Abstract
Currently, 80% of adults over the age of 65 have at least one chronic disease. The Chronic Disease Self-management Program (CDSMP) focuses on increasing self-efficacy for managing chronic disease. Few studies have evaluated the effectiveness of CDSMP when offered by multiple agencies, as a collaborative effort, in community-based settings. Seven agencies delivered 108 CDSMP workshops at 81 sites from October 1, 2008, to December 31, 2010. A total of 811 participants were eligible for analysis. Participants completed surveys at baseline and week 6, the end of instruction. Controlling for agency effect and general health at baseline, the general linear model was used to assess the significance of outcomes at 6 weeks. Outcomes showing significant improvement included self-efficacy to manage disease (p = .001), self-efficacy to manage emotions (p = .026), time spent walking (p = .008), and perceived social/role activities limitations (p = .001). Findings showed that CDSMP is an effective program at improving self-efficacy, increasing physical activity, and decreasing limitations.
Introduction
It is projected that by 2050, there will be 88.5 million older adults in the United States (U.S.Census Bureau, 2010). Approximately 80% of adults age 65 or older have at least one chronic condition (National Center for Chronic Disease Prevention and Health Promotion, 2011). The most common chronic diseases and conditions among older adults include hypertension, heart disease, diabetes mellitus, cancer, arthritis, and respiratory illnesses, such as asthma, emphysema, and chronic obstructive pulmonary disease (National Center for Health Statistics, 2010). Of adults over the age of 65, 35% report having limited activity due to mobility issues, the result of chronic conditions, with arthritis and cardiovascular conditions being the most common (National Center for Health Statistics, 2010). Individuals with a single chronic disease are more likely to develop additional chronic diseases (Tucker-Seeley, Li, Sorensen, & Subramanian, 2011). The majority of older adults manage two or more chronic conditions simultaneously (Wolff, Starfield, & Anderson, 2002), and 33% of older adults managing three or more chronic conditions (Partnership for Solutions, 2004).
Chronic Disease Self-Management Program (CDSMP)
The CDSMP was developed and evaluated by Lorig, Gonzalez, and Ritter (1999) and is considered an evidence-based program. CDSMP is targeted toward older adults with at least one chronic condition, or toward their caretakers. The program was specifically designed to be applicable to chronic conditions in general and is therefore suitable for people with multiple chronic conditions. CDSMP relies on self-efficacy theory and has been proven to be effective in achieving significant long-term improvements in patient self-efficacy, health behavior, social/role limitations, health care utilization, and chronic disease symptoms in randomized control trials (Elzen, Slaets, Snijders, & Steverink, 2007; Lorig, Ritter et al., 2001, Lorig, Sobel, et al., 1999; Lorig, Ritter, & Jacquez, 2005), a translation study in Kaiser Permanente clinics (Lorig, Sobel, Ritter, Laurent, & Hobbs, 2001), and a qualitative study on participant perceptions (Dongbo, Ding, McGowan, & Fu, 2006). The 2001 study in Kaiser Permanente clinics is the most similar to the evaluation of a community-based translation of CDSMP presented here. However, this evaluation is unique in that it was undertaken by a community agency and was not part of a designed research study.
Program Theories and Goals
Improving self-efficacy is a key component and goal of CDSMP, as both baseline self-efficacy levels and changes in self-efficacy have been shown to impact a person’s future health status (Lorig, Gonzalez, & Ritter, 1999; Bandura, 1997c). Another motivator for behavior is the combination of both goal setting and self-evaluative reactions (Bandura, 1977b). CDSMP attempts to improve self-management of chronic disease by improving self-efficacy through the use of goal setting, performance mastery, modeling, and social persuasion techniques delivered through both didactic and participatory workshop sessions. Other desired outcomes of CDSMP, such as increased social activity, increased physical activity, and decreased mental stress have been shown to result in improved self-efficacy (Bonsaksen, Lerdal, & Fagermoen, 2012). It is the interaction of skills, incentives, and efficacy that determine the ability of a person to engage in successful self-management (Bandura, 1977a).
Description of the Problem
Due to the increasing older adult population and prevalence of chronic conditions, emphasis has been placed on educating individuals to self-manage their conditions (Holman & Lorig, 2000; Institute of Medicine Committee on Health Care in America, 2001). The ultimate goal of self-management is to either improve current health status or prevent further disability by controlling existing symptoms (Bell & Orpin, 2006; Creer, Holroyd, Glasgow, & Smith, 2004). The promotion of evidence-based CDSMPs to older adults, the largest segment of the population to suffer from chronic conditions, has been shown to help prevent and control disease symptoms, resulting in improved quality of life and lower health care expenditures (Chodosh et al., 2005). This is an especially critical component in reducing the burden of physician-managed care from an already overloaded medical system (Institute of Medicine Committee on Health Care in America, 2001).
Previous studies have supported the efficacy of CDSMP, but the literature is lacking in studies that provide evidence for the program’s effectiveness. Since this study focused on evaluating short-term effectiveness, the lack of a control group should not be considered a significant design limitation. As funding agencies seek out evidence-based interventions, it would be informative to know how an intervention performs outside of a controlled setting. Such an evaluation would provide a foundation for realistic outcome expectations when delivered in a community setting. In addition to funding agencies and program implementers, the program designers can use the findings of this study to inform future iterations of CDSMP and improve the expected outcomes.
In response to the large population of older adults in South Florida, the Health Foundation of South Florida (HFSF) initiated the Healthy Aging Regional Collaborative Healthy Aging Regional Collaborative (HARC) (U.S. Census Bureau, 2011). The HARC aimed to offer evidence-based health promotion programs to older adults through community agencies in South Florida. By creating a network where best practices could be shared by participating agencies and start-up costs shared, barriers to implementation were reduced. CDSMP was selected to address chronic disease.
Purpose
The purpose of this study was to evaluate the short-term effectiveness of CDSMP to increase self-efficacy regarding multiple aspects of chronic disease management, decrease perceived social activity/role limitations, and increase time spent exercising when implemented by multiple, community-based, agencies through a large-scale collaborative effort in South Florida. Given that there is limited information about translating CDSMP into practice settings by community agencies, this study evaluated program outcomes, from baseline to 6 weeks, immediately following the end of program instruction, to determine whether CDSMP can be an effective program when delivered outside of a controlled research setting. By evaluating outcomes at 6 weeks, this study provides a reference point for other translational studies of CDSMP evaluating outcomes at longer term intervals. As this was a community-based implementation effort rather than a controlled research study, long-term follow-up data were not collected and there was no control group. However, finding significant improvement in outcome measures at 6 weeks provides preliminary evidence on whether a large-scale community-based translation effort has the potential to successfully improve outcomes. Research has shown that CDSMP in this translational setting can be delivered at relatively low cost (Page & Palmer, 2013), but another required piece of information in evaluating the effectiveness of CDSMP in this setting is an evaluation of program outcomes.
It was hypothesized that at 6 weeks, program participants would show statistically significant improvements in self-efficacy to manage disease, self-efficacy to manage emotions, self-efficacy to use mental and physical techniques discussed, self-efficacy to communicate with a physician, perceived social/role activities limitations, and time spent stretching, walking, and performing other aerobic activities, while controlling for agency effect and baseline general health status. These are standard outcomes evaluated by the program developers and other studies.
Method
Setting and Participants
From October 1, 2008, through December 31, 2010, the HFSF funded seven agencies that offered 108 CDSMP workshops, taught by 94 instructors, at 81 sites throughout Broward, Miami-Dade, and Monroe Counties. Each workshop was led by two trained instructors who followed the presentation order and scripts laid out in the Leader’s Manual. The types of agencies offering CDSMP included five community service agencies serving older adults, one hospital, and one county-level elder services department. Workshops were offered in community centers, churches, nursing homes, residential clubhouses, and health clinics.
Agencies recruited participants from both their existing client base and the community through fliers and word of mouth. The priority population consisted of adults aged 55 years or older having at least one chronic disease. For the purpose of this study, participants were excluded from analysis if age was missing or under 55 (n = 271) or if a participant did not complete both a baseline and post-intervention survey (n = 545; Figure 1). This study was approved by the Institutional Review Board of Florida International University, and all participants consented to participate in analysis. Consent was not required to participate in the workshops.
Flow diagram showing participant eligibility for analysis, CDSMP. CDSMP = Chronic Disease Self-management Program.
Training and Fidelity Monitoring
Workshop instructors received a 4-day (20 hr), program-specific training and were paired with an experienced instructor for their first workshop (Stanford Patient Education Research Center, 1993). Instructors were either health care professionals or peers with experience managing a chronic disease. Due to the large number of instructors and sites, random fidelity monitoring was conducted on 25% (n = 27) of all workshops offered to identify any deviations from prescribed program delivery. A fidelity monitoring instrument was developed specifically for this study using the CDSMP Leader’s Manual (Stanford Patient Education Research Center, 1993). Fidelity monitoring included evaluation of sites, the classrooms, interaction between instructors and participants, and program content and delivery. Sites were evaluated for accessibility and respect of class time by staff. Classrooms were evaluated for conduciveness to learning (layout, noise level, temperature, etc.) as prescribed by the program developers. Interactions between instructors and participants were evaluated by the level of respect and encouragement given to participants, as well as listening skills. Program content and delivery were evaluated by following along with the instructor manual to make sure that all content was covered as prescribed.
Intervention
Two-and-a-half hour classes were offered once a week for a total duration of 6 weeks. Topics covered during the course of the workshop included cognitive symptom management techniques; managing the emotions of fear, anger, and depression; problem solving and decision making; exercise techniques; communication skills; and nutrition. These topics were discussed at a breadth that is beneficial for both those with and without previous exposure to the topics. At the end of each workshop, participants created an action plan with a specific goal to be accomplished before the next workshop session. Using didactic lectures, participatory brainstorming, goal setting, and role-play, participants were taught skills to problem solve, manage common disease symptoms, utilize available resources, and to think critically (Lorig et al., 1999). By providing breaks, reducing distractions, including a text for participants to read along with, using peer facilitators, encouraging group discussions, and providing social interaction, CDSMP workshops incorporate techniques that have been shown to be beneficial for the older adult learner (du Plessis, Anstey, & Schlumpp, 2011).
Data Collection
Prior to the start of the first session, all participants completed demographic and baseline surveys. At the end of the final session, at 6 weeks, participants completed an immediate post-intervention survey. Surveys were administered by workshop instructors, and agency staff entered participant data into an online database. Data collection forms were then mailed to an evaluation team hired by the HARC for data entry verification.
Measures
This study used measures consistent with other CDSMP evaluations to allow for comparison (Lorig, Ritter, et al., 2001; Lorig et al., 2001, 1999, 2005). In an effort to reduce the burden of data collection on program staff, only a key number of outcome measures were included. These measures were selected since they are represent the main outcome targets of the program and are of interest to the funding agency. Outcome measures included health behavior and self-efficacy. Examples of questions and results of reliability, validity, and correlation can be found in Outcome Measures for Health Education and Other Health Care Interventions (Lorig et al., 1996).
Health Behavior Outcomes
Health behaviors were evaluated using measures of exercise frequency and perceived level of interference in social and daily activities by chronic disease symptoms. A single-item question was used to evaluate time spent performing stretching or strengthening exercises. Two measures were used to assess the amount of time spent walking and performing other aerobic exercises. All measures for stretching/strengthening and aerobic exercises used a Likert-type response scale (0 = none, 5 = more than 3 hr/week). The measure for perceived social/role activities limitations included 4 items with a Likert-type response scale (0 = almost totally, 4 = not at all). Participants were required to answer at least 3 of the 4 items to be included in analysis. Cronbach’s α for this measure was .92. The score for the scale was taken as the average across all answered items.
Self-Efficacy Outcomes
Self-efficacy was evaluated by measuring levels of confidence across several aspects of disease management including managing disease, managing emotions, communicating with a physician, and using techniques covered by the program using a Cantril ladder response scale (1 = not at all confident, 10 = totally confident). Self-efficacy to manage disease was calculated using a 3-item scale. The 3 items asked participants to rate their self-efficacy to keep health problems, discomfort, and fatigue from interfering with daily activities. Participants were required to answer all 3 items to be considered for analysis, resulting in 75 participants being excluded. Cronbach’s α for this scale was .91. Self-efficacy to manage emotions, communicate with a physician, and use techniques learned in class were each measured using the same metric. Self-efficacy to manage emotions and self-efficacy to communicate with a physician were adapted from previously validated measures (Lorig et al., 1996). The question to measure self-efficacy to use techniques learned in class was developed specifically for this study.
Demographics and Health Status Measures at Baseline
Demographic and health status measures at baseline were collected to describe the study sample and evaluated for use as controls in analysis. Each participant was asked to provide information on gender, age, race/ethnicity, income level, highest education level, marital status, disability status, household number, and county of residence in South Florida. Self-rated health was measured using a single-item scale adopted from The National Health Interview Survey (National Center for Health Statistics, 1991). Participants were asked to select one of the following: poor, fair, good, very good, or excellent. Participants were also asked to rate their level of pain, fatigue, shortness of breath, and frustration in the previous 2 weeks, the number of days, out of the past 30, that their physical and mental health was “not good” and the number of days that their health hindered their usual activities (Lorig et al., 1996). A 3-item scale was used to assess the communication between participants and their physicians. The number of visits to physicians, emergency departments, hospitalizations, and nights spent in a hospital, during the past 6 months were used to evaluate health care utilization.
Analysis
Participant data for the period October 1, 2008, to December 31, 2010, were extracted from an online database. All analyses were performed using Statistical Package for the Social Sciences 17.0 for Windows. Data were cleaned of outliers and values outside possible response limits. One-way analysis of variance was used to determine if outcome differences existed based on the demographic characteristics and baseline measures. Bonferroni method was used to determine if significant differences existed for multiple comparisons. Significant differences were observed for delivering agency and general health at baseline. Because the general linear model controls for multiple covariates simultaneously (McCullagh & Nelder, 1989), it was used to assess changes in outcome measures (self-efficacy, health behaviors, and social/role activities) at 6 weeks, while controlling for delivering agency (Localio, Berlin, Ten Have, & Kimmel, 2001) and general health at baseline (Satariano, 2006).
Results
Between October 1, 2008, and December 31, 2010, 1,356 participants, aged at least 55 years, attended at least one session of CDSMP and provided baseline data. From these participants, 811 (59.8%) completed both the baseline survey and the last session survey at week 6 (Figure 1). All participants having both baseline and last session surveys are included in the main analysis (Table 1). No significant differences in demographic and baseline characteristics were observed between participants included and excluded from analysis.
Change in Outcomes From Baseline to 6 Weeks for All Attendance, N = 811.
Note. p Value statistic from the general linear model.
Demographics, Baseline Health, and Health Care Utilization
Demographic, baseline health, and health care utilization information is presented in Table 2. Participants were, on average, 74 years of age. The majority of participants were female (81%), living in Broward County (65%), were single/not partnered (56%), and lived with others (52%). Forty seven percent were White, 37% reported an income of less than US$15,000, and 27% had a high school education level. Participants attended an average of 5.00 (±1.33) sessions of six and had an average of two chronic conditions, with 20.2% reporting three or more.
Baseline Demographic and Health Characteristics for CDSMP Participants.
Note. CDSMP = Chronic Disease Self-management Program; SD = standard deviation. Percentages may not add up to 100% due to missing data.
Study Outcomes
Results showed statistically significant improvements in four of the eight health behavior measures: self-efficacy to manage disease (Δ = 1.12, standard deviation [SD] = 2.41, p = .001), self-efficacy to manage emotions (Δ = 1.30, SD = 2.95, p = .026), social/role activity limitation (Δ = 0.19, SD = 1.09, p = .001), and time spent walking (Δ = 0.57, SD = 1.31, p = .008). No significant differences were observed between baseline and 6 weeks for self-efficacy to communicate with a physician (Δ = 0.88, SD = 2.56, p = .186), self-efficacy to use mental and physical techniques to manage symptoms (Δ = 1.52, SD = 2.91, p = .487), time spent performing stretching/strengthening activities (Δ = 0.53, SD = 1.43, p = .426,) and time spent performing other aerobic activities (Δ = 0.25, SD = 1.33, p = .860; Table 1). No significant differences in outcomes within demographic categories (e.g., between age groups) were found using Bonferroni corrections. The amount of missing data was different for each outcome and varied between 5.3% and 28.7%.
Discussion
This purpose of this study was to test the hypotheses that statistically significant improvements would be observed for measures of self-efficacy, health behavior, and perceived social activity/role limitations between baseline and week 6, the end of program instruction. Significant improvements were observed for perceived social/role activities limitations, self-efficacy to manage disease, self-efficacy to manage emotions, and time spent walking.
Chronic disease can greatly affect quality of life by limiting daily activities (Centers for Disease Control and Prevention & National Center for Health Statistics, 2007). In this study, statistically significant improvements were observed in social/role activities limitations by 6.7% (p = .001) and support findings from previous studies showing a 3.9% increase over baseline at 6 months (Lorig et al., 1999) and a 10.0% improvement over baseline at 12 months (Lorig et al., 2001). A meta-analysis that compared interventions targeting social limitation in older adults found that programs offered in a group format with participant interaction, as CDSMP does, were most effective (Dickens, Richards, Greaves, & Campbell, 2011). The larger increase over baseline observed in this study, compared to other studies evaluating CDSMP outcomes at longer intervals, was expected as participants had just completed the intervention, which itself requires social interaction. Maintaining social interaction is important, as it has been shown to reduce the risk of disability, reduce depression, and act as a protective effect against cognitive decline (Fratiglioni, Paillard-Borg, & Winblad, 2004; Mendes de Leon, Glass, & Berkman, 2003). Future research should investigate at what rate gains achieved in the short-term decline over the long term.
The promotion of self-efficacy is often used in self-management programs due to its established success in influencing behavior (Bandura, 1997c; Lorig & Holman, 2003). Participants’ self-efficacy to manage disease showed a significant increase of 16.4% (p = .001) between baseline and week 6. This finding of a 16.4% increase over baseline shows a much larger difference when compared to previous research by Farrell, Wicks, and Martin (2004), which also found a statistically significant increase among 48 participants, also at 6 weeks, but of only 5.1% (Δ = .31, p = .10). This difference in magnitude could be due to a factor present in the smaller sample size in the study by Farrell et al. that would have been muted in a larger sample. This study’s findings support a study by Lorig and colleagues (2001) found significant, positive improvements over baseline at 1 year and 2 years for self-efficacy to manage disease. Self-efficacy to manage emotions also showed statistically significant improvements of 19.5% at week 6 (p = .026). No comparisons exist for this general measure, as it was developed specifically for this study. Studies have evaluated the role of self-efficacy in managing specific emotions of anger, fear, and embarrassment among populations, but research design and study populations are not comparable here.
Improved patient self-efficacy translates into improvement in health behavior, chronic disease outcomes, and ultimately quality of life (Kennedy et al., 2007; Lorig et al., 2001, 1999). Improvements in self-efficacy suggest that participants in CDSMP are more likely to try new health behaviors and maintain or increase effort of existing health behaviors, resulting in an overall improvement in chronic disease self-management. In this study, significant improvement was found in physical activity for time spent walking (p = .008). With an average post-intervention survey response of 2.36 of five, program participants reported walking slightly more than the Likert response where 2 = 30–60 min per week. For older adults without physical limitations, the recommended minimum amount of moderate physical activity is 2.5 hr each week (Centers for Disease Control and Prevention, 2011). The increase in participant activity levels shows that program participants are taking action in pursuing a recommended health promotion activity.
Working together, as part of the HARC, agencies offering CDSMP were able to call on shared resources, previous experience in implementation, and best practices. Agencies participated in monthly telephone calls with an HARC director to report on their progress, voice concerns, and seek guidance. The HARC provided infrastructure for capacity building and quality improvement of programs in the community. While not evaluated in this study, future research could investigate the role collaboration played in ease of implementation.
Fidelity monitoring of classes found a high adherence rate for program content and delivery. In all observations, all prescribed content was delivered. The most often observed issue was the presence of distractions in the classroom setting, since many were conducted in common areas. Distractions did not interrupt class instruction such that delivery of program content was affected. Maintaining program fidelity is essential to the continued success of evidence-based programs.
The study had limitations. The single-group design can present a number of threats to internal validity and limits the ability to evaluate program efficacy. Since participants were recruited from sites that hold captive populations (nursing homes and day care centers) and sites with a standing client base (activity centers and health care clinics), the study population may not be representative the general older adult population living in the community. Study participants were also self-selected, showing a desire to learn about chronic disease management. This eagerness to learn may have influenced the outcomes of the study and can also bias the makeup of the sample, threatening both external and internal validity, by overrepresenting members of the population. Self-report and recall biases may mean the information provided by participants could be incorrect as it was not verified. In addition, a number of fields had missing data, most likely a result of the program not being implemented in a controlled setting where the completeness of participant responses is more closely monitored. A number of participants refused to provide certain demographic variables, with the most common reasons being that they felt it was too personal or that the information had already been provided at the same site, for a different program. Additionally, loss to follow-up contributed to missing data. Program staff made a single attempt to contact participants not present at the last session to complete their post-intervention survey. No significant differences were observed in demographic and baseline factors between participants who completed and those lost to follow-up. Instructors were present in the room as participants completed the forms, providing assistance as necessary. This may have caused a halo effect. As mentioned previously, 6 weeks may be too short a time period to evaluate the full impact the program has on measured outcomes. The large amount of item nonresponse and participants excluded due to missing either a baseline or post-intervention survey can impact the results. However, no statistical differences in demographic and baseline characteristics were observed between these groups. A study to evaluate long-term outcomes is currently being conducted.
Even with these limitations, the study had strengths. The use of an evidence-based program establishes a correlation between program participation and the outcomes of interest and shows the program to be efficacious. By using previously validated measures in this study, we are able to increase measurement accuracy. Since there was a heterogeneous mix of agencies offering the program, results are likely to be more representative of those expected when CDSMP is translated in other community-based settings. The encouraging results on intermediate outcomes suggest that an evaluation of long-term outcomes among program participants is warranted.
Conclusion
Overall, findings from this investigation show that CDSMP, when implemented through a community-based, collaborative effort, leads to significant improvements for participants between baseline and week 6 in the areas of self-efficacy, perceived social/role activity limitations, and physical activity. Previous studies have shown that similar health behavior changes, when sustained, continue to positively impact health and reduce utilization of health care services (Clark et al., 2000; Wagner et al., 2001). Based on the results of clinical trials of CDSMP, the successful implementation of the program in South Florida can be expected to improve quality of life for older adult residents (Lorig et al., 2001). While all outcomes showed improvements over baseline, a number were found to be nonsignificant. This may be the result of 6 weeks being too short a time period to evaluate the outcomes properly or may identify the areas of needed improvement in program design to accommodate delivery in an uncontrolled setting. Additionally, knowing the status of program participants at the end of instruction at 6 weeks can provide a baseline for comparison with assessments at future points in time. While having limitations, the results of this study are representative of what can be expected in future community-based translations of CDSMP. Further research should address long-term maintenance and rate of decline of improvements among program participants in South Florida, as well as the role of the Collaborative in the intervention’s success.
Footnotes
Acknowledgments
The authors would like to extend their appreciation to the member agencies that comprise the Healthy Aging Regional Collaborative. The authors would also like to thank Anamica Batra for her role in data management.
Declaration of Conflicting Interests
The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.
Funding
The author(s) disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: This study was funded as part of the Healthy Aging Regional Collaborative through the Health Foundation of South Florida.