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P1: FVF/GVM/GOQ/GMF/GDP/GFQ/FYJ Journal of Clinical Psychology in Medical Settings

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Style file version Oct. 19, 2000

c 2001) Journal of Clinical Psychology in Medical Settings, Vol. 8, No. 4, December 2001 (°

Profiles in Problem Solving: Psychological Well-Being and Distress Among Persons with Diabetes Mellitus Timothy R. Elliott,1,4 Richard M. Shewchuk,2 Doreen M. Miller,3 and J. Scott Richards1

Although social problem-solving abilities have been consistently associated with indicators of behavioral health, this work has been largely confined to tests of specific theoretical issues. Research has yet to demonstrate how the separate elements of the social problem-solving model relate to different patterns of adjustment, particularly among persons who live with chronic disease. We studied the occurrence of different profiles of social problem-solving abilities observed among persons living with diabetes mellitus. We then examined differences between clusters on measures of life satisfaction and depression. Results indicate that distinct profiles in problem-solving abilities do occur and these groupings can be distinguished by their different patterns of adjustment. Implications for theoretical models of problem solving and clinical assessment and interventions for persons with diabetes are discussed. KEY WORDS: problem solving; diabetes; depression; well-being.

INTRODUCTION

skills (D’Zurilla & Nezu, 1999). According to this perspective, the problem orientation component serves to (a) ward off negative emotions (e.g., anger, depression, anxiety in problem-solving situations), (b) facilitate positive affect and a sense of competency that enhances problem solving, (c) inhibit tendencies to impulsively and carelessly react in problem-solving situations, and (d) motivate the person toward effective problem solving (D’Zurilla & Nezu, 1999; Nezu & D’Zurilla, 1989). The second component entails actual problem-solving skills that involve the specific, goal-directed strategies by which individuals define problems, generate alternatives, decide on a solution, and implement and monitor problem-solving strategies. Early conceptualizations of this model emphasized the motivational function of the problem orientation component, and the cognitive-behavioral strategies essential to problem solving were subsumed under the problem-solving skills component (Nezu & D’Zurilla, 1989). More recently, D’Zurilla and colleagues have delineated the problem orientation component into positive and negative elements. A positive orientation entails beliefs, expectancies, and abilities that motivate a person and promote positive emotions

Theory and research concerning social problemsolving abilities have advanced our knowledge of these cognitive-behavioral characteristics in the prevention, development, and maintenance of difficulties people experience in everyday life (D’Zurilla & Nezu, 1999; Nezu & D’Zurilla, 1989). In particular, the study of social problem-solving abilities and their relations to matters of behavioral health have supported many of the basic theoretical tenets of available models and their accompanying measures (D’Zurilla & Nezu, 1999; Heppner & Baker, 1997). Research has benefited from a conceptualization of social problem-solving abilities into separate domains of problem orientation and problem-solving 1 Department

of Physical Medicine and Rehabilitation Medicine, University of Alabama at Birmingham, Birmingham, Alabama. 2 Department of Health Services Administration, University of Alabama at Birmingham, Birmingham, Alabama. 3 Department of Psychology and Rehabilitation Counseling, Southern University, Baton Rouge, Los Angeles. 4 Correspondence should be addressed to Timothy R. Elliott, Ph.D., ABPP, SRC 530, 619 19th Street South, Birmingham, Alabama 35249-7330; e-mail: [email protected].

283 C 2001 Plenum Publishing Corporation 1068-9583/01/1200-0283$19.50/0 °


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284 that facilitate problem solving; a negative orientation is characterized by pessimism and negative expectancies for future behavior and events (D’Zurilla & Nezu, 1999). The problem-solving skills component has also been demarcated into separate elements of rational problem solving, impulsive/careless, and avoidant tendencies (D’Zurilla & Nezu, 1999). These separate areas reflect cognitive-behavioral beliefs and problem-solving strategies that factor into these separate elements (D’Zurilla & Nezu, 1999). These factors are represented on the Social Problem-Solving Skills Inventory – Revised (SPSI-R; D’Zurilla, Nezu, & Maydeu-Olivares, in press). Much of the research examining the relation of social problem-solving abilities to indicators of behavioral health has supported many basic properties of the theoretical model. Research confirms that a greater negative orientation is significantly predictive of depression and psychosocial impairment among persons with disability, and of pain complaints and ill health among college students (Elliott, 1999; Elliott, Godshall, Herrick, Witty, & Spruell, 1991; Elliott & Marmarosh, 1994; Witty, Heppner, Bernard, & Thoreson, in press). Prospective research reveals that persons with a greater negative orientation develop more problems with depression, anxiety, and ill health over the course of a year (Elliott, Shewchuk, & Richards, in press). Similarly, research has found problem-solving skills are related in a predictable fashion with several indices of behavioral health. Avoidance tendencies have been associated with greater sedentary behavior and increased alcohol ingestion among undergraduates (Godshall & Elliott, 1997). Persons with disability who were diagnosed with preventable skin ulcers were also characterized by their avoidant tendencies (Herrick, Elliott, & Crow, 1994). Persons with spinal cord injury (SCI) who have family caregivers, possess more impulsive and careless problem-solving behaviors, have greater difficulty coming to terms with their disability, and are at significant risk for developing preventable skin ulcers over the initial year of acquired disability (Elliott, Shewchuk, & Richards, 1999). But these studies have typically investigated basic theoretical questions, using statistical techniques that often isolate the separate components of problem solving for the purposes of testing specific theoretical properties and clarifying the role of the separate components in the prediction of adjustment, behavior, or other relevant outcomes. Although this approach has advanced our theoretical understanding of social problem solving and its constructs, and it has

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Elliott, Shewchuk, Miller, and Richards demonstrated the utility of the model in understanding many issues in behavioral health, it does not inform us how the separate elements of problem solving might operate in tandem, or how different problem solving profiles might be distributed among people. The reliance on tests of specific theoretical tenets unfortunately contributes to a rather piecemeal view of social problem-solving abilities and their role in adjustment among people. This is a poignant concern when considering the potential impact of social problem-solving abilities among individuals who have a chronic health condition. Preliminary evidence suggests that the different components of social problem solving have a more complex influence on adjustment among persons with chronic health problems than originally implied in theoretical models of social problem solving (e.g., Witty et al., in press). People who live with chronic diseases that require adherence to daily selfcare regimens, for example, must attend to matters of diet, exercise, self-monitoring of symptoms, and self-medication. Psychological and physical health is largely dependent upon the ability of the individual to thoughtfully plan routines of diet, activity, and medication regardless of competing life demands, life stressors, or temporal moods. In these situations, all elements of the social problem-solving model would be instrumental in how a person would manage one’s mood, maintain motivation, and carefully adhere to self-care regimens and plan daily activities. Avoidance of these tasks, careless and impulsive attempts at adherence, and recurring bouts with negative moods and pessimism would thwart behavioral self-care and compromise personal health. Thus, the full array of optimal problem-solving abilities would be instrumental in promoting personal health and overall quality of life. In contrast, deficits in any or all problemsolving components may likely result in impaired health, poor quality of life, and increased psychological distress.

Diabetes, Adjustment, and Social Problem-Solving Abilities Diabetes is an incurable condition that necessitates daily adherence to dietary and other behavioral regimens to ensure optimal functioning and personal health. Failure to observe behavioral selfmanagement and self-care programs can have devastating effects. Heart disease is two to four times more common among people with diabetes and accounts for 75% of diabetes-related deaths. People


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Problem Solving and Diabetes with diabetes are also two to four times more likely to have a stroke than persons without diabetes; they also have 60–65% higher blood pressure than nondiabetic peers (American Diabetes Association, 1996, 1997). Persons with diabetes are more likely to have problems with visual impairment and blindness (12,000– 24,000 new cases every year), kidney disease (35% of new cases have end-stage renal disease), and amputations that account for more than half of lower limb amputations in the United States (American Diabetes Association, 1996, 1997). Finally, persons with diabetes are greater than three times more likely to have problems with depression than the general public (Glasgow et al., 1999). Behavioral self-management and good problemsolving skills are essential for optimal adjustment among persons with diabetes (Glasgow et al., 1999; Jenkins, 1995; Toobert & Glasgow, 1991). Unfortunately, many persons who have diabetes receive little more than traditional patient education concerning diabetes management, and few are exposed to interventions that can assist them with problems of daily living that directly impinge on their abilities to cope and observe personal regimens of care (Glasgow et al., 1999). Although problem-solving skills are important in the adjustment of persons with diabetes, there has been no systematic study of social problem-solving abilities among these individuals, and no demonstrated effects of problem-solving training on the health and well-being of persons with diabetes. Some research using diabetes-specific measures of problem solving and adjustment has indicated that the ability to solve problems associated with diabetes is positively associated with more optimal adjustment (Toobert & Glasgow, 1991). However, in the study of adjustment among persons with chronic health conditions, it is often assumed that the disease constitutes a major focus in everyday life, when in fact people vary considerably in the degree to which they attend to other aspects of life, and find meaning and pursue fulfilling activities independent of their disease. Individuals who adjust optimally following the onset of a chronic disease or disability do not regard their condition as the centerpiece of their life experience; conversely, persons who have greater difficulty coming to terms with their condition often have difficulty coping with other aspects of life (Elliott, Kurylo, & Rivera, in press). Thus, if individuals have difficulty solving problems in everyday life, it is probable that they will have similar difficulties tending to daily tasks and self-care regimens prerequisite for optimal adjustment with diabetes.


285 Individuals who have ineffective problemsolving abilities are more likely to experience ongoing problems under routine and stressful conditions (D’Zurilla & Nezu, 1990). Specifically, a person with a high negative orientation lacks the motivation requisite for engaging in a problem-solving process, and relatively minor hassles of everyday life are likely to exacerbate into stressful situations and circumstances. Persons with ineffective problem-solving skills and negative orientation are also prone to develop problems with depression (Nezu, 1987). These are critical issues in diabetes. Depression and stress can compromise diabetes management (Lustman, Griffith, Gavard, & Clouse, 1992; Surwit, Schneider, & Feinglos, 1992). We examined the relation of social problem-solving abilities to depression and life satisfaction among persons with diabetes in this study.

METHOD Participants Persons with diabetes who were receiving outpatient services from the Diabetes Education Center in Baton Rouge, LA, were mailed a questionnaire containing a cover letter explaining the study, a brief demographic form that did not request any personal identification, and the measures of social problemsolving abilities and adjustment. A clinic database was used to generate names and addressed for the mailings, and this information was kept confidential from the research team. A letter from the clinic director was included in the packet, describing the survey. A stamped envelope with a return address was provided for returning the materials. Participants were asked to return their packets to the third author. Enclosed in the packet was a magnet with the slogan, “I can manage my diabetes.” There was no monetary incentive for returning the materials. Three hundred and thirteen protocols were received. Useable self-report protocols were available from 259 respondents (86 men, 167 women; 6 respondents did not report this information). The sample averaged 57.36 years of age (SD = 15); 183 persons reported Type II and 48 reported Type I diabetes (28 persons did not report diabetes type). Two hundred and twenty individuals reported at least a high school education or equivalent, and 27 reported less than a high school education (three persons did not report their education level). The sample included 165 persons who were married, 33 who were single,


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286 27 who were widowed, 14 who were divorced, and 16 who were separated (three did not report their marital status). The sample was predominately Caucasian (N = 163) and African American (N = 82); six were Native American, one was Asian Pacific Islander, and one was Hispanic (one reported other and five did not report ethnicity).

Measures

Social Problem Solving Abilities – Revised (SPSI-R; D’Zurilla et al., in press) The SPSI-R is a 52-item, self-report measure of social problem-solving abilities (Maydeu-Olivares & D’Zurilla, 1996). Each item is rated on a 5-point Likert-type scale ranging from not very true of me (0) to extremely true of me (4). Higher scores on each scale indicate a greater propensity in that facet of problem solving. The SPSI-R is based on a 5D model of problem solving and provides five scales. Two of the scales measure the problem orientation dimensions: positive problem orientation (PPO) and negative problem orientation (NPO). The remaining three scales are considered problem-solving skills scales. These include rational problem solving (RPS), impulsivity/carelessness style (IC), and avoidance style (AV). The Positive Problem Orientation scale (PPO) assesses a general cognitive set that includes the tendency to view problems in a positive light, to see them as challenges rather than threats, to be optimistic about one’s ability to detect and implement effective solutions. Sample items from the PPO scale include “Whenever I have a problem, I believe that it can be solved,” “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.” The Negative Problem Orientation scale (NPO) assesses a cognitiveemotional set indicative of a greater pessimism, a lack of motivation toward problem solving, and a proclivity for negative moods that hinders effective problem solving. Sample items on the NPO scale include “I hate having to solve the problems that occur in my life,” “When I am trying to solve a problem I get so upset that I cannot think clearly,” and “When I am faced with a difficult problem, I doubt that I will be able to solve it on my own no matter how hard I try.” The Rational Problem Solving scale (RPS) assesses the tendency to systematically and deliberately employ effective problem-solving techniques by defining the problem, generating alternatives, eval-

Elliott, Shewchuk, Miller, and Richards uating alternatives, and implementing solutions and evaluating outcomes. Sample items on the RPS scale include “Before I try to solve a problem, I set a specific goals so that I know exactly what I want to accomplish” and “When I have a decision to make, I weigh the consequences of each option and compare them to each other.” The Impulsivity/Carelessness Style scale (IC) measures the tendency to solve problems in an impulsive, incomplete, and haphazard manner. The IC scale has items such as “When making decisions, I do not evaluate all my options carefully enough” and “When I am trying to solve a problem, I go with the first good idea that comes to mind.” The Avoidance Style scale (AV) assesses dysfunctional patterns of problem solving characterized by putting the problem off and waiting for problems to solve themselves. Sample items on this scale include “I go out of my way to avoid having to deal with problems in my life” and “I spend more time avoiding my problems than solving them.” Internal consistency estimates for the scales with college students range from alphas of .76 for PPO to .92 for RPS and test-retest (3 weeks) reliability ranges from .72 for PPO to .88 for NPO for the same sample (D’Zurilla, et al., in press). Significant correlations between the SPSI- R scales and similar constructs on the Problem-Solving Inventory (Heppner, 1988) and with other theoretically related constructs such as stress, somatic symptoms, anxiety, depression, hopelessness, and suicidality provide evidence of construct validity (Chang & D’Zurilla, 1996; D’Zurilla et al., in press). The SPSI-R scales have been predictably associated with self-esteem, life satisfaction, extraversion, social adjustment, and social skills (D’Zurilla et al., in press; Sadowski, Moore, & Kelley, 1994).

Depressive Behavior The Center for Epidemiological Studies Depression Scale (CESD; Radloff, 1977) was used to obtain an index of depressive behavior at each assessment. This instrument contains 20 items that assess current levels of depressive behavior, with a particular emphasis on the impact of depressed mood. Items are scored on a 4-point scale to indicate how often symptoms are experienced in the preceding week. Scores range from 0 to 60. Higher scores indicate higher levels of depressive behavior; scores greater than 16 have been found to differentiate depressed from nondepressed community-residing adults (Craig & Van Natta, 1978). Alpha coefficients have ranged from .84 to .90 in several field studies (Radloff, 1977).


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Problem Solving and Diabetes

287

Subjective Well-Being The Satisfaction with Life scale (SWLIFE; Diener, Emmons, Larsen, & Griffin, 1985) was used to assess subjective well-being at the annual evaluations. The SWLIFE is a 5-item instrument; each item is rated on a Likert-type response format ranging from 1 (strongly disagree) to 7 (strongly agree). Sample items on the SWLIFE include “In most ways my life is close to my ideal,” “The conditions of my life are excellent,” and “I am satisfied with my life.” Higher scores reflect greater subjective wellbeing. The SWLIFE has evidenced internal consistency (α = .87) and reliability (2 month test-retest coefficient = .82; Diener et al., 1985). Correlates with other instruments indicate that the scale is relatively independent of social desirability effects and psychopathology, and it is favorably associated with other measures of life satisfaction (Diener et al., 1985). Statistical Analyses The five problem-solving subscale scores were included in a K-means cluster analysis. This procedure was used to identify distinct homogeneous subgroups of people who evinced similar patterns of problemsolving characteristics. The K-means cluster analysis used in this analysis is a nonhierarchical or nonagglomerative method of clustering that employs simple Euclidean distance measures to assign individuals to groups based on their similarity across the selected problem-solving measures (Aldenderfer & Blashfield, 1984; Speece, 1990). K-means cluster analysis has been likened to “ANOVA in reverse given that its primary purpose is to minimize the variability within clusters, and maximize the variability between

Fig. 1. Standardized problem solving characteristics of the four cluster groups.

clusters” (Statsoft, 1999, p. 3173). As depicted in Fig. 1, a range of solutions consisting of four through six clusters was obtained. Assessment of various diagnostics indicated that the four group solution provided the most distinct classification of individuals. Betweengroup analyses of variance were used to examine the external validity of the cluster groupings using the CESD and the SWLIFE as criterion measures. RESULTS Table I presents information concerning the four clusters that were significantly profiled. The clusters did not differ significantly by gender, marital status, ethnicity, type of diabetes, or level of education. There were no differences by age across the four clusters. There was a significant difference, however, between the clusters on the depression measure,

Table I. Means and Standard Deviations for Social Problem-Solving Abilities and Adjustment Measures by Problem-Solving Clusters Cluster Cluster 1 (N = 55) Mean SD Cluster 2 (N = 45) Mean SD Cluster 3 (N = 82) Mean SD Cluster 4 (N = 77) Mean SD

PPO

NPO

RPS

IC

AV

CESD

SWLIFE

7.40 2.85

18.38 9.30

22.95 9.55

16.78 7.53

12.15 6.54

20.67 13.39

17.93 7.08

13.36 2.85

15.84 7.35

51.69 6.72

12.67 5.86

9.64 4.43

19.67 10.95

19.80 6.42

11.11 2.92

6.50 4.88

35.33 8.39

7.06 3.97

4.79 3.30

12.94 8.82

20.83 6.76

15.90 2.90

4.14 3.61

61.13 8.78

4.06 3.82

3.58 2.55

10.29 8.50

23.19 5.89


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288

Fig. 2. Standardized adjustment scores of the four problem solving groups.

F(3, 255) = 15.28, p < .001. Specifically, post hoc tests revealed that the average depression score in Cluster 1 was significantly different from Clusters 3 and 4, and the average score in Cluster 4 was significantly different from Cluster 2 ( ps < .0001). A significant difference was also found between the groups on the measure of life satisfaction, F(3, 255) = 7.35, p < .001. Post hoc tests indicated that the average score in Cluster 1 was significantly different from those in Clusters 3 and 4, and the average scores in Clusters 2 and 3 were not significantly different (all ps < .001). Figure 2 depicts the standardized profiles of the clusters on the two criterion measures. Cluster 1: Distressed and Unskilled. Individuals in Cluster 1 had the highest level of distress of the four clusters. This cluster also evidenced the most negative problem solving profile. As a group, these individuals possessed the lowest positive orientation toward problem solving, and they had the most negative orientation. They also reported fewer rational problemsolving skills, and were more apt to avoid problems and solve problems with impulsive and careless attempts. Persons in this cluster lacked confidence and likely experienced ongoing problems with negative moods and minor stressors (that would likely exacerbate into more substantive problems). Their ineffectual attempts to solve problems would likely perpetuate a stressful lifestyle that would compromise their ability to manage their diabetes, resulting a greater likelihood of complications (and further stress). Cluster 2: Pessimistic and Frustrated Problem Solvers. Individuals in this cluster reported the second higher level of distress. Notably, this group produced a problem-solving profile that argues against a sim-

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Elliott, Shewchuk, Miller, and Richards ple linear relationship between self-reported problem solving and adjustment. This group reported the second highest positive orientation and the second highest level of rational problem-solving skills. This pattern would suggest that these individuals were motivated to solve problems in everyday life, and they possessed an adequate repertoire of rational skills prerequisite for optimal adjustment. However, this group reported the second highest negative orientation and the second highest scores in impulsive/ careless and avoidant tendencies. These scores indicate that people in this group—despite their positive attributes—were also pessimistic, prone to negative moods, frustrated, and inclined to use ineffectual strategies at inopportune or inappropriate times. The overall profile implies that this group was rather frustrated and perhaps embattled, experiencing considerable problems managing their daily problems and their diabetes, and with their daily regimens. Cluster 3: Low-Key and Managing. This cluster had the most members and it evidenced the second highest level of optimal adjustment. Similar to Cluster 2, the group profile for this cluster is inconsistent with a simple linear interpretation of the problem-solving– adjustment relationship. This group evidenced the second lowest average scores on both orientation scales (positive and negative). Theoretically, individuals with lower positive orientation scores are not optimistic and they may lack motivation and confidence for solving problems. They may also experience few positive emotions. People who have a low negative orientation may experience few negative emotions and they are not likely to be overwhelmed by minor problems or stressors. Their negative moods do not interfere with their ability to process information and solve problems. This group also reported the second lowest rational problem-solving score, and it also had the second lowest scores on the avoidant and the impulsive/careless subscales. This pattern indicates these individuals did not see themselves as motivated toward solving problems, generally, but neither were they necessarily pessimistic about their ability to solve problems. This group may have been more invested in managing ongoing emotions and minor hassles without engaging in a strenuous problem-solving process, per se. In this fashion, then, they reported a higher level of adjustment than two of the other clusters because they were not frustrated or discouraged. Cluster 4: Ideal Problem Solvers. Persons in this cluster reported an optimal level of adjustment, and their


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Problem Solving and Diabetes problem-solving profile was theoretically consistent with an ideal problem-solving approach. The orientation scores reflect an optimistic, confident style motivated toward solving problems, unencumbered by negative moods, pessimism, or self-doubt. Individuals with similar scores would be able to handle minor problems without exertion, experience positive moods, and have the prerequisite motivation necessary for solving complex problems. These individuals also reported an optimal repertoire of rational problem-solving skills and were not inclined to use ineffectual strategies when facing a problem (e.g., avoidant, impulsive, or careless). The group had the second highest number of members. DISCUSSION The resulting problem-solving profiles indicate that there are nuances in the ways social problemsolving abilities relate to optimal adjustment among persons with chronic health conditions like diabetes. To a great extent, the extreme contrasts between clusters 1 and 4 in our sample represent theoretical characterizations of negative and positive adjustment, respectively. At first glance, these extremes imply a simple linear association might exist between problem-solving abilities and self-reported indices of adjustment. Theoretically, persons who are confident, motivated, able to regulate their emotions, and equipped to use rational approaches to solve problems should be better adjusted under routine and stressful circumstances. This description fits the fourth cluster of our sample; the first cluster depicts the inverse of this picture. But the two other clusters suggest that there are individuals who face an array of challenges despite possessing a positive orientation and a repertoire of rational skills, and others who manage well without displaying a full range of effective problemsolving abilities. Persons in the second cluster reported many characteristics typically associated with positive adjustment, yet this group was clearly distressed. It should be noted that common to the distressed profiles—and conversely, absent in the groups with optimal adjustment—was an elevation on the negative orientation scale. Persons with a high negative orientation are inclined to ruminate, harbor pessimism, and have difficulty regulating unpleasant emotions regardless of stress levels (Elliott, Sherwin, Harkins, & Marmarosh, 1995). A negative orientation can impair problem-solving efforts on discrete, objective tasks

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289 independent of negative affect (Shewchuk, Johnson, & Elliott, 2000). It is suspected, in part, that a NPO interferes with a person’s ability to process information, compromising their ability to engage in strenuous problem solving (Heppner & Krauskopf, 1987). As a higher NPO is prospectively predictive of increases in health problems, anxiety, and depression (Elliott et al., in press), there is concern that prolonged difficulties would result in impaired health and an increase in secondary complications among persons with chronic diseases such as diabetes. In sum, the results of this study and converging evidence indicate that an elevated negative orientation may override the beneficial attributes of more adaptive problem-solving abilities. Similarly, the present data also imply that persons who are not prone to be pessimistic or have recurrent bouts with negative moods, or ruminate about their circumstances may be less likely to have problems with adjustment. A lower NPO may be associated with better adjustment even in situations in which a lower positive orientation and fewer rational skills are present. Caution is warranted, however, in this latter observation: the standardized problem-solving scores in the third cluster (Fig. 1) were slightly below average for our sample, and thus may not indicate an absence of problem-solving ability, per se. Furthermore, programs could be developed to target those persons who appear to be most at-risk for secondary complications and maladjustment. Our results suggest that persons who possess characteristics similar to those in our first cluster will need specific attention. Persons with a greater negative orientation may be at particular risk regardless of their disease status, and these persons may require repeated interactions to prevent costly complications. In contrast, those with a lower negative orientation and more effective problem solving abilities—represented by the fourth cluster in our study—may be quite capable of adjusting well on their own recognizance, requiring little more than educational opportunities and routine follow-up care. This kind of strategic approach to programming interventions could translate into more cost-effective use of clinic resources. Many clinicians rely on educational programs to provide persons with diabetes with information considered essential for adjustment, disease management, and adherence to self-care regimens (Rubin & Peyrot, 1992). Unfortunately, knowledge about diabetes and self-care alone is insufficient for effective management, and it is unrelated to adherence with therapeutic regimens (Johnson, 1995).


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290 Patient education programs ultimately ignore socialcognitive characteristics and other individual differences that have considerable implications for clinical interventions (Elliott & Marmarosh, 1995). Intervention programs based in a problem-solving format have been effective in alleviating depression among community-residing individuals (Arean et al., 1993; Nezu & Perri, 1989), and they are effective in enhancing self-management skills (Richards & Perri, 1978). Problem-solving interventions can be implemented in individual (Kurylo, Elliott, & Shewchuk, in press) and group (Nezu & Perri, 1989) formats. Problem-solving interventions seem to have particularly beneficial effects on improving elements of the problem orientation component (Nezu & Perri, 1989). Rather than adapt a template approach to problem-solving training, however, it is critical that interventions be tailored to meet the individual needs of persons living with diabetes. With increasing demands on health care systems to develop cost-effective programs for persons who live with chronic health problems, there is a corresponding recognition that these individuals should be acknowledged as experts on the “. . . realities of their daily lives” (Mechanic, 1998, p. 24). Interventions should help persons with chronic disease become more active and expert in their self-management and to operate competently as extensions of the formal health-care system (Wagner, Austin, & Von Korff, 1996). In order to accomplish this, it is imperative that clinicians learn and understand the unique problems individuals encounter in their own terms as they live with diabetes, and direct problem-solving interventions to these issues (Miller, Shewchuk, Elliott, & Richards, 2000). Patient education programs that center on issues of unique concern to individual patients should be more effective than packaged programs (Anderson et al., 1995). These approaches overcome weaknesses associated with topdown or expert-oriented intervention strategies by involving the consumer as a vested member of the health-care-delivery team (Lengnick-Hall, 1995). Finally, problem-solving interventions need not be confined to traditional settings or formats to be effective. Emerging evidence indicates that problemsolving interventions can be delivered in community settings (Houts, Nezu, Nezu, & Bucher, 1996), and in home-based programs using telephone (Grant, 1999; Roberts et al., 1995) and telehealth applications (Kurylo et al., in press). Programs of this nature can circumvent barriers to participation that often accompany persons with chronic disease and disability (e.g., transportation difficulties, limited

Elliott, Shewchuk, Miller, and Richards resources, etc.) and increase generalizability by addressing immediate problems experienced in the home and community. ACKNOWLEDGMENTS This study was supported by a grant from the National Institute on Disability and Rehabilitation Research (grant number H133B30025-96A). Its contents are solely the responsibility of the authors and do not necessarily represent the official views of the funding agencies. REFERENCES Aldenderfer, M. S., & Blashfield, R. K. (1984). Cluster analysis. Newbury Park, CA: Sage. American Diabetes Association. (1996). Diabetes 1996 vital statistics. Alexandria, VA: Author. American Diabetes Association. (1997). Economics consequences of diabetes mellitus in the U.S. in 1997. Alexandria, VA: Author. Anderson, R. M., Funnell, M. M., Butler, P., Arnold, M. S., Fitzgerald, J., & Feste, C. (1995). Patient empowerment: Results of a randomized, controlled trial. Diabetes Care, 18, 943– 949. Arean, P. A., Perri, M., Nezu, A., Schein, R., Christopher, F., & Joseph, T. (1993). Comparative effectiveness of social problem-solving therapy as treatments of depression in older adults. Journal of Consulting and Clinical Psychology, 61, 1003–1010. Chang, E. C., & D’Zurilla, T. J. (1996). Relations between problem orientation and optimism, pessimism, and trait affectivity: A construct validation study. Behavior Research and Therapy, 34, 185–194. Craig, T., & Van Natta, P. A. (1978). Current medication use in symptoms of depression in a general population. American Journal of Psychiatry, 135, 1036–1039. Diener, E., Emmons, R. A., Larsen, R., & Griffin, S. (1985). The satisfaction with life scale. Journal of Personality Assessment, 49, 71–75. D’Zurilla, T. J., & Nezu, A. M. (1990). Development and preliminary evaluation of the social problem solving inventory. Psychological Assessment, 2, 156–163. D’Zurilla, T. J., & Nezu, A. (1999). Problem-solving therapy (2nd ed.). New York: Springer. D’Zurilla, T. J., Nezu, A. M., & Maydeu-Olivares, A. (in press). Manual for the social problem solving inventory-revised (SPSIR). North Tonawanda, NY: Multi-Health Systems. Elliott, T. (1999). Social problem solving abilities and adjustment to recent-onset physical disability. Rehabilitation Psychology, 44, 315–332. Elliott, T., Godshall, F., Herrick, S., Witty, T., & Spruell, M. (1991). Problem-solving appraisal and psychological adjustment following spinal cord injury. Cognitive Therapy and Research, 15, 387–398. Elliott, T., Kurylo, M., & Rivera, P. (in press). Positive growth and adjustment following acquired physical disability. In C. R. Snyder & S. Lopez (Eds.), Handbook of Positive Psychology. London: Oxford University Press. Elliott, T., & Marmarosh, C. (1994). Problem solving appraisal, health complaints, and health-related expectancies. Journal of Counseling and Development, 72, 531–537.


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