• We are sorry, but NCBI web applications do not support your browser and may not function properly. More information
Logo of nihpaAbout Author manuscriptsSubmit a manuscriptNIH Public Access; Author Manuscript; Accepted for publication in peer reviewed journal;
Eat Behav. Author manuscript; available in PMC Aug 1, 2010.
Published in final edited form as:
PMCID: PMC2726832

Problem Solving, Treatment Adherence, and Weight-Loss Outcome Among Women Participating in Lifestyle Treatment for Obesity



This study examined whether improvements in problem-solving abilities mediate the relation between treatment adherence and weight-loss outcome in the behavioral treatment of obesity.


272 women (mean ± SD age = 59.4 ± 6.2 years, BMI = 36.5 ± 4.8) participated in a 6-month lifestyle intervention for obesity. Body weight and problem-solving skills (as measured by the Social Problem Solving Inventory—Revised) were assessed pre- and posttreatment. The completion of self-monitoring logs during the intervention served as the marker of treatment adherence.


At posttreatment, participants lost 8.4 ± 5.8 kg, an 8.8% reduction in body weight. Changes in weight were associated with increased problem-solving skills and with higher levels of treatment adherence. Improvements in problem-solving skills partially mediated the relation between treatment adherence and weight-loss outcome. Moreover, participants with weight reductions > 10% demonstrated significantly greater improvements in problem-solving skills than those with reductions < 5%.


Improvements in problem-solving skills may enable participants to overcome barriers to adherence and thereby enhance treatment-induced weight losses.

Keywords: Obesity, Weight Loss, Problem-Solving, Adherence, Self-Monitoring

1. Introduction

Problem solving is the process by which a person works to develop adaptive solutions for difficult problems encountered in everyday life (D’Zurilla & Nezu, 1999). Studies have linked deficits in problem-solving abilities to a host of psychological conditions, including anxiety (Dugas, Gagnon, Ladouceur, & Freeston, 1998) and depression (Frye & Goodman, 2000; Marx & Schulze, 1991; Nezu, 1985). Impairments in problem-solving skills have also been associated with difficulties coping with chronic illnesses (Bodenheimer, Lorig, Holman, & Grumbach, 2002), including diabetes (Elliott, Shewchuk, Miller, & Richards, 2001), chronic pain (Kerns, Rosenberg, & Otis, 2002), and multiple sclerosis (Pakenham, 2001). Further, problem-solving therapy (PST), a cognitive-behavioral intervention focused on teaching of specific skills to improve adaptive coping, has been shown to be beneficial in multiple contexts, including smoking cessation, marital therapy, and the treatment of mood disorders (Arean et al., 1993; D’Zurilla & Nezu, 1999; Nezu & Perri, 1989; Nezu & D’Zurilla, 1989; Nezu, Nezu, & Perri, 1989).

Recent studies have demonstrated that PST may be particularly beneficial in promoting treatment adherence. From a PST perspective, adherence problems can be viewed as stemming from difficulties with motivation (e.g., ambivalence about one’s goals or participation in treatment) or with a specific skill deficit in overcoming barriers and obstacles related to adherence (e.g., limited resources or a lack of social support for change) (Nezu, Nezu, & Perri, 2006). Problems with motivation or difficulties addressing treatment barriers often exacerbate one another. For example, in the treatment of obesity, a participant’s lack of motivation to engage in the behaviors required to induce weight loss (e.g., regular exercise) may undermine his or her efforts to address barriers to behavioral change (e.g., wearing a pedometer, finding a workout partner, investigating low-cost gyms, etc). PST is designed to address both the negative motivational set and the behavioral skill deficits needed to overcome barriers to adherence (Nezu et al., 2006). Indeed, two recent studies conducted with children and adolescents have demonstrated that PST can effectively enhance adherence to treatment protocols (Kazdin & Whitley, 2003; Spirito, Boergers, Donaldson, Bishop, & Lewander, 2002).

Few studies have examined the use of PST within the context of lifestyle treatment for obesity, although PST is often used to guide clinical decision-making by interventionists (Perri, Nezu, & Viegener, 1992). For example, interventionists may utilize problem-solving techniques to guide their interactions with participants who report significant challenges. Participants may also be explicitly taught problem-solving techniques in order to address barriers to treatment adherence. However, although problem-solving techniques are frequently taught to participants in weight-management programs, few studies have examined the impact of PST on weight loss when it is used as the primary mode of intervention.

Indeed, only one investigation to date has evaluated the impact of PST on lifestyle treatment for obesity. In a study by Perri and colleagues (Perri, Nezu, McKelvey, Shermer, Renjilian, & Viegener, 2001) that focused on the weight maintenance phase of treatment, 80 obese women were randomized to receive one of three year-long extended care conditions following participation in a 5-month behavioral treatment (BT) intervention for obesity: Relapse Prevention Training (RPT), Problem-Solving Therapy (PST), or a BT only condition that involved no extended care treatment. No significant differences in weight losses were observed between participants in the RPT and BT only conditions or between participants in the RPT and PST conditions. However, results demonstrated that participants in the PST condition evidenced significantly greater weight losses as compared to participants in the BT only condition. Further, a significantly greater percentage of participants in the PST intervention achieved weight losses greater than 10% as compared to the BT only participants (35% versus 6%, respectively). PST participants also demonstrated significantly greater adherence to key behavioral weight management strategies taught during the intervention. Adherence to behavioral strategies was a partial mediator of the treatment condition effect, such that the long-term success of participants in the PST condition was partially accounted for by their better adherence to these strategies (Perri et al., 2001). Rates of attrition and attendance in the 12-month extended care conditions (RPT and PST) were equivalent, and at the final follow-up, 83%, 71%, and 66% of participants were assessed in the BT only, RPT, and PST conditions, respectively. This study suggests that problem-solving skills, as well as adherence to behavioral weight-loss strategies, are significantly associated with long-term weight loss maintenance.

1.1 Current Study

The aim of the present study was to investigate the association between problem-solving skills and weight loss outcome in the initial phase of obesity treatment. Specifically, we examined whether improvements in problem-solving abilities mediated the relation between adherence and weight loss outcome. We also examined changes in problem-solving abilities among participants who achieved differing degrees of weight loss. We hypothesized that increased problem-solving skills would mediate the relation between treatment adherence and weight loss outcome, and that participants with large weight reductions would evidence greater improvements in problem-solving abilities when compared to participants with moderate or small weight reductions.

2. Method

2.1 Participants

Participants were healthy but sedentary women (ages 50–75) from medically underserved rural areas who volunteered to take part in a study examining the effects of a lifestyle intervention for obesity (Perri et al., 2008). The highest rates of obesity in the U.S. are observed among women ages 50–69 (Flegal, Carroll, Kuczmarski, & Johnson, 1998), leading the World Health Organization (WHO) to emphasize the need for weight loss and physical activity interventions designed for obese women in this age range (WHO, 1998). Rural women appear to be at particular risk for obesity and associated health consequences. Studies demonstrate that women over 50 living in rural areas experience higher rates of obesity, depression, and heart disease as compared to their urban counterparts (Blazer, Kessler, McGonagle, & Swartz, 1994; Eberhardt, Ingram, & Makuc, 2001).

Participants were recruited via media articles, direct mailings, newspaper announcements, and presentations to community groups. Eligibility criteria included a body mass index (BMI) of 30 kg/m2 and above, with weight less than 159 kg (350 lbs). Potential participants were excluded if their medical history, clinical examination, or laboratory results revealed underlying diseases likely to limit lifespan and/or increase risk of intervention. In addition, prospective participants with medical conditions or behavioral patterns likely to interfere with the trial were excluded. Potential participants were also deemed ineligible based on metabolic values out of range (fasting blood glucose > 125 mg/dl if not known to be diabetic, fasting serum triglycerides > 400 mg/dl, and resting blood pressure > 140/90 mmHg) and use of certain medications (e.g., antipsychotic agents, monoamine oxidase inhibitors, chemotherapeutic drugs, or current use of prescription weight-loss drugs).

Exclusion criteria also included weight loss > 10 pounds in past 6 months, major psychiatric disorder, and excessive alcohol intake. Excessive alcohol intake was defined as the consumption of 6 or more drinks per day and assessed by participant self-report on a Personal Habits questionnaire. Participants who reported consumption of 1 or more drinks per day were interviewed by the study medical director for further assessment and potential referral for treatment. The presence of major psychiatric disorder was assessed during the telephone screening process and at the in-person medical visits. If participants identified themselves as experiencing symptoms of psychiatric disorder (e.g., depression, anxiety, bipolar disorder, etc.) or reported use of psychiatric medications, a licensed clinical psychologist interviewed the participant to determine whether they met criteria for a major psychiatric disorder and referred them to counseling if necessary. The primary goal of these exclusion criteria was to ensure participant safety, and treatment for either excessive alcohol intake or psychiatric disorder was always considered a higher priority than participation in the weight loss intervention.

2.2 Weight-loss Intervention

Participants took part in a 6-month group-based lifestyle intervention for obesity. Participants met for 24 weekly 90-minute sessions led by interventionists with a bachelor’s or master’s degree in nutrition, psychology or exercise science. The theoretical basis for the lifestyle intervention is rooted in cognitive-behavioral models, specifically social cognitive theory (SCT). SCT asserts that both personal factors (e.g., cognitions, emotions) and factors in the social and physical environment have the potential to influence behavior, and behavior in turn can have a reciprocal impact on personal and environmental factors. There are four sets of constructs that are thought to impact the initiation and maintenance of behavior change, including (1) health knowledge, (2) beliefs regarding self-efficacy and outcome expectancies, (3) self-regulatory skill, and (4) barriers to change. Lifestyle interventions target these key constructs by (1) increasing health knowledge related to diet, physical activity, weight loss, and disease; (2) enhancing self-efficacy and positive outcome expectancies through facilitating successful experiences in altering eating and exercise behavior; (3) enhancing self-regulatory skills through the use of goal-setting, written self-monitoring, self-reinforcement, stimulus control, and cognitive restructuring strategies; (4) by overcoming barriers to change through the use of problem-solving techniques.

In conjunction with a SCT perspective, each intervention session included a weekly weigh-in; a review of participants’ progress in implementing the strategies introduced in the previous session (a portion of the group referred to as “check-in”); skill training related to self-management skills, nutrition, or exercise; setting of the next week’s goals; and feedback and encouragement from the group leader and group members. Problem-solving therapy (PST) was used in the current study as part of a strategic intervention aimed at developing a personalized plan for each group member to enhance adherence to behaviors associated with successful weight loss (further described below).

Participants were asked to engage in daily self-monitoring of food intake and physical activity through the use of daily logs to record progress toward goals. Dietary goals included a reduction in energy intake by 500–1000 kcal/day. Physical activity goals included the addition of >3000 steps per day above baseline, or an increase of 30 min/day of walking, 6 days/week. Although the intervention was delivered in a group-based format, interventionists worked individually with each participant to develop weekly goals, monitor progress, and problem solve any barriers to adherence that were identified; this individual work typically took place during the check-in and goal-setting portions of group. Interventionists occasionally met individually with participants outside of the group for brief periods if they required additional support with regards to a particular skill.

Participants were compensated $5 at each group session to offset the cost of travel to the intervention site, and received $50 for completing the 6-month medical assessment. Participants were provided with pedometers, calorie-counting books, food scales, measuring cups, calculators and food logs at the start of the intervention. No incentives designed specifically to enhance attendance at intervention sessions were offered.

2.2.1 Use of Problem-Solving Therapy in the Intervention

The theoretical and practical framework for the intervention was based on PST, originally developed by D’Zurilla and Goldfried (1971) and rooted in both cognitive and behavioral theory. Specifically, the 5-step problem-solving model was utilized and consisted of the following: Problem Orientation (developing a positive mindset), Problem Definition (defining the problem in a concrete way and framing it in a way that allows for a solution), Generation of Alternatives (brainstorming to identify the maximum number of solutions), Decision Making (evaluating all possible solutions in order to identify the most effective and feasible option), and Solution Implementation and Verification (carrying out the solution and evaluating its effectiveness).

The PST model was employed both as a clinical decision-making tool for group leaders to guide their approach as well as a technique taught to participants to enhance their coping skills and address barriers to adherence. For example, goal setting was considered a vital treatment component in the current study. In the course of setting weekly goals, participants reported any anticipated obstacles and were provided with the opportunity to strategize about potential solutions with their interventionist. The interventionist would revisit the issue the following week and evaluate the effectiveness of the chosen solution (and problem solve again if necessary). Problem-solving techniques were thus used to develop and tailor an individualized action plan for each participant to facilitate adherence to key behavioral aspects of the intervention. In addition, participants received group-based instruction (including written materials) detailing the problem-solving process. As a result of their exposure to the problem-solving process, it was expected that participants would improve their problem orientation (i.e., develop a positive mindset when approaching problems) as well as their ability to engage in individual steps of the problem-solving process (defining the problem, generating creative solutions, making decisions, and successfully implementing solutions). Ideally, participants’ confidence in their ability to solve problems should be enhanced, and this skill development should generalize to problems beyond those associated with weight loss to others encountered in everyday life.

2.3 Measures

2.3.1 Social Problem Solving Inventory-Revised

Problem-solving abilities were assessed pre- and posttreatment with the Social Problem Solving Inventory-Revised (SPSI-R; Maydeu-Olivares & D’Zurilla, 1996). The SPSI-R is a 52 item, self-report measure that asks participants to rate statements on a 5-point Likert scale. The SPSI-R was used to assess changes in problem-solving abilities because its subscales are directly related to the 5-step problem-solving process taught to participants during the intervention. The SPSI-R is based on the five-component model of social problem solving and includes the following subscales: Positive Problem Orientation, Negative Problem Orientation, Rational Problem Solving, Impulsivity/Carelessness Style, and Avoidance Style. Positive Problem Orientation and Negative Problem Orientation were used to measure problem orientation (the intervention’s success at helping participants develop a positive mindset when approaching problems), while problem-solving style (Rational, Impulsive/Careless, Avoidant), was assessed on the three remaining scales. The Rational Problem Solving subscale is comprised of 4 composites representing steps of the problem-solving process (Problem Definition and Formulation, Generation of Alternative Solutions, Decision Making, and Solution Implementation and Verification). The scores are inter-correlated such that a positive problem orientation is most highly correlated with a rational problem solving style (r = .6 to.7). A negative problem orientation is most highly correlated with the dysfunctional problem solving styles of impulsivity/carelessness (r = .5 to.6) and avoidance (r = .6 to.7). Scale scores were used to create a composite score, Social Problem Solving Summary Score. The SPSI-R has sound psychometric properties, with an internal consistency of.76 to.92 and test-retest reliability of.72 to.88 (D’Zurilla, Nezu, & Maydeu-Olivares, 2002). The SPSI-R has been shown to possess the sensitivity necessary to assess the effects of problem-solving skills training in clinical settings (Nezu, Nezu, Friedman, Faddis, & Houts, 1998). Further, the relations between SPSI-R subscales have been shown to be stable across different populations, varying in both age and psychiatric status (Maydeu-Olivares & D’Zurilla, 1996).

2.3.2. Self-Monitoring Logs

Self-monitoring is supported in obesity research as an important predictor of adherence and treatment outcomes (Sarwer & Wadden, 1999); thus, completion of self-monitoring records was used as a proxy of treatment adherence in the present study. Self-monitoring records that included all consumed foods and had total daily caloric intake calculated were counted as a completed record toward adherence. Self-monitoring was measured over the 24 weeks of the intervention, and each participant had the opportunity to complete a maximum total of 161 records.

2.3.3. Weight Change

Each participant’s body weight was measured at pre- and posttreatment to the nearest 0.1 kilogram using a calibrated and certified balance beam scale. Weights were used to calculate net BMI and percent body weight change from pre- to posttreatment for each participant.

3. Statistical Analyses

Pearson product-moment correlations were used to investigate the association between change from baseline to six months in problem solving (SPSI summary scores), weight change (measured by change in BMI) and treatment adherence (number of records completed). In addition, a semi-partial correlation was used to examine the unique effect of change in problem solving on weight loss after controlling for baseline SPSI scores. Pearson product-moment correlations were also used to assess the association between subscales of the SPSI and change in weight between baseline and six months.

The mediation by problem solving of the association between adherence to the program, measured by the number of food records completed by each participant, and weight loss was tested using regression analyses and Baron and Kenny’s (1986) four-step method. Specifically, we examined whether increases in problem solving contributed to a portion of weight loss associated with program adherence. A linear regression was used to establish the relation between adherence and weight loss and between adherence and problem solving. Next, a hierarchical regression was used to investigate the association between adherence and weight change after controlling for changes in problem solving. Finally, a Sobel test was used to test whether the mediation was significant.

We also investigated whether changes in problem-solving scores varied depending on the magnitude of body weight lost. To investigate this, participants were divided into three groups. The first group contained participants who achieved large weight losses (10% or greater), the second group contained participants who achieved moderate weight losses (between 5 and 9.9%), and the third group achieved small weight changes (less than 5%, maintained their weight, or gained weight). A one-way ANOVA, followed by Bonferroni post-hoc tests, was used to examine the mean differences in problem solving for these three groups.

4. Results

4.1. Demographics

Participants were 298 women, ages 50 to 75 years, who were taking part in a six-month intervention that occurred prior to randomization for a clinical trial. Only women with recorded weights at baseline and at six months, and who completed the Social Problem Solving Inventory-Revised (SPSI-R) at each of these assessments were included in the present study (N = 272). At the start of the program, participants weighed an average of 95.6 kg ± 14.7 (BMI = 36.5 ± 4.8). A complete listing of baseline demographic characteristics of participants is included in Table 1.

Table 1
Characteristics of Study Participants at Baseline

4.2. Relation Between Problem-Solving Skills and Weight-Loss Outcome

Baseline problem solving skills were not significantly associated with weight change at 6 months (p = .229). A significant negative association was found between pre- to posttreatment changes in problem solving and body weight (r = −.23, p <.001). Specifically, larger increases in problem solving from pre- to posttreatment were related to larger weight losses during this time. Examination of the SPSI-R scales indicated that increases in problem orientation (r = −.15, p <.05) and rational problem solving (r = −.15, p <.05) were associated with weight loss, whereas increases in negative problem orientation (r = .19, p <.01) and impulsivity/carelessness style (r = .16, p <.01) were associated with weight gain.

4.3. Problem-Solving Skills as a Mediator of Adherence and Weight-Loss Outcome

A significant positive association was demonstrated between adherence and weight change (r = .47, p <.001), such that greater adherence to the program was related to larger weight losses. Additionally, a significant positive association between adherence and problem solving (r = .20, p <.01) was observed; participants with higher adherence demonstrated larger increases in problem solving from pre- to posttreatment. After controlling for adherence, the previously demonstrated association between problem solving and weight change remained significant (Fchange(1,269) = 7.14, p = .008), with increases in problem-solving scores resulting in larger weight losses, such that a 10% increase in problem solving was related to a .32 ± .01 reduction in BMI. Finally, after controlling for problem solving, the effect of adherence on weight change was significantly decreased (Sobel’s z = −2.13, p <.05). Thus, change in problem solving was a partial mediator of the relation between adherence and weight loss at six months.

4.4. Differences in Problem-Solving Skills by Weight-Loss Category

Change in problem-solving scores by category of percent change in body weight is displayed in Table 2. A one-way ANOVA found significant mean differences in problem-solving scores for participants who experienced small, moderate, and large weight losses (F(2,271) = 6.4, p < .01). Bonferroni adjusted post-hoc tests found that there were significant differences in problem-solving scores between the large and small weight loss groups (p < .01). There were not, however, significant differences in problem solving between the moderate and small weight loss groups (p = .14) or between the moderate and large weight loss groups (p = .28). That is, participants with large weight losses showed significantly larger increases in problem-solving scores than participants with small weight losses.

Table 2
Change in Problem-Solving Scores by Weight-Loss Category

Of the 79 participants in the small weight loss group, 10 gained weight during the intervention. These 10 participants were not significantly different from other participants in terms of baseline weight (p = .17), BMI (p = .47), income (p = .74), age (p = .08), ethnicity (p = .33), marital status (p = .48), education (p = .26), or SPSI subscale scores (all ps >.05).

5. Discussion

The results in this study showed that improvements in problem-solving skills served as a partial mediator of the relation between treatment adherence and weight change following lifestyle treatment for obesity. Improvements in problem-solving skills were significantly associated with weight change, and larger weight reductions were linked to higher levels of treatment adherence. These findings suggest that the impact of increased adherence to the intervention on weight loss was partially accounted for by improvements in problem solving skills.

Significant increases in problem-solving abilities were observed from pre- to posttreatment. There are several possible explanations for this finding. First, the interventionists modeled the use of PST for participants and guided them in the use of problem-solving techniques in response to participant-reported obstacles to treatment. Group leaders received extensive instruction in strategies to address adherence barriers, as well as the opportunity to practice techniques through group role-playing and observation. They were trained in the use of the 5-step problem solving process to address both motivational and behavioral challenges that may prevent participants from achieving their desired weight-loss goals. In addition, brief training in the problem-solving process may have increased both participants’ problem-solving skills and confidence in their ability to address obstacles to successful weight loss.

Our findings also showed that participants with weight reductions greater than or equal to 10% demonstrated significantly greater improvements in problem-solving skills (2.57±9.3) than those with weight losses less than 5% (−2.25±8.13). Thus, participants with the greatest decreases in weight also experienced significant improvements in their problem-solving skills, while participants with small weight losses actually experienced a decrease in their problem-solving scores. There are several potential explanations for this self-reported decrease in problem-solving skills. While these findings may represent actual decreases in problem-solving abilities, there is also the possibility that the participants’ assessments of their problem-solving skills may be influenced by the magnitude of their weight loss. For example, participants who lost small amounts of weight or gained weight may have characterized themselves as “poor” problem solvers. Of note, significant variation in changes in problem-solving scores was also observed over the course of the intervention. There is the possibility that these individual differences in response to problem-solving training may be partially accounted for by factors unrelated to the intervention (e.g., baseline levels of self-efficacy or depressive symptoms).

The findings in this study also demonstrated that improvements in particular problem-solving abilities (i.e., Positive Problem Orientation, and Rational Problem Solving) appear to be related to greater weight loss, while increased scores on Negative Problem Orientation and Impulsivity/Carelessness Style are related to smaller weight reductions. These results suggest that participants who exhibited a more positive outlook or orientation to problems over the course of the lifestyle intervention obtained better weight losses. Perhaps participants with improved positive problem orientation had a greater tendency to expect a positive resolution to their challenges, which may have facilitated more active utilization of specific problem-solving strategies (D’Zurilla & Nezu, 1999). Further, participants who improved their rational problem solving obtained better weight losses. It is possible that participants who improved their ability to problem solve in a deliberate, organized manner were better able to appropriately identify and employ effective solutions to their problems (D’Zurilla & Nezu, 1999). Finally, participants who reported decreased impulsivity or carelessness problem-solving strategies also exhibited greater weight losses. Participants who are less impulsive/careless may engage in problem solving in a more complete, effective manner (D’Zurilla & Nezu, 1999).

There are three potential limitations to the current study. First, as noted above, there is the possibility that participants’ assessments of their problem-solving skills may be influenced by the magnitude of their weight change, with participants characterizing themselves as either accomplished or poor problem-solvers depending on their degree of weight change during the intervention. Second, the use of completion of self-monitoring logs as the sole measure of treatment adherence may not have fully captured all the key aspects of treatment adherence. For example, some participants may have successfully utilized other self-management strategies (e.g., stimulus control, self-reinforcement) that were not specifically assessed in this study. Finally, it is important to note that participants in the study began the intervention with above-average problem solving skills, limiting the generalizability of the findings to individuals who score lower on assessments of problem-solving abilities.

In summary, this study contributes to a growing body of research which suggests that the inclusion of problem-solving training, both as a tool to guide clinical decision-making and a strategy to address barriers to treatment adherence, may enhance the efficacy of behavioral interventions for the management of obesity. As participants in the study also achieved differing degrees of improvement in problem-solving skills, it would be useful for future investigations to examine the potential predictors (e.g., demographic, psychological, and behavioral) of response to the problem-solving intervention. It may also be beneficial for future studies to explore the impact of changes in problem-solving skills on various behavioral patterns related to successful weight management, such as dietary and physical activity habits.


This research was supported by grant R18HL73326 from the National Heart, Lung and Blood Institute.


Publisher's Disclaimer: This is a PDF file of an unedited manuscript that has been accepted for publication. As a service to our customers we are providing this early version of the manuscript. The manuscript will undergo copyediting, typesetting, and review of the resulting proof before it is published in its final citable form. Please note that during the production process errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain.


  • Arean PA, Perri MG, Nezu AM, Schein RL, Christopher F, Joseph TX. Comparative effectiveness of social problem-solving therapy and reminiscence therapy as treatments for depression in older adults. Journal of Consulting and Clinical Psychology. 1993;61:1003–1010. [PubMed]
  • Baron R, Kenny D. The moderator-mediator variable distinction in social psychological research: Conceptual, strategic, and statistical considerations. Journal of Personality and Social Psychology. 1986;51:1173–1182. [PubMed]
  • Blazer DG, Kessler RC, McGonagle KA, Swartz MS. The prevalence and distribution of major depression in a national community sample: The National Comorbidity Survey. American Journal of Psychiatry. 1994;151:979–986. [PubMed]
  • Bodehnheimer T, Lorig KR, Holman H, Grunbach K. Self-management of chronic diseases in primary care. Journal of the American Medical Assocation. 2002;288:2469–2475.
  • Dugas MJ, Gagnon F, Ladouceur R, Freeston MH. Generalized anxiety disorder: A preliminary test of a conceptual model. Behaviour Research and Therapy. 1998;36:215–226. [PubMed]
  • D’Zurilla TJ, Goldfried MR. Problem solving and behavior modification. Journal of Abnormal Psychology. 1971;78:107–126. [PubMed]
  • D’Zurilla TJ, Nezu AM. Problem-solving therapy: A social competence approach to clinical intervention. 2. New York: Springer; 1999.
  • D’Zurilla TJ, Nezu AM, Maydeu-Olivares A. Manual for the social problem-solving inventory-revised. (SPSI-R) North Tonawanda, NY: Multi-Health Systems, Inc; 2002.
  • Eberhardt MS, Ingram DD, Makuc DM, et al. Health, United States, 2001. Hyattsville, MD: National Center for Health Statistics; 2001. Urban and rural health chartbook.
  • Elliot TR, Shewchuck RM, Miller DM, Richards JS. Profiles in problem-solving: Psychological well-being and distress among persons with diabetes mellitus. Journal of Clinical Psychology in Medical Settings. 2001;8:283–291.
  • Flegal KM, Carroll MD, Kuczmarski RJ, Johnson CL. Overweight and obesity in the United States: Prevalence and trends, 1960–1994. International Journal of Obesity. 1998;22:39–47. [PubMed]
  • Frye AA, Goodman SH. Which social problem-solving components buffer depression in adolescent girls? Cognitive Therapy and Research. 2000;24:637–650.
  • Kazdin AE, Whitley MK. Treatment of parental stress to enhance therapeutic change among children referred for aggressive and antisocial behavior. Journal of Consulting and Clinical Psychology. 2003;71:504–515. [PubMed]
  • Kerns RD, Rosenberg R, Otis JD. Self-appraised problem solving and pain relevant social support as predictors of the experience of chronic pain. Annals of Behavioral Medicine. 2002;24:100–105. [PubMed]
  • Marx EM, Schulze CC. Interpersonal problem-solving in depressed students. Journal of Clinical Psychology. 1991;47:361–367. [PubMed]
  • Maydeu-Olivares A, D’Zurilla TJ. A factor analytic study of the social problem solving inventory: An integration of theory and data. Cognitive Therapy and Research. 1996;20:115–133.
  • Nezu AM. Differences in psychological distress between effective and ineffective problem solvers. Journal of Counseling Psychology. 1985;32:135–138.
  • Nezu AM, D’Zurilla TJ. Social problem solving and negative affective conditions. In: Kendall PC, Watson D, editors. Anxiety and depression: Distinctive and overlapping features. San Diego, CA: Academic Press, Inc; 1989.
  • Nezu AM, Nezu CM, Friedman SH, Faddis S, Houts PS. Coping with cancer: A problem solving approach. Washington, DC: American Psychological Association; 1998.
  • Nezu AM, Nezu CM, Perri MG. Problem solving to promote treatment adherence. In: O’Donohue, Levensky, editors. Promoting Treatment Adherence: A Practical Handbook for Health Care Providers. Thousand Oaks, CA: Sage Publications; 2006.
  • Nezu AM, Nezu CM, Perri MG. Problem-solving therapy for depression. New York: Wiley; 1989.
  • Nezu AM, Perri MG. Social problem-solving therapy for unipolar depression: An initial dismantling investigation. Journal of Consulting & Clinical Psychology. 1989;57:408–413. [PubMed]
  • Pakenham KI. Coping with multiple sclerosis: Development of a measure. Psychology, Health, & Medicine. 2001;6:411–428.
  • Perri MG, Limacher MC, Durning PE, Janicke DM, Lutes LD, Bobroff LB, et al. Treatment of obesity in underserved rural settings (TOURS): A randomized trial of extended-care programs for weight management. Archives of Internal Medicine in press. [PMC free article] [PubMed]
  • Perri MG, Nezu AM, McKelvey WF, Shermer RL, Renjilian DA, Viegener BJ. Relapse prevention training and problem-solving therapy in the long-term management of obesity. Journal of Consulting and Clinical Psychology. 2001;69:722–726. [PubMed]
  • Perri MG, Nezu AM, Viegener BJ. Improving the long-term management of obesity: theory, research, and clinical guidelines. New York: Wiley; 1992.
  • Sarwer DB, Wadden TA. The treatment of obesity: What’s new, what’s recommended. Journal of Women’s Health & Gender-Based Medicine. 1999;8:483–493. [PubMed]
  • Spirito A, Boergers J, Donaldson D, Bishop D, Lewander W. An intervention trial to improve adherence to community treatment by adolescents after a suicide attempt. Journal of the American Academy of Child and Adolescent Psychiatry. 2002;41:435–442. [PubMed]
  • World Health Organization. Obesity: Preventing and managing the global epidemic. Geneva: Author; 1998. Publication No. WHO/NUT/NCD/98.1.
PubReader format: click here to try


Related citations in PubMed

See reviews...See all...

Cited by other articles in PMC

See all...


Recent Activity

Your browsing activity is empty.

Activity recording is turned off.

Turn recording back on

See more...