Search

Objective: This study compared, in treatment and control groups, the phenomena of coaction, which is the probability that taking effective action on one behavior is related to taking effective action on a second behavior., Methods: Pooled data from three randomized trials of Transtheoretical Model (TTM) tailored interventions (n=9461), completed in the U.S. in 1999, were analyzed to assess coaction in three behavior pairs (diet and sun protection, diet and smoking, and sun protection and smoking). Odds ratios (ORs) compared the likelihood of taking action on a second behavior compared to taking action on only one behavior., Results: Across behavior pairs, at 12 and 24 months, the ORs for the treatment group were greater on an absolute basis than for the control group, with two being significant. The combined ORs at 12 and 24 months, respectively, were 1.63 and 1.85 for treatment and 1.20 and 1.10 for control., Conclusions: The results of this study with addictive, energy balance and appearance-related behaviors were consistent with results found in three studies applying TTM tailoring to energy balance behaviors. Across studies, there was more coaction within the treatment group. Future research should identify predictors of coaction in more multiple behavior change interventions., (Published by Elsevier Inc.)

Objective: The major chronic diseases are caused by multiple risks, yet the science of multiple health behavior change (MHBC) is at an early stage, and factors that facilitate or impede scientists' involvement in MHBC research are unknown. Benefits and challenges of MHBC interventions were investigated to strengthen researchers' commitment and prepare them for challenges., Method: An online anonymous survey was e-mailed to listservs of the Society of Behavioral Medicine between May 2006 and 2007. Respondents (N=69) were 83% female; 94% held a doctoral degree; 64% were psychologists, 24% were in public health; and 83% targeted MHBC in their work., Results: A sample majority rated 23 of the 24 benefits, but only 1 of 31 challenge items, as very to extremely important. Those engaged in MHBC rated the total benefits significantly higher than respondents focused on single behaviors, F(1,69)=4.21, p<.05, and rated the benefits significantly higher than the challenges: paired t(57)=7.50, p<.001. The two groups did not differ in ratings of challenges., Conclusion: It appears that individuals focused solely on single behaviors do not fully appreciate the benefits that impress MHBC researchers; it is not that substantial barriers are holding them back. Benefits of MHBC interventions need emphasizing more broadly to advance this research area., (Copyright 2009 Elsevier Inc. All rights reserved.)

Objective: Risky behaviors such as smoking, alcohol abuse, physical inactivity, and poor diet are detrimental to health, costly, and often co-occur. Greater efforts are being targeted at changing multiple risk behaviors to more comprehensively address the health needs of individuals and populations. With increased interest in multiple risk factor interventions, the field will need ways to conceptualize the issue of overall behavior change., Method: Analyzing data from over 8000 participants in four multibehavioral interventions, we present five different methods for quantifying and reporting changes in multiple risk behaviors., Results: The methods are: (a) the traditional approach of reporting changes in individual risk behaviors; (b) creating a combined statistical index of overall behavior change, standardizing scores across behaviors on different metrics; (c) using a behavioral index; (d) calculating an overall impact factor; and (e) using overarching outcome measures such as quality of life, related biometrics, or cost outcomes. We discuss the methods' interpretations, strengths, and limitations., Conclusion: Given the lack of consensus in the field on how to examine change in multiple risk behaviors, we recommend researchers employ and compare multiple methods in their publications. A dialogue is needed to work toward developing a consensus for optimal ways of conceptualizing and reporting changes in multibehavioral interventions.

Objective: Rates of preventive counseling remain below national guidelines. We explored physician and patient predictors of preventive counseling across multiple cancer risk behaviors in at-risk primary care patients., Methods: We surveyed 3557 patients, with at least one of four cancer risk behaviors: smoking, diet, sun exposure, and/or mammography screening, at baseline and 24 months. Patients reported receipt of 4A's (Ask, Advise, Assist, Arrange follow-up); responses were weighted and combined to reflect more thorough counseling (Ask=1, Advise=2, Assist=3, Arrange=4, score range 0-10) for each target behavior. A series of linear-regression models, controlling for office clustering, examined patient, physician and other situational predictors at 24 months., Results: Risk behavior topics were brought up more often for mammography (90%) and smoking (79%) than diet (56%) and sun protection (30%). Assisting and Arranging follow-up were reported at low frequencies across all behaviors. More thorough counseling for all behaviors was associated with multiple visits and higher satisfaction with care. Prior counseling predicted further counseling on all behaviors except smoking, which was already at high levels. Other predictors varied by risk behavior., Conclusions: More thorough risk behavior counseling can be delivered opportunistically across multiple visits; doing so is associated with more satisfaction with care.

Background: Treating multiple health behavior risks on a population basis is one of the most promising approaches to enhancing health and reducing health care costs. Previous research demonstrated the efficacy of expert system interventions for three behaviors in a population of parents. The interventions provide individualized feedback that guides participants through the stages of change for each of their risk behaviors. This study extended that research to a more representative population of patients from primary care practice and to targeting of four rather than three behaviors., Methods: Stage-based expert systems were applied to reduce smoking, improve diet, decrease sun exposure, and prevent relapse from regular mammography. A randomized clinical controlled trial recruited 69.2% of primary care patients (N = 5407) at home via telephone. Three intervention contacts were delivered for each risk factor at 0, 6, and 12 months. The primary outcome measures were the percentages of at-risk patients at baseline who progressed to the action or maintenance stages at 24-month follow-up for each of the risk behaviors., Results: Significant treatment effects were found for each of the four behaviors, with 25.4% of intervention patients in action or maintenance for smoking, 28.8% for diet, and 23.4% for sun exposure. The treatment group had less relapse from regular mammography than the control group (6% vs. 10%)., Conclusion: Proactive, home-based, and stage-matched expert systems can produce relatively high population impacts on multiple behavior risks for cancer and other chronic diseases.

Background: Tailored interventions require the identification of distinct homogenous subgroups that will benefit from different intervention materials. One way to identify such subgroups is to use cluster analysis to identify an empirical typology., Methods: A sample of 346 adults completed surveys through a telephone interview that included questions related to participating in regular exercise. The three variables used in the cluster analysis were the Pros of Exercise, the Cons of Exercise, and Exercise Self-Efficacy., Results: Six resulting clusters were labeled Disengaged, Immotive, Relapse Risk, Early Action, Maintainers, and Habituated. A series of analyses tested the internal and external validity of the typology. The internal validity test revealed that four of the clusters demonstrated high stability and replicability, while the Relapse Risk and Early Action clusters were less stable. Differences among clusters on self-reported exercise behavior and a strong association with stage of change for regular exercise provided external validity evidence of the typology., Conclusions: The resulting typology reflects a range of motivational patterns that are likely to be responsive to different types of messages and strategies regarding adoption and maintenance of regular exercise. The typology also generates a number of hypotheses about the identified clusters that can be empirically tested in further studies.

Background: Children's exposure to environmental tobacco smoke (ETS) is unacceptably high; almost 40% of children in the United States are regularly exposed to ETS., Methods: This paper presents a review of the literature that evaluates interventions designed to reduce ETS exposure among young children. In addition, it presents the study design for Project KISS (Keeping Infants Safe from Smoke), an intervention designed to utilize exposure-related feedback to increase parents' motivation for ETS reduction and to reduce household ETS levels. Baseline data are presented to illustrate factors that should be addressed in ETS interventions., Results: The literature review demonstrates the dearth of studies in the literature targeting ETS reduction among children. Participants in Project KISS believed that smoking had affected their children's health and were in later stages of motivational readiness to quit smoking than is typically observed. However, they face a number of challenges to smoking, such as high prevalence of nicotine dependence, high prevalence of living with other smokers, and socioeconomic and stress-related barriers., Conclusions: The policy implications of this research are discussed, and recommendations are made for future research., (Copyright 2001 American Health Foundation and Academic Press.)

Background: Previous research has demonstrated the efficacy of an interactive expert system intervention for smoking cessation for a general population. The intervention provides individualized feedback that guides participants through the stages of change for cessation. Enhancing the expert system by adding proactive telephone counseling or a stimulus control computer designed to produce nicotine fading could produce preventive programs with greater population impacts., Methods: Four interventions were compared: (a) the interactive expert system intervention; (b) the expert system intervention plus counselor calls; (c) the expert system intervention plus the stimulus control computer; and (d) an assessment only condition. A 4 (intervention) x 4 (occasions) (0,6,12, and 18 months) design was used. Smokers were contacted at home via telephone or mail. The initial subject pool was the 24,178 members of a managed care company. Screening was completed for 19,236 members (79.6%), of whom 4,653 were smokers; 85.3% of the smokers were enrolled., Results: Thirty-eight percent were in the precontemplation stage, 45% in the contemplation stage, and only 17% in the preparation stage. At 18 months, the expert system resulted in 23.2% point prevalence abstinence, which was 33% greater than that of assessment only. The counselor enhancement produced increased cessation at 12 months but not at 18 months. The stimulus control computer produced no improvement, resulting in 20% worse cessation rates than the assessment only condition., Conclusions: The enhanced conditions failed to outperform the expert system alone. The study also demonstrated the ability of the interactive expert system to produce significantly greater cessation in a population of smokers than assessment alone., (Copyright 2000 American Health Foundation and Academic Press.)

Background: Research on cognitive factors and motivational readiness for exercise is important for increasing our understanding of behavior change among those with sedentary lifestyles. This study examines stage of change for regular exercise and self-perceived quality of life., Methods: Data are from 1,387 respondents to a random digit dial survey of health behaviors. Stage of change is assessed with a single item, and individuals are classified with respect to intention and exercise behavior. Quality of life is assessed with the SF-36, a multidimensional measure of health-related quality of life., Results: Exercise stage is associated with self-perceived quality of life. The three areas most strongly related were physical functioning, general health perceptions, and vitality. Physical functioning scores were lowest in precontemplation and highest in maintenance. Vitality and mental health scales were related to exercise behavior, but not to intention., Conclusions: Cognitions about self-perceived quality of life vary across the stages of change, with those who are least prepared to adopt regular exercise reporting the lowest levels of quality of life. These findings suggest that cognitive-motivational messages designed to emphasize quality of life benefits associated with exercise may be useful intervention strategies for people who are less motivationally ready to change., (Copyright 1999 American Health Foundation and Academic Press.)

Background: A key variable for the design of individual and public health interventions is the Stage of Change. The five stages of readiness to change are Precontemplation, Contemplation, Preparation, Action, and Maintenance. The distribution of individuals across the stages of change can provide a valuable tool for designing health interventions., Methods: The pattern of distribution across the stages of change for five behavioral risk factors is presented from five independent surveys, two from the United States and three from Australia. The five risk factors are smoking, low fat diet, regular exercise, reducing stress, and losing weight. Identical single-item questionnaire items for staging health behaviors were used in all surveys., Results: The stage distributions for the five risk factors were similar across the five independent samples. In general, the pattern of stage distributions was stable across health risk factors, gender, country, and sample., Conclusions: Single-item survey measures of stage of change that are readily applicable to population studies appear to provide important information about the population characteristics of readiness to change behavioral risk factors. The stability of these distributions suggests that interventions matched by stage may have broad applicability.

Background: Tailoring is a promising technique for encouraging greater performance of health-related behaviors. Tailored interventions are designed to be more individualized to personal characteristics, in contrast to "standard" interventions where all participants receive the same materials., Methods: A total of N = 1864 women aged 40-74 were recruited from a staff model HMO and randomly assigned to one of three intervention groups: (a) No Educational Materials, (b) Standard Materials, and (c) Stage-Matched Materials. A provider-directed component was common across all three conditions. The Standard and Stage-Matched groups each received two mailed educational packets after baseline and follow-up telephone interviews. The Stage-Matched intervention was based on the Transtheoretical Model of behavior change., Results: Analyses of n = 1397 women (after all attrition) showed that receipt of mammography after the baseline interview was higher for the Stage-Matched group (63.6%) than for the No Materials group (54.9%; OR = 1.43, 95% CI = 1.10, 1.86). The Standard intervention group was intermediate (58. 5%). The Standard group did not differ from the No Materials group, but did differ from the Stage-Matched group in multivariate analysis., Conclusions: Stage-matched, tailored materials may be a means to encourage screening mammography. Such interventions can be implemented by telephone and mail., (Copyright 1998 American Health Foundation and Academic Press.)

Objectives: A key variable for the design of individual and public health interventions for smoking cessation is Stage of Change, a variable which employs past behavior and behavioral intention to characterize an individual's readiness to change. Reactively recruited samples distort estimates of the stage distribution in the population because such samples attract a disproportionate number of late-stage participants. Three representative samples are described which provide accurate estimates of the stage distribution in the population. These samples are of adequate size to permit within-sample comparisons with respect to sex, age, Hispanic or non-Hispanic origin, race, and education level. The implications of using stage distribution as a tool for planning intervention is discussed., Method: The first sample of 4,144 smokers was from the state of Rhode Island and involved a random-digit-dial survey. The second sample of 9,534 smokers was from the state of California and involved a stratified random-digit-dial survey. The third sample of 4,785 smokers was from a total of 114 worksites located in four different geographic locations., Results: The stage distributions were approximately identical across the three samples, with approximately 40% of the sample in Precontemplation, 40% in Contemplation, and 20% in Preparation. The stage distribution was generally stable across age groups with the exception of the 65 years and older group. Education level did affect the stage distribution with the proportion of the sample in Precontemplation decreasing as education level increased. In all three samples, minor differences in stage distribution were related to Hispanic origin and race, but the pattern was not consistent across the samples., Conclusions: The pattern of stage distribution has important implications for the design of interventions. Existing interventions are most appropriate for the Preparation stage, but the majority of the three samples were in the first two stages, resulting in a likely mismatch between the smoker and the intervention. The stability of distribution across age suggests that interventions that are appropriately matched to stage can be applied across all age groups. The differences found with respect to education, Hispanic origin, and race can serve as a guide to the tailoring of intervention materials.

Many self-reported measures of health status, attitudes, and knowledge used by clinicians and researchers suffer from a variety of shortcomings, including limited empirical justification, excessive complexity, assessments of nonmodifiable historic or hereditary factors, and limited utility for public health program planning. The Health Attitudes and Behavior Scale is an instrument designed to overcome many of these shortcomings and direct public health professionals toward more efficacious interventions. One hundred sixty-four subjects responded to true-false and Likert scale items related to health beliefs, attitudes, and behavioral practices. A principal component analysis of the Likert items yielded six components, tentatively labeled (a) Lack of Social Support, (b) Hurdles to Health, (c) Health Attitudes/Weight Concerns, (d) Positive Environment, (e) Disease Concerns, and (f) Time and Work Pressure. Analyses of these scales using coefficient alpha indicated adequate internal consistency for each of them. These scales were then related to demographic variables of age, educational level, sex, and marital status. Next, these scales were correlated with individual true-false items reflecting self-reported behavioral practices or health histories. A component analysis of the true-false items yielded four principal components labeled (a) Organizational Health Concerns, (b) Smoking and Exercise Concerns, (c) Coronary and Weight Concerns, and (d) Blood Pressure and Risk Factor Programs. Finally, a cluster analysis yielded six typical profiles reflecting different levels of the original six components. Of interest is the fact that the Lack of Social Support and Time and Work Pressure scales had a very limited integration into the overall patterns. The assumption that organizational and environmental factors can have an important impact on health was supported. The need for further research in this area is also discussed.