).
With regards to severity, both the number of drugs used weekly (p < .000 and
phi = .155) and the frequency of use (p < .000 and phi = .106) were significant. Overall
severity was significant (p < .000, phi = .108).
68
Multinomial logistic regression
I created a model using the indicators that were statistically significant and
performed a multinomial logistic regression. Stage of change was regressed on the
variables included in the model: source of motivation, drug of choice, treatment
modality, legal status, referral source, number of prior drug treatments, and severity. To
model an outcome variable with multiple levels (three stages of change), two equations
were computed that estimated log odds. I used the “action” stage of change as the
baseline category because it had the largest sample size.
Multinomial logistic regression uses the chi-square as a test of the overall
significance of the model. The model was statistically significant (χ² = 712.852, df = 34,
p < .000). Based on the likelihood ratio test, each of the factors in the model were
significant. See Tables 3.9 and 3.10.
Model
Intercept
Only
Final
-2 log
likelihood
6370.990
Chi-square
Df
Sig.
5658.137
712.852
34
.000**
** p < .05
Table 3.9: Model Summary for Multinomial Logistic Regression
69
Effect
Intercept Only
Previous
treatment
Motivation source
Severity
Drug of Choice
Treatment
Modality
Legal Status
Referral Source
-2 log likelihood
5658.137
5803.610
Chi-square
.000
145.473
Df
0
2
Sig.
.000**
5696.610
5687.177
5704.859
5806.178
38.083
29.040
46.721
148.041
6
4
8
6
.000**
.000**
.000**
.000**
5672.379
5705.866
14.242
47.728
2
6
.001**
.000**
** p < .05
Table 3.10: Likelihood Ratio Tests for Multinomial Logistic Regression
Precontemplation vs. action
With regards to motivation source, people with external motivation sources were
more likely to be in the precontemplation than people with totally internal motivation
sources. People with totally external sources were 9.4 times more likely to be in the
precontemplation stage than the action stage, and people with a slightly external source
were 13 times to be precontemplation stage than the action stage.
With regards to alcohol and drug indicators, people with the primary drug of
marijuana were 6.5 times more likely to be in the precontemplation stage than people
with ‘other’ as their primary drug. People in the precontemplation stage were less likely
to be in residential (.4 times) or short-term inpatient treatment (.2 times) than in
outpatient drug free and were 6.0 times more likely to be in methadone maintenance than
in outpatient drug free. For every one previous treatment increase a person is .5 times
less likely to be in the precontemplation stage. People with the legal system as their
primary referral source were 12.7 times more likely to be in the precontemplation stage
70
than those with family/friends as the primary referral source. People with work /
community as their primary referral were 5.1 times more likely to be in the
precontemplation stage than those with family/friends as the primary referral source.
With regards to severity, people with low severity were 3.9 times more likely to
be in the precontemplation stage than people with high severity.
Contemplation vs. action
People in the contemplation stage were more likely to have slightly external and
slightly internal sources of motivation than totally internal sources. People with slightly
external sources of motivation were 1.2 times more likely to be in the contemplation
stage, and people with slightly internal sources were 1.3 times more likely to be in the
contemplation stage. With regards to criminal justice status, people with no legal status
were 1.2 times more likely than people with legal status to be in the contemplation stage
than the action stage.
With regards to alcohol and drug indicators, people with the primary drug of
marijuana were 1.65 times more likely to be in the contemplation stage and people with
opiates as their primary drug were 1.4 times more likely to be in the contemplation stage
than people in with ‘other’ as their primary drug. People in the contemplation stage were
3.3 times more likely to be in methadone maintenance than in outpatient drug free. For
every one previous treatment increase a person is .9 times less likely to be in the
contemplation stage. People with referral source of self and community/work were less
likely (1.3 times and 1.4 times respectively) to be in the contemplation stage than those
with family/friends as primary referral. People with low severity were .2 times less likely
to be in the contemplation stage than those with high severity.
71
Predictors
Source of Motivation
Totally External
Slightly External
Slightly Internal
Totally Internal
Demographics
Criminal Justice Status
Legal
No Legal
Drug and Alcohol Indicators
Primary Drug
Alcohol
Marijuana
Cocaine
Opiates
Other
Treatment Modality
Residential
Short-term Inpatient
Methadone Maintenance
Outpatient Drug Free
Previous Treatment
Referral Source
Self
Community / work
Legal
Family / friends
Severity
Low
Moderate
High
Precontemplation vs
Action
Contemplation vs Action
B
OR
B
OR
2.238**
2.565**
1.290
--
9.375
13.003
3.634
--
.034
.196**
.231**
--
1.034
1.217
1.260
--
-.570
-1.767
-.207**
-1.229
.682
1.870**
-.207
-.074
--
1.978
6.485
.813
.929
--
.014
.500**
.197
.313**
--
1.014
1.649
1.218
1.367
--
-1.027**
-1.851**
1.969**
--.723**
.358
.157
7.162
-.485
.048
.121
1.190**
--.075**
1.049
1.129
3.289
-.914
.059
1.622**
2.540**
--
1.061
5.062
12.684
--
-.192**
-.291**
-.041
--
.731
.639
.821
--
1.364**
.730
--
3.912
2.075
--
-.241**
.047
--
.786
1.048
--
Model Chi-Square (df) = 712.852**(34)
Cox and Snell pseudo R2 = .086
** p < .05
Table 3.11: Unordered Multinomial Logistic Regression for Multiple Outcomes
72
Data analysis: Hypothesis 2
To test the relationship between source of motivation and treatment outcomes, I
used logistic regression. A stratified sampling was done at the 12-month follow-up, and a
total of 2966 participants were interviewed at the 12- month follow-up. Of the
respondents completing the 12-month follow-up, 731 participants were included in the
final analysis, having valid responses for key variables included in the final analysis.
Tables 3.12, 3.13, and 3.14 provide a comparison of the original sample from Intake one
and two (n=8719) and the 12- month follow-up sample (n = 731).
The two samples were similar with regards to most of the demographic indicators,
alcohol and drug indicators, and severity indicators. The major differences in the two
samples were related to educational level, major source of income, and referral source. A
considerably higher percentage of respondents completed high school in the intake
interview than in the 12-month follow-up interview (31.8% at intake and 24.6% at 12months). A higher percentage of respondents cited legal work as the major source of
income at the 12-month follow-up than at intake (60.5% at 12-month follow-up and
42.2% at intake), and a higher percentage of respondents cited public assistance as the
major source of income at intake (20.6%) than at 12-months (8.6%). The difference from
intake to follow-up may be that individuals with legal work may have been easier to
contact at follow-up than respondents that cited other options as the major source of
income: people with legal work may have moved less than people in the other categories.
73
Variable
Intake
N = 8719
12-month
Follow-up
N = 731
Gender
Male
Female
Ethnicity
African American
Caucasian / white
Hispanic
Other
Marital Status at Intake
Never Married
Married
Divorced
Living as married
Separated
Widowed
Age at Admission
18-20
21-25
26-30
31-35
36-44
45+
Educational Level
High School Degree
High School
Some College
Grade School or Less
College / Associate Degree
College Degree
Advanced Degree
Major Source of Income
Legal Work
Public Assistance
Illegal Sources
Family/Friends
Social Security
No Income
Other
Blank
66.1
33.9
72.6
27.2
47.0
38.3
12.3
2.4
42.1
46.5
8.6
2.5
45.3
19.3
14.1
12.2
7.5
1.4
42.8
20.2
16.0
11.8
8.2
.5
3.2
14.2
24
26.3
26.2
6.1
2.9
11.6
25.2
29.1
26.5
4.4
38.1
31.9
17
4.3
4.2
3.7
0.7
39.9
24.6
20.4
3.0
4.5
6.2
1.1
42.2
20.6
14.8
6.7
4.7
4.5
1.6
5.0
60.5
8.6
17.2
6.3
2.2
1.2
2.1
1.6
Continued
Table 3.12: Percentage Distribution of Demographic Indicators of Respondents at Intake
and 12- month Follow-up
74
Table 3.12: Continued
Criminal Justice Status
No Legal Status
Legal Status
55.1
44.7
58.5
40.9
Another major difference was having the legal system as a referral source. 21.7%
of respondents identified the legal system as their referral source at intake and 3.8% of
the respondents identified the legal system as their referral source at the 12-month
follow-up. One reason for this difference may be that the legal system may have been
involved for only a brief time, or people with legal system involvement may have been
more difficult to locate for the follow-up.
75
Intake
N = 8719
Variable
12-month
Follow-up
N = 731
Primary Drug Problem
Cocaine/crack
Alcohol
Marijuana
Opiates
Other
51.5
21.1
3.1
20.7
4.5
58.5
12.3
3.1
19.3
4.8
Treatment Modality
Residential
Short-term Inpatient
Outpatient Drug Free
Methadone Maintenance
28.1
31.9
24.7
15.3
25.4
40.1
19.0
15.2
Previous Treatment
0
1
2-6
7+
44.9
20.7
25.7
8.6
41.3
18.1
30.0
10.4
Referral Source
Family / Friends
Self
Legal System (including
31.2
33.9
21.7
35.8
33.1
3.8
3.0
3.0
6.2
0.2
0.6
4.3
3.8
5.3
.4
1.0
probation/parole)
School/Employer
Medical Service
Community Agency
Veteran
Other
Table 3.13: Percentage Distribution of Alcohol and Drug Indicators of
Respondents at Intake and 12- month Follow-up
76
Variable
Frequency of Primary Drug Use
2 + times per day
Daily or almost every day
1-6 times per week
Less than once per week
None
Number of Drugs Used Weekly
0
1
2
3
4 or more
Overall Severity
Low
Moderate
High
Intake
N = 8719
12-month
Follow-up
N = 731
25.7
23.4
28.2
10.1
4.7
29.1
26.5
31.9
7.8
1.6
12.1
28.9
34.9
17.3
6.8
4.8
25.2
40.6
19.7
9.4
12.7
51.8
27.6
6.8
55.8
34.3
Table 3.14: Percentage Distribution of Severity Indicators of Respondents at
Intake and 12- month Follow-up
Characteristics of the sample
Gender, ethnicity, marital status, age at admission, educational level, major source
of income, and criminal justice status were analyzed as demographic information. The
majority of the participants were male (72.6.1%). With regards to ethnicity, 42.1% of the
respondents were African American, 46.5% were Caucasian, and 8.6% were Hispanic.
With regards to marital status, 42.8% reported having never married, 20.2% were
married, 16.1% were divorced, and 11.8% were living as married. The majority of the
77
respondents were over age 30 (50.0%) with a mean age of 32.52 (sd 6.799). 39.9% of the
respondents had a High School Degree and 27.6% had less than a high school degree.
The majority of the respondents (60.2%) identified the major source of income as legal
work, and about one-fifth (20.6%) stated that illegal sources were the major source of
income. The majority of the respondents had no legal status (58.5%). See Table 3.15.
Drug and alcohol indicators
Primary drug problem, number of prior treatments, referral source, treatment
modality, and length in treatment were the alcohol and drug indicators selected. The
majority of respondents (58.5%) identified crack/cocaine as the primary drug problem,
followed by alcohol (12.3%), opiates (19.3%), marijuana (3.1%), and other (4.8). The
average number of prior treatments was 2.30 (SD 4.291) with slightly less than half of the
participants (41.3%) reporting having no previous treatment. Of the respondents, 18.1%
reported having one previous treatment, and 30.0% identified having two to six prior
treatments. About one-third of the participants identified their primary referral source as
self (33.1%), about one-third were referred by family/friends (35.8%), and 3.8% were
referred by the legal system. Short-term inpatient was the most common treatment
(40.1%), followed by residential (25.4%), outpatient drug free (19.0%) and methadone
maintenance (15.2%). See Table 3.16.
78
Variable
Gender
Male
Female
Ethnicity
African American
Caucasian / white
Hispanic
Other
Marital Status at Intake
Never Married
Married
Divorced
Living as married
Separated
Widowed
Age at Admission
18-20
21-25
26-30
31-35
36-44
45+
Educational Level
High School Degree
High School
Some College
Grade School or Less
College / Associate Degree
College Degree
Advanced Degree
Major Source of Income
Legal Work
Public Assistance
Illegal Sources
Family/Friends
Social Security
No Income
Other
Blank
Criminal Justice Status
No Legal Status
Legal Status
Frequency
Percent
531
198
72.6
27.2
308
340
63
18
42.1
46.5
8.6
2.5
313
148
117
86
60
4
42.8
20.2
16.0
11.8
8.2
.5
21
85
184
213
194
32
2.9
11.6
25.2
29.1
26.5
4.4
292
180
149
22
33
45
8
39.9
24.6
20.4
3.0
4.5
6.2
1.1
442
63
126
46
16
9
15
12
60.5
8.6
17.2
6.3
2.2
1.2
2.1
1.6
430
299
58.5
40.9
Table 3.15: Frequencies and Percentages of Demographic Information
79
Number
Variable
Primary Drug Problem
Cocaine/crack
Alcohol
Marijuana
Opioids
Other
Percent
428
90
22
141
35
58.5
12.3
3.1
19.3
4.8
Treatment Modality
Residential
Short-term Inpatient
Outpatient Drug Free
Methadone Maintenance
186
293
139
111
25.4
40.1
19.0
15.2
Previous Treatment
0
1
2-6
7+
302
132
219
76
41.3
18.1
30.0
10.4
Referral Source
Family / Friends
Self
Legal System (including
262
242
28
35.8
33.1
3.8
31
28
39
3
7
4.3
3.8
5.3
.4
1.0
probation/parole)
School/Employer
Medical Service
Community Agency
Veteran
Other
Table 3.16: Frequencies and Percentages of Alcohol and Drug Indicators
80
Severity indicators
Two severity indicators were analyzed: frequency of use and multiple drug use.
With regards to frequency of use, 29.1% reported that they used their primary drug two
or more times per day, 26.5% reported using daily or almost every day, 31.9% reported
using one to six times per week, and 7.8% reported using less than once a week, and
1.6% reported no use. The number of drugs used weekly ranged from zero to eight:
4.8% indicated using zero drugs weekly, 25.2% reported using one drug weekly, 40.6%
reported using two drugs weekly, 19.7% used three drugs weekly, 9.4% used four to eight
drugs weekly. See Table 3.17.
Variable
Frequency of Primary Drug Use
2 + times per day
Daily or almost every day
1-6 times per week
Less than once per week
None
Number
Number of Drugs Used Weekly
0
1
2
3
4 or more
Percent
213
194
233
57
12
29.1
26.5
31.9
7.8
1.6
35
184
297
144
69
4.8
25.2
40.6
19.7
9.4
Table 3.17: Frequencies and Percentages of Severity Indicators
81
Dependent variable: Treatment outcome
The 12-month follow-up interview provided the dependent variable, treatment
outcome. The question was asked, “Did you complete treatment?” The possible
responses were “still in treatment”, “completed”, and “left before completing treatment”.
I used the responses “completed” and “left before completing treatment” in the data
analysis. The remaining responses were coded as missing.
Independent variable: Source of motivation
My second hypothesis states that treatment outcomes will differ by the strength of
the motivation source at intake: people with high levels of motivation (either internal or
external) will have better treatment outcomes than people with lower levels of motivation
(either internal or external). The independent variable, motivation, was coded as four
levels in the previous analysis: highly external, slightly external, slightly internal, and
highly internal. These responses were recoded into a two level variable: high motivation
and low motivation. “Highly external” and “highly internal” were recoded as “high
motivation”, and “slightly external” and “slightly internal” were recoded as “low
motivation”.
82
Variable
Treatment Outcome
Completed
Did not complete
Source of Motivation
High
Low
Frequency
Percent
443
225
60.6
30.8
226
503
30.9
68.8
Table 3.18: Frequencies and Percentages of Treatment outcome and Source of
Motivation
Severity: Major life areas
To determine severity at intake, three areas were analyzed: employment,
psychological barrier, and alcohol/drug use severity. Employment severity was
determined based on three questions: “How many weeks did you work full time during
the 12-months prior to admission?”, “Did you have problems due to drugs getting a job,
holding a job, or working?”, and “How serious were your job problems due to
drug/alcohol use?”. The responses were combined into a continuous composite variable
ranging from zero to one, with composite scores nearing zero designating the more severe
employment problems. Scores ranged form .28 to .92 with a mean employment score of
.475 (sd .14).
The psychological severity scale was determined by the overall depression,
anxiety, and suicidal ideation scores. The Problem Severity Index (PSI) is a derivative of
the Addiction Severity Index (McLellan et al, 1992), and scores “indicators to reflect
‘problems’” (Simpson, Joe, Fletcher, Hubbard, and Anglin, 1999, p. 509). The PSI index
score with regards to a psychological barrier reflects having a score higher than the
83
median on the Symptom Checklist 90 depression (1.5) or anxiety scales (1.0) or having
suicidal ideation (Simpson, et al, 1999). These three components were combined to
create a two-level variable, either having a psychological barrier or not.
As in the previous analysis, drug and alcohol severity was created using the
number of drugs used and the frequency of drug use. The levels of severity were low,
moderate, and high. See Table 3.19.
Variable
Psychological Barrier
Yes
No
Severity
Low
Moderate
High
Frequency
Percent
488
243
66.8
33.2
50
408
251
6.8
55.8
34.3
Table 3.19: Frequencies and Percentages of Severity in Major Life Areas
Bivariate analysis: Treatment completion
With regards to the relationship between treatment completion and demographic
information, criminal justice status and major source of income were significant (p = .001
and p< .000 respectively). No other demographic (gender, age at admission, ethnicity,
source of income, educational level, and marital status) was significant.
With regards to specific drug and alcohol use indicators, three of the four
indicators met the criteria for significance: primary drug problem (p = .030), treatment
modality (p < .000), and previous treatment (p = .041). Referral source was not
84
significant. With regards to severity, the frequency of use (p = .039) was significant. The
number of drugs used weekly and overall severity was not significant (p = .289 and
p = .330 respectively). Psychological severity was not significant (p = .116).
Variable
Demographic Information
Gender
Ethnicity
Marital status
Age
Educational Level
Major source of income
Criminal justice status
Alcohol and Drug Indicators
Primary drug
Treatment modality
Referral Source
Previous Treatment
Severity
Number of Drugs
Frequency of Use
Severity
Psychological severity
Chi-square
DF
.493
.237
.130
.746
.543
.000**
.001**
1
3
3
5
6
4
1
.030**
.000**
.109
.041**
4
3
3
3
.289
.039**
.330
.116
2
4
2
1
** Significant at p < .05
Table 3.20: Relationship between Treatment Outcomes and Key Indicators
85
Bivariate analysis: Source of motivation
Criminal justice status was the only demographic indicator that was significant
(p= .011). No other demographic (gender, age at admission, ethnicity, source of income,
educational level, marital status) met the criteria for significance.
With regards to specific drug and alcohol use indicators, three of the four
indicators met the criteria for significance: referral source (p = .006), primary drug
problem (p =.046), treatment modality (p = .001). Previous treatment was not significant
(p = .560). With regards to severity, the number of drugs use, the frequency of use, and
overall severity were not significant.
Variable
Demographic Information
Gender
Ethnicity
Marital status
Age
Educational Level
Major source of income
Criminal justice status
Alcohol and Drug Indicators
Primary drug
Treatment modality
Referral Source
Previous Treatment
Severity
Number of Drugs
Frequency of Use
Overall Severity
Chi-square
DF
.430
.160
.735
.826
.287
.659
.011**
1
3
3
5
6
4
1
.046**
.001**
.006**
.560
4
3
4
3
.331
.864
.330
2
4
2
** Significant at p < .05
Table 3.21: Relationship between Motivation Source and Drug/Alcohol Indicators
86
Logistic regression
For analysis of the full model, I used logistic regression. I created a model using
the main independent variable, source of motivation, and indicators that were statistically
significant in the bi-variate analysis. Treatment outcomes (treatment completed or not
completed) were regressed on motivation source and other significant variables:
employment severity, criminal justice status, primary drug of choice, treatment modality,
previous treatment, and frequency of use. Major source of income was the only variable
that was significant in the bi-variate analysis but not included in this model, as there is a
significant correlation between employment and the source of income (χ² = -.316,
p < .000). Logistic regression was used because the dependent variable had two levels.
Logistic regression uses the chi-square as a test of the overall significance of the
model. The overall model with all of the variables included was significant
(χ² = 182.867, df = 14). The number of correctly classified observations increased from
66.2 in the constant-only model to 75 in the model with the variables included: there
were 35% fewer errors in the full model than in the constant only model.
The variables were entered in two blocks: the first block contained the covariates employment severity, criminal justice status, primary drug of choice, treatment
modality, previous treatment, and frequency of use. The second block contained the
independent variable, source of motivation.
The total number in the final analysis was 645 due to missing values. The initial
-2 log likelihood for the constant-only model was 829.019; the -2 log likelihood for the
model including the covariates was 646.098 (χ² = 182.021, df = 14, p < .000).
87
The -2 log likelihood for the model with the covariates and independent variable was
646.051 (χ² = .869, df = 1, p = .351), and the overall model remained significant
(χ² = 182.996, df = 15, p < .000).
Model
Block 0: Constant Only
Block 1: Covariate
Block 2: IV
Final full model
-2 Log
Likelihood
825.200
645.725
644.932
Chisquare
179.475
.793
180.268
df
14
1
15
Significance
.000**
.373
.000**
** p < .05
Table 3.22: Model Fitting Information for Logistic Regression
The Hosmer and Lemeshow test for goodness of fit shows how well the model
fits. When the Hosmer and Lemeshow test is less than .05, the null hypothesis is
rejected (the null hypothesis states that there is no difference between the observed model
and the predicted model values of the dependent variable). Values on this test greater
than .05 indicate a better fitting model. In both blocks, the Hosmer and Lemeshow test
for goodness of fit was > .05 (.392 in block 1 and .742 in block 2), indicating goodness of
fit for both of the models.
In the final model, only treatment modality was a significant predictor of
treatment outcomes. When compared to individuals in out-patient drug free treatment,
individuals in methadone maintenance were 8.8 times more likely to complete treatment,
people in short-term inpatient were .2 times less likely to complete treatment, and people
88
in residential treatment were 2.6 times more likely to complete treatment. The
independent variable, source of motivation, was not a significant predictor of treatment
outcomes.
Predictor
Primary drug
Alcohol
Marijuana
Cocaine
Opioids
Other
Previous Treatment
Frequency of use
None
Less than once per week
1-5 times per week
Daily or almost daily
2 or more times per day
Legal Status
Treatment Modality
Residential
Short-term inpatient
Methadone maintenance
Outpatient drug free
Employment
Source of Motivation
Constant
**P < .05
Beta
SE
-.514
-.571
.464
-1.024
-.002
.558
.775
.497
.608
-.023
-1.281
-.273
-.440
-.380
--.203
1.182
.397
.262
.264
-.204
.941
-1.616
2.178
--.039
-.195
-.187
.259
.285
.503
-.741
.218
.668
Wald’s
20.923
.848
.543
.871
2.837
-.006
4.018
1.174
.475
2.820
2.068
-.991
109.681
13.206
32.118
18.742
-.003
.793
.078
df
4
1
1
1
1
-1
4
1
1
1
1
-1
3
1
1
1
-1
1
1
P
.000
.357
.461
.351
.092
-.939
.404
.278
.491
.093
.150
-.320
.000**
.000**
.000**
.000**
-.959
.373
.780
Odds
ratio
.598
.565
1.590
.359
-1.002
.278
.761
.644
.684
-.816
2.563
.199
8.832
-.962
.832
.830
Hosmer and Lemeshow test χ² = 5.141, df = 8, p = .742; Cox and Snell R² = .246, Nagelkerke R² = .341
Table 3.23: Logistic Regression Analysis: Treatment Outcome Regressed on
Key Indicators
89
Hypothesis 2b
To test the third hypothesis of the relationship between use of alcohol/drugs
within the 12-months after treatment started and motivation, I used logistic regression.
The dependent variable, use, was created as a two-level variable: use or no use. The
question “have you used a substance in the past 12 months?” was asked for each drug and
alcohol. A “yes” response to any of these questions was coded as “use”. The
independent variable was measured as a two-level variable as well: high or low
motivation. The sample used to test this hypothesis was the same sample that was used to
test hypothesis 2a.
Variable
Treatment Outcome: Use
Use
Did not Use
Source of Motivation
High
Low
Frequency
Percent
520
209
71.3
28.7
226
503
30.9
68.8
Table 3.24: Frequency and Percentage of Use and Source of Motivation
Bivariate analysis: Use
With regards to the relationship between use of drugs and/or alcohol and
demographic information, ethnicity was the only indicator that was significant (p = .050).
No other demographic indicator (gender, age at admission, source of income, educational
level, marital status, criminal justice status) was significant.
90
With regards to specific drug and alcohol use indicators, two of the four indicators
met the criteria for significance: primary drug problem (p = .020) and treatment modality
(p = .001). Referral source and number of previous treatments were not significant. With
regards to severity, none of the indicators were significant.
Variable
Demographic Information
Gender
Ethnicity
Marital status
Age
Educational Level
Major source of income
Criminal justice status
Alcohol and Drug Indicators
Primary drug
Treatment modality
Referral Source
Previous Treatment
Severity
Number of Drugs
Frequency of Use
Severity
Psychological severity
Chi-square
DF
.551
.050**
.485
.076
.911
.481
.704
1
3
3
5
6
4
1
.020**
.001**
.877
.441
4
3
3
3
.495
.721
.548
.580
2
4
2
1
** Significant at p < .05
Table 3.25: Relationship between Use and Severity Indicators
The variables were entered in two blocks: the first block contained the covariates primary drug of choice, treatment modality, and ethnicity. The second block
contained the independent variable, source of motivation.
91
The total number in the final analysis was 731. The initial -2 log likelihood for
the constant-only model was 853.825; the -2 log likelihood for the model including the
covariates was 826.808 (χ² = 27.018, df = 10, p = .003). The -2 log likelihood for the
model with the covariates and independent variable was 826.759 (χ² = .049, df = 1,
p = .825), and the overall model remained significant (χ² = 27.067, df = 11, p = .004).
Model
Block 0: Constant Only
Block 1: Covariate
Block 2: IV
Final full model
-2 Log
Likelihood
853.825
826.808
826.759
Chisquare
27.018
.049
27.067
df
10
1
11
Significance
.003**
.825
.004**
**P < .05
Table 3.26: Model Fitting Information for Logistic Regression
In both blocks, the Hosmer and Lemeshow test for goodness of fit was > .05 (.529
in block 1 and .462 in block 2), indicating goodness of fit for both of the models.
In the final model, only treatment modality was a significant predictor of use.
Participants in methadone maintenance were 2.7 times more likely to have used than
people in outpatient drug free programs. The independent variable, source of motivation,
was not a significant predictor of use of drugs/alcohol. See Table 3.27.
92
Predictor
Primary drug
Alcohol
Marijuana
Cocaine
Opioids
Other
Treatment Modality
Residential
Short-term inpatient
Methadone maintenance
Outpatient drug free
Race
Caucasian
African American
Hispanic
Other
Source of Motivation
Constant
**P < .05
Beta
SE
.850
.688
.330
.316
--
.440
.626
.381
.455
--
-.194
.158
.990
--
.245
.234
.411
--
.432
.219
-.115
--.041
.166
.526
.524
.580
-.186
.658
Wald’s
4.861
3.724
1.208
.752
.482
-10.182
.622
.455
5.811
-3.912
.675
.175
.040
-.049
.064
df
4
1
1
1
1
-3
1
1
1
-3
1
1
1
-1
1
P
.302
.054
.272
.386
.487
-.017**
.430
.500
.016
-.271
.411
.676
.825
-.825
.801
Odds
ratio
2.339
1.990
1.391
1.372
-.824
1.171
2.691
-1.540
1.245
.690
-.960
1.181
Hosmer and Lemeshow test χ² = 7.714, df = 8, p = .462; Cox and Snell R² = .037, Nagelkerke R² = .053
Table 3.27: Logistic Regression Analysis: Use Regressed on Key Indicators
93
CHAPTER 4
DISCUSSION
The primary purpose of this study was to examine the relationship between Selfdetermination theory and the Transtheoretical Model of Change. For analysis, I used the
stages of change (precontemplation, contemplation, and action) to represent the
Transtheoretical Model of Change and source of motivation (internal and external
motivation) to represent Self-determination theory. Additionally, this study examined the
relationship between source of motivation from Self-determination theory and treatment
outcomes.
Both Self-determination theory and the Transtheoretical Model of Change
primarily address motivation, and both of these theories together may provide a more
comprehensive view of a substance abuser in treatment. There is a significant
relationship between a person’s source of motivation and the stage of change they are in
at intake. With regards to treatment outcomes, no significant difference was found
between the source of motivation and treatment outcomes, measured either as treatment
completion or use of substances after intake.
Relationship between stage of change and source of motivation
One of the primary goals of the study was to understand the relationship between
the stages of change and intrinsic/extrinsic motivation. Because people in the
precontemplation stage do not view their substance use as a problem, it was hypothesized
94
that people in this stage would be presenting for treatment due to external pressures.
Further, as the contemplation stage is characterized by having some recognition of a
problem but having ambivalence about change, it was hypothesized that people in the
contemplation stage would have a slightly external or slightly internal source of
motivation. Finally, because people in the action stage are characterized by having taken
some action in the past 30 days, it was hypothesized that people in the action stage would
have high levels of internal motivation.
The results of the data analysis suggest that the stage of change is significantly
related to the source of motivation. Specifically, people with highly external sources of
motivation were significantly more likely to be in earlier stages of change
(precontemplation and contemplation) than people with highly internal sources of
motivation. Similarly, people with high internal motivation sources were more likely to
be in later stages (contemplation and action) than in the precontemplation stage of
change.
The significance of the source of motivation and stage of change is reflected in
the definitions of each stage of change. Precontemplators do not have an awareness that
there is a problem, so it stands to reason that people in this stage would have an outside
influence prompting them into treatment. People in the action stage have taken steps
toward behavior change and, by definition, have engaged in an activity to change the
behavior in the last 30 days. It may be that the steps that people in the action stage were
taking were not effective (or as effective as they wanted them to be) or that more
intensive assistance is needed to create lasting behavior change, reflecting a more
95
internalized source of motivation. The results of this study support the research that
suggests that the source of motivation is a determinant of the stage of change (O’Hare,
1996).
Other indicators were important in the analysis determining the relationship
between the stages of change and the source of motivation. For example, referrals from
the legal system were more likely to be in the precontemplation stage than people with
family/friends as their referral source. This supports the research that different types of
coercion have a different effect on people pursuing treatment, and that legal coercion may
differ from other types of coercion (Marlowe et al, 1996; Monahan et al, 1995).
Consequences related to family and friends referring a person to treatment may be more
important to an individual than consequences related to the legal system. For example, if
a person’s spouse is threatening to divorce the person if he/she doesn’t get treatment, this
may seem more severe than spending time in jail to that individual.
People who indicate that they have had previous treatment experience were less
likely to be in the precontemplation stage or contemplation stage than the action stage:
people that have had previous experience may have some insight that their substance use
is a problem and thus are further along in the stages of change than those with fewer or
no previous treatment. Further, people with previous treatment experience may also have
started attending 12-step meetings (AA, NA, CA) prior to re-entering formal treatment,
which would indicate that they are in the action stage.
With regards to severity, people with low severity were more likely to be in the
precontemplation stage and were less likely to be in the contemplation stage than people
with high severity. People with high severity may have more awareness of their
96
problems and may have seen their use evolve, as severity was measured with frequency
of use and number of substances used. People with high severity may also have more
consequences related to their use (health, legal, family, employment, etc.) and be more
action-oriented in changing their behavior to avoid suffering more consequences.
The Self-determination theory and the Transtheoretical Model of change are
significantly related to each other: more external sources of motivation are related to
earlier stages of change and more internal sources of motivation are related to later stages
of change. These two theories appear to complement each other, and creating a measure
utilizing components of both theories would be useful to help clients in substance abuse
treatment settings.
Source of motivation and treatment outcomes
A second goal of the research was to examine the relationship between source of
motivation and treatment outcomes. It was hypothesized that people with high levels of
external motivation or high levels of internal motivation would have better treatment
outcomes than people with low levels of external or internal motivation. The results of
this study found that source of motivation is not a significant predictor of treatment
outcomes. These findings are not supported by recent literature in which the source of
motivation is a predictor of treatment outcomes (Zeldman et al, 2004; Ryan et al, 1995).
However, other research has found similar results to the results in this study. For
example, Arahan et al (1965) found that motivation is not a significant predictor of
treatment outcomes in substance abusing populations.
97
One reason that the research hypothesis regarding treatment outcomes was
nonsignificant may be that the people that were still in treatment were not included in the
sample because the outcome of treatment was yet undetermined. People still in treatment
may either drop out or complete treatment, but at the time of data collection there was no
way to determine the final outcome of treatment. Further, because the 12-month followup instrument was delivered to a stratified sample of the original sample and only 731 of
the 2,966 had valid responses for key indicators, respondents that were not included in
the analysis may have had different sources of motivation and treatment outcomes.
Source of motivation and substance use after intake
Another goal of the research was to examine the relationship between source of
motivation and substance use after intake. It was hypothesized that people with high
levels of internal or external motivation would be more likely to be abstinent through and
after treatment, and that people with low levels of internal or external motivation would
be less likely to be abstinent through and after treatment. The results of this study found
that source of motivation is not a predictor of use after intake to a substance abuse
treatment program. Rapp et al (2003) found similar results in their study: motivation
was not a significant predictor of treatment outcomes.
The only significant difference that was found in use after starting a substance
abuse program was in treatment modality. There was a significant difference in the outpatient drug free treatment modality and methadone maintenance: people in methadone
maintenance programs were more likely to have used substances than people in
outpatient drug free. An anticipated difference would be that the people in the
methadone maintenance programs would significantly differ from each of the other three
98
treatment modalities due to the overarching goals of the programs: the process of
methadone maintenance is to maintain use over a long period of time to stabilize an
individual (Franey and Ashton, 2002). The other three treatment modalities have a
primary goal of abstinence.
Finding no significant relationship with regards to source of motivation and
treatment outcomes speaks to the dynamic, variable state definition of motivation:
motivation can and does change over time and is interactive with the environment.
Perhaps some sources of motivation were removed or lessened. For example, a person
that was on probation during intake may have been taken off of probation at the 12month follow-up, or an employer requiring random urine screens as a consequence at
intake may have stopped asking for random screens at 12-months.
Limitations of the study
This study has several limitations. Caution should be used when attempting to
generalize the results to other populations. The participants in this study were adults
seeking substance abuse treatment. Since there is a lack of empirical evidence that
substance abusers who seek treatment are similar to those who do not seek treatment, the
results of this study should not be generalized to the population of people with substance
abuse issues. Further, the correlational design used does not imply causality, and the
results should not be interpreted as such.
A limitation to this study is the Drug Abuse Treatment Outcome Study data. The
DATOS data was not a representative sample of the clientele in treatment or treatment
programs at the time data was collected (Franey and Ashton, 2002). Further, DATOS
99
focused on major cities to represent the major treatment modalities, so programs that
were not well defined or more rural programs were not included in the sampling frame.
Another limitation was the extensive data-gathering process. The intake
interview was broken up into two different interviews, and there were dropouts from the
time intake one was completed and the time intake two was completed. In the 12-month
follow-up interview a stratified sampling plan was used, and 62% of the targeted clientele
provided data (Franey and Ashton, 2002).
The types of treatment were divided into four modalities: residential, methadone
maintenance, drug-free outpatient, and short term inpatient. Within each type of
treatment, there was no monitoring of the actual treatment processes. The actual
treatment processes for each modality were not the focus of this study and it is important
to note that treatment outcomes may be affected by the treatment provided.
The measure of the stages of change may be a limitation to this study. The stages
of change data were not formally collected until the three-month follow-up, offering no
comparison from the initial interview to a point in time when an individual is already in
treatment. People that have been in treatment for three-months have been through at least
some of the processes of change and have had the opportunity to progress to a later stage
of change than when initially admitted to treatment.
Having a large sample size may impact the significant findings in this study. The
p value is sensitive to a large sample size and the significant findings may be a result of a
large sample size. Adding additional criteria, such as using phi, may strengthen the
significant findings.
100
A possible limitation of the data analysis is the discrepancy between the number
of people in the precontemplation stage (n = 129) and the number in the contemplation (n
= 5717) and action (n = 2873) stages. This could be in part due to coding responses and
creating a proxy measure.
Finally, the low number of responses able to be utilized in the data analysis from
the 12-month follow-up is a limitation. Of the 2966 completed interviews, 735
respondents had valid responses to key indicators that were used in the analysis.
Implications
The purpose of this study was to determine the nature of the relationship between
Self-determination theory and the Transtheoretical Model of Change. Clinically, the
findings have implications for treatment providers. Integrating components of both
theories to better understand the client’s motivation for treatment may allow for a more
comprehensive understanding of the client at assessment. Treatment may also be tailored
based on the source of motivation and the stage of change to help a client progress
successfully through treatment.
This study has implications for further development of treatment programs.
Knowing the source of motivation and determining the stage of change of an individual
allows for individualized treatment. Incorporating these characteristics of individuals may
not only assist the client, but could provide more cost-effective means of providing
treatment. Administrators in treatment centers should provide education for clinicians
and staff at drug and alcohol treatment centers to better tailor treatment to meet the needs
of each individual client.
101
Treatment centers must begin to take a more individualized approach to treatment.
Having an intake procedure that incorporates the stages of change and sources of
motivation are imperative. Knowing the referral source of an individual seeking
treatment is the first step in identifying the source of motivation, but the referral source is
not typically the only source of motivation for an individual nor is referral source often
seen as the most important reason to seek treatment. As Marlowe et al (1996) found, the
client’s definition of pressure to enter treatment was much different from the referral
source. Comprehensive measures need to be implemented in treatment centers to
discover motivation beyond the referral source.
This study also has implications for policy changes with regards to funding
treatment. Often, funding for treatment is limited. For example, insurance companies
may state in their policy “one treatment per lifetime” or “one treatment per year”. Also,
treatment centers may have policies for re-admission to their programs: if a person has
been in treatment several times over a period of time, the treatment center may not be
willing to accept the client for treatment again. The results of this study found that
people with more previous treatment experience were more likely to be in later stages of
change than people with few or no prior treatments. These findings support continued
funding for people who have had prior treatment admissions. Policies need to be
changed to reflect the possibility that people need to go through multiple treatments to
progress through the stages of change.
Social workers must be aware of their own biases when working with client’s
identified as being referred by an outside source such as the courts. (Typically, the
referral source is indicative of motivation to a clinician). The results of this study found
102
that there is no relationship between treatment outcomes or use after the initiation of
treatment and motivational source. Social workers must engage in therapy practices that
“meet the client where he/she is”, and not assume that because a person presents to
treatment at the demands of the legal system that treatment will be a success simply to
satisfy an outside requirement.
Future research
The relationship between the Transtheoretical Model of Change and Selfdetermination theory could be applied to other populations and subgroups.
Understanding a person’s source of motivation and stage of change may assist clinicians
in areas such as mental health and psychotherapy. More research is needed in different
clinical areas to expand the knowledge base surrounding these two theories.
Further research is needed on the impact of coercion on treatment outcomes.
Research on coercion and treatment outcomes has historically produced mixed results.
First, the operationalization of coercion needs to be a consistent definition to allow for
results to be compared. As Farabee et al (1999) found, the impact of external motivators
in treatment produces mixed results, and this study did not find a relationship between
treatment outcomes and high levels of external motivation.
The impact of the therapist on the client during treatment is a variable that has
been considered, both in research on motivation and in substance abuse treatment (Sterne
and Pittman, 1965; Miller and Rollnick, 2002). Further research involving the therapist /
client dyad is needed to better understand this relationship.
While many studies have focused on the effectiveness of treatment, fidelity to
treatment models is an important consideration for future research. In order to better
103
determine “what works” and best treatment practices, it is necessary to focus on the
treatment process and not just treatment outcomes.
104
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115
APPENDIX A
SOURCE OF MOTIVATION RECODING
116
DATOS
Value
1
2
3
9
11
12
13
14
19
21
22
23
24
25
26
29
31
32
33
34
35
36
37
39
41
42
43
44
49
51
52
53
54
DATOS
Label
Shortage of drugs available
Drugs of poor quality
Lost drug connection
Other problems with availability
Drugs cost too much / not support
habit
Not enough money to buy drugs
Not enough money to buy other
things
Wanted to be self-supporting
Other financial problems
Want to get off dugs
To cut down on the size of habit
Getting disgusted with lifestyle
Want to enter or stay in school
Want to find new friends
Became religious
Other desire to change lifestyle
Have drug related contagious
disease
Drugs (make/made) me sick
Afraid of getting AIDS, other
disease
Had health problems unrelated to
drugs
Pregnant or want to get pregnant
Want to improve my general
health
Want to improve my mental health
Other health reason
Want to save my
marriage/relationship
To improve my relations with
family
To avoid losing custody of
children
Want to get my children back
Other interpersonal reasons
To avoid being involved in
criminal acts
Want to avoid arrest
Court mandate
Have upcoming court heating
117
Recode
External
External
External
External
External
External
External
Internal
External
Internal
Internal
Internal
External
External
Undecided
Undecided
External
External
Undecided
External
Internal
Internal
Internal
External
External
External
External
External
External
External
External
External
External
59
61
62
63
69
71
72
73
75
75
76
77
78
79
81
82
83
84
85
86
87
88
89
91
Other legal reasons
To become eligible for pub
assistance
To become eligible for medical
services
To become eligible for job
services
Other access to services
Want to keep job or find better job
To prevent problems with my
supervisor
To prevent problems with my coworkers
Other job related problems
Do better in school
Prevent problems with
principal/teachers
Prevent problems with other
students
Condition of suspension
Other school related problems
Spouse/partner
Family
Friends
School
Job or employer
Legal (besides court mandate)
Treatment staff
Treatment clients
Other pressure
Other
118
External
External
External
External
External
External
External
External
External
External
External
External
External
External
External
External
External
External
External
External
External
External
External
External
APPENDIX B
DISTRIBUTION OF KEY INDICATORS ACROSS MAIN INDEPENDENT
AND DEPENDENT VARIABLES
119
Variable
Gender
Male
Female
Ethnicity
African American
Caucasian / white
Hispanic
Other
Marital Status at Intake
Never Married
Married
Divorced
Living as married
Separated
Widowed
Age at Admission
18-20
21-25
26-30
31-35
36-44
45+
Educational Level
High School Degree
High School
Some College
Grade School or Less
College / Associate Degree
College Degree
Advanced Degree
Major Source of Income
Legal Work
Public Assistance
Illegal Sources
Family/Friends
Social Security
No Income
Other
Blank
Criminal Justice Status
No Legal Status
Legal Status
Precontemplation Contemplation
Action
1.1
.3
43.3
22.3
21.6
11.3
.5
.7
.2
.1
31.7
23.6
8.8
1.4
14.8
14.0
8.6
.9
.7
.3
.3
.1
.1
0
29.1
13.1
8.4
8.8
5.0
1.0
15.5
5.9
5.4
3.3
2.5
.4
.1
.2
.3
.2
.4
.2
2.1
9.1
15.8
17.0
17.2
4.3
.9
4.8
7.9
9.2
8.5
1.6
.6
.5
.1
0
.1
.1
0
24.6
21.5
11.1
2.9
2.7
2.4
.4
12.9
9.9
5.8
1.4
1.4
1.2
.3
.7
.1
.1
.1
0
.1
0
.1
27
13.6
9.8
4.3
3
2.9
.1
3.5
14
6.8
4.7
2
2.2
1.5
.1
1.4
.4
1.1
38.1
27.5
16.6
16.4
Table B.1: Percentage Distribution of Demographic Indicators across Stages of Change
120
Variable
Primary Drug Problem
Cocaine/crack
Heroin
Alcohol
Marijuana
Opiates
Other
Precontemplation Contemplation
Action
.2
0
.2
.2
0
0
33.2
14.2
7.4
2
1.6
.21
18
4
4.5
.8
.6
.11
Treatment Modality
Residential
Short-term Inpatient
Outpatient Drug Free
Methadone
Maintenance
.2
.1
1.1
.1
17.3
21.1
14.4
12.7
10.6
10.7
9.2
2.5
Previous Treatment
0
1
2-6
7+
1.2
.2
0
0
32.2
13.4
15.4
4.6
11.5
7.2
10.3
4.0
Referral Source
Family / Friends
Self
Legal System (including
.1
.1
1
21.9
23
12.9
9.2
10.9
7.8
.1
.2
5.7
2
4.3
.8
probation/parole)
Community/Other
School /work
Table B.2: Percentage Distribution of Alcohol and Drug Indicators across Stage of
Change
121
Variable
Precontemplation Contemplation
Frequency of Primary Drug Use
2 + times per day
.1
19.3
Daily or almost every day
.1
17.3
1-6 times per week
.3
20.4
Less than once per week
.3
6.5
None
.1
3.0
Number of Drugs Used Weekly
0
.6
6.3
1
.5
19.1
2
.1
23.7
3
0
12.1
4 or more
0
4.4
Overall Severity
Low
.4
8.0
Moderate
.4
38.0
High
.9
20.5
Action
8.5
8.0
10
4.1
2.0
5.2
9.3
11
5.1
2.3
5.4
17.9
9.4
Table B.3: Percentage Distribution of Severity Indicators across Stage of Change
122
Variable
Gender
Male
Female
Ethnicity
African American
Caucasian / white
Hispanic
Other
Marital Status at Intake
Never Married
Married
Divorced
Living as married
Separated
Widowed
Age at Admission
18-20
21-25
26-30
31-35
36-44
45+
Educational Level
High School Degree
High School
Some College
Grade School or Less
College / Associate Degree
College Degree
Advanced Degree
Major Source of Income
Legal Work
Public Assistance
Illegal Sources
Family/Friends
Social Security
No Income
Criminal Justice Status
No Legal Status
Legal Status
Highly
External
Slightly
External
Slightly
Internal
Highly
Internal
3.5
2.2
24.8
12.5
23.2
11.8
14.6
7.4
2.1
2.4
1.0
.1
17.1
14.2
5.1
1.0
17.0
13.2
4.0
.8
10.7
8.5
10.7
.5
2.1
1.4
.8
.8
.4
.1
16.7
7.9
5.0
4.6
2.6
.4
16.5
6.0
4.8
4.2
2.9
.5
9.9
4.0
3.5
2.6
1.6
.3
.2
.9
1.3
1.3
1.5
.5
1.4
5.4
9.2
9.4
9.9
2.1
1.1
5.1
8.3
9.5
8.9
2.0
.5
2.8
5.1
6.2
5.9
1.5
2.2
1.8
.9
.2
.3
.2
0
13.9
12.5
6.1
1.8
1.6
1.3
.2
13.6
11.0
5.7
1.5
1.3
1.4
.3
8.4
6.6
4.3
.8
1.0
.8
.2
2.5
1.1
.6
.5
.3
.2
15.8
7.8
5.4
2.7
1.6
1.6
14.4
7.6
4.9
2.1
2.0
1.8
9.4
4.2
3.9
1.5
.9
.8
2.8
2.9
18.3
19.0
20.2
14.7
13.8
8.1
Table B.4: Percentage Distribution of Demographic Indicators across Motivation Source
123
Highly
External
Slightly
External
Slightly
Internal
Highly
Internal
Primary Drug Problem
Cocaine/crack
Alcohol
Marijuana
Opiates
Other
2.4
.8
.1
1.2
1.1
19.4
4.8
1.6
6.5
4.9
18.0
4.2
.9
8.6
3.3
12.7
2.6
.5
4.8
1.5
Treatment Modality
Residential
Short-term Inpatient
Outpatient Drug Free
Methadone
Maintenance
1.3
1.7
1.7
.9
9.9
11.7
11.0
4.7
9.6
10.3
8.9
6.2
7.2
8.2
3.1
3.4
Previous Treatment
0
1
2-6
7+
2.4
1.2
1.6
.5
17.3
8.1
8.9
3.1
16.3
7.0
8.9
2.8
9.0
4.4
6.4
2.2
Referral Source
Family / Friends
Self
Legal System
1.4
1.3
1.9
11.3
9.7
11.0
10.3
14.3
6.4
8.1
8.8
2.5
.8
.3
3.9
1.3
3.2
.9
2.1
.5
Variable
(including probation/parole)
Community/Other
School /work
Table B.5: Percentage Distribution of Alcohol and Drug Indicators across Motivation
Source
124
Variable
Frequency of Primary Drug
Use
2 + times per day
Daily or almost every
day
1-6 times per week
Less than once per week
None
Number of Drugs Used
Weekly
0
1
2
3
4 or more
Overall Severity
Low
Moderate
High
Highly
External
Slightly
External
Slightly
Internal
Highly
Internal
1.4
1.2
9.8
8.4
9.5
10.1
7.2
5.8
1.6
.7
.5
11.8
4.3
2.1
10.4
3.7
1.8
6.9
2.2
.7
1
1.7
1.7
.9
.3
5.3
10.5
12.8
6.5
2.3
4.0
10.4
12.2
5.9
2.4
1.6
6.3
8.2
4.1
1.8
1.0
2.8
1.5
5.5
20.4
10.5
4.9
20.2
10.4
2.4
12.9
7.6
Table B.6: Percentage Distribution of Severity Indicators across Motivation Source
125
Variable
Gender
Male
Female
Ethnicity
African American
Caucasian / white
Hispanic
Other
Marital Status at Intake
Never Married
Married
Divorced
Other
Age at Admission
18-20
21-25
26-30
31-35
36-44
45+
Educational Level
High School Degree
High School
Some College
Grade School or Less
College / Associate Degree
College Degree
Advanced Degree
Major Source of Income
Legal Work
Public Assistance/ SSI
Illegal Sources
Family/Friends
Other
Criminal Justice Status
No Legal Status
Legal Status
Treatment
Complete
Treatment Not
Complete
47.8
18.4
25.2
8.5
28.5
29.7
5.8
2.2
14.8
16
2.5
.3
16.5
15.7
6
28
6
7.6
4
16
1.9
8.1
16.2
19.5
17.2
3.3
1.2
4.3
9.6
9.4
8.1
1
26.7
15.4
14.4
1.3
3.3
4.3
.7
13.5
9.3
6.1
1.3
1.2
1.9
.3
44.3
5.8
8.2
6.5
1.2
18.4
2.7
8.8
3.8
.2
41.2
25.0
16.5
17.2
Table B.7: Percentage Distribution of Demographic Indicators across Treatment
Completion
126
Treatment
Complete
Variable
Treatment Not
Complete
Primary Drug Problem
Cocaine/crack
Alcohol
Marijuana
Opiates
Other
40.4
10.5
2.6
9.0
3.7
22.6
2.9
.6
6.1
1.7
Treatment Modality
Residential
Short-term Inpatient
Outpatient Drug Free
Methadone Maintenance
11.4
39
12.9
3.0
16.2
4.6
6.9
6.0
Previous Treatment
0
1
2-6
7+
29.8
12.6
18.6
5.2
12.7
5.4
11.1
4.5
Referral Source
Family / Friends
Self
Legal System (including
23.1
20.7
10.6
13
10.3
6.6
4.0
7.8
.6
3.1
probation/parole)
School/Employer
Community / other
Table B.8: Percentage Distribution of Alcohol and Drug Indicators across Treatment
Completion
127
Variable
Frequency of Primary Drug Use
2 + times per day
Daily or almost every day
1-6 times per week
Less than once per week
None
Number of Drugs Used Weekly
0
1
2
3
4 or more
Overall Severity
Low
Moderate
High
Treatment
Complete
Treatment Not
Complete
16.3
18.6
25
4.9
1.4
11.6
8.9
10.2
2.9
.2
3.9
16.9
26.2
13.3
5.8
1.0
9.1
14.5
5.8
3.1
5.1
39.9
21.3
1.8
19.4
12.5
Table B.9: Percentage Distribution of Severity Indicators across Treatment Completion
128
Variable
Gender
Male
Female
Ethnicity
African American
Caucasian / white
Hispanic
Other
Marital Status at Intake
Never Married
Married
Divorced
Other
Age at Admission
18-20
21-25
26-30
31-35
36-44
45+
Educational Level
High School Degree
High School
Some College
Grade School or Less
College / Associate Degree
College Degree
Advanced Degree
Major Source of Income
Legal Work
Public Assistance/ SSI
Illegal Sources
Family/Friends
Other
Criminal Justice Status
No Legal Status
Legal Status
Use after
Admission
No Use after
Admission
54.2
18.9
20.4
8.2
28.7
35.5
5.5
1.6
13.6
11.1
3.2
.8
14.7
17.9
7.7
31.2
7
6.0
2.6
12.9
1.8
8.6
18.8
19.9
18.4
3.8
1.1
3.0
6.4
9.3
8.2
.5
28.9
17.0
14.5
2.3
3.2
4.4
1.0
11.1
7.7
5.9
.7
1.4
1.8
.1
42.5
6.3
13.5
7.8
1.2
19.1
2.2
4.0
3.2
.2
42.4
28.9
16.6
12.1
Table B.10: Percentage Distribution of Demographic Indicators across Use
129
Use after
Admission
Variable
No Use after
Admission
Primary Drug Problem
Cocaine/crack
Alcohol
Marijuana
Opiates
Other
40.8
9.9
2.4
15.6
2.9
19.0
2.7
.7
4.1
2.0
Treatment Modality
Residential
Short-term Inpatient
Outpatient Drug Free
Methadone Maintenance
16.3
28.8
13.2
13.0
9.2
11.4
5.9
2.2
Previous Treatment
0
1
2-6
7+
28.8
12.8
21.5
8.2
12.6
6.3
8.5
2.2
Referral Source
Family / Friends
Self
Legal System (including
25.9
24.0
10.8
10.0
9.2
5.2
3.2
7.4
1.1
3.2
probation/parole)
School/Employer
Community / other
Table B.11: Percentage Distribution of Alcohol and Drug Indicators across Use
130
Variable
Frequency of Primary Drug Use
2 + times per day
Daily or almost every day
1-6 times per week
Less than once per week
None
Number of Drugs Used Weekly
0
1
2
3
4 or more
Overall Severity
Low
Moderate
High
Use after
Admission
No Use after
Admission
22.4
19.3
23.1
5.6
1.4
7.6
8.0
9.7
2.4
.3
3.4
17.1
29.4
14.4
7.0
1.4
8.1
11.4
5.3
2.5
5.2
40.5
26.2
1.8
17.1
9.2
Table B.12: Percentage Distribution of Severity Indicators across Use
131
Variable
Gender
Male
Female
Ethnicity
African American
Caucasian / white
Hispanic
Other
Marital Status at Intake
Never Married
Married
Divorced
Other
Age at Admission
18-20
21-25
26-30
31-35
36-44
45+
Educational Level
High School Degree
High School
Some College
Grade School or Less
College / Associate Degree
College Degree
Advanced Degree
Major Source of Income
Legal Work
Public Assistance/ SSI
Illegal Sources
Family/Friends
Other
Criminal Justice Status
No Legal Status
Legal Status
Low
Motivation
High Motivation
49.7
19.3
23.2
7.8
27.7
33.6
6.3
1.4
14.5
13
2.3
1.1
15.2
16.9
7.4
29.5
6.5
7
2.9
14.6
2.3
8.4
17.6
19.6
18.1
3.0
.5
3.3
7.7
9.6
8.5
1.4
29.1
17.3
13.3
1.8
2.6
4.4
.5
11
7.4
7.1
1.2
1.9
1.8
.5
42.5
6.0
11.4
8.1
.7
19.1
2.5
6.1
2.9
.6
38.5
30.5
20.4
10.6
Table B.13: Percentage Distribution of Demographic Indicators across Motivation
Source
132
Low Motivation
Variable
Primary Drug Problem
Cocaine/crack
Alcohol
Marijuana
Opiates
Other
High Motivation
39.5
8.1
2.5
15.4
3.2
20.3
4.5
.6
4.3
1.7
Treatment Modality
Residential
Short-term Inpatient
Outpatient Drug Free
Methadone Maintenance
17.6
24.8
15.1
11.5
8.0
15.4
4
3.7
Previous Treatment
0
1
2-6
7+
27.8
12.2
21.1
7.8
13.6
5.9
8.9
2.6
Referral Source
Family / Friends
Self
Legal System (including
23.3
23.0
13.3
12.6
10.2
2.7
2.7
6.6
1.5
4.0
probation/parole)
School/Employer
Community / other
Table B.14: Percentage Distribution of Alcohol and Drug Indicators across
Motivation Source
133
Variable
Frequency of Primary Drug Use
2 + times per day
Daily or almost every day
1-6 times per week
Less than once per week
None
Number of Drugs Used Weekly
0
1
2
3
4 or more
Overall Severity
Low
Moderate
High
Low
Motivation
High Motivation
20.7
18.6
22.6
5.6
1.4
9.3
8.7
10.3
2.4
.3
3.3
18.5
27.0
13.9
6.3
1.5
6.7
13.7
5.9
3.2
5.1
39.9
21.3
1.8
19.4
12.5
Table B.15: Percentage Distribution of Severity Indicators across Motivation Source
134