Nola J. Pender

The Health-promoting Lifestyle Profile: Development and Psychometric Characteristics

This article describes the development and initial psychometric evaluation of an instrument to measure health-promoting life-style. Based on responses from 952 adults in midwestern communities, the Health-Promoting Lifestyle Profile was evaluated using item analysis, factor analysis, and reliability measures. Factor analysis isolated six dimensions: Self-Actualization, Health Responsibility, Exercise, Nutrition, Interpersonal Support, and Stress Management. These six factors accounted for 47.1% of the variance in the 48-item measure. Second-order factor analysis yielded a single factor, interpreted as Health-Promoting Lifestyle. The alpha reliability coefficient for the total scale is.922; alpha coefficients for the subscales range from .702 to .904. Further evaluation of the measure with different populations appears warranted. This instrument will enable researchers to investigate patterns and determinants of health-promoting life-style, as well as the effects of interventions to alter lifestyle.

Evaluating Primary Care Behavioral Counseling Interventions An Evidence-Based Approach

Risky behaviors are a leading cause of preventable morbidity and mortality, yet behavioral counseling interventions to address them are underutilized in healthcare settings. Research on such interventions has grown steadily, but the systematic review of this research is complicated by wide variations in the organization, content, and delivery of behavioral interventions and the lack of a consistent language and framework to describe these differences. The Counseling and Behavioral Interventions Work Group of the United States Preventive Services Task Force (USPSTF) was convened to address adapting existing USPSTF methods to issues and challenges raised by behavioral counseling intervention topical reviews. The systematic review of behavioral counseling interventions seeks to establish whether such interventions addressing individual behaviors improve health outcomes. Few studies directly address this question, so evidence addressing whether changing individual behavior improves health outcomes and whether behavioral counseling interventions in clinical settings help people change those behaviors must be linked. To illustrate this process, we present two separate analytic frameworks derived from screening topic tools that we developed to guide USPSTF behavioral topic reviews. No simple empirically validated model captures the broad range of intervention components across risk behaviors, but the Five As construct-assess, advise, agree, assist, and arrange-adapted from tobacco cessation interventions in clinical care provides a workable framework to report behavioral counseling intervention review findings. We illustrate the use of this framework with general findings from recent behavioral counseling intervention studies. Readers are referred to the USPSTF (www.ahrq.gov/clinic/prevenix.htm or 1-800-358-9295) for systematic evidence reviews and USPSTF recommendations based on these reviews for specific behaviors.

Does counseling by clinicians improve physical activity? A summary of the evidence for the U.S. Preventive Services Task Force.

Sedentary behavior (little to no recreational, household, or occupational physical activity) is one of the strongest risk factors for many chronic diseases and conditions, including cardiovascular disease, hypertension, diabetes, obesity, osteoporosis, colon cancer, and depression (1, 2). Only 25% of Americans achieve the level of physical activity recommended in Healthy People 2010 guidelines, that is, 30 minutes of moderate activity on 5 or more days per week or 20 minutes of vigorous activity three or more times per week (3). Twenty-nine percent report getting no regular physical activity. A recent review of observational studies reported that risk for all-cause mortality was 20% to 30% lower among adults who met the Healthy People 2010 recommendations and somewhat lower for adults who exercised moderately or vigorously at least a few times per month or once per week (4). Despite inconclusive evidence that counseling by primary care clinicians improves patient activity levels, in 1996 the U.S. Preventive Services Task Force (USPSTF) recommended counseling to promote regular physical activity for all children and adults based on evidence of the benefits of increased physical activity. Surveys of patients suggest that a minority of clinicians follow this recommendation. In the 1997 Behavioral Risk Factor Surveillance System, 42% of adult respondents reported receiving clinician advice to increase physical activity levels (5, 6). Approximately three fourths of the patients who reported receiving clinician advice also reported increasing physical activity levels, compared with only half of the patients who reported receiving no clinician advice. Two recent systematic reviews came to different conclusions about the efficacy of counseling (7, 8). One review focused on eight studies published between 1988 and 1998 in which primary care clinicians directly advised patients to increase physical activity (8). The authors rated only two of these studies as good quality; in four studies, counseling led to small, short-term increases in self-reported activity levels. The other review summarized 15 studies published between 1979 and 1999 of interventions initiated or conducted in the primary care setting, regardless of whether the primary care clinician played any role (7). This review concluded that counseling was moderately effective but did not use study quality as a criterion for inclusion. Neither review sought evidence about the potential harms associated with increasing physical activity. Since these reviews were published, results of several additional trials of counseling have been made available. In consultation with members of the USPSTF, we performed a new systematic review that focused on controlled trials published since the 1996 USPSTF guidelines and addressed these questions: 1) Do adults counseled by primary care clinicians improve or maintain physical activity behavior? 2) If so, what types of interventions are most effective? From the trials on physical activity counseling, we also assessed the harms associated with increased physical activity. Methods Search Strategy and Study Selection The scope of the two previous systematic reviews (7, 8) differed sharply: One included only studies of counseling by the clinician alone (8), while the other included studies of interventions performed in the primary care setting even when clinicians did not interact with patients in any way (7). In consultation with members of the USPSTF, we took the middle ground of including all controlled clinical trials in which some components of the intervention were performed by the patients primary care clinician (nurse practitioner, nurse, physician, or physician assistant). To describe the clinicians role as well as other components of interventions consistently, we used an abstraction tool developed by the Behavioral Counseling Work Group of the current USPSTF (9). The tool is based on a practical 5-A framework (Assess, Advise, Agree, Assist, and Arrange/Adjust) originally developed to describe the elements of brief provider tobacco-cessation interventions (10). We limited our review to trials that had been published since the last USPSTF review (1994 and later) and that reported behavioral outcomes of an intervention to increase physical activity. We searched the Cochrane Database of Systematic Reviews and Registry of Controlled Trials through March 2002 using the term physical activity and found abstracts for 49 reviews and 966 controlled trials. We searched the MEDLINE and HealthStar database from 1994 to March 2002, using the Medical Subject Headings exercise, physical fitness, counseling, patient education, and health education, and found 549 abstracts. Experts and reference lists of pertinent articles provided an additional 145 references. We excluded two randomized, controlled trials that reported physical activity outcomes but did not mention counseling to increase physical activity (11, 12). We excluded one ongoing trial that has not yet reported results for the physical activity intervention in the treatment groups (13). We excluded four randomized, controlled trials (14-17) in which all components of the intervention were provided by a research staff member or exercise specialist. For example, in one study (15), a research associate recruited patients from waiting rooms or from lists provided by the general practitioners. The patients were mailed an invitation to participate in an intervention conducted by health educators at a fitness center. As a team, we reviewed this study and excluded it because no components of the intervention were performed by a primary care clinician. Data Abstraction and Synthesis A single reviewer abstracted information about setting, patient participants, providers, interventions, adherence, and outcomes. The outcome of primary interest was the proportion of patients who met the Healthy People 2010 goal in the long term, which we defined as at least 6 months after randomization. When this outcome was not available, we recorded mean changes in activity levels. We also recorded short-term results if reported. At least two reviewers summarized the quality of each study using criteria developed by the current USPSTF (18). In applying the USPSTF criteria to trials that used randomization by practice rather than by individual patient, we placed particular importance on the methods used to create comparable groups, such as matching and stratification, and on whether the groups were similar at baseline. We also placed emphasis on whether the interventions were clearly described and whether most patients were retained throughout the study. The internal validity of each trial was rated good, fair, or poor. A rating of good means that the trial met all criteria and was very likely to be valid. A fair rating means that the study was possibly or probably valid, depending on the nature or severity of its flaws. Poor studies have fatal flaws rendering the results invalid; such studies were excluded from further consideration. We summarized the design, quality, and results of each included trial in an evidence table, focusing on the magnitude of change in and duration of physical activity. We examined the consistency of results among studies and the relationship between effects and specific components of the interventions, discussing studies that compared an intervention with usual care separately from those that compared two interventions. Role of the Funding Source This review was funded by the U.S. Agency for Healthcare Research and Quality under a contract to support the work of the USPSTF. Task Force members participated in the initial design of the review and reviewed interim summaries as well as the final manuscript. The funding source had no role in the study design, data collection, or data synthesis; however, representatives of the Agency for Healthcare Research and Quality reviewed interim summaries and copies of the manuscript. Since our report was prepared for the current USPSTF, it was distributed for review to 13 outside experts and representatives of professional societies and federal agencies. Results Seven randomized, controlled trials (19-25) and one nonrandomized, controlled trial (26) met our inclusion criteria (Table). A pilot study for one of the trials (20) was excluded (29). Five other trials (30-34) were excluded because they received a quality rating of poor according to criteria developed by the current USPSTF (18). (See the Appendix Table for a description of the excluded studies.) Table. Summary of Controlled Trials of Counseling for Physical Activity Most of the trials were conducted in typical primary care practices, and all included multiple sites. Clinicians delivered advice themselves but usually did not perform the initial assessment. In some trials, the patients completed a self-report tool on physical activity levels (20, 22, 26) or answered selected questions from larger validated health-assessment tools administered by telephone, in the office waiting area, or in the home (19, 21, 23). Often, a nurse or research assistant conducted a baseline assessment and placed it on the medical chart for review during the clinicians visit (20, 22, 26). The clinician used the assessment information to exclude patients for whom physical activity was contraindicated or to tailor the intervention to each patients needs. In most trials, the clinician advised sedentary or minimally active patients to achieve regular, moderate-intensity physical activity; in some trials, clinicians recommended vigorous activity as an option. Five studies (20, 22, 24-26) targeted physical activity alone, while three (19, 21, 23) also had other behavioral targets (for example, diet change, smoking cessation). In three of the trials, the primary care clinicians condensed advice and counseling on behavior change into a single 3- to 5-minute encounter and, for some patients, a follow-up session wi

Predicting health-promoting lifestyles in the workplace.

A multivariate model proposed as explanatory and predictive of health-promoting lifestyles was evaluated in a sample of 589 employees enrolled in six employer-sponsored health-promotion programs. Perceived personal competence, definition of health, perceived health status, and perceived control of health accounted for 31% of the variance in health-promoting lifestyle patterns. Employees who reported more health-promoting lifestyles perceived themselves as competent in handling life situations, defined health as high-level wellness rather than merely the absence of illness, evaluated their health positively, and perceived their health as affected by significant others but not by chance or luck. Those who were female, older, and in the maintenance phase of the company fitness program also had healthier lifestyle patterns. These variables and the perception of health as internally controlled were predictive of health-promoting lifestyles three months later.

Health-promoting life styles of older adults: comparisons with young and middle-aged adults, correlates and patterns.

The purposes of the study presented were to compare the health-promoting behaviors of older adults with those of young and middle-aged adults, to examine the relationship of age and other sociodemographic characteristics to life style throughout adulthood, and to identify differing life-style patterns among older adults. Six dimensions of life style were measured by the Health-Promoting Lifestyle Profile in 452 adults aged 18 to 88. Older adults had higher scores in overall health-promoting life style and in the dimensions of health responsibility, nutrition, and stress management than both young and middle-aged adults. Sociodemographic variables accounted for only 13.4% of the variance in life style and for 5.2% to 18.6% in its six dimensions. Five major health-promoting life-style patterns were identified among older adults, depicting a heterogeneous group with varying needs for health promotion programming.

Attitudes, subjective norms, and intentions to engage in health behaviors.

The theory of reasoned action was used as the conceptual framework for analyzing the relationships among attitudes, subjective norms, and intentions to exercise regularly, maintain/attain recommended weight, and avoid highly stressful life situations. The sample (N = 377) consisted of adults between the ages of 18 and 66 living in two midwestern communities. Data were collected using a structured questionnaire designed according to guidelines developed by Ajzen and Fishbein (1980). The theory was supported in part by study results. Attitudes were useful in explaining intentions to engage in all three health behaviors studied. Subjective norms contributed only to the explanation of intentions to engage in regular exercise. Three factors, attitudes, subjective norms, and weight, affected intentions to engage in regular exercise, R = .364, p < .01. Attitudes, weight, and perceived health status were the principle determinants of intention to eat a diet consistent with weight control, R = .428, p < .001. Of the variables studied, only attitude was associated with intention to manage stress, R = .271, p < .01.

Gender differences in the psychosocial and cognitive correlates of physical activity among taiwanese adolescents: A structural equation modeling approach

This study examined gender differences in the factors related to physical activity in 832 Taiwanese adolescents. Differences in psychosocial and cognitive correlates were noted by gender group. Taiwanese adolescent girls reported lower physical activity self-efficacy and less perceived benefits and more perceived barriers to being active than boys. Girls compared to boys reported significantly more positive social support, modeling, and norms from parents to be active but significantly less social support and norms from their peers. Structural equation modeling was used to test the direct and indirect paths of a model of proposed correlates and physical activity. The results indicated that peer influences had both direct and indirect paths to physical activity for both genders. Among all examined variables, perceived self-efficacy was the strongest correlate of physical activity for these adolescents. The findings of this study provide information relevant to designing physical activity interventions targeted to Taiwanese adolescents.

Psychometric evaluation of the exercise self-efficacy scale among Korean adults with chronic diseases

The purpose of this study was to assess the psychometric properties, appropriateness, and demographic response patterns of an exercise self-efficacy scale for Korean adults with chronic diseases. After assessment of face validity by an expert Korean panel, 249 Korean adults with chronic diseases, ages 18-79 years, were recruited from hospitals or health centers in five Korean cities and surrounding rural areas to complete the questionnaire. In a factor analysis the original 18-item exercise self-efficacy scale converged to one factor without rotation and to three subfactors with rotation: situational/interpersonal factor, competing demands factor, and internal feelings factor. Descriptive analysis showed that Korean adults with chronic diseases perceived they had relatively low exercise self-efficacy, with the situational/interpersonal factor as the lowest factor. Exercise self-efficacy was significantly correlated with gender, education, regular exercise, and frequency of exercise. The exercise self-efficacy scale was shown to be a useful measure of exercise beliefs of Korean adults with chronic diseases.

Self-efficacy and perceived exertion of girls during exercise

BackgroundAn important national goal in Healthy People 2010 is to reduce the high prevalence of sedentary lifestyles and resultant overweight and obesity among girls. ObjectivesThe purpose of the present study was threefold: (a) to determine if pre-exercise self-efficacy predicted girls’ perceptions of exertion during exercise, (b) to determine if these perceptions, in turn, influenced postexercise self-efficacy, and (c) to assess if exercise self-efficacy increased following completion of an exercise task. MethodsA sample of 103 girls, 8 to 17 years of age, pedaled 20 minutes on a cycle ergometer at 60% of their predetermined peak VO2 in a climatic chamber (90°F, 50% relative humidity). Ratings of perceived exertion were obtained every 4 minutes. Exercise self-efficacy was assessed before and after the exercise session. ResultsControlling for peak VO2 and percent body fat, pre-exercise efficacy exerted an independent effect on perception of exertion during exercise with girls high on pre-exercise self-efficacy reporting lower perceived exertion during exercise, than girls low on self-efficacy. Both pre-exercise efficacy and perceived exertion explained postexercise efficacy. Exercise self-efficacy increased significantly from pre- to postexercise. ConclusionsPre-exercise efficacy is an important factor influencing girls’ perceptions of exertion during exercise and their postexercise efficacy. Increased exercise self-efficacy of girls following successful completion of an exercise challenge suggests possible strategies to increase physical activity.

A panel study of physical activity in Taiwanese youth: testing the revised health-promotion model.

The rate of inactivity among young people in Taiwan remains high. However, few studies have explored physical activity patterns with a longitudinal approach in this population. Based on the revised health-promotion model, this study used 2-wave panel data to test a structural model of how individual characteristics, cognitions, and interpersonal influences predicted physical activity of Taiwanese adolescents. The findings suggest that gender, social support, modeling, self-efficacy, and perceived benefits and barriers to performing physical activity directly and indirectly influence the behavior of physical activity in Taiwanese adolescents. The hypothesized model explained 25% of the variance in physical activity. The implications for parents and policy are discussed.