Philadelphia College of Osteopathic Medicine
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PCOM Psychology Dissertations
Student Dissertations, Theses and Papers
2007
Analysis of the Goodwin Sentence Completion
Test in the Screening of Clinical Depression
Karyn L. Goodwin-Tribble
Philadelphia College of Osteopathic Medicine, [email protected]
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Goodwin-Tribble, Karyn L., "Analysis of the Goodwin Sentence Completion Test in the Screening of Clinical Depression" (2007).
PCOM Psychology Dissertations. Paper 56.
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Philadelphia College of Osteopathic Medicine
Department of Psychology
AN ANALYSIS OF THE GOODWIN SENTENCE COMPLETION TEST IN THE
SCREENING OF CLINICAL DEPRESSION
By Karyn L. Goodwin-Tribble
Submitted in Partial Fulfillment ofthe Requirements of the Degree of
Doctor of Psychology
April 2007
PHILADELPHIA
PHILADELPHIA COLLEGE
COLLEGE OF
OF OSTEOPATHIC
OSTEOPATHIC MEDIdI~E:l
MEDldI~E
DEPARTMENT
PSYCHOLOGY
DEPARTl\fIl:NT OF
OF PSYCHOLOGY
Dissertation
Dissertation Approval
Approval
th
This
to certifY
to us
This is
is to
certify that
that the
the thesis
thesis presented
presented to
us by
by Karyn
Karyn L.
L. Goodwin-Tribble
Goodwin-Tribble on
on the
the 99th
day
of April,
in partial
fulfillment of
for the
day of
April, 2007,
2007, in
partial fulfillment
of the
the requirements
requirements for
the degree
degree of
of Doctor
Doctor of
of
Psychology, has
and is
is acceptable
scholarship and
Psychology,
has been
been examined
examined and
acceptable in
in both
both scholarship
and literary
literary quality.
quality.
Committee Members' Signatures:
Christopher Royer, Psy.D., Chairperson
Stephanie H. Felgoise, Ph.D., ABPP
Tina Woodruff, Ed.D.
Robert A. DiTomasso, Ph.D., ABPP, Chair, Department of Psychology
III
Dedication
I must first thank God for providing me with the strength and ability to achieve this most
important professional goal. Without His guidance, I doubt that this journey would have
ended with such unexpected pride. I dedicate the body of my work to those individuals
who have given my life such happiness throughout this arduous experience. To my
husband, Tobias, I thank you for your love and unceasing encouragement. You always
knew this was possible. To my parents, thank you for your strength, unconditional love
and support, and for providing me with a solid foundation. And it is with great joy that I
dedicate both this work and my heart to my beautiful son, Kristian. You have given my
life purpose and made me look forward to each day on this emih. I love you all.
IV
Abstract
The Goodwin Sentence Completion Test (GSCT) was developed as a screening
instrument for clinical depression. This instrument, composed of 25 sentence stems, was
designed to indicate the level depression and to assess the strength of negative
perceptions associated with dimensions of the cognitive triad (self, world, and future).
Although the GSCT follows the typical format of most projective sentence completion
tests, an objective scoring method was also constructed in order to evaluate more reliably
individual results. The tool was administered to 80 adult volunteers ranging in age from
18 to 72 years of age. Volunteers were randomly selected from a variety of public and
private settings and represented diverse cultural, socio-economic, and educational
backgrounds. Pmiicipant scores from the GSCT were compared with scores gleaned
from the second edition of the Beck Depression Inventory (BDI-II) and the Hamilton
Rating Scale for Depression (HDI). Results supported the primary hypothesis, which
predicted statistical significance and a positive correlation between GSCT scores and
scores from the BDI-II and HDI tests. As anticipated, the investigation also highlighted
the strength of any negative or depressive attributes related to self-based, world-based,
and future-based perceptions evaluated through GSCT subtest items. Fmiher analyses
also found a positive correlation between the aforementioned GSCT subtest items, the
BDI-II, HDI, and the HDI Melancholia Subscale.
v
Table of Contents
.
...
· 0 fF'Igures .......................................................................................
L1st
VIlI
List of Tables ......................................................................................... ix
CHAPTER 1: INTRODUCTION .................................................................. 1
CHAPTER 2: HISTORICAL UNDERPINl"-rINGS .............................................. 3
Sentence Completion Tests (SCTs) ....................................................... 3
Depression and Related Theoretical Assumptions ...................................... 7
SCTs and Depression Screening .......................................................... 11
CHAPTER 3: TI"-rSTRUMENT ANALySIS ..................................................... 19
Constructing the Goodwin Sentence Completion Test (GSCT) ..................... 19
CHAPTER 4: METHOD ........................................................................... 22
Participants ................................... , ............................................. 22
Participant Recruitn1ent ................................................................... 27
Apparatus .................................................................................... 27
Scoring Methods ........................................................................... 28
Procedure .................................................................................... 30
Statistical Design: Conelational Analyses ..................................... 31
Additional Analyses ............................................................... 31
CHAPTER 5: RESULTS ........................................................................... 32
Qualitative Analysis: Evaluating Subject Responses on the GSCT ................. 32
Statistics ..................................................................................... 32
Descriptive Statistics: BDI-II, HDI, and GSCT Scores ...................... 32
Conelations and Statistical Significance ...................................... .47
VI
Testing the Primary Hypothesis ....................................... .47
BDI-II and GSCT Dimension Subtests ................................ 48
HDI & GSCT Dimension Subtests .................................... 53
R Squared and Supplementary Analyses .............................. 62
Qualitative Analysis: Evaluating for Differences across GSCT item
scores ............................................................................... 64
CHAPTER 6: DISCUSSION ..................................................................... 69
Findings ...................................................................................... 69
Implications ........................................................................ 69
Limitations ........................................................................ 72
Use of Self-RepOli Measures .......................................... 72
Test Construction ........................................................ 73
GSCT Scoring Methods ................................................ 74
Evaluating Inter-rater Reliability ....................................... 76
Control and Experimental Groups ..................................... 77
Generalizability & Sample Size ........................................ 78
Additional Research Questions and Considerations ................................... 79
CHAPTER 7: CONCLUSION .................................................................... 80
References ............................................................................................. 81
Appendix A ........................................................................................... 93
Appendix B .......................................................................................... 95
Appendix C ........................................................................................... 97
Appendix D ................................................................................... , .... 101
Vll
Appendix E ........................................................................................ 103
Appendix F ........................................................................................ 105
V111
List of Figures
Figure 1: Distribution of age of volunteers participating in this study ....................... 23
Figure 2: Illustration of participant racial group categories .................................... 25
Figure 3: Illustration of age and racial differences across "Minimal" BDI -U scores .... " 34
Figure 4: Example comparison ofBDl-IT,HDl, and GSCT lowest score sets around age
and racial factors .................................................................................... 43
Figure 5: Comparisons ofBDI-II, HDT, and GSCT total score distributions ............... .45
IX
List of Tables
Table 1: Descriptive Analysis of Pmiicipant Age Range ...................................... 22
Table 2: Racial Frequencies and Percentages ................................................... 24
Table 3: Cross-tabulation of Age, Race, and Pmiicipant Gender Factors ................... 26
Table 4: Cross-tabulation of Pmiicipant Age, Race, and BDT-II Range of Scores ..... , ... 32
Table 5: Cross-tabulation ofBDl-II Scores when Accounting for Age, Race, and
Gender ................................. , .......................................... , ................... 35
Table 6: Cross-tabulation of Age, Race, and Gender Factors and HDI Score Ranges ..... 37
Table 7: GSCT Score Ranges, Frequency Count, and Actual Participant Scores ......... .40
Table 8: GSCT Score Ranges and Age, Race, and Gender Cross-tabulation ............... 41
Table 9: BDI-1I and GSCT Correlation Results ................................................ 47
Table 10: Positive Con-elation between GSCT and HOI Total Scores ..................... .48
Table 11: Statistical Significance Determined when BDI-II and GSCT Dimension Totals
Compared ............................................................................................ 49
Table 12: Statistical Significance Established with BDT-II Scores and GSCT Self
Dimension Compared .............................................................................. 50
Table 13: Positive Correlation of .362 found when BDI-II and GSCT World Dimension
Scores Compared ...................................................... '" ...... '" ................ 51
Table 14: BDI-II and GSCT FutlU'e Dimension Scores Demonstrate Positive
Correlation .......................... , ............... '" ........ '" ., ................................ 52
Table 15: Positive Correation Demonstrated when HDI and GSCT Dimension Total
Scores Conlpared .................................................................................. 54
x
Table 16: Comparison of the Strongest Correlation between the HDI Total Score and
GSCT Self Dimension ...... , ... , .... , .. , ........ , ........... , ...................................... 55
Table 17: HDI Total and GSCT World Dimension: Weakest Positive Correlation ........ 56
Table 18: Significant Correlation Demonstrated between the HDI Total Score and the
GSCT Future Din1ension .................................................. , .. , ..................... 57
Table 19: Pearson Comparison of GSCT Total Scores and HDI Melancholia
Subscale ............................................................................................... 58
Table 20: Statistical Significance Demonstrated when aSCT Dimension Total compared
with HDI Melancholia Subscale ................................................................... 59
Table 21: Positive Correlation of .501 Demonstrated on the HDI Subscale and GSCT Self
Dimension Subtest. ..... '" ................ , ......... , '" ... '" .... , ................................. 60
Table 22: COlTelation between HDI Melancholia Subscale and GSCT World Dimension
Subtest only Significant with an Alpha Level of .05 (p :::; .05) ............................... 61
Table 23: HDI Melancholia Subscale and GSCT Future Dimension Compared ........... 62
Table 24: Pearson CorrIeations between aSCT Total and GSCT Dimension Subtest
ItelTIs .................................................................................................. 65
Table 25: Highest Correlation demonstrated when GSCT TOTAL Scores and GSCT
Dimension Total Scores compared ................................................................ 66
Table 26: Pearson Correlational comparisons of aSCT Subtest Items Self and
World ................................................................................................. 67
Table 27: Significant Correlation between aSCT Self and Future Subtest Items .......... 67
Table 28: No Conelation found when GSCT World and Future Dimension Subtests
Compared ........... " .. , , " ....... , .. , ....... , .. , ................................................... 68
An Analysis of the Goodwin Sentence Completion Test in the
Screening of Clinical Depression
CHAPTER l: INTRODUCTION
Throughout its development, psychology worked to synthesize research,
evaluation, and clinical treatment into an approach that both comments on and enhances
the human condition. In its early stages, many psychologists relied upon scientitic
experimentation to test their hypothetical suppositions (Hergenhan, 1997). The earliest
fonn of assessment was often considered to be the clinical interview. Yet, during the
1960s and 1970s, sole dependence upon such methods was the subject of heated debate
(Groth-Marnat, 1999). As many interview techniques were perceived as unreliable and
lacking in empirical validation, psychological tests were introduced in order to counter
the subjectivity and bias of these approaches. Gradually, empirically based
methodologies joined with applied approaches and engendered more efficient clinical
assessment. Technological advances continued to propel this field towards an age where
psychological assessment is the foundation of treatment. These influences, as well as
scientific study and experimentation, helped to facilitate the development of a variety of
assessment instruments.
According to Groth-Marnat (1999), psychological assessment has become a tool
that is crucial to the definition, training, and practice of professional psychology. Though
assessment has always been important in professional psychology, its patterns of use and
its relative importance have evolved with the times. In addition, psychological
2
assessment has come to consist of a variety of activities that may include conducting
structured and unstructured interviews, behavioral observations in natural settings,
observations of interpersonal interactions, and neuropsychological, personality, and
behavioral evaluation. Assessment is no longer relegated to the laboratories and
universities of old, but may now be found in outpatient settings, hospitals, and schools.
In spite of scientific advances designed to enhance the validity and reliability of
numerous instruments, other areas continue to provoke discussion among both
researchers and clinicians. Some criticisms have often focused on the assessment of
personality. Initially, personality was evaluated primarily through experience, case
studies, and clinical judgment (Hergenhan, 1997). Contemporary professionals now tend
to gravitate towards ideas that describe the analysis of the personality as characterized by
systematic evaluation and objectivity. The assessment of "personality," indicating that
personality refers to the characteristic ways in which an individual perceives the world,
relates to others, copes with and solves problems, regulates emotions, and manages stress,
is an integral component of treatment (Davis, 2001). Many instruments have been
developed as measures of personality, such as the Rorschach Inkblot Test, the Thematic
Apperception Test, and Projective Drawing Tests (Groth-Mamat, 1999). Such tests vary
with respect to structure, content, and attention to or reliance on objective scoring
techniques. Specifically, the Rorschach Test, comprised of a series of inkblots that are
shown to subjects whose responses to these figures are later interpreted and scored, has
seen dramatic movement towards scientifically based objectivity and analysis (Davis,
2001). Although it may arguably be among the most well known standardized projective
instruments, the Rorschach is not the only tool to have developed in this manner.
3
CHAPTER 2: HISTORICAL UNDERPINNINGS
Sentence Completion Tests
The sentence completion method of assessing personality is a semi-structured
projective technique that requires the respondent to finish a sentence for which the first
word or words are provided (Rotter, Lah, & Rafferty, 1992). The words or shmi phrases,
or stems as they are often called, have been organized into various combinations to
evaluate distinct attributes, response styles, and levels of functioning (e.g., Tyler, Gatz, &
Keenan, 1977; Evans & Wanty, 1979; Catanzaro, 1991; Ames & Riggio, 1995; Holaday,
Smith, & Sherry, 2000). Over the years, many different sentence completion tests have
been developed for a variety of general and specific purposes (Rotter et aI., 1992).
Regardless of the areas of interest, such tests have proved advantageous for a variety of
reasons. Some of these advantages include the freedom of response, somewhat covert
purpose of the individual instruments, and ease and flexibility of administration.
According to some research (Craig & Horowitz, 1990), the sentence completion method,
also referred to as the incomplete-sentences method, continues to be among the most
frequently used psychological assessment tools by clinicians.
According to Rotter, Lah, and Rafferty (1992), Rotter and Willerman began the
process of providing objective scoring for a sentence-completion test during World War
II. This process began as an attempt to determine which of the soldiers suffering from
4
psychological trauma had recovered sufficiently well to return to active duty. Following
the war, Rotter, Rafferty, and Schachtitz developed a similar objective scoring system for
a sentence-completion test of adjustment for college students. In 1950, Rotter and
Rafferty published a manual for the scoring and interpretation of responses to the Rotter
Incomplete Sentences Blank (RISB), a semi-structured measure of personality adjustment
consisting of 40 incomplete phrases, or stems. This test, which has versions designed for
use with high school students, college students and adults, also provides a reportedly
objective scoring system for evaluating the responses (Rotter et aI., 1992).
The RISB was conceived as an attempt to standardize the sentence-completion
method in the study of adjustment among college populations (Rotter, 1951). Rotter and
associates (1992) defined adjustment as the relative freedom from prolonged unhappy/
dysphoric states (emotions) of the individual, the ability to cope with frustration, to
initiate and maintain constructive activity, and the ability to establish and maintain
satisfying interpersonal relationships. Their test quantified adjustment into what was
called an overall adjustment score. The scoring method associated with this instrument
eventually allowed the RISB to be a useful tool in the screening of overall adjustment.
Results from this measure helped clinicians to determine whether or not college students
should be refened for counseling, therapy, or be observed for problems in their
adjustments to campus life. Since then, the RISB has been researched extensively
(Logan & Waehler, 2001). Additional studies with college populations have also
examined anxiety and defensiveness (Milliment, 1972), and state-trait anxiety levels
(Newmark, Hetzel, & Frerking, 1974). With minimal adjustments to the sentence stems,
5
the revised second edition of the RISB attempted to preserve the historical continuity of
the fust (Rotter et aI., 1992).
Although the RISB has been updated in an effort to ensure more objective scoring
practices, the most recent version does not provide detailed information on corresponding
validation or reliability studies. Attempts to validate the efficacy of the tool appear to be
based largely upon inter-rater comparisons. In fact, the principal argument for the
reliability and validity of this instmment is reliant upon the fact that subjective
interpretations of pmticipant responses tended to be cOlTespondingly similar. That is to
say, more often than not, other professionals tended to come to similar clinical
conclusions when scoring responses (Rotter et aI., 1992). This investigation revealed no
clear experimental data, such as statistical results indicating specific testing protocols,
comprehensive scoring templates, and/or objective methods for interpretation. Despite
the fact that it is preferred by numerous clinicians, the present RISB version may
conclude only that one clinician's SUbjective interpretations may be similar to those
offered by other professionals. It does not appear able to evaluate response severity
objectively, in contrast to scoring a BDI-II for example, to sort responses into clinical
syndromes reliably or to highlight possible treatment foci (as in the Rorschach).
Relatively easy to administer, many professionals use the different versions of the
Sentence Completion Test (SCT) in order to augment patient conceptualization and
treatment. Some of these versions have also been developed in order to assess the need
for achievement (Oshodi, 1999), locus of control (e.g., Aiken & Baucom, 1982; Ames &
Riggio, 1995; Smith, Trompenaars, & Dugan, 1995), and emotional problems and
learning (Lanyon & Lanyon, 1979). Although some studies were built upon the work of
6
Rotter to evaluate various constructs including mood (Evans & Wanty, 1979; Aiken &
Baucom, 1982), very little research has been devoted specifically to the development of
the SeT in the assessment of depression.
Depression is considered to be among the most common presenting problems
encountered by mental health professionals (Young, Beck, & Weinberger, 1993; National
Institute of Mental Health [NIMH] & National Institute on Drug Abuse [NIDAJ, 2002).
In fact, its prevalence is noted within a variety of treatment settings including hospital s,
clinics, and institutions (Barlow, 1993). Depressive disorders are also pat1icularly
common in primary care settings. The atiicle Screening Instruments for Identification of
Depression (1995) statcs that the prevalence of major dcprcssion in any given primary
care setting is estimated to be 6 to 9 percent. It goes on to argue that as many as 35 to 50
percent of these patients may go undiagnosed.
Individuals with a Major Depressive Episode frequently present with tearfulness,
in-itability, brooding, obsessive rumination, anxiety, phobias, or excessive
WOlTY
over
one's own physical health, and somatic complaints (American Psychiatric Association
[AP A], 1994). Other symptoms frequently associated with depression involve
anhedonia, or lack of continued interest in preferred activities, feelings of hopelessness
(K won, 1999), and guilt (NIMH & NIDA, 2002). The degree of impairment associated
with such disorders varies (APA, 1994). In fact, there may be clinically significant
distress or interference in social, occupational, or other imp0l1ant areas of functioning in
even the mildest of cases.
7
Depression and Related Theoretical Assumptions
Depression was initially researched as a personality trait or feature based upon a
style of adapting to the environment. Therefore, many of the early theoretical analyses of
the depressive personality originated from the psychodynanlic phenomenon of early
object loss (Huprich, 2001). Such theories argued that melancholia, or depression, was
similar to grief reactions, because the individual grieves the loss of a significant person of
attachment over a specific period of time. Among some of the earliest psychological
accounts of depression were described by Freud in 1917. He believed that depression
was associated with maladaptive coping mechanisms that developed as a result of early
negative experiences. In his works, Freud suggested that feelings of anger and reproach
may be inwardly directed and may result in feelings of self-reproach, low self-esteem
(Altshuler & Rush, 1984), and melancholia. This melancholia, or depression, was said to
have initiated as feelings of anger and reproach towards a loved one surrounding a
negative experience such as death or abandonment. Subsequently, instead of expressing
anger toward the disappointing attachment figure, the individual was said to direct his or
her anger towards the self, a process referred to by Freud as reaction formation. Thus,
reaction formation is said to occur when an individual never resolves or uncovers these
feelings of anger which leads to a negative pessimistic view of oneself and others.
Although they expressed divergent ideas surrounding the cultural, environmental,
and gender differences impacting the self, Karen Horney (1945) and Melanie Klein
(1957) expanded upon these early psychoanalytic views in their writings on depression.
Their work described depression as an experience wherein the individual was viewed as a
8
complex being with many subconscious traits struggling for recognition and acceptance.
This struggle often resulted in an affective state, which was replete with interpersonal
confusion. Later these experiences were regarded as a 'divided self that required
treatment interventions which focused on incorporating these psychological processes
into a stable, integrated identity. A study conducted by K won (1999) also highlighted the
contributions of negative attributional styles and psychodynamic defense mechanisms in
depression. In addition to describing the psychodynamic processes associated with
dysphoria, results of this study also provided some support for the applicability and
validity of hopelessness theories of depression.
According to Ozment and Lester (2001), the first cognitive theories of depression
subscribed to the idea that depression was in paJ1 due to feelings of helplessness (Ozment
& Lester, 2001). Beck's cognitive theory of depression hypothesized that an individual's
negative or distorted thoughts triggered the development and maintenance of depression
(Beck 1972, 1974). Feelings of hopelessness, negative attitudes and beliefs, and
selectively perceiving information pertaining to one's self, the world, and the future in a
negative, distorted manner were also associated with depressive symptomologies
(McGinn,2000). Over the years, investigations have provided support for the validity of
this theory. Levels of depressive symptomology have been found to be associated with
greater levels of dysfunctional attitudes and beliefs by the Dysfunctional Attitude Scale
01'
DAS (Moilanen, 1995). Similarly, research conducted on results from the
Hopelessness Scale (HS) found that the depressive experiences of adults have been found
to be significantly associated with more pessimistic expectancies of the future (Beck,
Kovacs, & Weissman, 1975).
9
Later theories focused on learned helplessness (Abramson, Seligman, & Teasdale,
1978) and an enduring belief in an external versus an internal locus of control (Rotter,
1966; Evans, 1981; Chung & Ding, 2002). These ideologies proposed that through
environmental conditioning and negative attributions, individuals learn a pervasive style
of helplessness that characterizes both their perceptions and their subsequent behaviors;
and that depressed individuals tend to believe that forces outside of their control tended to
dictate the course(s) taken by their lives. Another theory, which also focused on the
influences of the individual's cognitions, was outlined in a 2001 study conducted by
Gladstone and Parker. This investigation explored the Lock and Key Hypothesis of adult
depression. This hypothesis suggests that early adverse life events or circumstances are
capable of establishing vulnerability 'locks' which may be later primed when the
individual is faced with mirroring life events ('keys') in adulthood. This hypothesis is
similar to other diathesis-stress models of cognitive vulnerability. This premise holds
that early adversity (whether acute or chronic in nature) creates a cognitive template, or
schema, through which an individual sees, interprets, and interacts with the rest of the
world. Results from this study highlighted the need for a closer look at the methodology
involved in identifying depressive core beliefs or schemas in depressed individuals.
Behavioral theories of depression also emerged with alternative views of this
condition. These theories were concemed with behaviors of the depressed individual in
the contexts of social settings and interactions (Ferster, 1973; Wolpe, 1972, 1982). For
example, those persons experiencing depression or those said to be vulnerable to
depression supposedly tended either to suppress behaviors that elicited positive responses
from others or enacted behaviors that elicited negative feedback from others.
10
Behaviorists were largely concerned with altering patterns of depressive behaviors and
with reducing proposed underlying anxieties associated with depressive experiences.
Similarly, behavioral theories emphasized the impOliance of positive reinforcement in
preventing depression, and preventing problems with self-reinforcement, self-monitoring,
and self-evaluation (Street, Sheeran, & Orbell, 1999).
Unlike psychoanalytic, cognitive, or behavioral theories of depression, Coyne's
(1976) interpersonal theory of depression proposed that the interpersonal behaviors of
depressive individuals produce an interpersonal space filled with rejection from others.
Negative consequences may ensue in this escalating cycle in which satisfied requests for
reassurance begets fUliher requests. These consequences may be that others reject the
depressed person, others become depressed themselves, and the depressed person's
symptoms may worsen as a result of rejection. Joiner, Brown, Felthous, Banatt, and
Brown (1998) analyzed Coyne's 1976 theory. In their investigation, Joiner and
associates hypothesized that social contact scores of depressed subjects would be lower
than those of subjects with other disorders. Results of their study were consistent with
the theory because depressed subjects did in fact score lower on a measure of social
contact than did non-depressed individuals.
A variety of approaches have been applied to the treatment of depression, with
growing emphasis on shOli-term psychotherapies. Such modalities, including cognitive
and cognitive-behavioral strategies, have been found to be effective approaches in the
treatment of depressed patients (Altshuler & Rush, 1984; Young et aI., 1993). The
efficacy of these treatments (Rush, Beck, Kovacs, & Hollon, 1977; Dobson, 1989, Young
et aI., 1993) suggests that early screening for depression can help clinicians select the
11
most appropriate therapeutic approach. Increased numbers of individuals accessing
mental health systems, greater time constraints, and decreased hospital stays, however, do
not often allow for the use of the systematic comprehensive assessment as compared to
previous decades. Yet the number of individuals requiring assessment, particularly in the
area of depression, continues to suggest an ongoing need for evaluation and intervention
(Young et aL, 1993). Such data, along with the significant number of clinicians relying
upon the results gleaned from various sentence completion tests (Crag & Horowitz,
1990), further suggests that a tool that is already widely used in the field, like the SCT,
would be beneficial in the assessment of this disorder. Nevertheless, very few studies
have attempted to adapt this tool in the evaluation of depression.
SCTs and Depression Screening
According to the NIMH and the NIDA (2002), diagnostic measures of depression
have fallen typically into two categories: patient self-report of symptoms or the rating of
patient symptoms by clinicians. Measures in each of these traditions have been widely
used for multiple purposes including validation of treatment and identification of
potential candidates that would benefit from such treatment ("Screening instruments",
1995). The most widely used instruments focus on describing the severity of depression
and generally fail to target or provide ratings of specific symptom clusters or dimensions.
Because of the uniqueness of individual vulnerabilities (Lerman & Baron, 1981), such
focus would allow for more precise treatment conceptualization and intervention. More
12
precise description of symptom clusters that were based upon empirically validated
methods could increase the clinical utility of instruments used to measure depression.
Although very few professionals have studied the use of a SCT in the screening of
depression, most would agree that many individuals would benefit from additional
instruments designed to assess this condition (NIMH & NIDA, 2002). In a study
conducted by Yeung, Neault, Sonawalla, Howarth, Fava, and Nierenberg (2002),
researchers not only compared the effectiveness of a culturally-adapted, Chinese version
of the Beck Depression Inventory with the original, but they also made a case for the
continued development of screening instruments. They similarly argued that the use of
interviews alone to conduct depression screening may be time consuming, costly, and
may not be feasible in some settings (i.e., primary care). According to the APA (2000),
there are many instruments that have been designed to measure the severity and existence
of depressive disorders such as the second edition of the Beck Depression Inventory
(BDI-II) and the Hamilton Rating Scale for Depression (HDI). The BDI-II, composed of
21 self-statements that describe symptom severity along an ordinal continuum from
absent or mild (a score of 0) to severe (a score of 3) (APA, 2000), is among the most
widely used tools in the screening of depression. The HDI (a 23-item self report test
designed to measure severity of depressive symptoms) is also an instrument that has been
used in a variety of settings to evaluate patients, meaSl,lfe symptomology, and inform
treatment. In spite of the wide use of such instruments, only a few specifically evaluate
underlying personality traits as well as depressive symptoms (Catanzaro, 1991). Thus, a
screening tool that is able to screen for depression effectively and offer data on an
13
individual's perceptions, personality, and cognitions could not only provide a wealth of
clinical information but would also dramatically enhance the overall evaluative process.
In the age of managed care, shortened lengths of stay and brief therapy,
professionals must increasingly rely upon their ability to render thorough assessments
that are both efficient and accurate. Research conducted in the medical field also
supports the cost-utility of screening for depression in primary care (Valenstein, Vijan,
Zeber, Boehm, & Buttar, 2001) as compared to the effects of not screening for this
disorder. Specifically, results from the Valenstein et al., study indicated that 82 more
quality-adjusted days were gained per 1000 patients (costing well over $50,000 for each
individual) when this condition was effectively evaluated. Even with a growing number
of practitioners trained in evaluation, there is a tremendous focus on clinically validated
treatment and efficacious programming. Although important in the conceptualization,
assessment, and treatment of a patient, clinical judgment is most often regarded as a
complement to professional intervention rather than as the fundamental basis of patient
evaluation (Groth-Mamat, 1999). As a result, experimentation and validation studies
help to address the need for reliable assessment.
Each year numerous studies are conducted in order to construct relevant
assessment instruments. These experiments seek to broaden the understanding of the
psychological community, assist in the accurate conceptualization of patient pathology,
and select appropriate interventions. Although the RISB has been noted as one of the
most researched SCTs (Goldberg, 1965; Lah, 1989), few modem studies actively pursue
the advancement ofprojective tests initially developed during the early days of
psychology (e.g., Chung & Ding, 2002; Okamoto, 2001; Oshodi, 1999). Like many tools
14
that were constructed by the progenitors of what has evolved into the psychology of
today, the SCT is frequently regarded as an instrument of historical interest (Logan &
Waehler, 2001) rather than of modem study.
Most would agree that the instruments, like the RISB, would benefit from further
study based upon cultural sensitivity, objective assessment, and standardized
psychometric propel1ies (Lah, 1989; Oshodi, 1999; Logan & Waehler, 2001; Roberts &
Reid, 1978; Marsh & Richards, 1987). Such tools are likely to be the subject of ongoing
experimentation and development. In fact, continued research and development can
work only to enhance areas of psychological assessment and study. Holaday, Smith, and
Sherry's (2000) study suggested that test usage surveys find consistently that many
different professionals from various cultures and ethnic backgrounds rank Sentence
Completion Tests (SCTs) among the highest of projective measures. This study found
that when 100 members of the Society for Personality Assessment were surveyed, a 60%
return rate indicated that most psychologists who use incomplete sentence tests use the
RISB with children (18%), adolescents (32%), and adults (47%). Results also revealed
that most practitioners reported that they neither read stems aloud nor record answers
themselves, and even fewer use formal scoring. The investigation fm1her suggested that
despite the recognized popularity of the SCTs, what is not known is whether or not
practitioners score these instruments according to any theory or guideline, or why
professionals group the tests together as if all of them provide the same psychological
information. It is also ironic is that significant numbers of mental health consumers
possess distinct depressive disorders (Young et aI., 1993; NIMH & NIDA, 2002), and
many psychotherapists utilize sentence completion methods (Holaday et aI., 2000), yet
15
few SCTs evaluate or screen for this specific pathology. The fact that there is limited
research on the use of SCT in the screening of clinical depression emphasizes the need
for additional exploration in this area.
A secondary interest of this study is to highlight the presence of any dominant,
dysfunctional attitudes that may be part of a vulnerability factor that can contribute to
depression (Beck, 1976). Cognitive science research emphasizes the importance of
information processing in depressive symptomatology (Ingram & Holle, 1992). These
theories argue that negatively biased cognition is a core process in clinical depression
(Young et al., 1993). In fact, Beck (1976) believed that depressed individuals process
information through system errors that affect the manner in which meaning is attributed
to various stimuli. For example, in processing errors such as arbitrary influence, a person
draws a conclusion that is irrational when compared with the evidence. Similar errors,
such as selective abstraction and all-or-nothing thinking, refer to the process by which
individuals selectively attend to one negative aspect of the situation and focus on it, and
when individuals think in a rigid, black or white manner, respectively.
According to Beck (1967), people who are predisposed to depression have
acquired the 'negative triad,' wherein an indiyidual views himself or herself, the world,
and the future in a global, rigid, and negative fashion. The philosophy of this negative
triad, also referred to as the cognitive triad, asserts that those with this perspective tend to
view the world as a hostile place and possess a pessimistic outlook on the future. His
proposal is that some people are more likely than others to become depressed because of
this process (Beck, 1976). Furthermore, Beck (1967) claims that other system errors,
such as overgeneralization, magnification and minimization, and personalization
16
influence the individual's thought processes thereby strengthening the depressive
symptoms. In overgeneralization, individuals tend to establish set rules that they use to
generalize to all future experiences regardless of the evidence. When a depressed
individual overestimates the meanings of undesirable events and devalue desirable
events, they are said to be engaging in magnification and minimization. Persons who
relate external events to themselves---especially negative ones-are said to be
personalizing these events.
Young, Beck, and Weinberger (1993) also assert that depressed patients
consistently distOli their interpretations of events so that they maintain negative views of
themselves, of the environment, and oEthe future. TIlese distortions repOliedly represent
deviations from the logical processes of thinking typically used by most people. An
impOliant predisposing factor for many patients with depression is the presence of early
schema (Beck, Freeman, & Associates, 1990). These schema or cognitive structures for
screening, coding, and attributing meaning to or evaluating stimuli, develop during
childhood and continue to develop possibly throughout an individual's life. Hence, the
relationship between thoughts and feelings, beliefs and experiences, and personality
becomes increasingly apparent in the conceptualization of persons with depression. In
light of this and of other supporting information (Beck, 1967; Young, 1990; Stein &
Young, 1992; Holaday et al., 2000; NIMH & NIDA, 2002), an instrument designed to
captme the dimensions of the cognitive triad (seLf, world, and future) (Beck, 1967; Beck
1976; Beck et al., 1979; Beck et al., 1990), as well as screen for clinical depression could
dramatically improve our understanding of this condition, enhance its assessment, and
could fmiher augment the treatment of the disorder (NIMH & NIDA, 2002).
17
Beck's work further allowed for a conceptual framework on the role of
dysfunctional cognitive processes in the lives of depressed individuals. His theories also
hypothesized on the etiological role of dysfunctional cognitive processes in the onset of
depression (Moilanen, 1995). This research engendered the development of screening
measures or those designed to identify those who may be at-risk for depression, such as
the BDI-II. However, there is very little research on whether or not a tool were
constructed and modeled after the chief components of the most recent RISB would
positively correlate with depression. This study sought to determine whether or not the
Goodwin Sentence Completion Test (GSCT) would positively correlate with clinical
depression (or in this case, scores associated with tests designed to evaluate depression in
individuals: the BDI-II and the HDI), would indicate the strength of negative cognitions
that are associated with the three dimensions of Beck's (1967) cognitive triad: self,
world, and future, and determine whether or not the GSCT Dimension Subtest items
would correlate with the other measures.
Even among the medically ill, a cognitive-based approach to screen for depression
has distinct utility in identifying depressed patients (Parker, Hilton, Hadzi-Pavlovic, &
Bains,2001). Yet using a self-repOli measure alone, such as the BDI-II, can overestimate
or underestimate the presence of depressive symptoms or confuse them with other
negative emotional states such as grief reactions, post-traumatic stress, or an acute
adjustment disorder. According to McGrath and Ratcliff (1993), depression scales tend
to conelate highly with measures of anxiety and other such negative emotional states.
Thus it brings into question the possibility of overlap and the inability of self-report
measures to lend specificity to the clinical assessment. The social desirability of
18
presenting without significant pathology, cultural factors which exaggerate or
underestimate symptom severity, or volitional factors also impact upon the degree to
which self-report measures should be used independently as screening tools. Unlike selfreport measures, a projective instrument increases ambiguity, and to some degree
minimizes the overt recognition of questions designed to assess depressive symptoms.
Coupled with an effort to objectify scoring practices, the implementation of a tool like the
GSCT, may allow for more accurate and comprehensive clinical assessment.
Because there are no versions of the RISB that presently screen for depression,
this area of research may be enhanced by an assessment instrument that does screen for
this syndrome. Compared to the BDI-II, the GSCT can enable individuals to experience
greater flexibility when providing their responses. As with most projective instruments,
this flexibility can consequently produce a wealth of clinical information that may later
be assessed. The addition of the cognitive dimensions associated with depression (self,
world, and future) will enhance this tool's ability to make qualitative analyses of an
individual's experience. In contrast to the BDI-II and other self-report inventories or
questionnaires, results from the GSCT may not only capture symptom severity, they may
also help to plan subsequent treatment by identifying, specificaLly, the underlying
negative schema in need of clinical attention. In a relatively short amount of time, a
professional may not only be able to screen for depression, but he or she may also
evaluate the intensity of the illness, and expose the fundamental negative cognitions
possessed by the individual.
19
CHAPTER 3: INSTRUMENT ANALYSIS
Constructing the Goodwin Sentence Completion Test
In order to establish content validity, three non-mental health consumers
voluntarily took the initial prototype version of the GSCT. The aim of this initial
assessment was to evaluate the appropriateness of the sentence stems, and to identify
early indicators of depressed styles versus non-depressed response styles. The adult
participants, consisting of one male and two females, in this convenience sample ranged
in age from 25 to 70 years.
A complete version of the GSCT, as well as the separate
self, world, and future subtests, was randomly administered to these volunteers.
Preliminary examination indicated that more complex sentence stems tended to elicit
responses that held either existential or overly specific information such as religious
doctrines, ambiguous self-statements, or one-word responses. This initial analysis also
revealed that respondents tended to qualify their responses based upon what they
perceived as the desired responses. Further investigation suggested that sentence stems
that were readily identifiable either as self, world, or future stems also seemed to elicit
clearer responses from the volunteers (Appendix A). These stems also appeared to be
more easily sorted into weighted categories that could be later scored (Appendix C).
Such stems were used as a model in the design of the final version of the GSCT. In
addition to the stems related to the Cognitive Triad, filler items, or stems included in
order to obscure the exact nature of the test, were also inserted into the completed GSCT.
20
Additional exploration revealed that responses seemed to fall in four primary
categories: active, moderately active, indolent, and inactive. Active refers to responses
associated with heightened physical, mental, or spiritual activity. Active responses
provided by the participants in all three of the sentence stems (self, world or future) did
not appear to correspond to features of depression as described in the DSM-IVor the
fourth edition of the Diagnostic and Statistical Manual of Mental Disorders text revision
(DSM-lV-TR) (2000). Conversely, responses that were moderately active, required
minimal activity, or displayed little or no activity, together seemed to be consistent with
similar levels of depressive thoughts, feelings, or behaviors. These findings suggested
that responses could be sOlied into categories that corresponded with a particular
weighted score. Final results of the convenience sample analysis suppOlied the need for
additional, more empirically based exploration both of the hypothesis and of this
instrument.
The principal hypothesis of this study states that if the GSCT is administered to a
"normal" sample of non-disordered volunteers, then GSCT scores should be positively
correlated with scores from the BDl-II and HDl tests. Additionally, the examination
should reveal that subtest items designed to evaluate an individual's perceptions of self,
world, and future-oriented statements would highlight the strength of any negative or
depressive symptoms. If subtest items reveal dimension scores associated with the
relative strength of self, world, or future perceptions, then the secondary hypothesis
supposed that these scores should also be positively correlated with scores from the BDlII, HDl, and HDI Melancholia Subscale.
Because its impact was evaluated in this study,
the GSCT served as the independent variable. GSCT test scores, and corresponding
21
subtest scores associated with the cognitive triad dimensions (self, world, and future),
made up the dependent variables that were analyzed.
22
CHAPTER 4: METHOD
Pru1icipants
Eighty individuals from California, Texas, Colorado, Pennsylvania, and New
Jersey volunteered to participate in this study. Participants ranged in age from 18 to 72
years. For the sake of the analysis, the individuals were s011ed by age into. six categories;
18-25 years of age, 26-35 years, 36-45,46-55, 55-70, and over 70 years. Using these
subgroups, a majority of the subjects fell within the age range of 18 to 25 years. A few
subjects were between the ages of 55 and 70, and only one individual was over 70 Crable
1).
The mean age of the entire experimental group (N = 80) was 34.79 years, or
approximately 35 years (Figure 1).
Table 1
Descriptive Analysis of Participant Age Range
Percent
Fl'equency
Valid
Cumulative
Percent
Percent
18-25 Years of Age
35
43.8
43.8
43.8
26-35 Years of Age
15
18.8
18.8
62.5
36-45 Years of Age
11
13.8
13.8
76.3
46-55 Years of Age
10
12.5
12.5
88.8
55-70 Years of Age
8
10.0
10.0
98.8
70+ Years of Age
1
1.3
1.3
100.0
23
Total
100.0
80
100.0
Figure 1. Distribution of age of volunteers participating in this study.
Distribution of Participant Age
20
15
[
Q)
10
~
5
10
20
30
50
40
Mean = 34.79
Std. Dev. = 14.277
N=80
60
70
80
Age
As Table 1 demonstrates, 44% of the participants were under 25 years of age. Although
student status or employment was not part of the demographic information collected, a
vast majority ofthis age group reported to be or was observed to be college students, to
be enrolled in training or certificate programs, andlor to be employed often less than fu]]time. On the other hand, many ofthose who composed the mid 55% of the remaining
24
participants (26-70 years of age) reported to be or were observed to be currently
employed full-time, had completed their college educations, or were engaged in some
form of professional training programs. Figure 1 illustrates the differences in age across
the paIiicipants and the way in which the subject population aligns in a normal
distribution.
Although this information was not recorded or evaluated through statistical
analysis, paIiicipants also represented diverse socio-economic and educational
backgrounds including students from various disciplines, working professionals, and
retirees.
However, race was a demographic factor included within the investigation.
Specifically, volunteers fell within six major racial!ethnic groups: African Americans,
Caucasians, Hispanic/Latinos, Asian/Pacific Islanders, Biracial! Mixed Race, and Other
(Table 2; Figure 2).
Table 2
Racial Frequencies and Percentages
Freguency
Valid African American
34
Caucasian
37
Hispanic/ Latino
4
Asian/ Pacific
3
Islander
Biracial! Mixed
1
Race
Other
1
Total
80
Cumulative
Percent
42.5
88.8
93.8
Percent
42.5
46.3
5.0
Valid
Percent
42.5
46.3
5.0
3.8
3.8
97.5
1.3
1.3
98.8
1.3
100.0
1.3
100.0
100.0
Figure 2. Illustration of participant racial group categories.
25
Race
III African American
Ill! Caucasian
o Hispanic/ Latino
III Asian! Pacific
o
III
Islander
Biracial! Mixed
Race
Other
A majority or approximately 89% ofthe participants described themselves either as
Caucasians or as African Americans. The remaining individuals made up the additional
four racial categories included in this study: Hispanic/Latino, Asian!Pacific Islander,
Biracial!Mixed Race, and Other. Although these racial differences create a diverse
experimental population, this group may not reflect population demographics typically
associated with randomly sampled groups. As far as gender was concerned, 56 of the 80
subjects were female and 24 were male. Table 3 depicts how subjects differed on age,
race, and gender characteristics, the three demographics analyzed in this study.
26
Table 3
Cross-tabulation
~lAge,
Race, and Participant Gender Factors
Afi:ican
Gender
Female
Amedcan
Caucasian
Pacific
Mixcd
Latino
Islander
Race
2
Other
Total
0
0
28
0
0
12
Age Range
18-25
3
23
0
in Years
26-35
7
2
2
36-45
6
1
0
0
0
0
7
2
0
0
0
0
3
46-55
56-70
3
3
0
0
0
0
6
70+
0
0
0
0
0
0
0
20
31
2
3
0
0
56
0
0
0
0
0
0
0
3
0
0
0
0
4
1
7
2
Total
Male
Hispanic!
Age Range
18-25
3
3
in Years
26-35
2
1
36-45
3
46-55
3
1
1
0
56-70
2
0
0
0
0
0
70+
1
0
0
0
0
0
14
6
2
0
1
Total
Participant recruitmenJ
24
27
Volunteers were randomly selected from a variety of locations and public settings.
These settings included, but were not limited to, college classrooms, neighborhoods,
professional conferences, work sites, and other public areas. Other than requesting the
pmiicipation of individuals who appeared to be at least 18 years of age, no additional
discriminating criteria were used during the recruitment process. Prospective pmiicipants
were selected primarily by virtue of ease of access or availability. That is to say, the
experimenter knew some of the participants, but others were solicited through word of
mouth or coincidental affiliation with the investigation team. Thus it was assumed that
volunteers represented individuals who functioned with "normal" mental and emotional
health. Participants, therefore, were not divided into separate control and experimental
groups. Other than age, race, and gender, no other personal information was taken from
the subjects.
Apparatus
The final version of the GSCT (Appendix B), the
BDI~II
(Appendix E) and the
HDI (Appendix F) were the assessment instruments used in the evaluation of the
pmiicipants. In order to ensure pmiicipant anonymity, each of the three tests was coded
with a randomly assigned,
three~digit
subject number. These tests packets were then
provided to all 80 volunteers. Administrations were conducted individually or in groups,
in classrooms, conference rooms, private homes, lobbies, and other public areas. Except
28
for standard issue pens or pencils no additional materials were required for the
experiment.
Scoring methods
Standard objective scoring methods were utilized to evaluate participant
responses both from the BDI-II and from the HDI (Reynolds et al., 1995) tools. For
example, BDI-II requires that an investigator sum the 21 responses (where subjects select
the best response to self-statements using an ordinal continuum between 0 and 3) and
assign an overall score of "Minimal", "Mild", "Moderate" or "Severe" based on this total
(AP A, 2000). The 23 items from the HDI, which also measure severity of depressive
symptoms, requires a series of mathematical computations to score subject responses.
Overall scores can later be sorted into categories of "Not Depressed", "Subclinical",
"Mild", "Moderate", "Moderate to Severe", and "Severe". Similarly, specific formulas
are required to calculate HDI sub scale items, including the HDI Melancholia Sub scale
which was compared in this investigation. However, because no formal scoring methods
were found to evaluate sentence completion tests, a Likert-Scale method to score the
GSCT instrument was developed. An objective method of scoring the responses, similar
to that used in the Vocabulary section of the Wechsler Adult Intelligence Scale-Third
Edition (WAIS-III), was selected as a model scoring template (Wechsler, 1997).
The newly developed GSCT scoring method required that each response (except
for filler stems) be given a score ranging from 0 to 3 (Appendix C). Example response
sets were developed in order to assist in assigning an appropriate clinical score for each
29
item. For instance, responses that demonstrated minimal and/or an absence of physical,
emotional, social, or spiritual activity were assigned a score of (3). Scores of (3) were
more heavily weighted and indicated a response considered to be most closely associated
with depressive symptomology as described in the DSM-IV-TR (APA, 2000).
Conversely, non-depressive responses, or those atypical of depressed individuals, gleaned
scores of (0). Responses could also earn scores of (1) or (2) (wherein 1 represents mildly
depressed symptoms and 2 refers to moderately depressed symptoms).
In addition to deriving an overall score, the GSCT scoring method also allowed
for the analysis of perceptions related to self, world, and future. After the filler items
were excluded, the sentence stems associated with each of the three dimensions were
sOlied into their relative categories. Then the subtest items were averaged, and a
dimension score was assigned to each of the three domains. This average dimension
score represented the subtest score relating to an individual's self-, world-, or futurerelated perceptions (Appendix D). A total dimension score was then computed by adding
together the separate subtest dimension scores. Because the premise of this investigation
was to compare the GSCT with other standardized measures, a method of ranking total
GSCT scores on symptom severity was also developed. Like the BOl-II and HDI, a
range of scores was assigned to specific categories. BOI- n ranges were selected for
adaptation because of the multiple levels associated with the HOI score ranges. Four
equidistant ranges were then constructed and assigned severity levels. For example,
GSCT total scores between 0-18 corresponded to the "Minimal" range, 19-37 represented
"Mild" symptoms, and scores of38-56 or 57-75 were associated with "Moderate" and
"Severe" symptoms, respectively. Although developing ranges and assigning symptom
30
severity levels based upon the results of the investigation would have been preferred, this
method allowed for the establishment of a baseline for eventual comparison. In an effort
to avoid influencing participant responses, subjects were not informed that this was a
newly formulated tool with corresponding scoring methods.
Procedure
Prospective volunteers were invited to participate in an anonymous study that
would require approximately 15-30 minutes of their time. If interested, potential
candidates were informed that only general demographic information associated with
age, race, and gender; no personal or identifying information would be requested at any
time during the experiment. These pmticipants were instructed that their individual
results would remain anonymous and that collective results of the study would be used to
augment research associated with the assessment and treatment of depressive disorders.
After consenting to participate in the study, each participant was given the three
tests that had been grouped by a pre-selected, random subject number. Ifneeded, writing
utensils were made available to the subjects. The GSCT was provided first (as opposed
to last or following another instrument in order to minimize the risk of cuing the
participants), followed by the remaining tests. After they were in possession of the test
packets (GSCT, BDI-II, and HDI), volunteers were directly to read carefully the
instructions at the top of each test and to finish all of the items on the test. These
administrations OCCUlTed individually and/or in groups, and involved only one session.
Upon completion, the above-mentioned instruments were returned by the examinees.
31
Statistical Design: Correlational Analyses
The primary statistical methodology of this study is a correlational design. A
Pearson Correlation was selected in order to determine whether or not there was a
con-elation between scores from the GSCT, BDI-II, HDl, and related subtest items.
Results would show whether scores in the GSCT would correspond with higher/lower
scores from the BDI-II and HDl tests. A two-tailed test and an alpha level of .01 (p:S .01)
were chosen in support of this evaluation. This statistical design was employed in order
to measure and describe the relationship and to determine significance, if any, between
the constructs in question.
Additional Analyses
R squared, sometimes referred to as the proportion of explained variation, was
also utilized to evaluate participant scores.
Because R squared is the relative predictive
power of a model, this regression analysis was chosen to evaluate further whether or not
total scores from the GSCT test had any predictive relationship with the BDI-II, HDl, or
GSCT subtest scores. The higher the predictive rate, the greater the ability the construct
in question (the GSCT) could predict how an individual might perform on the other
measures.
CHAPTER 5: RESULTS
32
Qualitative Analysis: Evaluating Subject Responses on the GSCT
Statistics
Descriptive Statistics: BDI-II, HDI, and GSCT Scores
During the initial phase of statistical analyses, ifthere were any qualitative scores
differences such as race and age, between subjects' performances on the three instruments
in question were examined. Results indicated that as expected, a majority of the
participants scored within the "normal" or minimal range on the BDI-II (Table 4, Figure
3).
Table 4
Cross-tabulation ofParticipant Age, Race, and BDI-II Range ofScores
BDI-II Descriptive
African
Range
American
Caucasian.
Asian!
Biracial!
Hispanic/
Pacific
Mixed
Latino
Islander
Race
Other
Total
Minimal
Age
18-25
6
21
1
1
0
0
29
(0-13)
Range in
26-35
6
2
2
0
0
0
10
Years
36-45
7
2
0
0
0
0
9
46-55
4
3
1
0
0
1
9
33
56-70
3
0
0
0
0
0
29
31
4
5
70+
Total
0
8
0
0
1
0
1
66
0
0
3
Mild
Age
18-25
0
3
0
(14-19)
Range in
26-35
3
1
0
0
0
5
3
4
0
0
0
8
0
Years
Total
Moderate
Age
18-25
0
2
0
0
0
0
2
(20-28)
Range in
36-45
2
0
0
0
0
0
2
Years
46-55
0
0
0
0
0
1
2
2
0
0
0
5
Total·
Severe
Age
(29-63)
Range in
18-25
1
Years
Total
1
34
Figure 3. Illustration of age & racial differences across "Minimal" BDI -II scores.
*BDI-II Descriptive Range=Minimal (0-13)
Race
25
• African American
Caucasian
D Hispanic/ Latino
• Asian! Pacific
Islander
D Other
20
§
1
0
U
1
5
o
18-25
26-35
36-45
46-55
55-70
70+
Years of Years of Years of Years of Years of Years of
Age
Age
Age
Age
Age
Age
Age Range
Only one of the volunteers scored within the "Severe" range on the BDI-II.
Conversely, 66 of the 80 participants scored within the "Minimal" range, 8 individuals
scored in the "Mild" range and only 5 scored within the "Moderate" range (Table 4).
Scores from African Americans and Caucasians appeared to be similarly distributed on
the BDI-II (approximately 85% of the participants scoring in the "Mild" range,
approximately 10% in the "Minimal", and approximately 5% and 0% falling in the
Moderate and Severe ranges, respectively). All Hispanic/Latino subjects (n = 4),
35
however, scored within the "Mild" range. Similarly, Asian/Pacific Islander,
Biracial/Mixed Race, and Other respondents did not demonstrate scoring patterns similar
to the African American and Caucasian subjects.
A notable difference was observed when Gender was introduced into the
tabulation analyses ofBDI-II scores (Table 5). The addition of this factor revealed that a
single "Severe" score was obtained by a female subject of Asian or Pacific Islander
descent. As compared to Caucasian male and female reporting styles, African American
and Hispanic/Latino males tended to respond more similarly to their female counterparts.
No apparent trends existed among male or female respondents from the other racial
groups.
Table 5
Cross-tabulation of BDl-ll Scores when A ccoun tingfor Age, Race, & Gender
Gender-Female
Race
BDI-II Descriptive
African
Range
American
Caucasian
"
18
Asian/
Biracial!
Hispanic/
Pacific
Mixed
Latino
Islander
Race
Other
Total
0
0
22
Minimal
Age
18-25
.)
(0-13 )
Range in
26-35
4
2
0
0
0
7
Years
36-45
4
0
0
0
0
5
2
0
0
0
0
3
3
0
0
0
0
6
46-55
56-70
,.,
.)
0
36
70+
Total
0
0
0
0
0
0
0
15
25
2
1
0
0
43
Mild
Age
18-25
0
3
0
0
0
0
3
(14-19)
Range in
26-35
3
1
0
1
0
0
5
3
4
0
0
0
8
Years
Total
Moderate
Age
18-25
0
2
0
0
0
0
2
(20-28)
Range in
36-45
2
0
0
0
0
0
2
2
2
0
0
0
0
4
0
0
0
1
0
0
0
0
0
1
0
0
Years
Total
Severe
Age
(29-63)
Range in
18-25
Years
Total
Gender-Male
Race
Minimal
Age
18-25
3
3
1
0
0
0
7
(0-13)
Range in
26-35
2
1
0
0
0
0
3
Years
36-45
3
1
0
0
0
0
4
46-55
3
1
1
0
0
1
6
56-70
2
0
0
0
0
0
2
70+
1
0
0
0
0
0
14
6
2
0
0
1
0
0
0
0
Total
Moderate
Age
46-55
0
23
37
Range in
(20-28)
Years
o
Total
o
o
o
o
1
1
As in the case of the BDI-ll, descriptive analyses of the HDI indicated that a
majority of respondents scored within the lowest possible range ("Not Depressed"). As
with the BDI-l1, HOI scores fj'om African American males and females were more
similar than their male and female Caucasian counterparts. Furthermore, as on the BDIII the single "Severe" score was obtained by one subject: an Asian/Pacific Islander
female.
Table 6
Cross-tabulation of Age, Race, and Gender Factors and HDI Score Ranges
Ge nder-Female
Race
HDI Descriptive
African
Range
American
Caucasian
Asian!
Biracial!
Hispanic/
Pacific
Mixed
Latino
Islander
Race
Other Total
Not
Age
18-25
3
19
0
1
0
0
23
Depressed
Range
26-35
4
2
2
1
0
0
9
(0-13.5)
in Years
36-45
5
1
0
0
0
0
6
46-55
1
2
0
0
0
0
3
38
56-70
Total
3
3
0
0
0
0
6
16
27
2
2
0
0
47
Subclinical
Age
18-25
0
3
0
0
0
0
3
(14.0-18.5)
Range
26-35
2
0
0
0
0
0
2
2
3
0
0
0
0
5
1
0
0
0
0
0
1
0
0
0
0
0
1
0
1
0
0
0
0
1
0
0
0
0
1
in Years
Total
Mild
Age
(19.0-25.5)
Range
36-45
in Years
Total
Moderate
Age
18-25
(26.0-32.5) Range
in Years
Total
Moderate
Age
to Severe
Range
(33.0-39.5)
in Years
0
26-35
Total
Severe
Age
(40.0+)
Range
18-25
1
0
0
0
0
0
1
1
0
0
0
0
0
1
0
0
0
1
0
0
1
0
0
0
1
0
0
1
in Years
Total
39
Not
Age
18-25
3
2
1
0
0
0
Depressed
Range
26-35
2
1
0
0
0
0
3
(0-13.5)
in Years
36-45
2
0
0
0
0
3
46-55
3
1
1
0
0
1
6
56-70
1
0
0
0
0
0
1
0
0
0
0
0
1
12
5
2
0
0
1
20
70+
Total
Subclinical Age
36-45
1
0
0
0
0
0
1
(14.0-18.5) Range
46-55
0
0
0
0
1
0
1
56-70
1
0
0
0
0
0
1
2
0
0
0
1
0
3
0
1
0
0
0
0
1
0
1
0
0
0
0
in Years
Total
Mild
Age
18-25
(19.0-25.5) Range
in Years
Total
When compared with the BDI-II and HDI, the most apparent differences noted
across GSCT scores involved the range in scores. BDI-II and HDI participant range of
scores tended to be more similar than those found on the GSCT. For example,
participants did not achieve beyond the "Mild" range (Table 7) on the GSCT. That is to
say, individual scores ranged from a total score of 6 to 29 and fell within the "Minimal"
and "Mild" ranges, respectively.
40
Table 7
GSCT Score Ranges, Frequency Count, and Actual Participant Scores
Unlike
from
BDI-II
Cumulative
Percent
Freguency
Percent
59
73.8
73.8
73.8
21
26.3
26.3
100.0
80
100.0
100.0
Valid Minimal
(0-18)
Mild
(19-37)
Total
8
9
10
II
12
13
14
15
16
17
18
19
21
22
23
24
25
28
29
Total
Valid
Percent
3
3
4
5
6
1
9
8
6
6
5
6
4
1
3
2
I
2
1
80
3.8
3.8
5.0
6.3
7.5
1.3
11.3
10.0
7,5
7.5
6.3
7.5
5.0
1.3
3.8
2.5
1.3
2.5
1.3
100.0
3.8
3.8
5.0
6.3
7.5
1.3
11.3
10.0
7.5
7.5
6.3
7.5
5.0
1.3
3.8
2.5
1.3
2.5
1.3
100.0
8.8
12.5
17.5
23.8
31.3
32.5
43.8
53,8
61.3
68.8
75.0
82.5
87.5
88.8
92.5
95.0
96.3
98.8
100.0
results
the
and
RDI measures, no scores feLl within the "Severe" range. Despite this difference, African
American and Caucasian GSCT scores appeared to fall similarly within the "Minimal"!
"Mild" (BDI-II) and "Not Depressed"! "Subclinical" (RDI) ranges (Table 8). Although
41
the difference between ranges of scores was less on the GSCT results, all three measures
appeared to have similar pattern of scores across age and racial lines (Figure 4).
Table 8
GSCT Score Ranges & Age, Race, and Gender
Cross~tabulation
Gender~F emale
Race
GSCT Descriptive
African
Range
American
Caucasian
Asian!
Biracial!
Hispanic!
Pacific
Mixed
Latino
Islander
Race
Other
Total
Minimal
Age
18-25
2
17
0
1
0
0
20
(O~18)
Range
26-35
5
2
2
0
0
0
9
in Years
36-45
4
1
0
0
0
0
5
46~55
1
1
0
0
0
0
2
56~70
3
2
0
0
0
0
5
15
23
2
0
0
41
0
0
8
0
0
3
2
Total
Mild
Age
18~25
1
6
0
(19~37)
Range
26-35
2
0
0
in Years
36-45
2
0
0
0
0
0
Total
46-55
0
1
0
0
0
0
56~70
0
1
0
0
0
0
5
8
0
2
0
0
Gender~Male
1
15
42
(0-18)
Age
18-25
2
Range
26-35
2
in Years
36-45
3
46-55'
3
56-70
70+
Total
0
0
0
5
0
0
0
0
3
0
0
0
0
4
0
0
0
0
1
4
1
0
0
0
0
0
1
1
0
0
0
0
0
1
12
4
1
0
0
1
18
1
0
0
0
0
2
1
0
1
0
3
0
0
0
0
0
1
0
2
Mild
Age
36-45
1
(19-37)
Range·
46-55
0
in Years
56-70
1
0
2
2
Total
6
43
Figure 4. Example comparison ofBDI-II, HDI, and GSCT lowest score sets around age
and racial factors.
*BDI-II Descriptive Range=Minimal (0-13)
Race
25
III
African American
[l;U Caucasian
D Hispanic/ Latino
Asian/ Pacific
Islander
D Other
20
1:l 15
;:1
o
U
70+
18-25
26-35
36-45
46-55
55-70
Years of Years of Years of Years of Years of Years of
Age
Age
Age
Age
Age
Age
Age Range
44
*HDI Descriptive Range=Not Depressed (0-13.5)
Race
25
African American
Caucasian
20
+-'
§
1
D
o
Asian! Pacific
Islander
Other
U
5
o
55-70
70+
] 8-25
26-35
46-55
36-45
Years of Years of Years of Years of Years of Years of
Age
Age
Age
Age
Age
Age
*GSCT Descriptive Range=Mild (19-37)
§
7
Race
6
African American
II!] Caucasian
D Hispanic! Latino
5
II Asian! Pacific
Islander
o Biracial! Mixed
4
o
Race
U
3
18-25
Years of
Age
26-35
Years of
Age
36-45
Years of
Age
Age Range
46-55
Years of
Age
55-70
Years of
Age
45
Results also indicated that the distribution of subject scores on the BDI-II, HDI, and
GSCT tests differed (Figure 6). BDI-II and HDI scores demonstrated a similarly skewed
distribution pattern, in which most of the scores fell within the lower ranges. However,
the GSCT djstrjbutjon pattern more closely resembled a normal distribution (in which
higher scores fell within the mjddle of the distribution).
Figure 5. Comparisons of BDI-lI, HDI, and GSCT total score distributions.
BDI-U Score
o
Mean = 7.41
Std. Dev. = 7.122
N=80
10
20
BDI-II Score
30
40
46
HDI Score
0.00
10.00
20.00
30.00
40.00
50.00
Mean = 8.6635
Std. Dev. =
7.41194
N = 80
GSCT TOTAL Score
14
12
10
;>-,
u
t:1
II)
8
5<JJ
!-<
r..t-.
6
4
2
0
5
10
15
20
GSCT TOTAL Score
25
30
Mean = 15.49
Std. Dev. = 5.166
N=80
47
Correlations and Statistical Significance
Testing the Primary Hypothesis
The chief hypothesis of this experiment maintained that if the GSCT was
administered to a "normal" sample of non-disordered volunteers, then GSCT scores
would be positively correlated with scores from the BDI-II and HDI tests. Thus a
Pearson correlational analysis was conducted in order to evaluate the relations4ip, if any,
between the GSCT and the other two measures. When compared with the BDI-II, results
demonstrated statistical significance on a two-tailed test and an alpha level of .01 (p ::s
.01). Thus this evaluation illustrated the point that total scores on the GSCT were, in fact,
positively correlated (.451) with total BDI-II scores (Table 9).
Table 9
BDI-ll and GSCT Correlation Results
BDI-II Score
BDI-II Score
GSCT TOTAL Score
Pearson
.45
.000
Sig. (2-tailed)
N
GSCT TOTAL Score
Pearson Correlation
Sig. (2-tailed)
80
.451 **
1
.000
N
** .Correlation is significant at the 0.01
80
80
level (2-tailed).
80
48
Similarly, a Pearson correlation was also used to evaluate the relationship between the
GSCT and HDI. A two-tailed test and a .01 alpha level (p:'S .01) were also employed to
evaluate this aspect of the initial hypothesis. Results again suppOlied the hypothetical
premise, determining that there was statistical significance, and showing a .541 positive
correlation between the two tests (Table 10).
Table 10
Positive Correlation betyveen GSCT and HDI Total Scores
GSCT TOTAL Score
GSCT TOTAL Score
Pearson Correlation
HDI Score
1
.000
Sig. (2-tailed)
N
HDI Score
Pearson Correlation
80
80
.541 **
1
.000
Sig. (2-tailed)
80
N
** .Correlation is significant at the 0.01
.541 **
level (2-tailed).
BDI-II and GSCT Dimension Subtests
Positive correlations were also determined and found to be statistically significant
(at the 0.01 level, whereas p:'S .01) when the BDI and GSCT Dimension items were
80
49
compared. As Table 11 indicates, BDI total scores demonstrated a .497 positive
correlation with the GSCT Dimension Total scores.
Table 11
Statistical ,-~'igniflcance Determined when BDJ-JJ and GSCT Dimension Totals Compared
GSCT Dimension
BDI-II Score
TOTAL
BDT-II Score
Pearson Correlation
1
Sig. (2-tailed)
N
GSCT Dimension TOTAL
Pearson Correlation
Sig. (2-tailed)
N
.000
80
80
.497**
1
.000
80
**.Correlation is significant at the 0.0 1 level (2-tailed).
When the additional GSCT Dimension subtest items were compared with the BDT total
scores, significance was again established. Pearson statistics found that BDI total scores
positively correlated with the Total Self, World, and Future subtest scores at rates of .449,
.362, and .308, respectively (Tables 12, 13, and 14).
.497**
80
50
Table 12
Statistical Sign(ficance Established with BDI-II Scores and GSCT Self Dimension
Compared
GSCT Dimension Self
BDI-II Score
BDI-II Score
Pearson Correlation
1
Sig. (2-tailed)
N
GSCT Dimension Self
Pearson Correlation
Sig. (2-tailed)
N
**.Correlation is significant at the 0.01 level (2-tailed).
.449**
.000
80
80
.449**
1
.000
80
80
51
Table 13
Positive Correlation of. 362 found when BDI-II and GSCT World Dimension Scores
Compared
BDI-II Score
BDI-II Score
GSCT Dimension World
.362**
Pearson Correlation
.000
Sig. (2-tailed)
N
GSCT Dimension World
Pearson Correlation
Sig. (2-tailed)
N
** .Correlation is significant at the 0.01 level (2-tailed).
80
80
.362**
.000
80
80
52
Table 14
BDJ-JJ and GSCT Future Dimension Scores Demonstrate Positive Correlation
GSCT Dimension
BD I-II Score
Future
BDI-II Score
Pearson Correlation
1
.005
Sig. (2-tailed)
N
GSCT Dimension Future
Pearson Correlation
Sig. (2-tailed)
N
.308**
80
80
.308**
1
.005
80
**.Correlation is significant at the 0.01 level (2-tailed).
Although Table 14 indicated a statistically significant correlation between scores from
the two measures (BDI-II and GSCT Dimension subtests), results also revealed that BDIII scores had the weakest correlation on GSCT items related to Future content material.
Of the two remaining GSCT Subtest items, Self-related stems were more positively
correlated with BDI-II scores than with World-related sentence stems. These two
Pearson comparisons revealed correlations of .449 and .362, respectively.
80
53
HDJ and GS'CT Dimension S'ubtests
HD1 Total Scores were also compared with GSCT Dimension Subtest items.
Results from the two-tailed Pearson Correlation indicated that an alpha level of .01 (p .:s
.01) yielded statistical significance when HDI Total Scores were compared with GSCT
Dimension Total Scores (Table 15). The strength of the correlation between the HD1
Total Score and GSCT Total Dimension Score was measured as .600. As indicated on a
similar comparison to the BD1-II, Tables 16, 17, and 18 show that there was, in fact, a
significant positive correlation between the HDI Total Scores and all three of the GSCT
Dimension Subtests (Self, World, and Future). However, the Pearson Correlation
indicated that Self and Future GSCT Subtests were more positively correlated with the
HDI than with their World counterpart. In fact, the strongest positive correlation of .558
was found in the relationship between HDI and the GSCT Dimension Self Subtest (Table
16). Following the Self Subtest, the BDI-II correlated most notably with the Future
scores (.438), followed by the GSCT World Dimension Subtest (.351) (Tables 17 and
18). In other words, subjects who achieved elevated HDI total scores were more likely to
articulate a greater number of negative self responses (or those most associated with
depressive symptoms) than they would articulate negative statements related to the
future. These same individuals tended to offer the negative or depressive statements
about others less often.
54
Table 15
Positive Correlation Demonstrated when HDI and GSCT Dimension Total Scores
Compared.
GSCT Dimension
HDI Score
TOTAL
HDI Score
Pearson COlTelation
1
.000
Sig. (2-tailed)
N
GSCT Dimension TOTAL
Pearson Con-elation
Sig. (2-tailed)
N
** .ColTelation is significant at the 0.01 level (2-tailed).
.600**
80
80
.600**
1
.000
80
80
55
Table 16
Comparison of the Strongest Correlation between the HDI Total Score and GSCT Self
Dimension
GSCT TOTAL Score
GSCT TOTAL Score
.541 **
Pearson Correlation
.000
Sig. (2-tailed)
N
HDI Score
Pearson Correlation
Sig. (2-tailed)
N
**.Conelation is significant at the 0.01 level (2-tailed).
HDI Score
80
80
.541 **
1
.000
80
80
56
Table 17
HDI Total and GSCT World Dimension: Weakest Positive Correlation
GSCT Dimension Wodd
HDI Score
HDI Score
.351 **
Pearson Correlation
.001
Sig. (2-tailed)
N
GSCT Dimension World
Pearson Correlation
Sig. (2-tailed)
80
.351 **
1
.001
N
** .Correlation is significant at the 0.01
80
80
level (2-tailed).
80
57
Table 18
Sign(ficant Correlation Demonstrated between the HDI Total Score and the GSCT
Dimension Future
GSCT Dimension
HDI Score
Future
Pearson Correl ation
HDI Score.
1
.000
Sig. (2-tailed)
N
GSCT Dimension Future
Pearson Correlation
Sig. (2-tailed)
N
.438**
80
80
.438**
1
.000
80
* * .Correlation is significant at the 0.01 level (2-tailed).
When the HDI Melancholia Subscale and GSCT scores were compared, an
additional facet of the secondary hypothesis was tested. This analysis proved that HDI
Melancholia Subscales positively cOITelated both with GSCT total scores and with GSCT
Dimension totals (Tables 19 and 20). That is to say, the higher the GSCT Total or
Dimension Subtest, the higher the resulting HDI Melancholia Scores. In these cases, a
Pearson two-tailed test (p S .01) found statistical significance and positive correlations of
.444 between the HDI Melancholia Subscale and GSCT Total (Table 19) and .497
between the lIDT Melancholia Subscale and GSCT Dimension Total (Table 20).
80
58
Table 19
Pearson Comparison ofGSCT Total Scores and HDI Melancholia Subscale
GSCT TOTAL Score
GSCT TOTAL Score
Pearson Correlation
1
.000
Sig. (2-tailed)
N
HDI Melancholia
Pearson COlTelation .
Sig. (2-tailed)
N
** .Correlation is significant at the 0.01 level (2-tailed).
HDI
80
80
.444**
.000
80
80
59
Table 20
Statistical Significance Demonstrated when GSCT Dimension Total compared with HDI
Melancholia Subscale
IIDI Melancholia
GSCT Dimension
TOTAL
GSCT TOTAL Score
Pearson Correlation
.497**
1
.000
Sig. (2-tailed)
N
HDI Score
Pearson Correlation
Sig. (2-tailed)
N
80
80
.497**
1
.000
80
80
** .Correlation is significant at the 0.01 level (2-tailed).
Additional analyses of the HDI indicated that scores from the IIDI Melancholia
Subscale were also positively correlated with scores from the three GSCT subtests.
When the HDJ Melancholia Subscale was compared to the subtests through a two-tailed
Pearson Correlation analysis (p
:s .01), signHicant relationships were found.
A
correlation of .501 and .390 existed between the HDI measure and GSCT Self and Future
subtests, respectively (Tables 21 and 23). However, an alpha level of .05 was required to
establish statistical significance when the HDI Melancholia Subscale was compared with
the GSCT World Subtest. Results indicated that tIlls was the weakest correlation.
Specifically, there was a .245 positive correlation on a two-tailed test (p:S .05) when
60
these two measures were evaluated. In this instance, a modified alpha level (from .01 to
.05) was required in order to establish a significant relationship between the HDI
Melancholia Subscale and GSCT World Subtest (Table 22).
Table 21
Positive Correlation of.501 Demonstrated on the HDI Melancholia Subscale and GSCT
Self Dimension Subtest
GSCT Dimension Self
HDI Melancholia
HDI Melancholia
Pearson Correlation
1
.000
Sig. (2-tailed)
N
GSCT Dimension Self
80
80
.501 **
Pearson Correlation
Sig. (2-tailed)
.000
N
80
** .Correlation is significant at the 0.01 level (2-tailed).
Table 22
Correlation between HDI Melancholia Subscale and GSCT World Dimension Subtest
only Significant with an Alpha Level of. 05 (p
.501
~. 05)
80
61
HDI Melancholia
HDI Melancholia
GSCT Dimension
.245*
Pearson Correlation
.028
Sig. (2-tailed)
N
GSCT Dimension World
Pearson Conelation
Sig. (2-tailed)
80
80
.245*
1
.028
80
80
N
*.Correlation is significant at the 0.05 level (2-taiIed).
Table 23
HDIlvfelancholia Subscale and GSCT Future Dimension Compared
HDI
Future
62
HDI Melancholia
Pearson Correlation
1
.000
Sig. (2-tailed)
N
GSCT Dimension Future
Pearson Correlation
Sig. (2-tailed)
N
.390**
80
80
.390**
1
.000
80
* *.Correlation is significant at the 0.01 level (2-tailed).
R Squared and Supplementary Analyses
In order to evaluate the relative predictive power ofthis model, R Squared was
employed during the next phase ofthe statistical examination. This analysis allowed for
both the evaluation of the relationship between the BDI-II, HDI, GSCT, and related
subtests and tbe examination of the degree, if any existed, tbat a predictive relationship
existed between the measures. When the GSCT was compared with the BDI-lI, results
indicated an r2 = .203. Additionally, an R Squared value of .293 (1'2 = .293) was reve';lled
when the GSCT and II OI tests were assessed. These findings indicated that an
individual's score on the BDI-II would be likely to predict resulting GSCT total scores
20.3% ofthe time. Similarly in the case ofthe GSCT and HDI, an r2 value of .293 found
a relative predictive power of29.3%.
This regression test was also initiated in order to evaluate the variance across
factors related to the GSCT. For example, R Squared values were also recorded when the
GSCT sub test scores (self, world, and future) were evaluated against those from the total
80
63
GSCT scores. Results indicated that GSCT subtest scores, or those perceptions related to
self, world, and future, could predict an individual's Total GSCT scores 57% (self=
.570), 52.4% (world = .524), and 43.9% (future = .439) of the time. When compared
together, GSCT Total Dimension subtest scores and GSCT overall total gleaned a 92.9%
predictive rate.
Although the data supported the principal and secondary hypotheses (that the
GSCT total would demonstrate a positive, significant correlation with the BDI-II and
HDI total scores; and that the GSCT subtest scores would also be positively correlated
with scores from the BDI-II, HDI, and HDI Melancholia SUbscale), supplementary
analyses were also conducted in order to augment the initial set of statistical findings.
An additional correlational analysis was conducted in order to determine
whether or not additional variables, such as the subject demographic factors of age, race,
and gender had any impact upon the GSCT Total or GSCT Subtest scores. Results
indicated that there was no significant relationship between age, race, or gender when
compared with participant scores. Similarly, R Squared analyses suggested that when
compared with GSCT Total and subtests scores there was very little predictive power
when the variables of age, race, or gender were introduced.
Qualitative Analysis: Evaluatingfor Differences across GSCT Item Scores
In order to evaluate whether or not GSCT Total and Subtest items were actually
evaluating different factors of depression, the relationship between all GSCT scores were
assessed. Findings showed high correlational values when Total GSCT scores were
64
compared with GSCT subtest totals. For example, a two-tailed Pearson Correlational test
indicated at the Total GSCT scores were positively correlated with the Self, World and
Future test totals. As shown in Table 24, statistical significance was demonstrated at the
.01 level (a = .01) and gleaned correlational values of .755, .724, and .663, respectively.
When the GSCT Total scores were compared with GSCT Dimension Total scores,
significance was associated with a .964 correlational value (Table 25).
Table 24
Pearson Correlations be/ween GSCT Total and GSCT Dimension Subtest Items
N = 80
Correlation
Significance Level
65
TOTAL Score
.755
0.01
.724
0.01 level (2-tailed)
.663
0.01 level (2-tailed)
.663
0.0 I level (2-tailed)
And GSCT Dimension Self
GSCT TOTAL Score
And GSCT Dimension World
GSCT TOTAL Score
And GSCT Dimension Future
GSCT TOTAL Score
And GSCT Dimension Total
** .Correlation is significant at the 0.01
level (2-tailed).
Table 25
Highest Correlation demonstrated when GSCT TOTAL Scores and GSCT Dimension
Total Scores compared
66
GSCT TOTAL Score
GSCT Dimension
TOTAL
GSCT TOTAL Score
1
Pearson Correlation
.964**
.000
Sig. (2-tailed)
N
GSCT Dimension TOTAL
Pearson Correlation
Sig. (2-tailed)
80
80
.964**
1
.000
N
80
80
'** .Conelation is significant at the O.Ollevel (2-tailed).
When GSCT Dimension Totals were compared with the three individual
dimensions (Self, World, and Future), high correlations were also achieved. This Pearson
analysis resulted in statistically significant relationships on a two-tailed test (a = .0 1).
That is to say, GSCT Dimension Totals were positively correlated with separate subtest
items of Self: World, and Future at rates of.770, .730, and .675 respectively. However,
when each of the subtest items was compared with each item's respective counterpart,
there was less correlation than on previous analyses or there was demonstrated no
significant relationship at all (Tables 26-28).
Table 26
Pearson CorrelaOonal comparhlOns olGSCr Subtest Items Se(f and World
GSCT TOTAL Score
GSCT Dimension
TOTAL
67
GSCT Dimension Self
.318**
1
Pearson Correlation
.004
Sig. (2-tailed)
N
GSCT Dimension World
Pearson Correlation
Sig. (2-tailed)
80
.318**
1
.004
80
80
N
**.Correlation is significant at the 0.01
80
level (2-tailed).
Table 27
Significant Correlation between GSCT Self and Future Subtest items.
GSCT TOTAL Score
GSCT Dimension
GSCT Dimension
Self
Future
Pearson Con-elation
1
.000
Sig. (2-tailed)
N
GSCT Dimension TOTAL
Pearson Con-elation
Sig. (2-tailed)
80
80
.391 **
1
.000
80
N
**.Con-elation is significant at the 0.01
.391 **
level (2-tailed).
Table 28
No Correlation found When GSCT World and Future Dimension Subtests Compared
80
68
GSCT Dimension World
GSCT Dimension
GSCT Dimension
World
Future
Pearson Correlation
1
.051
Sig. (2-tailed)
N
GSCT Dimension Future
Pearson Correlation
Sig. (2-tailed)
N
** .Correlation is significant at the 0.01 level (2-tailed).
.219**
80
80
.219**
1
.051
80
80
69
CHAPTER 6: DISCUSSION
Findings
As hypothesized, Goodwin Sentence Completion Test scores were positively
correlated with scores from the BDI-II and HDI tests. The investigation also highlighted
the relative strength of self-, world-, and future-oriented items associated with the
Cognitive Triad (Beck 1967; Beck 1976). Further analysis proved that all three of these
factors (GSCT Dimension Subtests) were also positively correlated with the Beck
Depression Inventory (2 nd Edition), Hamilton Depression Inventory, and HDI
Melancholia Subscale. Thus both the principal and secondary hypotheses were supported
when examined by Pearson Correlation and R-Squared statistics.
Implications
The sample population selected to evaluate this study comprised "normal" or nondisordered volunteers. All three measures (BDI-II, HDI, and GSCT) were designed to
evaluate these individuals for symptoms of depression. Thus results were consistent with
this sampling and showed almost no instances of elevated scores associated with
clinically depressed people. The outcome of this investigation can be interpreted to
suggest that the GSCT does, in fact, do what it purports to do: screen individuals for and
evaluate symptoms of depression. Although qualitative analyses appeared to indicate that
there might have been differences in respondents along racial lines, statistical analyses
70
proved that this variable was unrelated to GSCT scores. Similarly, no difference was
found when the remaining subject demographic factors of gender and age were assessed.
Despite the fact that the instruments were positively correlated, distribution of
BDI-II, HDI, and GSCT scores did not fall within the same patterns (Figure 6). Instead,
both BDI-II and HDI test scores showed a negatively skewed distribution. However,
GSCT scores were normally distributed. These findings indicated that as expected, a
majority of the non-disordered individuals used in this study achieved correspondingly
lower BDI-II and HDI scores. llowever, GSCT scores were normally distributed.
Therefore they did not show a negatively skewed pattern of subject scores which one
might have expected in a sample of "normal" subjects. Similarly, GSCT scores fell only
within the established "Minimal" and "Mild" ranges. However, associated BDI-II and
HDI subject scores showed a greater difference and fell across more than two ranges
(Tables 5, 6, & 8). This suggests that although the GSCT positively correlates with the
other two measures, the actual instrument does not appear to demonstrate the relative
strength and ability to discriminate depressive symptoms as do the BDI-II and HDI tests.
Results from a comparison of the BDI-II and HDI measures and GSCT
Dimension subtest scores also provided a great deal of useful information. For example,
HDI Melancholia subscale and GSCT subtest score correlations suggest that individuals
with higher negative self perceptions will score higher on the HDI Subscale than those
with negative world views. In fact, the correlation between these items was reasonably
lower than HDI Melancholia Subscale and self, future, or total dimension analyses.
Furthermore, this relationship was signiticant only when the alpha level was changed
from .01 to .05. This adjustment in alpha (a"'" .05) increased the test's potential to find a
71
statistically valid cOlTelation. This outcome seems to indicate that this weaker
relationship may be due in pat1 to the fact that individuals tend to have a consistent self
view. On the other hand, because different individuals are likely to provoke distinct
responses from subjects, results are likely to capture this variance and express it through
weaker correlations, Overall HDI scores and BOI-II comparisons with the GSCT Self
Dimension subtests also supported this interpretation.
When compared with GSCT Total scores, Self, World, and Future Dimension
scores demonstrated relatively strong predictive rates (57%, 52.4%, and 43.9%,
respectively). That is to say, one could use specific subtest scores to predict how an
individual would score on the GSCT. The fact that the values for these items was lower
than the R Squared value found when GSCT Total Dimension and GSCT Total scores
was compared (1'2 = .929), fm1her proved that the subtest items were actuaLly evaluating
different aspects of pru1icipant responses. This explanation was supported again when
the GSCT Subtest items were compared with each other using a Pearson correlation
(Tables 26-28). Although results suggested that the subtest items were correlated, the
significance values were relatively low (as compared to analyses involving the GSCT,
BDI-II and HOI). In fact, there was no con'elation at all between World and Future
GSCT Subtest scores.
72
Limitations
Use ofSe(f-Report Measures
Although many studies have demonstrated the usefulness of self-report measures,
other works conversely suggest that measures of depression correlate highly with
measures of anxiety and other emotional states (McGrath & Ratliff, 1993). Thus, despite
its proven ability to screen for clinical depression, the GSCT runs the risk of underrep011ing or over-reporting symptoms that may be attributed either to depression or to
another clinical syndrome. Because of the common role of negative affect in depression
and anxiety, this overlap brings into the question of the specificity of the GSCT results.
This point was highlighted in McGrath and Ratliffs 1993 study, wherein their results
suggested that mood often failed to discriminate between depressed and anxious mood
states because they believed that existing measures did not adequately address positive
affective states. Their study demonstrated the need to show that a theory of depression is
truly a theory of depression, instead of a theory of emotional distress. They found that in
order to discriminate truly between depression and other mood states, particularly
anxiety, researchers should load measures both with information related to negative
affectivity and positive affectivity to allow for true discriminations. Because the GSCT
was designed principally to measure the negative attributions, and depressive behaviors
or cognitions associated with this condition, it may have failed to evaluate adequately for
the pro social, optimistic experiences.
Although the Beck Depression Inventories have been found to be both valid and
reliable measures for assessing depression, some studies suggest that these measures may
73
be more likely to detect enduring symptoms such as sleep problems, suicidal ideation,
and somatic complaints rather than the initial features of depression immediately
following an adverse event (Abela & D' Alessandro, 2002). Immediately following a
negative event, cognitively vulnerable individuals show marked increases in depressed
mood. At the same time, they may not yet demonstrate typical signs of depression such
as loss of energy, or changes in sleep or appetite. As time progresses, the intensity of a
person's initial depressive mood reaction may lessen to that of most individuals
experiencing the same type of event. Thus, because the BDI-II evaluates a range of
depressive symptoms in addition to depressed mood, it may not be sensitive to intense
initial depressive mood reactions unless other symptoms (like sleep disturbances,
suicidality, and anhedonia) have also emerged. Because this study compared the results
of the GSCT to the BDI-II, results may be similarly insensitive to these phenomena.
Test Construction
The GSCT was modeled after a widely used projective instrument (RISB) without
standardized scoring methods; this fact should be considered when evaluating these
results. In addition, the sentence stems were initially administered to a convenience
sample; therefore, the methodology of stem selection may have also affected the final
outcome. A greater number of sentence stems used in this initial investigation of the
GSCT may have allowed for greater evidence concerning whether or not these
components added to (or detracted from) the overall construct validity of this tool. Such
an analysis alone could have actually set the stage for later comparisons.
74
The construction of the GSCT directions may have also impacted the reliability of
individual and overall subject scores. For example, the directions asked respondents to
complete the sentence stems with his/her" ... true feelings." Although this statement is a
standard request on many self-report tests such as the BDI-II and RISB tests (Beck, 1990;
Rotter et al., 1992), it may have elicited feeling statements in pa11icipants who, without
this prompting, may not have responded in this manner. Because feeling statements
tended to be associated with more active responses, these individuals may have achieved
slightly different scores had they chosen, instead, simply to describe their behaviors.
Finally, the theoretically underpinnings ofthe GSCT and comparison instruments
could have also been a factor that might limit the construct validity of this investigation.
For example, both the BDI-II and GSCT are based upon cognitive and behavioral factors
contributing to depression. However, the HDI was principally designed using a medical
modeL That is to say, a significant number of the statements are designed to elicit
information relative to an individual's somatic, biological, or physical experience
(Reynolds & Kobak, 1995). Although some of these elements are also included in the
BDI-II, the GSCT makes no references at all to these factors. As a result, these features,
which have proven to be associated with depression, mayor may not be adequately
evaluated for or adequately impact the results of GSCT scores.
GSCT scoring methods
Albeit the principal hypothesis of this study was related to the GSCT's ability to
correlate with the other measures, one of the main factors required in the evaluation
75
phase was a method by which to score this test. Scoring the Goodwin Sentence
Completion test requires the use of a newly-developed method based upon the
Vocabulary section of the WAIS-III (Wechsler, 1997). The WAIS-UI scoring methods
have been statistically proven to be reliable and valid; however, the GSCT adaptation has
not been evaluated. Similarly, the GSCT ranges assigned to depression levels (Minimal,
Mild, Moderate, and Severe) were based upon levels associated with the BDI-II (1976).
Therefore there is no evidence that the equidistant ranges assigned by the experimenter
were valid and actually captured the desired results. This fact may have contributed to
the apparent difference in ranges of scores found across the BDI-Il, HDI, and GSCT
measures. Reassigning the range of scores based upon the results of this investigation,
and subsequent studies (if appropriate) would thereby increase the reliability and validity
of the GSCT scoring methodology.
An additional issue which may have affected the results of this study involved the
scoring of omitted items. Although written (and oral) directives instructed participants to
complete all test items, volwlteers occasionally skipped some of the questions on the HDI
and GSCT tests. The HDI scoring allowed for these phenomena by assigning adjusted
scores and/or by modifying the mathematic calculations. However, these items were
simply omitted when scores on the GSCT were computed.
Scoring the GSCT involved averaging figures. Hence these adjustments did not
interfere with the ability to obtain results. Nonetheless, the omission of these items likely
affected the ability to describe participants' total scores accurately. Rather than omitting
subject scores, it may have been more effective to interpolate missed items. For example,
an average of an individual's scores on similar items could have been taken,
01'
the
76
average of the item immediately above or below the missed stem may have been more
reliable than a simple omission. In either case, not including a limit on the number of
skipped items might have also impacted the outcome. In fact, establishing the number of
items that can be missed in order to have a valid protocol is a critical feature of test
construction. Additional research can determine which of the two techniques (omitting
skipped items or interpolation) is a more statistically reliable method of scoring the
GSCT.
Evaluating inter-rater reliability
If a randomly selected subset group completed GSCT protocols was analyzed in
order to establish inter-rater reliability, then the reliability of the GSCT instrument would
have been greatly enhanced (Okamoto, 2001; Kazdin, 1998). Licensed mental health
professionals could have been invited to participate in this investigation. In so doing,
scoring differences among evaluators, as well as any scoring issues, could be highlighted.
Such a comparison might demonstrate inter-rater reliability if results showed that there
was agreement (or relative similarity) between evaluators. Even though possible
responses and scores were included in the GSCT Administration Procedures and Scoring
Instructions, the reliability of this instrument may be also enhanced by including actual
subject response examples and score examples from this investigation. These additions
would allow for greater similarity between clinician raters and may provide greater
clarity when scoring.
77
Control and Experimental Groups
The use of control and experimental groups could have also enhanced the validity
of this investigation. By comparing a depressed group with a "normal" group of
individuals, the results could have more accurately determined whether or not the GSCT
was actually measuring what it was designed to measure. Such a comparison would have
also required the use of more complex statistical analyses such as multivariate analyses.
For example, a MANOV A multivariate analysis could have been employed to evaluate
differences between the depressed and non-depressed individuals. If a difference was
found between these groups, and the null hypothesis (Ho) was rejected, then a Post Hoc
ANOVA test could have been used. This test would have allowed for the further
evaluation of the additional dependent variables (self, world, and future dimensions).
According to Anastasi (1985), psychological testing has been relying more
heavily upon instruments that yield multiple scores. A profile of an individual's scores,
illustrating both high and low points and strengths and weaknesses, is more informative
than a single, global score. If subtests are to be used, reliabilities of the subtests should
also be available. Thus the Post Hoc test may illustrate whether or not there is a
difference between these individual constructs; it can also determine the degree of
difference, and may help to demonstrate which, if any, of the dimensions are principally
responsible for the signifIcant difference(s) found within this statistical analysis.
78
Generalizability and Sample Size
As previously mentioned, this investigation did not include a sampling of
depressed individuals in order to compare test performances by their non-depressed
counterparts. For exan1ple, it did not evaluate depressive symptoms with respect to
children or adolescents. As a result, the outcome of this investigation should not
automatically be considered relevant with respect to youth under the age of 18 (Moilanen,
1995). Because some studies have shown that depression experienced by adults may
have emerged from maladaptive cognitions (Bender, 2002), attributions and/or schema
initially developed in childhood (Beck 1972 & 1974), assessing children could be a
valuable next step in the validation of this tool. Similarly, cultural or socio-economic
differences were not specifically controlled for or evaluated an10ng the participants; this
could have provided significant clinical information.
The relatively small sample size also impacts the ability to generalize these
results. In fact, because they were derived from fewer items,
Subtest~
achieved from
clinical analyses of the cognitive dimensions may be less reliable than total scores
(Anastasi, 1985). Future studies may work to enhance the sentence stems, provide
additional statistical analyses to validate the reliability of the stems, and utilize a greater
number of patient participants (Anastasi, 1985,2001; Helmes & Barillco, 1988).
79
Additional Research Questions and Considerations
The construction of the Goodwin Sentence Completion Test and its comparison
with the other measures was a prime example of how additional research can allow for
greater exploration of this tool. As described above, ongoing investigation can help to
determine whether or not these results may be replicated, potentially assisting in further
refinement of the scoring methodologies developed for this study. Longitudinal studies
of the GSCT can help to determine the nature and degree of change, if any, across subject
responses. For example, how distinct treatment modalities, the effects of time, and other
natural factors impact GSCT scores. Additionally, further investigations can help
determine whether or not the GSCT is able to discriminate state versus trait depression
(or anxiety for that matter).
Other sample populations, such as young children, racially homogenous groups,
and/or the elderly should be used for future studies involving the GSCT. These types of
population groups can allow that such variables be specifically validated in order to
determine how, if at all, they might impact results. Similarly, factors associated with
education levels, socio-economic status, profession, and other mental health conditions
should be considered because they may also alter the outcome of subsequent studies.
Although this investigation analyzed only the impact of age, gender, and race on subject
scores, the actual GSCT protocol request pmiicipants to repOli additional infOlmation
such as name, marital status, and occupation. Therefore it is recommended that further
studies also examine the effects, if any, of these demographic variables.
80
CHAPTER 7: CONCLUSION
The GSCT has proven to be a measure that can assist investigators both in
screening for and in evaluating symptoms associated with clinical depression. It
incorporates both historical knowledge and novel approaches to assessing and treating
depressed individuals. Because the experiment involved a sampling of non-disordered
volunteers, these results can be generalized to "normal" populations and be used in a
variety of settings. In so doing, screening tools can not only report relative levels of
pathology, adjustment, or discomfort, but may also provide a more evaluative glimpse
into the individual's personality and perceptions. Furthelmore, the relative ease of
scoring can allow both entry-level clinicians and seasoned practitioners to evaluate
subject's depressive symptoms and underlying perceptions. The GSCT can thereby
become a widely used and well-regarded method of screening for depression, evaluating
and individual's perceptions, and developing client-centered treatment approaches.
Ongoing research and investigation can only help to solidify the benefits of this new
measure. Indeed, the development of the GSCT represented an exciting research
oPPOliunity for this investigator. More impOliantly, results indicated that it may also
represent an exciting new frontier of studying and objectifying projective measures which
can impartially screen for clinical syndromes.
81
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93
Appendix A
Goodwin Sentence Completion Test (GSCT)-Prototype
Numbers 1-25 color-coded for analysis only. Numbers 1-6 refer to self-stems, 713 serve as filler items, 14-19 correspond to world-focused stems, and 20-25 refer
to future-based stems.
94
*PROTOTYPE ONLY*
Complete these sentences to express your tl'ueleelings. Please complete each one with a complete sentence.
1. I am _____~ _._______...__ ._.._~____._. __ _
C;
I cannot
3. 1 regret
4. [lear
5. [Vly appearance is __ ~_ ... __~._._.__._..__ ..~___....___ .____________~~_____________~__ _
15. Women
16. Men
17. [Viy mother ___._~____________________.. __________ _
]8. My lhther
II), rlsdati\'e~
will
---_.. _------- - - - -
95
Appendix B
Goodwin Sentence Completion Test (GSCT)-Final Version
Final version of the GSCT included. Filler items, and self, world, and future dimensions
have been randomly arranged and returned to normal font color to avoid participant bias.
96
Complete these sentences to express your true feelings. Please complete each one with a complete sentence.
1. lam
2. When I am able .-----_._---
3, My father
4. Eventually __
5. My personality is
6. What frustrates me
7, The f\ltuJ.'e ______________________ ~____________~
8. My mother ____.
9. Mywork
10,Icannot ________________________________________________________________
ll. In a few years _____________~____________.
12. Summer is _____.________.
13. My appem'ance is ______
14. Mwrriage ________________________________________
15. I fear
16, During holidays _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ __
17. Men
18. Winter is _____________________________________
19, Relatives _______________________-----______________
20.0nweekends ____________________________________________
21. I will be _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ __
22. Women _____________________
23, I regret
---------------~---.---.~------------
24,Sool1
25. At night ________.
97
Appendix C
GSCT Administration and Scoring Instructions
Administration and scoring instructions describe administration and scoring
procedures, give examples of how to score items, and provide scoring and
administration tips.
98
CJ'].)~['ATJ ill :l~ I1t~I1~:'} I~.] 111 ~ r~ H-] i1
i;}:)i (C}:j ~
!~U\niiIf:1ftJrreJil :lm:~q:tlIJ1:I:J~iT~ :f~mnuJ nl-iijU:ei[oliJ.'I
(PanB 1 of 3)
Testing ConsiderationsMaterials: pencll(s)
Inclusion crllerla: adults 18 years and older
General Directions·
After providing the individual with the instrument, say:
Investigators may repeat instruGiions if necessary. Partlcipants/subjeGis should be diractad to read instructions printed on
protocol if needed. Notable difficulties wllh these directions should be documented by the evaluator.
PromptingNo further direGiions should be provided to the examinee once they have begun the administration. If there are additional
questions, i.e., regarding clarification of the stems, the Individual should be prompted to:
Indlviduaillem responses·
In order to score each of tho 25 items, use Scoring Table to lind a corresponding, similar response type. INDIVIDUAL RESPONSES
DO NOT HAVE TO BE IDENTICAL TO THE EXAMPLES.
When similar response types are located, the investigator should assign the corresponding item score to the subject's response
and place this score next to appropriate the item number found on the GSCT Scoring Sheet. This scoring procedure applies to all
25 sentence stems.
Overall GSCT test scoresWhen all 25 of the items have been scored, and the appropriate scores have been placed next to the corresponding items on the
GSCT Scoring Sheet, then the Investigator should sum the total responses and place this number In the GSCT TOTAL SCORE line.
Tho aSCT TOTAL SCORE may be used to determine the severity of depressive symptoms:
Minimal «()"18), Mild (19·37), Moderate (38-56), 8. Severe (57-75)
Cognitive Triad items"Self" Ilems (1, 5, 10,13,15, and 23); "World" Items (3, 8, 14, 17, 19, and 22); "future" Items (2, 4, 7, 11, 21, and 24).
To determine average scores on these items, separately sum the total response scores for all set! items, world iiams, and future
Items (SumS, SumW, and SumF, respectively). Divide these sum 01 scores by 610 find average score for eech dimension:
SumS/6 = Self Score; SumW/6 = World Score; SumF/6" Future Score
99
~lJjnnl~jrt!lITuliI1{jl~qJ\Jr:J:J rrml :f~culir:J r.J.if'!Ieltl'mI-"i
(pil!Je 2013)
®©®rnlffi'@ l®[t)ll®
START HERE.
am
2) Whan 1am abla
3) My lather
emply, wortl,""",, hopeless",
ClY",
~dumb,
~ scared,
~ ma,e
~ ang!)"looeiy,
5) My personality is
~--+-:~-:s--:iiOrlii\i:iiiipojiiilir;
depressed,
I;O(lfuse<J,
plans, Ihin" w{:,h lor
selfish, didn'l k...
U', Is doaU, Is \1000, I:i un!tn<r~ll,,,
wUi und'llilsnd mG, gel oven,,,
changeable, 'ntl)marliable,,,
?J!!!.; 1..1ool\or, h"s lriends, go
?J!!!.; wain;!, unusual, Ihoughtlul,
!Jl!; happy, humorous, altracUvs,
ootter d"l", TV, gel 0 hairCllL..
1J!!; ok!, lal, !>aiding, rich, poor,
place., b'l popular",
InSOOJro, needy, unslab!e",
delermifl€~, ble.~ed, ~,~",_~
!Jl!; play, "x<lIr.L"" g,rdetl, read,
handsome, dNOr<OO, In shape,,,
1.ilt. wCII'1 need lreattnenl, have
ill; siiong, uni<1ue, shy, Rmid,
go to 11\OVIe:l",
Jl]!ij; OgOQd mall, h,mblo,
mOlley, be mora aluacllve, in 0000
goo<1, lair, hones I, kind",
!!..I!ffi chllfl!le can.'0rn, buy IlQlOO,
frl"nd~,
shape, "Ill finl3h1.IDrl..
!!..I!ffi leman<able, .lIong-wiifed,
!lJ!!l!: (goal$ln lar lulur6)
stubborn, eager, deienmlne<l",
prrJ.~kj}mc{{102I
rnZfatiDrt!i(,"J "
~ eneIgelic,
playful, .lll!elk;,
"D",Jeriul, oulgoing",
nooy, wis<!, bos,'y,,,
I 0010 schOOl, hal'\) cl,ildllln",
If''~''3\<lS nl'}
1) The future
8) My mother
10)1 cannot
oonsldering, doomed",
lllID abusive, C(lfOI, alaJhollc,,,
Ino klgelher, ochleve much",
~ \\'OOIS<lIOO,
!1J!!!; dumb, selfish, prornlsCUOtJs,
~ make my
of suess, somelhlng to .'IOk1...
jealous, Is douO, I. ~one".
goods glndes, lind Walk,,,
1J!!:.lnevilBbie, SGCIlfe, okay,,,
1J2t old, molherly, dNOrced,
1Jlt speak anolh.r languegB, Itt
QJl!j; eXcilin9, iJlighl, hopeful,,,
IMrrted,ls In 0110100[ ,lBla,,,
" plone, find my giJJ"".~",
!!Jl!!; beaulilul, h,mb1e, friendly,
!ll!!llail, wony, be hnrd on
.------~~i·~~S~'h~~~~~ss~,7oo~t~W~QM~----·~--"s.~.~a~~~o""MYU7~La~m7e~~~----
no
rJangeroll., fun
'"nuly happy, gol
OO)y, 9MnO, kind, bossy",
11) In a fewye~r~--­
13) My appearance Is
~ dealh will come,
1Jl!!: ugl1, repUlsive, somelhlng
I don't
know, I'll be wome oU",
wenllo chaTlle. "mwrmsslll9",
DO
i ~amply,tempom!)'",
all".
1J2t okay, healU,y, somalhing
tn~
,nat(rnctive, uornmarltabiB",
peoplo do, OOI1lonl, lor rxi,IIs,,,
Io.er, making mlslllkes
!Jl!; gel degrw, .eve money,
!Jl!; ave (HUB, fine, n\re.looklng,
~ wDnd",Iul,
1Ill; nothing, dealh, loSing my
vacation, cIlHdren grlmn".
'.are about, want 10 improve,,,
~ I'll
~ irnpori;mt, al~actlvn,
~ be older,
Ihlnk e!loul
r-lU!' SCnFt?
changing, will get help,,,,
be .occessful, have a
hp.allhy 1Brnlly, make, dfffernnce,,,
Dming 1if!\idGys
~
oVBrVllllghl, lao thin,
soxy,
1,If<iling, fun,
excillng, romantic, challenging,
I.mily/job, snokes, heigh"",
!lJ!llI; losing con~DI, Ios~g lamlly,
laifiOlj,!lOt achiavill!! goalS",
17) Men
cheal, steal, lie",
~ rfoo't lil<a
llJI'I: bother me, nosy,
me, unattllinabla,
DO
not InlercsUng, IniIllUng ..,
!J!t slrong, Spelts, like women".
1Jl!;,l1<llp, ,uPIlorl, Imperlnnl",
!ll!!l canng, handsome,
~ lamily 9othenng5,
"""'<led,,,
10 Innue!1oo 11v ... , loyaL.
eslrnOljed"
NOlliCOHE
lun, help
21)1 will be
a
loser, unhoppy forever".
~ bored,
,red, sick, alooo,,,
!Jl!;, older, lale, a macher",
1Jl!!: being born, tofe, my
~
1llm; manipulative, se~"h,
chil:iren .. ,
ovar",
promiscuous, slupkl",
tDJ£; lac, 01 Iiduca"'n, IOlllJd
£llI!\ 90 10 sl"'lP, thin!}, will
il!IDdon'IIII,. n'e, Irritallng",
fI1Intionshlps",
chang., be alono.. ,
11!J:. mj"Ifl,es, hllrtJng oli18rs .. ,
!!J!l!: nolhlng, ""lllYing al "II,,,
11!!; will ochlevo UDrrl.,,,
See also "Men"#17
!In\§; napfl)', k1Ved, loyal, islfOOS, !J!tmolhers, wives, iIlmnilll),,,
heallhj",
l ~C<lring, neotled, sexy,,,
H,
laj(es a 101 01 VXln<" ,
great..
~ con~ol,
~ dying soon, nothing,
being v,in8(1lble, baing a
I'll be dead, life will be
O.!!li; grad, ale, many, lelocale,,,
NOT
100
cJeJeJ~~'!'J [11 :J~ Ht~ H~:} I~.J ill ~ r~ He] 11 i~:)i
!lJ'\lTnT~ frJ troJil ifml!:Ili'Jl:t:i ami JeIo]1I1l:] rll-jJ1lJeilr.liJ.'I
(Page 3 of 3)
Scoring R&sponses-
"
3 point scorel: should indicate more SEVERE symptoms of depression .. Suicidal thoughts, extreme
negatiVism, hopelessness, anger, maladaptive cognitions, affects or bahaviorn, etc.
NOTE: R~i!ponse!l which glean thesIl5cores may alao be inactive behaviors, apathy, and lack of energy or motivation.
..
2 pOint scores: are associated with MODERATE depressive symptoms. Dysphoria, agitation, negative
thinking, Ilnd/or behaviom associated with minimal activity.
..
win! scores: should correspond to responses that do not necessarily Indicate depresllive symptomology.
These statoments may be direct, unambiguous responses that describe general levels of functioning,
evoryday cognitions, and normlJtlve emotions.
NOTE: One point should be glvon to responses thai Indicate an ovorall adaptive level of well-baing. Realistic rel;ponsas ar\!
acceptable, but should not be p05slmililtlc in nature. Future-oriented responses may achlevo scores of "1" as long as goals
and/or events afelmnHldlate, approaching, or inevitable. Spiritual or roligious roopons3S Involving action as a dimct result of
the Individual's partiCipation should be coded here (I.e., prayer, going 10 church, Gte.).
..
0 point scores: are assigned to responses that are freo from depressive thinking, negative affects, or
maladaptive behaviol1l. These responses should indicate high levels of functioning, self-efficacy, motivation,
and self·datermination. Spiritual or roligiolls activities may also be codsd here if Involve the individual's
direct participation and are optimistic, future-oriented.
NOTE: Responses ansociated with scoros of "0" should Involve rlgorouu levels of physical activity, positive-thinking, and
hopefulneSlS. Future goals may be morelong-Ienn or may roquiro significant effort to complete. The overall style of tho
response should howavQr, be optlmisllc with respect to fulflillno porsonal, profosslonal, or familial obJectives.
Cognitive Triad Items-
""
Average scores found on thase itoms should b0 0xamlnod with respect to individual's Overall GSCT test
score.
Skipped Items-
..
Do not include skipped items or related scores in mathematical computations.
n"",..1,,,;n"T... ihht ..
v
I
l"lnn1\
101
Appendix D
GSCT Scoring Sheet
GSCT scoring sheet developed in order to assist in scoring 25 stem responses and
achieving scores for self, world, and future dimensions.
102
:.} '~'J 1H~ r~ 1[1] 11 i!J3;:
@@®uftmoo ®~
asz::za:wz
STEMS
item
"SELF" Items (S):
(1,5,10,13,15, & 23)
Score
(3,2,1,0 pis)
SumS/6:::: Self Score
_ _1_6_ ::::
1) I am
2) When I am able
3) My father
"WORLD" Items (W):
(3,8, 14, 17, 19, & 22)
4) Eventually
5) My personaltty Is
6) What frustrates me
SumW 16:::: World Score
_ _1_6_ ::::
t\!!i !JGOfH
7) The future
8) My mother
"FUTURE" Items (F):
(2,4,7,11,21, & 24)
l'10 Sco('o
9) My work
10) I cannot
SumF 16::: Future Score
_ _1_6_ ::::
11) In a few years
12) summer is
f·!O
13) My appearance is
Self Score:::: 0
14) Marriage
15) I fear
Sum Total
Dime nslon
Ite ms
3.00
a
World Score:::: 03.00
16) During holidays
No Sr:ore
=
Future scoreD~3.00
17) Men
(~9.
No ;](;')1""
18) Winter is
19) Relatives
20) On weekends
i\jo
TOTAL GSCT
SCORE:
f~co!
21) I will be
22) Women
23) I regret
24) soon
No ;;;,;ol'e
25) At night
TOTAL GSCT SCORE
I
I>
~
~
Please Indicate severity level-
MINIMAL
MILD
In 1m
liQ.'H\
MODERATE
SEVERE
Goodwin-Tribble, K. L. 2003
U::.1.1~\
103
Appendix E
Beck Depression Inventory (2 nd Edition)
BDI-II included so that directions presented to volunteers may be compared with
HDI and GSCT measures. (Individual items obscured in order to adhere to
copyright laws.)
104
Dale:
Name:
Madta1 Status;
Occupation:
Education:
Age:
~~_
Sex; _ __
Instructions: This questionnaire consists of 21 groups of statements. Please read each group of statements carefully, and
then pick out the one statement in each group that best describes the way you have been feeling during the pHst two
weeks, including today. Circle the number beside the statement you have picked. If several statements in the group
seem to apply equally well, circle the highest number for that group. Be sure that you do not choose more than one
statement for any group, including Item 16 (Changes in Sleeping Pattern) or Item 18 (Changes in Appetite). '
Copyright protected.
Subtotal Page
t\ffiIJ THE
\1;Y
PSYCHOLOGICAL CORPORATION
llarcourl Brace
{'r COin/WilY
SAN ANTONIO
J:\:~i~~i~~l: ~1;hW.~(1:1~f\~~; ~'~~~~;I~~~ll&~~(\~'I~~;~ ~'~~~~)i!~~~\.' {;~~JI\\~ :A~::I,'\~~
Copyright © 1996 by Aaron T, Beck
All rights ff1sorved, Prlnlad In 'he United
Slat~s
of America,
0154018392
105
Appendix F
Hamilton Depression Inventory (HDI)
The Hamilton Inventory Form HS Item Booklet Cover, test directions, and 23item answer sheet have been included for comparison with the GSCT. (Individual
items obscured in order to adhere to copyright laws.)
106
a
it
nI
rmHS I mB
klet
by
William M. Reynolds, PhD
Kenneth A. Kobak, MSSW
PsycltlOlogical Assessment Resom'ces,ll1c. -162114 N. Florida Avenue 'ltllz, Fl335·19 ·1.800.331.83'78· www.pm.inc.com
Copyright © 1991, 1992. 1995 by PSYGi10logict\! Assessment Resources. Inc. All rights reserved, May not be I!'prod\lcsd in whole or in pall in
ilny torm or by any mt'!"ns without writlen permission 01 Psychological Assllssment Resources, Inc, Prinled in blue iok on while paper, Any other
version Is un authorized.
9 8 76 543
Reorder ItRO"28!J3
Printed in the U,S.A.
107
DIRECTIONS
Use il sharp pendl or bililpoint pen (not a soft-Lip pen) for compleling this questionnilirc on the answe,' sheet provided,
Do riot mark in tilis booklet, Print your name, today's dilte, your sex, race, age, years of education, and occupation on
the answer sheet. If you have an identification l1umber, please enter this in the space provided.
rhis questionnaire asks about your current feelings and behavior. Read each question and select the answer that best
describes your behavior or how you have been feeling for THE PAST 2 WEEKS. Darken the circle with the number on
your answer sheeLLhat corresponds to the answer you have selected. Please darken in only one d.'de for each question.
Do 'lOt make any marks or write in this booklet. If you wish to change your answer on the answer sheet, put an X
Lhrough the incorrect circle and fill in the correct circle. DO NOT ERASE. 8e sllre La answer p.ach question. DO NOT
leave any question blank unless the instructions tell YOIl tD skip that qUEstion.
Copyright protected.
108
Hamilton Inventory form HS Answel' Sheet
Name _ _ _ _ _ _ _ __
Date _ _ _ _ 10 _ _ _ _ Sex _ _ Race _ _ _ __
Education _ _ _ _ _ _ _ OccupQlioll _ _ _ _ _ _ _ _ _ _ _ _ __
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