Copyright 1998 by
The Cerontological Society of America
The Cerontologist
Vol. 38, No. 2,209-216
This study investigated demographic and psychological predictors of 58 older adults'
successful adjustment to a nursing home. Predictors included demographic variables, locus of
control, and self-efficacy beliefs. Successful adjustment was defined by activity level and by
positive and negative affect. Findings suggest that demographic variables were not effective
predictors of successful adjustment. Perceived self-efficacy accounted for more of the unique
variance in adjustment than locus of control. Results are discussed in the context of
improving resident adjustment to nursing home environments.
Key Words: Social learning theory, Positive affect, Negative affect, Activity level
The Relationship of Demographic Factors,
Locus of Control and Self-Efficacy
to Successful Nursing Home Adjustment1
Brian D. Johnson, PhD,2 Gerald L Stone, PhD,3
Elizabeth M. Altmaier, PhD,34 and Laurie D. Berdahl, MD 5
The importance of investigating how psychological variables and interventions affect a range of
health-related variables has been well documented
(Adler & Matthews, 1994; Altmaier & Johnson, 1992;
Rodin & Salovey, 1989). With the percentage of individuals over 65 expected to increase dramatically
during the next two decades (U.S. Department of
Commerce, 1989), health-related issues facing older
adults are an important focus for research and practice. Although aging is a predictable and inevitable
process, its associated biological and environmental
changes can affect one's perceived range of controllable situations and competence in exercising
behaviors necessary to control events (Birren & Livingston, 1985). Rowe and Kahn (1987) have suggested that individuals who are able to minimize
these negative effects undergo "successful aging,"
while those who become impaired undergo "usual
aging." Two constructs from social learning theory,
locus of control (Rotter, 1966) and self-efficacy (Bandura, 1977), may help to explain why some individuals undergo successful aging while others undergo
usual aging.
Locus of control has been defined as the degree
to which an individual perceives having control
over the environment (Rotter, 1966). According to
Rotter (1975), there are two types of control, internal
The authors would like to thank Ron and Arlene Gates and the nursing
home residents for their gracious assistance in this study.
department of Educational Psychology, University of Oklahoma. Dr.
Johnson is now in private practice. Address correspondence to Brian D.
Johnson, 1530 N. Boise, Loveland, CO 80538. E-mail: [email protected]
3
Division of Psychological and Quantitative Foundations, University
of Iowa.
'Center for Health Services Research, University of Iowa.
5
University of Oklahoma Health Sciences Center.
Vol. 38, No. 2,1998
and external, which anchor a continuum that approximates a normal distribution. People are said to
have an internal locus of control when they believe
reinforcements are contingent upon their own behavior or stable personal characteristics. External
locus of control results when people believe that
reinforcements are due to luck, fate, or powerful
others outside of their control.
The relationship between an older adult's health
and sense of control has been well documented
(e.g., Rodin, 1986; Waller & Bates, 1992). The American Medical and Nursing Associations concluded
that "a sense of purpose and control over one's life
is integral to the health of the aged" (Rodin, 1986).
Research suggests that elderly individuals with internal locus of control beliefs are more active, alert,
and have lower mortality rates than those with external beliefs (Brothen & Detzner, 1983; Langer &
Rodin, 1976; Waller & Bates, 1992). Studies have also
demonstrated that by giving the older adults more
control, similar benefits can result (Langer, Rodin,
Beck, Weinman, & Spitzer, 1979; Schultz, 1976).
How locus of control should be measured is an
issue of debate. Rotter (1975) stated that general expectancy measures suggest personality characteristics and define dimensions of generalization. Thus,
general measures allow for broad predictions from
limited data and are especially useful when situations are novel or ambiguous. Others have suggested that locus of control measurement should
be focused on the sample of interest (Lefcourt,
1981). Lefcourt (1981) argued that if the comparison
of personal traits is of interest, then measures
which have normative information should be used,
regardless of their relevance to the sample. However, if ascertaining specific causal beliefs is of in-
209
Demographic variables such as age, education
and marital status have been found to be associated
with successful adjustment among elderly individuals living in independent or semi-independent living situations (Brown & Granick, 1983; Cicirelli,
1980). Relatively little, however, is known about the
association of these variables with nursing home
adjustment.
There were two specific purposes for this study.
The first was to investigate factors which may predict successful nursing home adjustment. Specifically, the study compared three types of variables
(demographic, locus of control, and self-efficacy), to
determine which were better predictors of adjustment. The second purpose of this study was to evaluate the different types of measures for locus of
control (general and specific) and self-efficacy (general, specific, and barrier) to determine their comparative ability to predict successful nursing home
adjustment. Table 1 provides an overview of the
predictor and criterion variables used.
terest, then measures designed to assess specific
groups or sets of behaviors should be developed.
The other social learning construct, self-efficacy,
is defined as peoples' judgments of their capabilities to organize and execute courses of action required to attain designated types of performances
(Bandura, 1986). Self-efficacy is not concerned with
a person's level of skills per se, but rather with judgments of what can be done with the skills one currently possesses. Self-efficacy can be heightened
through personal success, vicariously experiencing
the success of similar others, reduction in physiological arousal, and verbal persuasion. It is considered to be both a transitory state and, with experience, a dispositional variable (Bandura, 1986).
Self-efficacy can be distinguished from locus of
control in that locus of control centers around the
causal beliefs people have about the relationship
between their actions and particular outcomes.
Self-efficacy, however, pertains to personal judgments people make about their competence in
performing the behaviors that may lead to desired
outcomes.
Little research has specifically investigated selfefficacy among older adults. Holahan and Holahan
(1987) found that perceived self-efficacy beliefs
were predictive of current levels of depression and
of later levels at a one-year follow up. Avorn and
Langer (1983) demonstrated that helping older
adults perform tasks they were capable of performing independently actually decreased their subsequent performance, presumably by undermining
their sense of self-efficacy.
There is also debate over how self-efficacy should
be measured. Traditionally, self-efficacy has been
measured as a situation-specific variable (Bandura,
1986), in which behaviors relating to a particular task
are identified and people rate their confidence in
being able to perform the requisite behaviors. Others (Sherer et al., 1982) argue that self-efficacy should
be measured as a generalized construct in which
one's history of mastery experiences produces a set
of generalized expectancies that are drawn from
when novel situations are encountered. A third way
that self-efficacy has been measured is by assessing
an individual's perceived capability to overcome obstacles or barriers that may hinder successful performance (Colletti, Supnick & Payne, 1985).
Methods
Participants
Fifty-eight participants, 43 women and 15 men,
were drawn from two nursing home locations in the
same rural Midwestern community. Within the two
locations, there was a combined population of approximately 160 residents. Forty-three participants
came from one location and 15 came from the
other. The proportion of female and male participants, approximated the 3 to 1 (female:male) ratio
in the nursing homes. The average age of the study
sample was 81.9 years old. Participants were, on average, 79.6 years old when they entered the home
and had lived there for 2 years. All participants were
Caucasian. Descriptive demographic characteristics
of the sample are found in Table 2.
The two nursing home locations were approximately one mile apart and were owned and operated by the same family. The nursing and support
staffs frequently alternated between the two locations and there was one activity director who coordinated the recreational activities at both sites. In
addition, many of the activities involved bringing together residents from both locations. Placement of
Table 1 . Overview of Study Variables and Measures
Predictor
Variables
Self-efficacy
Specific
General
Barrier
Locus of control
Specific
General
Demographic
Criterion
Measures
Specific SE scale (10 items)
Self-efficacy scale (17 items)
Barrier SE scale (10 items)
Variables
Measures
Positive affect
Negative affect
Activity level
Vigor (7 items)
Depression/dejection (15 items)
Activity level during a 1 month period
Desired Control Measure (16 items)
Abbreviated Rotter Scale (10 items)
Demographic questionnaire (15 items)
210
The Gerontologist
Table 2. Demographic and Medical Variables
Demographic variables
Current age (years)
Age of entry (years)
Length of stay (years)
Level of education (years)
Number of living siblings
Number of living children
Days since last visit
Medical variables
Prescribed medications
Hypertension
Diabetes
Ambulatory
Bowel/bladder control
M
SD
81.9
79.6
2.0
10.4
1.8
2.1
28.3
10.0
10.2
2.7
3.3
1.9
2.1
104.4
5.68
2.89
YES
NO
47%
26%
48%
78%
53%
74%
52%'
22%
'All nonambulatory residents were able to walk with assistance
(e.g., with walkers, or with the assistance of an aide).
residents in one of the nursing home locations was
essentially random, based upon room availability at
the time of application.
Participants were eligible for the study if they
were judged by the head nurses as being physically
healthy enough to participate and as being oriented
to time (day, month, and season) and place (name
of nursing home and community). In addition, an
attempt was made to control for activities in daily
living (ADLs) by including only individuals who
were judged capable of doing the following behaviors "independently or with minimal assistance":
dressing self, attending to personal hygiene (e.g.,
toileting, bathing), communicating needs, managing
spending money, and feeding oneself.
One hundred percent of the individuals approached agreed to participate, and only one terminated consent before completion. Nine participants
chose to complete all or part of the questionnaire
themselves, while the remaining 49 chose to have
the questionnaire read to them by an experimenter.
Results from a t test revealed no significant differences between those who chose to read the questionnaire and those that had it read to them.
Measures
The two locus of control measures were an abbreviated version of the Rotter (1966) scale and the
Desired Control Measure (Reid & Ziegler, 1981). The
Rotter scale asks participants to choose between
one of two statements which best describes themselves. It was developed to measure general locus
of control beliefs and a high score indicated an internal locus of control orientation. School concerns
and "filler" items were deleted and the resulting 10item scale contained items showing the highest biserial correlation with the internal-external scores, as
reported by Rotter (1966). The internal consistency
reliability for this measure was reported to be .61
(Kuypers, 1972) and it compared favorably with the
Vol. 38, No. 2,1998
reported reliability of the original scale (Cicirelli,
1980).
Specific locus of control was assessed by the Desired Control Measure (Reid & Ziegler, 1981). This
16-item measure asked participants to indicate the
degree to which they felt particular reinforcements
could be obtained through their efforts. Responses
were recorded on a 5-point Likert scale ranging
from "strongly agree" to "strongly disagree" and a
high score indicated an internal orientation. Items
represented factors that contribute to older adults'
contentment, happiness, and adjustment (Reid &
Ziegler, 1981). For example, respondents were asked
to rate how strongly they agreed with the statement,
"I can entertain friends when I want." The test-retest
reliability, at a 12-month interval, ranged from .54
to .63.
Self-efficacy was assessed by general, specific, and
barrier measures. The general self-efficacy measure
was the Self-Efficacy Scale developed by Sherer et al.
(1982). This 17-item measure asked respondents to
endorse on a 5-point scale the degree to which they
agreed with statements such as, "When I make plans,
I am certain I can make them work." The higher the
score, the greater the perceived general self-efficacy.
This scale has a Chronbach's alpha of .88 (Morris &
Altmaier, 1988).
Both the specific and barrier self-efficacy measures were constructed for this study because such
measures were not available in the literature. Items
found on these measures were generated from the
responses of a nursing home's staff to the question,
"What kinds of problems are residents likely to encounter while living in the home?" The intercorrelations between the self-efficacy and locus of control
measures are reported in Table 3. Considering that
these measures were assessing the same or closely
related constructs, these intercorrelations were
judged to be acceptable and each measure was
treated as a unique variable.
Specific self-efficacy was assessed by a 10-item
measure that asked participants to indicate how
confident they were in their abilities to perform behaviors necessary to achieve specific outcomes. For
example, respondents were asked to rate, on a
5-point scale, their confidence in "Being responsible for taking my own medications." A high score
on this scale also indicated greater specific selfefficacy. With the sample used in this study, this
measure obtained a Chronbach's alpha of .57 which
is considered to be quite low, but deemed to be acceptable given the exploratory nature of this study.
The barrier self-efficacy scale was also a 10-item
measure which asked participants to indicate, on
a 5 point scale, how confident they were in their
ability to overcome barriers that may hinder achievement of various outcomes. A sample item is "You
catch someone stealing something from your room
and want to make sure that it won't happen again."
High scores indicated greater perceived barrier selfefficacy beliefs. Chronbach's alpha for this measure
with this sample was also a rather low .63.
Demographic information was collected from
211
Table 3. Correlations Among Self-efficacy and Locus of Control Measures
Self-efficacy
Specific
Self-efficacy
Specific
General
Barrier
Locus of Control
General
AV
Barrier
General
.45***
.36*
.18
.16
.00
Locus of Control
General
Specific
Demographic Variable
Home
Specific
.28*
.06
.23
.24
.20
.03
.40*
-.10
.26*
*p < .05; **p < .01, ***p<.001.
each participant and included date of birth, gender,
marital status, date of entry to the nursing home, primary occupation, last year of formal education,
number of living siblings and children, and days
since last visit by a relative or friend. The following
medical information was also collected from the resident's records: presence of hypertension, diabetes
and bowel/bladder control problems; number of
prescribed medications; and degree of ambulation.
This study operationally defined successful adjustment as positive affect, negative affect, and activity level. Positive affect was derived from the
7-item, vigor scale from the Profile of Mood States
(POMS: McNair, Lorr, & Droppleman, 1981). Negative affect was derived from the 15-item, depression-dejection scale of the POMS. The POMS asks
respondents to rate, on a 5-point scale ranging from
"not at all" to "extremely," the degree to which they
have experienced various affective states over a one
week period. The two scales of the POMS had their
adjective-items mixed together according to the sequence of their appearance on the original 64-item
scale. A high score on either the vigor or depression-dejection scales indicated greater levels of that
affect being present. Using this sample, Chronbach's alpha for positive affect was .79 and it was .90
for negative affect.
Activity level was obtained by recording the number of times that each person participated in regularly scheduled activities during a one-month interval. Examples of these activities included crafts,
bingo, movies, and going for rides. The 30-day interval in which activities were recorded began immediately after each participant completed the
questionnaire.
Procedure
Once potential participants were identified by the
nursing home staff as meeting study criteria, each
person was approached and asked to participate in
the study. It was anticipated that some participants
would be unable to finish the questionnaire in one
sitting and the time when they stopped would vary,
so the order in which the measures were presented
in the questionnaire was random. It took approximately 45 minutes to complete the questionnaires
212
and most participants completed it in one sitting.
Of those who did request to take a break (N = 11),
the questionnaire was completed within 24 hours.
Recording of activity participation began immediately after completion of the questionnaires.
Results
Relationship of Demographic Variables
to Adjustment
To determine which demographic variables predicted nursing home adjustment, zero-order correlations were calculated to assess the relationships
among the following demographic variables with
each dependent variable: current age, age of entry
to the nursing home, length of stay, level of education, number of living siblings, number of children,
and days since last visit by a family member or
friend. Activity level was the only variable significantly related to demographic variables, and it correlated with current age (r = -.22), age of entry to
the nursing home (r = -.29), and length of stay (r =
.25). Consequently, individuals who were younger
at the time of the study, younger when they entered
the nursing home, and who had lived in the home
for a longer period of time were more active.
A two-tailed t test was used to determine the relationship of sex with the demographic variables. Significant sex differences were found for the number
of days since last visited (p < .001). Women had a
shorter period of time (M = 8 days) when compared
to men (M = 57 days). Three men, however, accounted for much of the variance, with 154, 285, and
730 days since last visited. When these 3 men were
removed and another t test conducted for number
of days since last visited, significant sex differences
no longer emerged. The mean number of days became 8 for women and 9 for men. It is noteworthy
that the data from these three men were retained
for all other analyses. Two-tailed t tests were also
conducted to determine if a significant relationship
existed between each adjustment variable and sex.
No significant sex differences were found on the
adjustment variables.
Separate one-way ANOVAs were conducted on
The Gerontologist
the variables of occupation level, marital status, and
nursing home location for each adjustment variable. No significant relationships were found for
positive or negative affect; however, the residents at
one nursing home location were significantly more
active (p < .001). The location from which 15 participants were drawn was significantly more active.
Given the similarities between residents at the two
locations, this is likely to be an artifact of the small
sample, rather than a true difference between
groups. Additional t tests revealed no further differences between the nursing homes on the demographic variables.
Relationship of Self-efficacy and Locus
of Control Beliefs with Adjustment
A series of hierarchical multiple regressions were
conducted to determine the degree to which selfefficacy and locus of control beliefs were related to
adjustment. Three blocks of variables were entered
into each regression. Given that difference between
the nursing home locations resulted from characteristics unique to this sample, location was entered
first as a demographic block. A locus of control
block (general and specific) and a self-efficacy block
(general, specific, and barrier) were then entered in
a stepwise manner.
Table 4 reports the results of the regression analysis for the adjustment variables. When positive affect was regressed onto the predictor variables, the
demographic variable was a nonsignificant contributor. Self-efficacy explained a significant increment
in the R2 value, ^(4,55) = 7.65, p < .001. Locus of con-
Table 4. Self-efficacy and Locus of Control
as Predictors of Nursing Home Adjustment
Predictor Variables
Positive Affect
Stepi:
Location
Step 2:
Self-Efficacy
Step 3:
Locus of Control
Model:
Negative Affect
Stepi:
Location
Step 2:
Locus of Control
Step 3:
Self-Efficacy
Model:
Activity Level
Stepi:
Location
Step 2:
Self-Efficacy
Step 3:
Locus of Control
Model:
Vol. 38, No. 2,1998
R2
<.O5
F
F(1,55) =
p
.03
.87
.35
F(4,55) = 8.24
<.001
.06
.41
^(6,55)= 2.47
F(6,55) = 5.92
.09
<.001
<.O5
F(1,55) =
.58
.45
.12
f(3,55) = 3.46
.05
.06
.19
F(6,55)= 1.26
F(6,55) = 1.91
.30
.10
.40
F(1,55) = 34.95
<.001
.12
r"(4,55) = 3.52
.05
.04
.56
F(6,55) = 1.13
F(6,55) = 10.71
.40
<.001
trol was the last block to be entered, and did not account for a significant increment in variance (see
Table 4). When negative affect was regressed onto
the predictor variables, only locus of control explained a significant increment in the R2 value,
F(3,55) = 3.52, p < .05. While the demographic variable, nursing home location, accounted for 40 percent of the variance for activity level, self-efficacy
accounted for a significant increment in the R2
value, F(4,55) = 3.40, p < .05. Locus of control was a
nonsignificant contributor.
Types of Beliefs as Predictors of Adjustment
Zero-order correlations were calculated to determine the relationship between each locus of control and self-efficacy measure with the adjustment
variables. The specific locus of control measure was
more strongly related than general locus of control
to each of the dependent variables. The specific and
barrier self-efficacy measures were strongly correlated with positive affect while none of the selfefficacy measures obtained a correlation significantly
different from zero for negative affect or activity
level (see Table 5).
In order to determine which locus of control and
self-efficacy measures were most strongly related to
the adjustment variables, a series of linear regressions were performed. The adjustment variables
were regressed on the self-efficacy and locus of control measures in a stepwise manner so the unique
variance of each measure could be determined. The
results of these analyses are in Table 6.
For positive affect, the specific self-efficacy measure contributed the most R2, while the specific locus
of control measure explained a significant increment
to the total R2 (see Table 6). For negative affect, the
specific locus of control measure accounted for the
largest increment in R2; however, this increment
was not sufficient to achieve conventional levels of
statistical significance, F(1,55) = 3.68, p = .06. The
nursing home variable accounted for the largest increment in R2 for activity level; however, the barrier
self-efficacy (R2 = .08) and the specific locus of control measures (R2 = .06) did account for significant
increments in R2. No other measures emerged as
significant contributors to the total R2 for the adjustment variables.
Table 5. Correlation of Measures to Dependent Variables
Positive
affect
Negative
affect
Activity
level
Locus of Control:
Specific
General
.40**
.25
-.25
-.05
.36*
.01
Self-efficacy:
Specific
General
Barrier
.51***
.21
.29*
-.14
-.19
-.02
*p<.05;**p<.01;***p<.001.
213
.18
-.11
.11
Table 6. Types of Self-efficacy and Locus of Control
Measures as Predictors of Adjustment
Predictor Variables
Positive Affect
Stepi:
Specific Self-efficacy
Step 2:
Specific Locus of Control
Model:
R2
F
P
.30
F(1,55) = 22.81
<.0001
.07
.37
F(2,55)= 5.74
F(2,55) = 15.29
.02
<.0001
Negative Affect
Stepi:
Specific Locus of Control
Step 2:
General Self-efficacy
Model:
.07
F(1,55) = 3.68
.06
.03
.10
F(2,55) = 2.26
F(2,55) = 3.02
.10
.06
Activity Level
Stepi:
Location
.40
F(1,55) = 34.47
<.0001
.08
F(2,55) = 8.05
<.007
.06
F(3,55) = 6.53
.01
.02
.56
F(4,55)= 2.59
F(4,55) = 15.92
.11
<.0001
Step 2:
Barrier Self-efficacy
Step 3:
Specific Locus of Control
Step 4:
Specific Self-efficacy
Model:
Discussion
This study investigated the relationship among demographic variables, locus of control beliefs, and
self-efficacy beliefs with nursing home adjustment.
Our data demonstrated that the demographic variables were not useful predictors of successful adjustment. Prior research has found the demographic
variables of age, education, and marital status to
be significantly related to adjustment (Brown &
Granick, 1983; Cicirelli, 1980). These studies, however, used younger participants, and most were still
living independently. It is possible that demographic
variables are useful predictors of adjustment to a
certain age or functional level, and thereafter their
predictive power decreases. It is also likely that the
older residents in this sample had more health problems, and demographic variables lose their predictive value with decreased health. Kasl and Beckman
(1981) have suggested that the relationship between
an individual's health and the effects of psychological variables might grow stronger in old age. In addition, characteristics of a nursing home, such as fixed
schedules, may also mask the contributions made by
demographic variables. Future work to isolate factors that reduce the predictive power of demographic variables will be important.
Overall, our data demonstrated that the perceptions of older adults' personal competence in performing behaviors (self-efficacy) were more strongly
related to successful nursing home adjustment than
were their perceptions that outcomes were the result of intentional acts (locus of control). Residents
with relatively stronger self-efficacy beliefs reported
more positive affect (vigor) and were more involved
in scheduled activities. Locus of control beliefs were
associated with a relative decrease in self-reported
negative affect (depression-dejection). It is possible
that in the fairly regimented environments of nursing
homes, most outcomes of daily living are provided as
a service. Consequently, perceiving personal control
over outcomes was not as influential as believing
that one was capable of performing the same tasks as
the staff. When the participants did not perceive that
they were capable of exhibiting particular behaviors
or attributed outcomes to an external influence, they
reported more negative affect.
Finally, our data suggest that specific measures of
locus of control and self-efficacy are more strongly
related to successful adjustment than general measures of these same constructs. This study suggested that residents with relatively stronger selfefficacy beliefs reported more positive affect (vigor)
and were more involved in scheduled activities.
Locus of control beliefs were associated with a relative decrease in self-reported negative affect
(depression-dejection). Consequently, when assessing dimensions of adjustment to a nursing home,
domain-specific measures appear more sensitive
than dispositional measures. Bandura (1988) stated
that when general items are used to assess selfefficacy beliefs, there is a greater burden on respondents to define what is being asked of them.
While general measures may help define the range
to which a belief has generalized, specific measures
appear to be more useful in a targeted prediction.
A recent survey of nursing home administrators
(Crose & Kixmiller, 1994) reported that nursing
homes have particular difficulty managing residents
who are depressed, confused, or exhibit demanding
and combative behaviors. By screening for factors
related to adjustment, nursing homes could become more proactive and perhaps diminish the
need for more restrictive interventions. Activities as
simple as giving residents the responsibility to care
for a plant or to determine when to watch a movie
have been shown to have a dramatic effect on resident's psychosocial adjustment, presumably by improving their sense of control (Langer & Rodin,
1976; Rodin, 1986). Similar types of interventions
could be utilized to help increase the perceived
control of nursing home residents. Interventions
that decrease an individual's anxiety while performing a task, or that provide opportunities for vicarious learning by observing a fellow resident perform
a task, may be useful to help increase the selfefficacy expectations of nursing home residents.
Clearly these types of interventions will not be appropriate for all residents and the residents in this
study likely represented the "healthier" end of the
spectrum. However, with the number of individuals
entering nursing homes expected to triple by the
year 2040 (U.S. Senate, 1987), interventions that can
improve the quality of life, even for a small percentage, could improve the quality of life for many elderly individuals. This study demonstrated that selfefficacy and locus of control beliefs were related to
successful adjustment in a relatively healthy sample
of nursing home residents.
214
The Gerontologist
There are several limitations of this study that
should be mentioned. Possibly the most significant
one is that activities of daily living (ADLs) were not
statistically controlled. While the study design controlled for ADLs by limiting participation to nursing
home residents that were capable of doing various
activities "independently or with minimal assistance/' there was still variability among participants.
Activities of daily living have also been described as
being important for the successful adjustment of
the elderly (e.g., Sinnott, 1989). Future studies that
statistically control for ADLs and evaluate how significant psychological variables are to adjustment
would be helpful.
The reliability estimates of some measures, particularly for barrier and specific self-efficacy, were
rather modest and replication with another sample
will be important. In addition, efforts to develop additional measures sensitive to the issues related to
nursing home adjustment are needed. Another potential limitation of this study is related to outcome
expectancies. Elderly individuals who entered the
nursing homes with the belief that their placement
was temporary may have behaved differently from
those who believed their placement was long term.
With an average length of stay for this sample being
2 years, however, it is unlikely that these expectancies were a major factor. However, the attributions
that older adults make regarding why they are going
to a nursing home and how permanent their placement will be is likely to be a very important component in predicting adjustment.
This study also utilized a cross-sectional design,
which is useful in identifying a relationship between these variables and adjustment. However, in
order to determine if these variables "predict" adjustment, longitudinal research will be needed. In a
7 year longitudinal study, self-efficacy beliefs were
found to be significantly related to ADLs (Willis, Jay,
Diehl, & Marsiske, 1992). However, the authors concluded that it was one's prior ability level which predicted self-efficacy beliefs seven years later. Further
longitudinal research investigating the relationship
among prior ability, self-efficacy, and later adjustment would be useful. In addition, longitudinal
studies that evaluate the process of coping with and
adjusting to a nursing home are needed.
All participants in this sample were Caucasian and
most were female. The generalizability of these results may be limited, and studies evaluating crosscultural and cross-gender reactions to nursing
home placements would be very useful. Rodin and
Salovey (1989) have reported on how gender and
race are related to a variety of health related risk
factors. Finally, there are a number of other psychological variables that have been shown to be related
to adjustment and health which were not evaluated
in this study. Factors such as hardiness (Kobasa,
1982), optimism and pessimism (Petersen & Seligman, 1987), emotional expressiveness (Ahrens &
Deffner, 1986) and social support (Holahan & Moos,
1986) have all been shown to be related to how one
adjusts and copes with various stressful situations.
Vol. 38, No. 2,1998
How useful these variables would be in predicting
nursing home adjustment remains to be evaluated.
Currently, nursing homes are required to perform federally mandated preadmission screenings
for mental illness and mental retardation (OBRA,
1987). These screening procedures could easily be
enhanced to include assessing factors related to
successful adjustment. Identifying individuals at risk
during preadmission screenings may facilitate appropriate placement decisions and the development of special services. For example, if residents
are found to exhibit negative affect at preadmission,
efforts to have them engage in activities where they
are likely to experience performance accomplishments may increase their perceived self-efficacy
and sense of control. With repeated exposure to
successful performances, they may be expected to
begin to realize their own abilities to complete tasks
and achieve desired outcomes. As a result, more
positive attributions about the nursing home are
likely to occur, which may help to reduce or even
buffer residents from experiencing the often debilitating negative cognitions associated with depression. Much work remains to be done in order to
identify types of interventions that are likely to help
facilitate a sense of control and self-efficacy. With
the changing demographics, the need to identify
factors which may impede adjustment and to develop interventions to target these factors will continue to be an important focus for research and
practice.
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Received September 30,1996
Accepted June 20,1997
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