A randomized clinical trial of a wellness intervention for women with multiple sclerosis

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ARTICLES

A Randomized Clinical Trial of a Wellness Intervention for Women With Multiple Sclerosis Alexa K. Stuifbergen, PhD, RN, FAAN, Heather Becker, PhD, Shelley Blozis, PhD, Gayle Timmerman, PhD, RN, Vicki Kullberg, MA ABSTRACT. Stuifbergen AK, Becker H, Blozis S, Timmerman G, Kullberg V. A randomized clinical trial of a wellness intervention for women with multiple sclerosis. Arch Phys Med Rehabil 2003;84:467-76. Objective: To examine the effects of a wellness intervention program for women with multiple sclerosis (MS) on health behaviors and quality of life (QOL). Design: Randomized clinical trial. Setting: Community setting in the southwestern United States. Participants: Convenience sample of 113 women with physician-confirmed MS (mean age, 45.79y). Interventions: The 2-phase intervention program included lifestyle-change classes for 8 weeks, then telephone follow-up for 3 months. Participants were followed over an 8-month period. Main Outcome Measures: A series of self-report instruments to measure barriers, resources, self-efficacy for health behaviors, health promotion behaviors, and health-related QOL were completed at baseline, 2 months (after the classes), 5 months (after telephone follow-up), and at 8 months. Principal outcomes measures were health-promoting behaviors (scores on the Health Promoting Lifestyle Profile II) and QOL (scores on the Medical Outcomes Study 36-Item Short-Form Health Survey [SF-36] scales). Results: Hierarchical linear modeling techniques revealed a statistically significant group by time effect for self-efficacy for health behaviors, health-promoting behaviors, and the mental health and pain scales of the SF-36. Conclusion: These data provide initial support for the positive effects of wellness interventions to improve health behaviors and selected dimensions of QOL for women with MS. Key Words: Health behaviors; Multiple sclerosis; Quality of life; Rehabilitation; Wellness Programs; Women. © 2003 by the American Congress of Rehabilitation Medicine and the American Academy of Physical Medicine and Rehabilitation ERSONS WITH MULTIPLE SCLEROSIS (MS) encounter many stresses and challenges in living with a chronic P neurologic disease whose cause is unknown. Although the

From the University of Texas at Austin School of Nursing, Austin, TX (Stuifbergen, Becker, Timmerman, Kullberg); and University of California, Davis, CA (Blozis). Supported in part by the National Center for Medical Rehabilitation Research, National Institute of Child Health and Human Development, Office for Research on Women’s Health, National Institutes of Health (grant no. R01HD35047). No commercial party having a direct financial interest in the results of the research supporting this article has or will confer a benefit upon the authors or upon any organization with which the authors are associated. Reprint requests to Alexa Stuifbergen, PhD, RN, FAAN, University of Texas at Austin, Sch of Nursing, 1700 Red River, Austin, TX 78701, e-mail: [email protected]. 0003-9993/03/8404-7339$30.00/0 doi:10.1053/apmr.2003.50028

prognosis for MS is uncertain, it nearly always results in some degree of functional disability.1,2 Until the last decade, people with MS had limited options for treatment or rehabilitation. Once diagnosed as having MS, patients were sent home after symptomatic treatment and often advised not to overdo. Restrictions in their social and physical activities often led to isolation and economic, physical, and psychologic declines even before the disease progressed to result in impairment and disability. The outlook for persons with MS has become more promising with the introduction of disease-modifying agents that substantially reduce the risk of exacerbations, slow the progression of the disability, and reduce the disease’s neuroanatomic burden as measured by magnetic resonance imaging.2 Concurrently, many persons with MS have sought to reestablish and/or to maintain control over their lives and to sustain their quality of life (QOL) by practicing health-promoting behaviors. In fact, recent evidence3-6 suggests that several health-promoting behaviors—notably physical activity and stress management—may have a positive effect on disease activity, functional status, mental and physical health, and overall QOL. Consequently, many MS clinics, Multiple Sclerosis Society chapters, and other self-help groups are launching wellness programs in response to both consumer and provider interest. Although these developments are encouraging, few of the wellness programs are based on sound theoretical or empirical evidence. In addition, little evidence exists on how effective these interventions are at improving either the proximate (health-promoting behaviors) or the distant outcomes (health, QOL). This is not unusual for wellness programs. Watt et al7 conducted an extensive review of the scientific evidence for the association between wellness programs and improvements in QOL. A MEDLINE search yielded 1082 relevant references to studies published between 1980 and 1996. However, only 11 of the studies met all of the inclusion criteria of Watt,7 that is, the study reported a randomized clinical trial (RCT) or prospective study, measured outcomes, and did not take place in the workplace or include patients with human immunodeficiency virus or cancer. All 11 studies did report some positive effects of wellness-oriented interventions. However, the content of the interventions and the outcomes measured were highly variable, leading Watt to conclude that the evidence for wellness interventions is inconclusive.7 MS is among several chronic diseases with an autoimmune component that predominates in women. Of the 350,000 patients with confirmed MS currently in the United States, it is estimated that two thirds are women.1,8,9 Unfortunately, most studies of chronic illness and disability have been gender neutral despite existing data that suggests that women with chronic disabling conditions such as MS often experience different, and sometimes more difficult, life courses than their male counterparts.10 For example, compared with men with disabilities, women with disabilities are less likely to be employed, are more likely to live in poverty, and are more likely Arch Phys Med Rehabil Vol 84, April 2003

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WELLNESS INTERVENTION FOR WOMEN WITH MS, Stuifbergen

Fig 1. Conceptual model for intervention and operational measures. From Stuifbergen, A, Becker, H, Rogers, S, Timmerman, G, & Kullberg, V. (1984). Promoting wellness for women with multiple sclerosis. Journal of Neuroscience Nursing, 31, 74. © 1999 by the American Association of Neuroscience Nurses. Reprinted with permission.13

to have a severe disability.11 Specifically, women with MS are more likely to have greater activity limitations and to need more assistance with activities of daily living than are men with MS.9 Overall, women spend twice as many years disabled before death than do their male counterparts.12 These data suggest that women with MS and other chronic disabling conditions may face unique demands as they struggle to fulfill multiple roles that are critical to their QOL. As women, they must care not only for themselves but also for other family members. Consequently, their need for interventions to develop skills to promote their own health within the confines of limited time, energy, and mobility may be accentuated. This study tested a theoretically and empirically based intervention to promote the health and well-being of women with MS. The development and specific components of the Wellness Program for Women with MS have been described elsewhere13 and are briefly summarized here. The intervention is based on a conceptual model (fig 1) that integrates concepts from the health belief model,14 the Pender model of health promotion,15 and self-efficacy theory.16-18 The model proposes that a combination of barriers, resources, and specific self-efficacy for health behaviors influence the frequency of health-promoting behaviors. Consequently, it is assumed that an intervention that focuses on the development of knowledge and skills that will reduce barriers and enhance resources and self-efficacy will result in greater participation in health-promoting behaviors and a more positive QOL.13 The design and content of the intervention were guided by data from a series of preliminary studies. These included 2 quantitative studies with persons (N⫽252) with different disabilities,19,20 4 quantitative studies that included more than 1000 persons with MS,4,21-23 and 2 qualitative studies that included in-depth interviews with 33 persons with MS.24,25 Participants in all the studies were interested in health-promoting behaviors, and most had positive definitions of health that generally focused on being able to function well, rather than on the presence or absence of illness or disability. Findings clearly identified the need for adapting health-promoting behaviors to the context of the disabling condition. Women valued their families highly and were most interested in behaviors that they could incorporate into their family activities and lifestyles. Findings suggested that interventions that address self-perArch Phys Med Rehabil Vol 84, April 2003

ceived barriers to health promotion and serve to build participants’ sense of mastery of their health behaviors may be more effective than interventions that focus only on providing information about good health practices.13,18,20 Our specific aim was to determine the efficacy of the wellness intervention on self-efficacy, resources, barriers, healthpromoting behaviors, and QOL. Three specific hypotheses were proposed: (1) women with MS who participate in the wellness program intervention will report significantly greater increases in specific self-efficacy and resources and a reduction in perceived barriers postintervention than women with MS in a control group, (2) women with MS participating in this wellness program intervention will report significantly greater frequency of health behaviors postintervention than women with MS in a control group, and (3) women with MS participating in the program will report significantly greater improvements in QOL (physical functioning, mental health, emotional and physical role–related functioning, pain, vitality, general health) postintervention than women with MS in the control group. The effects of the intervention on outcome variables were assessed over an 8-month period, with measurements at baseline, at 2 months (immediately after the educational/skillbuilding component), at 5 months (after 3mo of telephone support), and at 8 months. METHODS Participant Recruitment After the study was approved by our institutional review board, several methods were used to recruit potential participants for the RCT. These included publicizing the study in MS chapter newsletters, posting fliers about the study in neurologists’ offices, distributing recruitment brochures at support groups and at an MS adaptive fitness day, and recruitment mailings to former participants in a descriptive survey. In all cases, potential participants contacted staff by mail or telephone to provide their names and addresses and to indicate their interest in the study. Five cohort groups were established to maintain smaller individual group sizes for the class intervention. Recruitment continued over a 10-month period from 2 separate metropolitan areas. A total of 142 subjects initially ex-

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Fig 2. Flow chart of intervention study. *Hierarchical linear modeling analysis technique is able to estimate values for variables with missing data when at least 2 valid data points are available.

pressed interest. Inclusion criteria included being female, having physician-diagnosed MS for at least 6 months, and being between the ages of 20 to 70 years. Verification of the diagnosis of MS and clearance to participate in the intervention was obtained from the women’s physicians. Women were excluded from the study if they were pregnant or had concurrent medical conditions for which changes in exercise or diet would be contraindicated. Figure 2 depicts the flow of participants through recruitment and data collection. As each potential participant entered the study, she was randomized to control or treatment groups by using the random number table method (76 assigned to treatment, 66 assigned to control). The project director verified that potential participants met the inclusion and exclusion criteria, explained the study’s purpose and requirements, and answered

questions. Of the 142 women, 85% (61 treatment, 60 control) were verified as eligible and agreed to participate. A power analysis to determine sample size was computed for an ␣ level of .05 and a moderate effect size of f equal to .25 (scores on the measure of health-promoting behavior, the Health Promoting Lifestyle Profile II [HPLP-II]) for a directional hypothesis in a comparison of treatment and comparison group means. A total sample size of 110 would correspond to a power level of .85.26 We oversampled to allow for expected attrition during the study. Study Overview Data were collected from participants at the following time intervals: baseline, 2 months, 5 months, and 8 months. Women randomized to the treatment group completed an 8-week lifeArch Phys Med Rehabil Vol 84, April 2003

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WELLNESS INTERVENTION FOR WOMEN WITH MS, Stuifbergen

style-change program, after which data were collected (2mo) and 3 months of supportive telephone follow-up before a third data collection (at 5mo). Control group participants had contact only with the project manager, who was not involved in the delivery of the intervention. Women assigned to the wait-list control group were offered the lifestyle-change classes and telephone follow-up at the completion of time 4 data collection (8mo). To our knowledge, there was no contact between intervention and control participants during the study. Participants were asked to complete the study questionnaires at home and return them by mail in a postage-paid envelope. Nonresponders received a reminder postcard after 3 weeks and a replacement questionnaire after 6 weeks. If a questionnaire was not returned at a selected data point, the participant was still sent questionnaires at subsequent data collection points. Participants were not withdrawn from the study and follow-up data collection attempts unless they specifically requested this (n⫽1). Each participant could receive a maximum of $50 for participating in the study ($10 for the first 3 questionnaires, $20 for the final questionnaire). Subsamples of women in the study also completed food diaries, arm ergometry protocols, 6-minute walks, and goal attainment scaling—this study includes only analysis of data from the self-report measures of the primary study outcomes completed by all women. Intervention Program The intervention was intended to engage the women in assessing their present health behaviors; setting meaningful goals for change; and addressing the barriers, resources, and skills necessary to change those behaviors. The 3 processes used to achieve the program goals included (1) providing accurate information that was specific to health promotion within the context of MS, (2) enhancing self-efficacy for health behaviors,18,27 and (3) individualizing goal setting and monitoring. These processes were integrated into the 2 phases of the wellness program: an educational and skill-building lifestyle change program and a supportive telephone follow-up. The lifestyle change program consisted of 8 sessions over an 8-week period that presented information; guided participants in self-assessment of behaviors, resources, and barriers; and supported specific strategies aimed at building self-efficacy for health behaviors.13 Topics for the sessions included how to maximize health when living with a chronic disabling condition; lifestyle adjustment; exercise and physical activity for fun, endurance, and strength; eating healthy (with particular attention to changing needs over the woman’s life span); stress management; intimacy and sexuality; and women’s health issues (including building relationships with providers). Program content was based on general health promotion literature, qualitative and quantitative data from earlier studies of persons with MS, existing educational materials for persons with other chronic and disabling conditions (eg, spinal cord injury, arthritis), and consultation with experts in nutrition, exercise physiology, and neurology. Participants were given notebooks with self-assessments, outlines of class content, homework assignments, and goal-setting activities.13 The intervention is described elsewhere,13 and a modular program guide with detailed outlines of the intervention content is available from the first author (AKS). Table 1 contains an outline of 1 session. Group sessions lasted 90 minutes and were held at a time and in a place that was convenient and accessible. Several formats for the 8 sessions were used successfully— 8 weekly sessions in the evening or during the daytime (cohorts 1, 2) and a schedule of every other Saturday with a lunch break between 2 Arch Phys Med Rehabil Vol 84, April 2003

Table 1: Outline of Sample Session: Stress Management and Dealing With Depression Introduction Review and reinforce content from prior week Clarify information Solicit success stories Discuss individual goals Use performance accomplishment and vicarious experience regarding success with meeting short-term goals to build selfefficacy to work toward larger goals Mind-body interaction The human stress response Controllable vs uncontrollable stressors Class activity—Life Change Index Discussion and interpretation of external stressors Signs and symptoms associated with stress Emotional signs Thought-related signs Physical signs Strategies for stress management Consider importance of and ability to control stressor Awareness skills Acceptance skills Coping skills Action skills Depression and MS Common signs of depression What to do about depression Relaxation techniques Imagery Meditation Progressive relaxation Hypnosis Yoga Practice techniques in class Imagery Progressive relaxation Class activity—stress management goal setting Identify 3-month goal Identify barriers—what factors within my control make it hard to reach the goal Identify facilitators—what or whom can help me reach my goal What will I do this week to move toward my goal

sessions (cohorts 3, 4, 5). Participants were assigned to groups sequentially and did not choose their session format. After completing the 8 sessions of education and skill building, participants entered the supportive environment component of the intervention. In the 3 months after the skill-building component, they received telephone calls bimonthly from the intervention facilitator to encourage them to progress toward their goals and to monitor their goal attainment.28 The facilitator continued to build participant self-efficacy during the telephone calls through verbal persuasion, by recognizing their performance accomplishments (even small increments can be used to build efficacy), and by telling them about the successful lifestyle changes of other women with MS (vicarious experience).18 The intervention facilitator was a clinical nurse specialist who was experienced in working with persons with chronic conditions, including MS. A woman with MS who had a strong background in health promotion cofacilitated the group. Other members of the intervention team, several of whom had a

WELLNESS INTERVENTION FOR WOMEN WITH MS, Stuifbergen

disability, included a registered dietitian, an adaptive fitness instructor, a nurse practitioner associated with a woman’s wellness center, and a counselor. Instruments A series of self-report instruments were bound in booklet format. The instruments were printed in a font size of 14 points to enhance readability and to facilitate their completion. When measuring psychologic states or behaviors that are expected to vary over time, the most appropriate measures of reliability are those based on internal consistency—a measure of how the different items of a scale are all measuring the same thing.29 Cronbach ␣ coefficients for internal consistency reliability of the instruments in this study sample were all satisfactory (⬎.70). Demographic and disability-related questions were included in 1 portion of the baseline questionnaire booklet. Data were collected about participants’ age, race and ethnicity, marital status, children, and education and employment status. Participants were also asked to indicate their type of MS (benign sensory, relapsing remitting, progressive, or severe progressive), the year in which MS symptoms were first noted, and the year in which MS was first diagnosed by a physician. Information regarding employment status, marital status, medication and treatment use, and severity of impairment was collected in the final questionnaire, as well as in the baseline questionnaire. Severity of impairment. Individual ratings on the Incapacity Status Scale30 provided a measure of functional disability caused by MS. This scale was 1 of 2 developed and validated by the International Federation of Multiple Sclerosis Societies for research involving persons with MS.31 For this study, the structured interview form was adapted to a self-administered questionnaire to provide an assessment of the degree of impairment in 16 personal functions that could be influenced by MS.6 Each of the 16 items is rated on a 5-point scale, with 0 indicating normal or unimpaired functioning and 4 indicating a complete inability to perform the activity (eg, ambulation, dressing). Scores can range from 0 to 64. The rating was completed during both the baseline (␣⫽.83) and final data collection (␣⫽.89) periods. The Pearson product-moment correlation generated between the first and second ratings of impairment was .91 (P⬍.001). Barriers. The intrapersonal, interpersonal, and environmental factors that inhibited health-promoting behaviors were measured by the Barriers to Health Promoting Activities for Disabled Persons Scale.32 This 18-item scale asks respondents to indicate on a 4-point scale, from 1 (never) to 4 (routinely), how often the listed barriers keep them from taking care of their health. Higher scores (possible range, 18 –72) on this summated rating scale indicate more perceived barriers. Research has supported the reliability and validity of this measure in samples of persons with chronic disabling conditions, including those with MS.32 The 2-week test-retest correlation in a sample of undergraduate students was .75.20 The Cronbach ␣ of scores across the 4 time points ranged from .85 to .87. Resources. In this study, social support was the key resource assumed to influence health-promoting behaviors and health and well-being. The Personal Resource Questionnaire33 (PRQ-85, Part 2) was used to measure the multiple dimensions of interpersonal relationships within support networks. Responses to the 25 items are scaled from 1 (strongly disagree) to 7 (strongly agree). Scores can range from 25 to 175, with higher scores indicating higher levels of perceived support. There is evidence to substantiate the content, construct, and criterion-related validity of this instrument in a variety of samples, including community-residing adults and adults with

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chronic conditions.33 Test-retest reliability was evaluated on a sample of 100 community-residing adults and the Pearson product-moment correlation was .72. Internal consistency ranged from .92 to .94. Self-efficacy. Participants’ beliefs about their ability to perform health-promoting behaviors were measured with the Self Rated Abilities for Health Practices34 scale (SRAHP). This 28-item scale covers the domains of nutrition, physical activity and exercise, psychologic well-being, and responsible health practices. It asks respondents to rate how well they are able to perform each health practice on a 5-point scale from 0 (not at all) to 4 (completely). Ratings for all 28 items are summed to yield a total score on the SRAHP (range, 0 –112), with higher scores indicating greater self-efficacy for health practices. Previous research with the SRAHP among adults with and without disabilities demonstrated adequate reliability and predicted relationships with other health measures.4,22 Two-week test-retest reliability was evaluated in a sample of undergraduate students, and the Pearson product-moment correlation was .73.34 In this study sample ␣ ranged from .92 to .95. Health-promoting behaviors. The primary measure of health-promoting behavior was the HPLP-II.35 This 52-item, 4-point scale assesses the frequency with which individuals report engaging in activities to increase their level of health and well-being. Responses are scaled from 1 (never) to 4 (routinely), with higher scores indicating more frequent practice of a health behavior. Scores may range from 52 to 208. This instrument has 6 subscales (physical activity, spiritual growth, health responsibility, interpersonal relations, nutrition, stress management) derived from the earlier HPLP, from literature review, and from expert confirmation. The reliability and validity of the HPLP-II have been supported in psychometric testing with 712 community-residing adults,36 and earlier studies have supported the appropriateness of the measure for chronically ill and disabled populations.4,22 Test-retest reliability over 3 weeks was .89 in a sample of undergraduate students.36 Internal consistency reliability of subscale scores ranged from .71 to .90, and ␣ for the total score ranged from .93 to .95 across the 4 time points in this study sample. Quality of life. The Medical Outcomes Study 36-Item Short-Form Health Survey37 (SF-36) was used to measure the participants’ perceived health status and QOL. The SF-36 is a multi-item scale that measures 8 general health concepts: physical functioning, role limitations because of physical health problems, bodily pain, general health perceptions, vitality, social functioning, role limitations because of emotional problems, and mental health. These summated rating scales are coded and recalibrated so that higher scores indicate better health states. All scales are linearly transformed to a 0 to 100 scale, with 100 indicating the most favorable health state and 0 the least favorable. Scoring algorithms are provided in the SF-36 manual. In a random sample of the US population (N⫽1692), internal consistency reliability (Cronbach ␣) ranged from .63 to .94 across the 8 subscales.38 Two-week testretest reliability of the scales in general practice patients (n⫽187) ranged from .60 to .81.38 Analyses with 3455 patients across 24 subgroups with different sociodemographic, disease severity, and diagnosis characteristics revealed that scales had adequate item internal consistency and item discriminant validity.39 Data Analyses Descriptive data analyses were conducted by using SPSS, version 10.05,a for Windows. Frequency distributions, means, and standard deviations (SDs) were calculated for the demographic and disability-related variables. Independent sample t Arch Phys Med Rehabil Vol 84, April 2003

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tests were used to test for mean differences in outcome variables between the intervention and control groups at baseline. Chi-square analyses were used to assess for differences between groups in demographic variables at baseline and at the final data collection. A mixed-model multivariate time by intervention condition analysis was used to assess for differences in group cohorts and scheduled presentation. A mixed-effects linear regression analysis was used to test for group differences in each outcome measure at the 3 follow-up assessments, adjusting for baseline differences in the respective outcome variable and severity of impairment. Mixed-effects models take into account correlations among observations nested within individuals, a characteristic typical of repeated-measures data.40 Conventional regression techniques that ignore the nested structure of repeated-measures data could result in biased estimates if the data within individuals correlate. Another advantage to the methodology is its ability to handle missing data, which is also common to repeated measures. Assuming an appropriate model, the results are considered valid when the reasons for the missing data are independent of the missing values themselves. Consequently, this analytic technique can estimate values for variables with missing data when at least 2 valid data points are available. A mixed-effects linear regression analysis using HLM 5b was performed on individual outcome measures (barriers, resources, self-efficacy, health-promoting behaviors, QOL scales). For each outcome measure, estimates of the mean responses at months 2, 5, and 8 were obtained, allowing for differences between the intervention and control groups and adjusting for baseline differences in the outcome measure and severity of impairment. By using plots of the individual response curves across the 3 time points and exploratory hierarchical linear modeling (HLM) analyses, a 2-level model with random intercepts seemed appropriate for all outcome measures with the exception of role–physical, a subscale of the SF-36: Level 1: Yij⫽␤0⫹␤1䡠Mo⫺5ij⫹␤2䡠Mo⫺8ij⫹␤3䡠(Mo⫺5䡠Grp)ij ⫹␤4䡠(Mo⫺8䡠Grp)ij⫹eij Level 2:

␤0⫽␥00⫹␥01䡠Grpi⫹␥02䡠Measure at Baselinei ⫹␥03䡠Severity of Impairmenti⫹u0 where Yij is the outcome response for individual i at measurement occasion j, for j equal to 0, 3, and 6. The values for the measurement occasions (j⫽0, 3, 6) represent a shift in the actual months of measurement so that the intercept in the equation (␤0) represents the average response at month 2. That is, months were centered at month 2 by subtracting 2 from each value.41 At the first level of the model, the intercept ␤0 represents the estimated mean outcome response at month 2 for all individuals, adjusting for baseline differences in the respective outcome measure and severity of impairment. The coefficients ␤1 and ␤2 represent the average difference in the mean response at months 5 and 8, respectively, relative to month 2 for all individuals. The coefficients ␤3 and ␤4 represent the difference in mean responses at months 5 and 8, respectively, between the intervention and control groups, relative to month 2. The within-individual error at a particular point in time is denoted by eij. At the second level of the model, the intercept at level 1 is considered to vary between individuals. That is, the height of the individual response curves may vary from person Arch Phys Med Rehabil Vol 84, April 2003

to person. To account for these individual differences in response, 3 effects were examined. The coefficient ␥01 represents the mean difference in response at month 2 between the intervention and control groups. The coefficient ␥02 is the effect of the outcome measure taken at baseline on the outcome response at month 2 for all individuals. Last, the coefficient ␥03 is the effect of the baseline measure of severity of impairment on the outcome response at month 2 for all individuals. The error at the second-level equation is given by u0. In addition to random intercepts, role–physical seemed to also require random variation in the slope for month 5, ␤1i. The effects of the intervention and the baseline measures of role–physical and severity of impairment in accounting for variation in the random slopes were tested, but none were statistically significant. RESULTS To be included in the final study sample for analysis of the intervention, participants had to complete data collection for at least 2 of the 4 time points and to attend at least 75% of the intervention classes. As seen in figure 2, 8 individuals did not complete the required data collection instruments, bringing the final study sample to 113 subjects (56 treatment, 57 control). The final sample represents 80% of those who initially expressed interest and 93% of those who provided written consent to participate. The 113 women ranged in age from 21 to 70 years (mean ⫾ SD, 45.79⫾10.09y) and included 92 whites, 13 African Americans, 1 Asian American, 3 Hispanic/Mexican Americans, and 4 women of “other” ethnic or racial background. The majority were married (n⫽66, 58%) and not employed full-time (n⫽78, 69%). The sample was well educated, with 92% (n⫽104) having completed high school and 49.5% (n⫽56) having earned a college degree. The length of time since diagnosis with MS ranged from 1 to 37 years (mean, 10.76⫾6.92y). The majority of the women (55%, n⫽62) reported that they had relapsing-remitting MS. Because the intervention was delivered to small groups of 8 to 14 women, we first compared scores for the 5 different intervention cohorts across the 4 time periods to determine if there were significant differences among the scores of the cohorts. Estimation of a multivariate mixed-model with a time by intervention group interaction revealed no statistically significant differences between those who attended different intervention groups, and no statistically significant interactions between time and session attended for all major study variables but the subscales of the HPLP. While there was an overall statistically significant effect for intervention cohort in this analysis, subsequent tests for the 6 individual subscales did not detect any individual subscale that yielded a statistically significant difference for group cohort. Because there appeared to be minimal differences among intervention cohorts in the outcome measures, we combined data across intervention cohorts for all subsequent analyses. We also compared at baseline and at month 8 scores of those who received the intervention in 8 weekly sessions (lasting 11⁄2h) with those who attended 4 biweekly sessions (lasting 3h) over an 8-week period. Estimation of a multivariate mixedmodel with a time by session type interaction revealed no statistically significant differences between those who attended 4 versus 8 sessions and no significant interactions between time and type of session attended. Chi-square tests used to assess group differences in the variables of marital status and employment at baseline and at final data collection revealed only 1 statistically significant difference. At baseline, there was no statistically significant association between employment status and group member-

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WELLNESS INTERVENTION FOR WOMEN WITH MS, Stuifbergen Table 2: Means and SDs for Study Variables Across Time Control Group Variable

T1

Severity of impairment Social support (PRQ) Barriers Specific self-efficacy (HPLP-II) Total Health responsibility Activity Nutrition Spiritual Interpersonal relations Stress management SF-36 scales Physical function Role–physical Bodily pain General health Vitality Social functioning Role–emotional Mental health

16.4⫾8.6

T2

T3

Intervention Group T4

T1

16.3⫾8.9

14.9⫾7.1

T2

T3

T4

14.1⫾7.3

139.2⫾22.4 34.4⫾8.7

139.2⫾22.5 33.0⫾8.6

137.1⫾23.7 33.4⫾8.4

142.7⫾22.3 32.0⫾8.4

140.6⫾23.1 33.4⫾8.2

142.0⫾24.1 31.8⫾7.7

142.7⫾26.2 31.6⫾8.2

145.1⫾22.3 31.4⫾7.5

81.9⫾18.7 141.9⫾23.0 24.3⫾5.6 14.9⫾5.1 24.2⫾5.4 27.8⫾4.8 29.3⫾4.7 21.4⫾5.4

85.2⫾14.7 145.1⫾20.6 24.9⫾5.1 15.6⫾4.6 24.8⫾5.0 28.3⫾5.1 29.1⫾4.5 22.4⫾5.2

83.1⫾18.8 142.3⫾25.5 25.3⫾5.6 15.2⫾5.6 24.7⫾5.8 27.0⫾5.9 29.0⫾5.0 22.4⫾5.5

83.6⫾19.2 146.9⫾23.2 25.8⫾5.7 16.0⫾5.1 25.5⫾5.3 27.8⫾5.4 29.5⫾4.3 22.4⫾5.2

84.1⫾19.5 142.2⫾22.0 25.0⫾4.8 16.8⫾5.9 23.4⫾4.3 27.6⫾5.6 28.6⫾5.1 20.9⫾4.8

91.0⫾15.8 152.7⫾22.5 27.0⫾4.8 19.0⫾6.1 25.2⫾4.5 29.0⫾5.3 29.5⫾4.8 23.0⫾4.8

92.6⫾14.8 156.2⫾23.9 27.4⫾5.3 20.0⫾5.7 26.1⫾4.7 29.3⫾5.6 29.9⫾5.3 23.7⫾4.5

93.5⫾14.4 158.3⫾21.8 27.7⫾4.2 20.0⫾5.7 26.3⫾4.8 29.9⫾5.1 30.1⫾4.6 24.3⫾4.4

42.3⫾30.3 38.2⫾38.1 66.5⫾23.0 59.4⫾20.7 39.7⫾20.1 70.8⫾26.6 67.8⫾42.2 71.1⫾19.7

40.5⫾29.4 31.6⫾36.1 61.4⫾24.0 61.2⫾21.8 37.9⫾21.6 67.6⫾25.9 58.0⫾43.0 67.0⫾23.0

41.9⫾30.8 29.0⫾34.3 56.0⫾28.0 57.0⫾23.2 36.1⫾23.7 60.5⫾28.4 57.7⫾44.7 69.4⫾23.1

40.2⫾30.8 41.4⫾42.0 63.8⫾28.2 60.4⫾23.9 41.2⫾21.5 70.2⫾24.4 65.5⫾42.5 71.7⫾19.7

51.3⫾27.0 42.9⫾40.7 65.1⫾25.1 52.1⫾22.1 40.5⫾20.7 70.5⫾24.5 63.1⫾40.5 69.1⫾20.1

53.1⫾27.3 44.9⫾41.9 67.0⫾25.0 55.7⫾23.9 42.5⫾23.1 74.5⫾24.4 70.4⫾40.8 73.6⫾18.5

52.6⫾28.9 47.2⫾42.7 64.9⫾27.2 53.6⫾23.3 43.3⫾23.3 72.1⫾26.9 72.3⫾40.7 74.0⫾21.4

51.0⫾29.1 46.9⫾43.8 66.7⫾24.6 57.1⫾24.9 44.0⫾22.3 69.6⫾25.9 76.2⫾36.0 74.6⫾15.0

NOTE: Data collection points are designated as T1, T2, T3, T4.

ship. However, by month 8, women in the intervention group were more likely to be employed than women in the control group (␹2⫽3.91, P⬍.05). Table 2 provides the means and SDs for the intervention and control groups for each study variable across the 4 time periods. Table 3 provides the parameter estimates for the 2-level

models fitted to each outcome measure. A statistically significant intervention effect, reflected in the column labeled “Group” in table 3, was found for the total Self-Rated Abilities Scale (measure of self-efficacy), suggesting that across the 3 follow-up occasions, individuals in the intervention condition reported on average greater levels of self-efficacy after adjust-

Table 3: HLM Parameter Estimates (Nⴝ113) Month 5

Month 8

Month 5⫻Group

Month 8⫻Group

Measure at Baseline

Severity of Impairment

6.4⫾2.0† ⫺1.0⫾1.1 2.6⫾2.4

0.7⫾0.1‡ 0.6⫾0.1‡ 0.8⫾0.1‡

0.1⫾0.1 0.1⫾0.1 ⫺0.1⫾0.1

0.9⫾0.6 0.4⫾0.6 ⫺0.1⫾0.6 0.9⫾0.5 0.3⫾0.7 ⫺0.5⫾0.7 1.8⫾2.3

1.4⫾0.6* 1.2⫾0.5* 1.3⫾0.5* 1.4⫾0.6* 2.5⫾0.7‡ 2.1⫾0.6† 9.8⫾2.8†

0.7⫾0.0‡ 0.8⫾0.1‡ 0.8⫾0.1‡ 0.8⫾0.1‡ 0.7⫾0.1‡ 0.7⫾0.1‡ 0.8⫾0.1‡

0.0⫾0.0 0.0⫾0.0 ⫺0.0⫾0.0 0.0⫾0.0 ⫺0.0⫾0.0 0.1⫾0.0 0.1⫾0.2

⫺1.1⫾2.5 1.8⫾7.0 ⫺7.5⫾7.1 ⫺5.4⫾3.7 ⫺7.5⫾4.0 1.8⫾2.7 ⫺2.7⫾3.0 ⫺2.6⫾3.3

4.3⫾2.8 11.4⫾6.3 7.2⫾6.3 8.3⫾3.6* 5.6⫾4.2 1.3⫾2.9 7.9⫾3.0* 4.3⫾3.2

0.7⫾0.1‡ 0.5⫾0.1‡ 0.4⫾0.1‡ 0.7⫾0.1‡ 0.4⫾0.1‡ 0.8⫾0.1‡ 0.6⫾0.1‡ 0.5⫾0.1‡

⫺0.6⫾0.2† ⫺0.9⫾0.4† ⫺1.1⫾0.4† ⫺0.3⫾0.2 ⫺0.8⫾0.2‡ ⫺0.3⫾0.2 ⫺0.1⫾0.2 ⫺0.5⫾0.2*

Measure

Constant

Self-efficacy Barriers Social support HPLP-II Stress management Nutrition Interpersonal relations Spiritual Activity Health responsibility Total SF-36 scales Physical function Role–emotional Role–physical Bodily pain Social functioning General health Mental health Vitality

26.5⫾5.9‡ 10.0⫾2.0‡ 23.2⫾10.1*

⫺0.5⫾1.5 ⫺0.2⫾0.7 ⫺0.8⫾1.8

⫺1.3⫾1.7 ⫺0.8⫾0.6 2.1⫾1.7

0.7⫾1.9 0.0⫾1.0 1.1⫾2.5

2.4⫾2.0 0.5⫾0.9 ⫺0.1⫾2.4

6.2⫾1.4‡ 4.9⫾1.4† 6.5⫾1.6‡ 4.1⫾1.9* 6.1⫾1.1‡ 6.1⫾1.3‡ 25.2⫾8.8†

0.2⫾0.5 0.2⫾0.5 0.3⫾0.5 ⫺0.9⫾0.4* ⫺0.0⫾0.6 0.7⫾0.4 0.2⫾1.6

0.1⫾0.5 0.7⫾0.4 0.3⫾0.4 ⫺0.4⫾0.4 0.3⫾0.5 0.9⫾0.5 2.0⫾1.7

0.2⫾0.6 0.6⫾0.6 0.0⫾0.6 1.1⫾0.6 0.6⫾0.8 ⫺0.7⫾0.6 2.0⫾2.3

19.9⫾6.1† 41.2⫾9.7‡ 38.2⫾9.2‡ 18.8⫾6.4‡ 53.5⫾7.6‡ 16.8⫾5.5‡ 24.0⫾7.3‡ 24.1⫾7.6†

1.5⫾2.4 1.2⫾5.5 ⫺1.8⫾5.2 ⫺3.7⫾2.9 ⫺5.5⫾3.6 ⫺2.4⫾1.7 3.0⫾2.3 ⫺0.8⫾2.4

⫺0.5⫾1.7 6.4⫾5.2 9.2⫾5.4 2.7⫾2.6 3.2⫾3.2 0.1⫾1.9 4.1⫾2.4 3.4⫾2.2

⫺1.1⫾2.8 4.2⫾7.4 6.2⫾6.8 ⫺0.0⫾4.1 4.4⫾4.5 1.3⫾2.6 ⫺1.5⫾3.1 1.2⫾3.3

Group

NOTE. Values are mean ⫾ standard error. * P⬍.05. † P⬍.01. ‡ P⬍.001.

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ing for baseline differences in self-efficacy scores and severity of impairment. Statistical significance tests of the coefficients for months 5 and 8 and the interactions of these measurement occasions with group suggest that, although there was a difference in means between groups at month 2, scores remained stable through the remaining follow-up points for both groups. Although the effect of the baseline measure of severity of impairment was not statistically significant, the baseline measure of self-efficacy was, suggesting that preintervention levels of self-efficacy related positively to self-efficacy scores through follow-up. In contrast, no intervention effect was found for either the Barriers Scale or the Personal Resources Questionnaire, the measure of social support. Similar to the self-efficacy scale, scores on both of these scales remained stable through follow-up. Tests of the effects of the baseline measure of severity of impairment on both variables were not statistically significant, although the effects of the baseline measures of the respective variables were, suggesting that preintervention levels of these measures related positively to the respective scores across all 3 follow-up points. A key interest in this study was the effect of the intervention on the proximate outcome measure of health-promoting behaviors (HPLP-II scores). Statistically significant intervention effects were found for all subscales of the HPLP-II. Across the 3 follow-up occasions, individuals in the intervention group reported on average greater levels of health-promoting behaviors, after statistically adjusting for baseline differences in the respective subscale and the severity of impairment. Baseline scores on each subscale were positively and significantly related to the respective scale scores across all follow-up occasions. In all cases, the effect of the baseline measure of severity of impairment was not statistically significant, suggesting that there was no relation between level of impairment at baseline and health-promoting behaviors across the study period. Unique to the spiritual scale, the difference between the intervention and control groups was statistically significant at month 5, suggesting that scores on this scale were lower on average for the intervention group compared with the control group at this follow-up. Finally, the effects of the intervention on the distant outcomes of QOL and health as measured by the SF-36 subscales were assessed. Statistically significant effects were found for 2 subscales, bodily pain and mental health, after adjusting for baseline differences in the respective subscale and severity of impairment. These results suggest that average scores for both scales were higher for the intervention group. Similar to the previous results, the effects of baseline measures of the individual scales were statistically significant on individual outcome variables measured across follow-up, suggesting that preintervention levels of each scale related positively to the respective scale scores across follow-up. With regard to the effect of the baseline measure of severity of impairment, statistically significant negative effects were found for physical function, role– emotional, role–physical, social functioning, and vitality, suggesting an association between lower individual scale scores across the follow-up period and higher levels of impairment severity at baseline. For all scales, no differences between score means at months 5 and 8 relative to month 2 were found for either group, suggesting stability in scores across follow-up. DISCUSSION Findings from this trial of a wellness intervention for women with MS must be interpreted with caution because of the convenience sample and the potential for selection bias. Participants were recruited primarily through contacts with the MS Arch Phys Med Rehabil Vol 84, April 2003

Society and may not have been representative of the general population of women with MS. In addition, it seems likely that women responding to recruitment materials for the study may have been more interested in health behaviors than other women with MS, and thus more likely to initiate positive change. Although the sample size was not large, it was sufficient to find significant differences in the proximate outcome variables (health behaviors) and, in fact, is larger than the average sample size of 40 per group (total N⫽80) that has been reported in several collections of published intervention studies.42 Despite these limitations, this wellness intervention for women with MS succeeded in improving self-efficacy, health behaviors, and selected aspects of QOL (pain, mental health). The findings of this RCT were robust across cohorts and variations in delivery format. The intervention was systematically evaluated before it was implemented, and at multiple data collection points over 8 months it showed its positive effects. The most substantial changes were seen in the proximate (antecedent, health behaviors) versus distant outcomes (health, QOL). This is not surprising because the target of the intervention was the development of self-efficacy and subsequent improvement of health promotion behaviors. The unexpected positive change in employment status in the intervention group may be related to the improvements in self-efficacy. Extended follow-up may be required to evaluate subsequent change in health and QOL outcomes. The success of this intervention may be because of its systematic development, refinement, and implementation in a manner consistent with the principles of intervention quality identified by Mullen et al.43,44 In 2 meta-analyses43,44 of the effects of patient education, the quality of the intervention was the key determinant of effectiveness. The quality of the intervention was defined as the application of 5 principles from the behavioral sciences: (1) relevance—tailoring the program to knowledge, beliefs, and circumstances of the learner; (2) individualization—allowing learners to have personal questions answered or pacing their instructions; (3) feedback—providing information to learners about their level of accomplishment; (4) reinforcement—rewarding the behavior in ways other than feedback (eg, social support); and (5) facilitation—providing a way for the learner to take action and/or reduce barriers. These principles are consistent with the 3 key processes of the Wellness Intervention for Women with MS: providing information that is specific to health promotion within the context of MS, enhancement of self-efficacy for health behaviors, and individualized goal setting and monitoring. The intervention content and format were based on extensive research to document the experiences of women with chronic disabling conditions. Consequently, the intervention was relevant to women with chronic disabling conditions who wanted to promote their health; it provided them with the information and skills required to tailor their approaches to changing circumstances, specific needs, and desires. The self-assessments and goal setting, as well as the use of goal attainment scaling in follow-up telephone support made operational the important aspects of individualization and feedback. The development of skills and group social support enhanced reinforcement and facilitation of behavior change. Although women in the intervention group had significant improvements in scores on the SF-36 scales of pain and mental health, they did not experience significant improvements when compared with the control group in vitality, physical function, role–physical or role– emotional, social functioning, or general health. The items comprising these SF-36 subscales address the aspects of health and QOL that are most impacted by MS

WELLNESS INTERVENTION FOR WOMEN WITH MS, Stuifbergen

(fatigue, weakness, mobility impairments). In fact, some of these decreases in functioning may be permanent and not amenable to change. The effect of the severity of MS-related impairment is reflected in the statistically significant effect of the baseline severity of impairment measure on the 4 SF-36 scales that reflect function. One of our most encouraging findings was the positive change in self-efficacy and health behavior experienced by the intervention group. Mean scores rose sharply after the group intervention and continued to improve during the telephone follow-up and the 3 months of maintenance, even when baseline levels of self-efficacy were statistically controlled. Over the 8 months, participants did not experience a sharp relapse. Self-reports and written comments from women in the intervention group indicated that they viewed the follow-up telephone support as a critical component that helped them to successfully change and maintain health behaviors. They emphasized that changes in behaviors require time as well as skills and information, and they consistently agreed on the need for the combination of a structured educational intervention with the supportive problem-solving environment. The pattern of mean scores among control group participants is somewhat puzzling. As expected, scores tended to be stable or to worsen over the first 3 measurement periods. Surprisingly, sharply improved scores were reported for many variables at the final measurement period. We suspect that the improved scores may reflect reactivity to measurement combined with an awareness of health promotion issues that was catalyzed by the invitation to participate in the wait-list health promotion intervention. As part of the study protocol, invitations to participate in the wait-list control classes were mailed with the fourth data collection instrument. To encourage response to this final data collection, control participants were told that classes would be scheduled as soon as they returned their final questionnaire. In future research, invitations to participate in the control classes, plus related information, should be mailed only after the last data collection instrument has been returned by participants. Contamination of the control group could also explain the change in scores. Although we are not aware of any contact between the intervention and control participants, because the women were all community-residing adults, this possibility of treatment contamination cannot be ruled out. The consistent positive response to the intervention raises the question of how long this response might be maintained and whether distal outcomes (health, QOL) might also show greater improvement with time. Recent findings in a longitudinal descriptive study suggest that women with MS who practice health behaviors more frequently accumulate significantly less impairment over a 3-year period than do women who infrequently practice these behaviors.6 Although the long-term effects of the wellness intervention can only be ascertained through a longitudinal follow-up, the sustained improvement in the practice of health behaviors may have major cost implications for this population. Persons with MS are at high risk for a variety of secondary conditions, including depression, urinary tract infections, contractures, and osteoporosis, all of which increase the direct and indirect costs of chronic conditions. Serious consideration should be given to “upstream” health promotion programs that may prevent expensive complications and may improve QOL. CONCLUSION This Wellness Program for Women with MS is an effective intervention with which to give women with chronic disabling

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conditions information they need to develop skills that have the potential to influence attitudes and health behaviors that will promote their overall QOL. Future research should explore how this intervention might be adapted to enhance health promotion behaviors and related outcomes among both women and men with other chronic disabling conditions (arthritis, fibromyalgia, lupus). Acknowledgment: We gratefully acknowledge the assistance of Seon Hi Shin, MA, with data entry and analysis. References 1. Anderson DW, Ellenberg JH, Leventhal CM, Reingold SC, Rodriquez M, Silberberg DH. Revised estimate of the prevalence of multiple sclerosis in the United States. Ann Neurol 1992;31: 333-6. 2. Frohman EM, Racke M, van Den Noort S. To treat, or not to treat: the therapeutic dilemma of idiopathic monosymptomatic demyelinating syndromes. Arch Neurol 2000;57:930-2. 3. Petajan JH, Gappmaier E, White AT, Spencer MK, Mino L, Hicks RW. Impact of aerobic training on fitness and quality of life in multiple sclerosis. Ann Neurol 1996;39:432-41. 4. Stuifbergen A, Seraphine A, Roberts G. An explanatory model of health promoting behavior and quality of life for persons with chronic disabling conditions. Nurs Res 2000;49:122-9. 5. Mohr DC, Goodkin DE, Bacchetti P, et al. Psychological stress and the subsequent appearance of new brain MRI lesions in MS. Neurology 2000;55:55-61. 6. Stuifbergen A, Becker H. Health promotion practices in women with multiple sclerosis: increasing quality and years of healthy life. Phys Med Rehabil Clin North Am 2001;12(1):9-22. 7. Watt D, Verma S, Flynn L. Wellness programs: a review of the evidence. CMAJ 1998;158:224-30. 8. Duquette P, Pleines J, Girard M, Charest L, Senecal-Quevillon M, Masse C. The increased susceptibility of women to multiple sclerosis. Can J Neurol Sci 1992;19:466-71. 9. Foley FW. Multiple sclerosis in behavioral medicine and women: a comprehensive handbook. New York: Guilford Pr; 1998. 10. Thorne S, McCormick J, Carty E. Deconstructing the gender neutrality of chronic illness and disability. Health Care Women Int 1997;18:1-16. 11. Jans L, Stoddard S. Chartbook on women and disability in the United States. An InfoUse Report. Washington (DC): US Department of Education, National Institute on Disability and Rehabilitation Research; 1999. 12. LaCroix A, Newton K. Healthy aging: a woman’s issue. West J Med 1997;167:220-32. 13. Stuifbergen A, Becker H, Rogers S, Timmerman G, Kullberg V. Promoting wellness for women with multiple sclerosis. J Neurosci Nurs 1999;31:73-9. 14. Becker MH. The health belief model and personal health behavior. Thorofare (NJ): Slack; 1974. 15. Pender NJ. Health promotion in nursing practice. East Norwalk (CT): Appleton & Lange; 1987. 16. Bandura A. Self-efficacy mechanism in human agency. Am Psychol 1982;37:122-47. 17. Bandura A. Perceived self-efficacy in the exercise of control over AIDS infection. Eval Progr Plan 1990;13:9-17. 18. Bandura A. Self efficacy: the exercise of control. New York: WH Freeman; 1997. 19. Becker HA, Stuifbergen AK, Ingalsbe K, Sands D. Health promoting attitudes and behaviors among persons with disabilities. Int J Rehabil Res 1989;12:235-50. 20. Stuifbergen A, Becker H. Predictors of health promoting lifestyles in persons with disabilities. Res Nurs Health 1994;17:3-13. 21. Stuifbergen A. Meeting the demands of illness: types and sources of support for individuals with MS and their partners. Rehabil Nurs Res 1992;1:14-23. 22. Stuifbergen A. Health promoting behaviors and quality of life among individuals with multiple sclerosis. Sch Inq Nurs Pract 1995;9(1):31-50. 23. Stuifbergen A. Physical activity and perceived health status in persons with multiple sclerosis. J Neurosci Nurs 1997;29:238-43. Arch Phys Med Rehabil Vol 84, April 2003

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