Rehabilitation Psychology 2005, Vol. 50, No. 3, 232–238
Copyright 2005 by the Educational Publishing Foundation 0090-5550/05/$12.00 DOI: 10.1037/0090-5550.50.3.232
Social Problem-Solving Abilities and Psychological Adjustment of Persons in Low Vision Rehabilitation Laura E. Dreer, Timothy R. Elliott, Donald C. Fletcher, and Marsha Swanson University of Alabama at Birmingham Objective: Tested the relations of social problem-solving abilities to distress, depression, and well-being and impairment reported by persons participating in a low vision rehabilitation program. Study Design: Correlational and multiple regression analyses. Setting: Outpatient low vision rehabilitation clinic. Participants: 25 men (M ⫽ 73.88 years old, SD ⫽ 11.94 years) and 29 women (M ⫽ 68.79 years old, SD ⫽ 17.25 years) participating in a comprehensive admitting examination. Main Outcome Measures: Emotional distress specific to the condition, depressive behavior, satisfaction with life, and functional ability. Results: A negative problem orientation significantly predicted depression and emotional distress; rational problem-solving skills predicted life satisfaction. Conclusions: A negative problem orientation toward problem solving predicts poor emotional adjustment reported by persons with low vision, and proactive problem-solving skills appear to promote optimal adjustment. Keywords: social problem solving, low vision, rehabilitation, adjustment
living, and complicate changes related to old age in general (Pollard, Miner, & Cioffi, 2000). Persons with low vision may also present with co-occurring chronic disease processes that can necessitate lifestyle and behavioral changes (e.g., diabetes, hypertension). Furthermore, vision loss can restrict spatial orientation and the ability to perform daily tasks such as reading, writing, and driving, which can subsequently lead to social, economic, and personal consequences (Colenbrander, 1996). As a result, persons with vision loss and their families are often taxed physically and emotionally as they confront these issues (Lamoureux, Hassell, & Keefe, 2004; Pollard et al., 2000). Individuals with low vision problems vary considerably in their emotional and behavioral reactions and in their ability to solve problems in everyday living that may follow in the wake of vision loss. Research indicates that a significant minority of persons with vision loss experience depression and distress (Casten, Rovner, & Edmonds, 2002; Horowitz & Reinhardt, 2000; Karlsson, 1998; Rovner, Casten, & Tasman, 2002; Rovner, Zisselman, & ShmuelyDulitzki, 1996) that compromise their activities of daily living (Heyl & Wahl, 2001; Lindo & Nordholm, 1999; Rovner & Ganguli, 1998; Ryan, Anas, Beamer, & Bajorek, 2003). However, a fuller understanding of the psychological processes that influence adjustment is lacking. Current research implicates social– cognitive variables as important determinants of adjustment following vision loss. For instance, individuals who have a low sense of self-efficacy appear to be particularly at risk for depression (Horowitz & Reinhardt, 2000). In contrast, persons who maintain an active sense of control over their condition experience less functional impairment than persons who do not share this sense of control (Wahl, Becker, Burmedi, & Schilling, 2004). Higher levels of hope have also been associated with better functional abilities among persons with vision loss (Jackson, Taylor, Palmatier, Elliott, & Elliott, 1998). A proactive problem-solving perspective appears to help individuals find creative solutions to the difficulties they encounter following
Vision impairment is one of the 10 leading causes of disability in the United States. An estimated 2.85% of the general U.S. population has some form of visual impairment (including blindness; National Eye Institute, 2002). Thus, living with a vision impairment is the reality for a substantial portion of the U.S. population and is likely to only increase given the expected rise in older adults because of extended life expectancy. The leading causes of vision loss include macular degeneration, cataracts, glaucoma, diabetic retinopathy, and optic nerve atrophy, all of which can have a significant impact on personal adjustment and quality of life. Unfortunately, the psychological factors that influence adjustment following vision loss have been understudied despite the fact that clinicians are urged to assess emotional reactions and provide appropriate interventions (including counseling; Fletcher, 1994; Morris, Fletcher, & Scott, 2002). Many persons with low vision face new and unique challenges that include alterations in social, personal, and vocational roles. These changes may restrict mobility, impede activities of daily
Laura E. Dreer, Department of Physical Medicine and Rehabilitation, University of Alabama at Birmingham; Timothy R. Elliott, Department of Psychology, University of Alabama at Birmingham; Donald C. Fletcher and Marsha Swanson, Center for Low Vision Rehabilitation, Department of Ophthalmology, University of Alabama at Birmingham. This study was funded by the Helen Keller Eye Foundation for Research and Education, National Institute on Disability and Rehabilitation Research Grants H133N5009 and H133B980016A, National Institute on Child Health and Human Development Grant T32 HD07420, and National Center for Injury Prevention and Control Grant R49/CCR403641 awarded to the University of Alabama at Birmingham. The content of this article is solely the responsibility of the authors and does not necessarily represent the official views of the funding agencies. Correspondence concerning this article should be addressed to Laura E. Dreer, PhD, who is now at the Center for Low Vision Rehabilitation, 1720 University Boulevard, Suite 380, University of Alabama at Birmingham, Birmingham, AL 35233. E-mail:
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vision loss (Brennan & Cardinali, 2000; Kleinschmidt, 1999). Planful problem-solving coping strategies are also associated with less impairment and distress among persons with blindness (Upton, Bush, & Taylor, 1998). Therefore, it is imperative that researchers begin to identify the cognitive– behavioral characteristics of persons with vision impairments that predict adjustment so that theory-driven interventions can be developed and implemented in low vision rehabilitation programs. Contemporary models of social problem-solving abilities stipulate that individuals differ in (a) the cognitive– behavioral skills that influence the processing of information about their problems, (b) their ability to regulate emotional experiences when problem solving, and (c) their ability to implement effective strategies for resolving problems (D’Zurilla & Nezu, 1999). Essentially, social problem solving involves the cognitive– behavioral processes through which an individual identifies and copes with everyday problems (Nezu, 2004). Specifically, social problem-solving theory and research focus on all kinds of problems in living, including personal (e.g., cognitive, emotional, behavioral, health), impersonal (e.g., insufficient finances), interpersonal (e.g., relationship issues), and broader societal problems (e.g., environment, crime; D’Zurilla, Nezu, & Maydeu-Olivares, 2002). Problem-solving outcomes in the real world are determined by two general processes: (a) problem orientation (negative or positive) and (b) problemsolving style (rational problem solving, impulsive/careless style, and avoidant style; D’Zurilla et al., 2002). The problem-orientation component encompasses beliefs and attitudes people have about their overall abilities, their level of confidence in problem solving, and their abilities in regulating their emotions so that they are motivated to handle minor problems efficiently and work diligently on more time-consuming problems. Problem-solving styles entail both effective tendencies (e.g., rational, logical) and ineffective tendencies (e.g., impulsive, careless, avoidant; D’Zurilla et al., 2002). Social problem-solving abilities have been associated with optimal levels of adjustment following chronic disease and disability (Elliott, Grant, & Miller, 2004). This research has been guided by a theoretical framework that poses specific theoretical properties for research and directions for developing clinical interventions (D’Zurilla & Nezu, 1999). Treatments based in social problemsolving principles have been effective in the amelioration of depression among caregivers of stroke survivors (Grant, Elliott, Weaver, Bartolucci, & Giger, 2002) and in lowering distress and improving self-regulation among persons diagnosed with severe health problems (e.g., cancer; Nezu, Felgoise, McClure, & Houts, 2003). Effective social problem-solving abilities have also been associated with less psychosocial disability among persons with physical disability (Elliott, Godshall, Herrick, Witty, & Spruell, 1991) and less emotional distress among pregnant women (Elliott, Shewchuk, Richeson, Pickelman, & Weaver-Franklin, 1996). Thus, problem-solving interventions hold considerable promise for augmenting rehabilitation programs (Rath, Simon, Langenbahn, Sherr, & Diller, 2003). Despite the various empirical investigations demonstrating support for an association between social problem solving and health behaviors, there are no prior data concerning the relations between social problem-solving abilities and psychological adjustment of persons with vision loss. According to the basic tenets of the social problem-solving model, negative problem orientation predicts neg-
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ative emotional experiences, and programmatic research has supported this assumption among persons with a variety of health conditions (Elliott et al., 2004). Therefore, we hypothesized that a negative problem orientation would uniquely predict domain-specific emotional distress, depressive symptoms, well-being, and functional abilities reported by persons in a low vision rehabilitation program. However, women are more likely to report more depressive symptoms than men (Geller, Graf, & Dyson-Washington, 2003), and older women often report a higher negative problem orientation than men (D’Zurilla, Maydeau-Olivares, & Kant, 1998). We subsequently examined our data for possible gender differences in adjustment and social problem-solving ability.
Method Participant Characteristics The sample included 25 men (M ⫽ 73.88 years old, SD ⫽ 11.94 years) and 29 women (M ⫽ 68.79 years old, SD ⫽ 17.25 years) who had completed a low vision evaluation upon admission to an outpatient low vision rehabilitation program. Individuals agreed to participate in a brief psychological assessment as part of their initial evaluation. The men averaged 13.11 years of formal education (SD ⫽ 3.67); the women averaged 12.30 years of education (SD ⫽ 2.53). Eighty-eight percent of the men were retired (N ⫽ 22), 48% of the women were retired (N ⫽ 14), and 24% (N ⫽ 7) said they had disability status. Sixty percent of the men (N ⫽ 15) were married at the time of the evaluation, and 20% (N ⫽ 5) were widowers. Forty-one percent of the women (N ⫽ 12) were married, and 27.6% (N ⫽ 8) were widows. Half of all participants lived with a spouse; 26.9% lived alone. Macular degeneration was the most frequent primary referring diagnosis (61.1%, N ⫽ 33); approximately 7.4% (N ⫽ 4) had diabetic retinopathy as a primary diagnosis; 5.6% (N ⫽ 3) were diagnosed with glaucoma; 22.2% (N ⫽ 12) carried diagnoses of other various vision impairments (e.g., Stargardt’s disease); and 3.7% (N ⫽ 2) were given a diagnosis of vision impairment of unknown origin upon intake. Forty-eight persons were Caucasian and 6 persons—all women—were African American.
Measures Social problem-solving abilities. The Social Problem-Solving Inventory—Revised short form (SPSI–R; D’Zurilla et al., 2002) was used to assess social problem-solving abilities. According to D’Zurilla et al. (2002), the SPSI–R short form assesses two constructive or adaptive problem-solving dimensions (positive problem orientation and rational problem solving) and three dysfunctional dimensions (negative problem orientation, impulsive/careless style, and avoidance style). The five major scales, along with sample questions that comprise each scale, are as follows: Positive Problem Orientation (PPO), “When I have a problem, I try to see it as a challenge or opportunity to benefit in some positive way from having a problem”; Negative Problem Orientation (NPO), “I become depressed and immobilized when I have an important problem to solve”; Impulsive/Careless Style (ICS), “When I am attempting to solve a problem, I act on the first idea that occurs to me”; Avoidance Style (AS), “When a problem occurs in my life, I put off trying to solve it for as long as possible”; and Rational Problem Solving (RPS), “When I have a problem to solve, I examine what factors or circumstances in my environment might be contributing to the problem.” Higher scores on each factor denote greater intensity on that particular dimension, and total scores range from 0 to 100. Items on the SPSI–R are rated on a 5-point Likert-type scale (0 ⫽ not at all true of me to 4 ⫽ extremely true of me). Participants indicate how they usually respond to problems. An enlarged copy of the 5-point Likerttype scale responses was given to participants to aid their recall when
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responding. The SPSI–R short form has shown high reliability, ranging from .69 to .93, and has been found to be moderately correlated with other external measures of psychological distress and well-being with significant correlations (D’Zurilla & Chang, 1995; D’Zurilla et al., 2002). Emotional distress. Tactile analog scales (TASs) were used to evaluate negative emotions specifically attributed to vision loss. These scales were concerned with feelings that might be expected to be evoked by vision loss or by thinking about the condition: anger, fear, depression, anxiety, and frustration. Each TAS was presented in the form of a 10 mL syringe without an attached needle. Each emotion TAS was anchored by the verbal description none at all ⫽ 0 and by the phrase most severe imaginable ⫽ 100. Participants indicated the extent of depression, anger, fear, frustration, and anxiety by pulling the syringe tube between the anchors. Higher scores on each scale indicate greater negative affect. The five items were averaged to provide a single indicator of distress. Internal consistency for the averaged index score of emotional distress associated with vision loss was acceptable (␣ ⫽ .81). Similar alphas have been observed for a variation of this instrument (visual analogue scales; VAS) in research with older clinical samples (.89; Harkins, Elliott, & Wan, 1999), community-residing adults (.70, .71; Elliott, Chartrand, & Harkins, 1994), and undergraduate women (.86; Elliott & Harkins, 1992). Higher VAS emotional distress scores are positively and significantly related to negative affectivity (Elliott et al., 1994; Harkins, Price, & Braith, 1989). These studies support the validity of an emotional distress average score as a meaningful measure of domain-specific distress associated with a health problem (Harkins et al., 1989). To determine the reliability of the syringe analog measurement of these dimensions, we decided that a subsample of consecutively referred participants (N ⫽ 13) should complete a second administration. For this administration, we used a large emotional “thermometer,” which was developed for the clinic and this study. The thermometer was made with poster board and was divided into 10 equal intervals, ranging from 0 (none at all) to 10 (most severe imaginable). All participants were able to correctly identify the figure as a thermometer with numbers. Participants were given the same instructions and indicated on the thermometer the intensity of each emotion, either by pointing directly on the thermometer to denote their response or verbally giving a number to the examiner. The correlation between the average score from the syringe administration and the thermometer indicated a moderately high degree of reliability (r ⫽ .88, p ⬍ .001). Depressive behavior. The Center for Epidemiological Studies—Depression Scale (CES–D; Radloff, 1977) was used to obtain an index of depressive behavior. This measure assesses current levels of depressive behavior with 20 items that are scored on a 4-point scale to indicate symptom frequency during the preceding week. Scores can range from 0 to 60; higher scores indicate greater levels of depressive behavior. Several studies have supported the discriminant and convergent validity of the scale (Husaini, Neff, Harrington, Hughes, & Stone, 1980; Radloff, 1977; Roberts & Vernon, 1983; Weissman, Sholomskas, Pottenger, Prusoff, & Locke, 1977), and acceptable internal reliability coefficients have been reported (ranging from .84 to .90; Radloff, 1977; Roberts, 1980; Ross & Mirowsky, 1984; Turner & Turner, 2004). The CES–D is often used to assess depression among persons with vision impairments (Owsley & McGwin, 2004). Life satisfaction. The Satisfaction With Life Scale (SWLS; Diener, Emmons, Larsen, & Griffin, 1985) was used to evaluate subjective wellbeing and overall life satisfaction. The SWLS is a 5-item instrument with items rated on a Likert-type response format ranging from 1 (strongly disagree) to 7 (strongly agree). Higher scores reflect greater subjective well-being. Psychometric studies of the SWLS have evidenced internal consistency (␣ ⫽ .87) and reliability (2 month test–retest coefficient ⫽ .82; Diener et al., 1985). Daily functioning and vision-related quality of life. A modification of the original National Eye Institute—Visual Function Questionnaire (NEI– VFQ; Ellwein, Fletcher, Negrel, & Thulasiraj, 1995; Mangione, Berry, et
al., 1998; Mangione, Lee, et al., 1998) was used to evaluate the impact of visual impairment on daily functioning. The modified version used in this study contains 27 of the 52 original NEI–VFQ items (Massof & Fletcher, 2001) and 7 of the original 13 subscales (i.e., domains): Near Vision (7 items), Distance Vision (7 items), Social Functioning (3 items), Dependency (4 items), Role Functioning (1 item), Mental Health (2 items), and Vision Expectations (1 item). Responses for 17 of the items include the following range: 1 ⫽ no difficulty at all, 2 ⫽ a little difficulty, 3 ⫽ moderate difficulty, 4 ⫽ extreme difficulty, 5 ⫽ stopped doing this because of your eyesight, and 6 ⫽ stopped doing this for other reasons or not interested in doing this. The other 10 items require frequency or level of agreement ratings. Similar to the NEI–VFQ, this version is scored by a linear transformation of a respondent’s ratings for each item to values that range from 0 to 100. The average of the item scores for each subscale is computed to produce subscale scores, which are combined to produce a total impairment score (Parrish et al., 1997). For this study, we relied on the average score of the five subscales that had more than one item (Near Vision, Distance Vision, Social Functioning, Dependency, and Mental Health), and we included only fully completed questionnaires (i.e., no unanswered items).
Procedure Participants completed information as part of their initial evaluation in a low vision rehabilitation clinic. Interested individuals gave consent to participate in the evaluation. The modified version of the NEI–VFQ was mailed to each participant prior to their appointment date. Although participants were instructed to complete this measure prior to the appointment, some participants arrived with incomplete protocols and subsequently completed the modified version of the NEI–VFQ in the clinic. Some individuals completed the measure independently, and others completed it with the assistance of a family member. Some participants reported that family members assisted them with the modified NEI–VFQ at home. A doctoral-level clinical psychologist met individually with each participant and read all instructions and individual items on the remaining self-report measures to each participant. Participants were also handed a sheet of potential item responses for each questionnaire to serve as a guide for answering items. Item responses were printed in bold and increased to a 50-point Arial font. For the few individuals that could not read this type of font, items were repeated to assist participants’ responses to questionnaire items.
Data Analyses Correlational procedures were used to test the prediction that the problem-orientation component—specifically, negative problem orientation— would predict distress, depressive behavior, life satisfaction, and daily functioning. Prior research has relied on conservative use of hierarchical regression procedures to test the theoretical properties of the social problem-solving model (Elliott, 1999; Elliott, Sherwin, Harkins, & Marmarosh, 1995). After controlling for any variance attributable to age and gender, we then entered the three problem-solving-styles variables (RPS, AS, ICS) as a block at the second step of the equation. The two problem-orientation variables—PPO and NPO—were then entered at the final step as a block. Tests for significant incremental changes in the R2 statistic were performed at each step. In the event of significant changes at a specific step, t tests were performed for the specific variables within the block to determine their unique contribution. Separate regression equations were anticipated for the four criterion variables: emotional distress, depressive behavior, life satisfaction, and daily functioning.
Results Means, standard deviations, and correlations for the self-report measures are contained in Table 1. Elements of social problem
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Table 1 Means, Standard Deviations, and Correlations for Variables Used in Regression Analyses Variable 1. 2. 3. 4. 5. 6. 7. 8. 9. 10. 11.
PPO NPO RPS ICS AS ED CES–D SWLS M-VFQ Gender Age
1
2
—
⫺.05 —
3 .45 ⫺.03 —
4 .00 .39 ⫺.31 —
5 ⫺.19 .35 ⫺.27 .39 —
6 .05 .37 ⫺.05 .15 ⫺.13 —
7
8
⫺.00 .58 ⫺.09 .31 .22 .34 —
.09 ⫺.27 .43 ⫺.40 ⫺.36 ⫺.39 ⫺.34 —
9
10
11
M
SD
N
⫺.02 ⫺.10 .06 ⫺.09 ⫺.07 ⫺.41 ⫺.04 .18 —
.24 .27 .23 .14 .13 .08 .22 .03 .08 —
⫺.06 .00 .07 ⫺.12 .03 ⫺.18 ⫺.15 ⫺.00 ⫺.08 ⫺.17 —
12.69 5.87 11.26 5.07 4.63 46.96 11.61 25.63 35.20
3.30 4.43 4.06 3.50 4.59 25.88 0.50 6.24 20.47
71.15
15.11
54 54 54 54 54 50 51 54 37 54 54
Note. PPO ⫽ Positive Problem Orientation (observed range ⫽ 5–19); NPO ⫽ Negative Problem Orientation (observed range ⫽ 0 –17); RPS ⫽ Rational Problem Solving (observed range ⫽ 3–19); ICS ⫽ Impulsive/Carelessness Style (observed range ⫽ 0 –12); AS ⫽ Avoidance Style (observed range ⫽ 0 –17); ED ⫽ emotional distress (observed range ⫽ 0 –100); CES–D ⫽ Center for Epidemiological Studies—Depression Scale score (observed range ⫽ 0 –36); SWLS ⫽ Satisfaction With Life Scale score (observed range ⫽ 11–34); M-VFQ ⫽ modified National Eye Institute—Visual Function Questionnaire total score (observed range ⫽ 0 – 86.79); Gender ⫽ gender of participant (coded as 0 ⫽ male, 1 ⫽ female); Age ⫽ age at time of initial assessment (range ⫽ 23–92 years old). All correlations ⬍ ⫺.26 and ⬎ .26 are significant at p ⬍ .05.
solving were not significantly correlated with the modified NEI– VFQ total score, indicating there was no relation between effective problem-solving abilities and self-reported disability. Therefore, social problem-solving abilities could not significantly predict daily functioning. Separate one-way analyses of variance were conducted by gender for each of the self-report variables. Women reported a significantly higher negative problem orientation (M ⫽ 6.97, SD ⫽ 4.61) than men (M ⫽ 4.60, SD ⫽ 3.92), F(1, 52) ⫽ 4.06, p ⬍ .05. No other significant differences were found between men and women.
Prediction of Depressive Behavior Age and gender were entered at the first step of the equation to predict depression scores, and this block was not significant, F(2, 48) ⫽ 1.52, ns. The block of problem-solving styles did not contribute significantly to the equation at the second step, Finc (3, 45) ⫽ 0.09, ns. The block of problem-orientation variables significantly augmented the equation at the final step, Finc(2, 43) ⫽ 7.70, R2inc ⫽ .23, p ⬍ .01. As expected, a higher negative problem orientation was associated with higher depression scores ( ⫽ .55), t(43) ⫽ 3.38, p ⬍ .01.
Prediction of Emotional Distress Age and gender were not significantly associated with distress at the first step of the equation, F(2, 47) ⫽ 0.81, ns. Similarly, the block of problem-solving styles did not augment the equation at the second step, Finc(3, 44) ⫽ 0.84, ns. The block of problemorientation variables significantly predicted distress at the third step, Finc(2, 42) ⫽ 5.71, R2inc ⫽ .20, p ⬍ .01. As predicted, a higher negative problem orientation was associated with greater distress ( ⫽ .54), t(42) ⫽ 3.38, p ⬍ .01.
Prediction of Life Satisfaction Age and gender did not significantly contribute to the prediction of life satisfaction scores, F(2, 51) ⫽ 0.02, ns. However, the block of problem-solving styles was significant at the second step of the
equation, Finc(3, 48) ⫽ 6.57, R2inc ⫽ .29, p ⬍ .01. Inspection of beta weights revealed that greater rational problem-solving skills were associated with greater life satisfaction ( ⫽ .30), t(48) ⫽ 2.21, p ⬍ .01. The block of problem-orientation variables did not significantly augment this equation, Finc(2, 46) ⫽ 1.04, ns. Contrary to our initial hypothesis, then, negative problem orientation did not predict life satisfaction. In light of this unanticipated finding and to determine whether these results were influenced, in part, by the order of entry into the equation, we reversed the order of the last two steps to examine whether rational problem-solving skills would remain predictive of life satisfaction after controlling for any variance attributable to the problem-orientation component. With this order, the block of problem-orientation variables did not significantly augment the equation at the second step, Finc(2, 49) ⫽2.33, ns. The block containing the problem-solving-styles scores remained significant at the final step, Finc(3, 46) ⫽ 5.31, R2inc ⫽ .24, p ⬍ .01. Rational problem-solving skills were again positively associated with life satisfaction ( ⫽ .38), t(46) ⫽ 2.50, p ⬍ .05. Thus, a negative problem orientation evidenced no predictive relation to life satisfaction; however, greater rational problem-solving skills remained predictive of life satisfaction.
Post Hoc Tests of Mediation Emotional distress was significantly correlated with depression (.34), life satisfaction (⫺.39), and negative problem orientation (.37). This pattern suggests that these constructs may have a degree of shared variance and statistical redundancy; in such cases, it is possible that the condition-specific measure of distress might mediate the negative problem orientation– depression relation. Mediation is suspected in correlational research when similar patterns of significance are found (Baron & Kenny, 1986), and this is a particular concern in clinic research involving self-report measures (Holmbeck, 1997). The emotional distress variable in this study has evidenced high correlations with negative affectivity in prior research (Elliott et al., 1994; Harkins et al., 1989), and it has accounted for 26%– 46% of variance in other popular measures of
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depression among persons with chronic pain (Wade, Price, Hamer, Schwartz, & Hart, 1990). Negative affectivity predicts depression and distress among persons with vision loss (Rovner & Casten, 2001), and it has been found to mediate the relation of negative problem orientation to general distress among undergraduates in a prospective study (Elliott et al., 1995). Tests of mediation were satisfied, in part, by examining the correlations contained in Table 1. The significant correlations among negative orientation, depression, and emotional distress satisfied the first condition that mediation might exist in the negative problem orientation– depression relation. It is interesting that distress was not significantly associated with rational problemsolving skills. Therefore, distress could not mediate the predictive relation between rational problem-solving and life satisfaction. Partial correlation coefficients were examined to conduct the final test of mediation (Watson & Pennebaker, 1989). After controlling for the relation of distress to negative problem orientation and depression, the resulting partial coefficient between NPO and depression was significant (pr ⫽ .52 [N ⫽ 46], p ⬍ .001). Thus, distress did not mediate the predictive relation between negative problem orientation and depressive behavior in this sample.
Screening for Depression A final matter of clinical interest concerned the detection of individuals with elevations on the CES–D that might indicate depressive episodes. Using a conservative cutoff recommended for older samples (⬎19 indicative of possible depression; Himmelfarb & Murrell, 1983), we found that 7 of the 51 persons who completed the CES–D exceeded this cutoff score (14%). Although the relatively low number in this group renders subsequent means unstable and further analyses tenuous, a series of one-way analyses of variance indicated that these persons were significantly younger (M ⫽ 59.71 years old, SD ⫽ 23.69 years) than those who were not depressed (M ⫽ 72.66 years old, SD ⫽ 13.21 years, N ⫽ 44), F(1, 49) ⫽ 4.56, p ⬍ .05.
Discussion These results provide partial support for our hypotheses. As expected, a negative problem orientation toward solving problems was significantly predictive of emotional distress associated with vision loss and with higher scores on the depression measure. However, negative problem orientation was not associated with life satisfaction; rational problem-solving skills were positively associated with higher scores on the life satisfaction measure. No component of problem solving predicted self-reported disability. Although emotional distress was significantly associated with depression, it did not mediate the negative problem orientation– depression relation. In many respects, these results are consistent with prior work in this area. Effective problem-solving abilities are associated with better psychological adjustment of persons who live with a chronic health condition (Elliott et al., 2004). As this literature attests, however, there are some inconsistencies that have defied theoretical explanation and have yet to be clarified empirically. In the present study, for example, the relation between rational problemsolving skills and life satisfaction was not anticipated. Elements of a “positive problem-solving style”—that is, the positive problem
orientation and rational problem-solving skills— have been associated with indicators of positive adjustment such as disability acceptance (Elliott, 1999), but a lower negative problem orientation has also emerged as a significant predictor of positive mental health (Elliott & Shewchuk, 2003; Grant, Weaver, Elliott, Bartolucci, & Giger, 2004). There is also conflicting evidence that at times a greater reliance on rational problem-solving skills may be related to more frustration and distress (e.g., among persons with diabetes; Elliott, Shewchuk, Miller, & Richards, 2001). These inconsistencies may stem in part from the reliance on correlational procedures to test specific theoretical properties of the social problem-solving model (Elliott et al., 2004). The number of participants in the present study precluded examination of possible subgroups in the sample, which is one method for examining the full array of problem-solving abilities and their relation to global indicators of adjustment (see Elliott et al., 2001). Despite these nuances, the results of the present study provide evidence that social problem-solving abilities are associated with important aspects of adjustment among persons experiencing vision loss. Specifically, it appears that a negative problem orientation increases vulnerability for distress specific to the condition, and this in turn may elevate a risk for depressive symptoms. A negative problem orientation also contributes to errors in decision-making, independent of mood (Shewchuk, Johnson, & Elliott, 2000), and these cognitive distortions may then result in ongoing problems with depressive symptoms, which may impede motivation for low vision rehabilitation, adherence with treatment, and/or performance in activities of daily living. It is interesting to note that social problem-solving abilities were not significantly associated with the total score on the visionrelated functional ability measure. The NEI–VFQ is often used in low vision rehabilitation clinics; its relation with important psychological variables deserves further scrutiny. It is possible that the lack of relationship between social problem-solving abilities and vision-related functional ability may have been due in part to the limited number of items included in the modified version of the NEI–VFQ that we used in the present study. It is also possible that responses to the modified NEI–VFQ were confounded by the presence of family members. This measure was mailed to participants prior to their clinic evaluation and, in some cases, was completed with the assistance of family members. This procedure was at variance with the way in which all other measures were administered. Participants may have given inconsistent responses with their family members present, or this feature may have presented demand characteristics that (altered responses to certain items) resulted in an item response bias. Other research has found that self-reported impairment is associated with social problemsolving abilities in predictable directions (e.g., among persons with spinal cord injury, Elliott et al., 1991; among persons with chronic pain, Shaw, Feuerstein, Haufler, Berkowitz, & Lopez, 2001). This is an issue that should be addressed in future research, preferably with the 25-item version (Owsley & McGwin, 2004) or the 51item version (Mangione et al., 1998) to increase generalizability with the extant literature. Previous studies of larger samples have found lower rates of possible depressive syndromes, as indicated by the CES–D, among persons with vision impairments than that observed in our data (8%; Owsley & McGwin, 2004). It is interesting to note that we used a more conservative higher cutoff score (⬎19) than these
SOCIAL PROBLEM SOLVING AND LOW VISION
researchers. This higher cutoff score is recommended for older samples, given the number of items on the CES–D that can be confounded by age-related health problems. We believe this conservative approach is a more informed way to examine this issue, yet we cannot account for the higher rate of persons reporting greater severity of depression in our sample. Inspection of the individual TAS scores that were combined into the single index of emotional distress indicates that the higher mean scores on the frustration (M ⫽ 69.80, SD ⫽ 30.69) and anxiety (M ⫽ 50.00, SD ⫽ 33.96) TAS scales were higher than the mean TAS depression score (M ⫽ 45.80, SD ⫽ 33.03). Participants in this study may have been more goal-directed yet concerned as they were entering the rehabilitation program. Longitudinal research is required to monitor their adjustment over time. These results imply that the social problem-solving model may be useful to guide psychosocial interventions in low vision rehabilitation. One randomized clinical trial has demonstrated that persons with macular degeneration benefit from self-management interventions that strategically increase self-efficacy (Brody et al., 1999). A problem-solving perspective can be used to present basic information about the condition, teach active coping skills, and encourage the use of assistive devices and the development of new goals with considerable success (Nezu et al., 2003). Additionally, such an approach may be particularly helpful to foster a more positive orientation or framework for solving problems associated with low vision. These strategies could be adopted for use in individual and group sessions in low vision rehabilitation. Several recommendations for future studies are warranted. For example, longitudinal investigations are needed to provide for a more comprehensive understanding of the relation between adjustment and social problem-solving abilities across time. Additionally, investigations identifying specific problems related to persons with low vision would be helpful to inform and tailor social problem-solving interventions unique to this particular population and their encountered problems. Finally, development of alternative assessment measures of psychosocial functioning are warranted, given the constraints of current assessment devices when used with persons with visual impairments.
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Received July 18, 2004 Revision received October 19, 2004 Accepted October 22, 2004 䡲
