Initial efficacy of MI, TTM tailoring and HRI’s with multiple behaviors for employee health promotion
Introduction
Increasingly it is recognized that a major barrier to dissemination of evidence-based health promotion programs is that most programs were not designed or developed to reach at-risk populations (Glasgow et al., 2003). They were designed for and evaluated on self-selected samples of at-risk individuals. For example, in the United States Public Health Services 1996 Clinical Guidelines for the Treatment of Tobacco, over 3000 studies on tobacco were identified. The guidelines were able to recommend a broad range of evidence-based interventions for motivated smokers; i.e., those prepared to quit in the next month (Fiore et al., 1996). There were no evidence-based interventions recommended for unmotivated smokers, even though they make up more than 80% of all U.S. smokers (Velicer et al., 1995) and more than 90% of daily smokers (Wewers et al., 2003). In the second edition of the guidelines there were over 6000 studies identified (Fiore et al., 2000). These evidence-based treatments were not designed to reach the vast majority of unmotivated smokers.
When health care systems disseminate free, evidence-based smoking cessation clinics for motivated smokers, the percentage of smokers who participate nationally is 1% (Lichtenstein and Hollis, 1992). When states issue Requests For Proposals (RFPs) to deliver for free, evidence-based quit lines recommended by CDC, they typically budget for one quarter of 1% of smokers using the programs each year (our analysis of four RFPs). Our project applied health promotion interventions that were developed and evaluated with unmotivated as well as motivated populations since these are the types of programs that can have the most impact.
MI was originally developed for addictions counseling in the 1980s and is described as a “directive [goal-oriented], client-centered counseling style for eliciting behavior change by helping clients to explore and resolve ambivalence” (Miller and Rollnick, 2002). This approach has been found to produce significant efficacy across a broad range of health risk behaviors including alcohol abuse, smoking, high-risk sexual behaviors, exercise, and diet (Burke et al., 2003, Hettema et al., 2005). MI-based health coaching has also been found to improve physical and mental health status in a worksite setting (Butterworth et al., 2006). In most MI studies, however, only a single risk behavior has been targeted at one time. The present study is the first to apply MI-based health coaching simultaneously to four health risks in a worksite setting.
TTM-tailored print feedback has been found to be effective with a broad range of single health behaviors including smoking (e.g., Prochaska et al., 1993, Prochaska et al., 2001a, Prochaska et al., 2001b), stress (Evers et al., 2006), medication adherence (Johnson et al., 2006a, Johnson et al., 2006b), mammography (Rakowski et al., 1998), diet (Greene et al., in press), sun protection (Weinstock et al., 2002), exercise (Marcus et al., 1998, Velicer et al., 2006), and depression (Levesque and VanMarter, 2007). TTM-tailored print feedback has also been found effective when treating: (1) three health behaviors in a population of parents whose teens were participating in health promotion at school (Prochaska et al., 2004); (2) four behaviors in a population of primary care patients (Prochaska et al., 2005); 3) three behaviors in a population of patients with diabetes (Jones et al., 2003); and (4) three behaviors in a population of overweight individuals (Johnson et al., in press). Comparable TTM-tailored feedback has also been presented in a multimedia format (Redding et al., 1999), but not yet online.
This project is the first time that TTM tailoring was delivered online to a population of adults. This project is also the first time that MI delivered in person and telephonically was compared to TTM tailoring.
This report is part of the first randomized population trial to be based on impact on multiple behaviors. The original impact equation was reach (percent participating) times efficacy (percent who change). Our first report compared three additive recruitment strategies to enhance reach: 1. persuasive communications; 2. persuasive communications plus small incentives; and 3. both of these plus person-to-person telephone outreach (Butterworth et al., 2007). This report compares the initial efficacy of three interventions (health risk assessment and intervention only (HRI), online HRI plus Transtheoretical Model-tailored communications (TTM), and online HRI plus Motivational Interviewing-based health coaching (MI)) targeting four health risks: stress, exercise, smoking, and BMI.
Section snippets
Procedure
Prior to recruitment, a random sample of N = 6000 employees at a major medical university were randomly assigned to one of three additive recruitment strategies (mail/email only, mail/email + incentive, and mail + incentive + phone prompt) and to one of three treatment groups (HRI, MI, and TTM). Employees in recruitment group 1 received a persuasive letter and email inviting them to participate in the study. Employees in recruitment group 2 received the same letter and email plus a small incentive for
Participants
After random assignment to recruitment/treatment groups, the following sample was recruited. Approximately N = 1730 employees responded to the letters/emails and N = 1400 were eligible and completed the online baseline assessment. A total of 25% of eligible employees were recruited across the three additive recruitment strategies (Butterworth et al., 2007). A total of 23.3% (N = 464) were recruited to the HRI only condition, 21.7% (N = 433) to the MI treatment, and 25.2% (N = 504) to the online
Discussion
This study generated a series of important results. It is the first study we could find demonstrating MI to produce significant efficacy on at least two behaviors when simultaneously treating multiple behaviors within a population. The results are particularly important given how widely MI has been disseminated and the fact that it has been found to be more effective with less ready and less motivated participants as well as those prepared to act. It is also worthy to note that there were only
Future research
Future reports will include analyses of outcomes over longer term follow-ups. These reports will include outcomes based on recent advances in assessing impact for multiple behavior change (Prochaska et al., 2007). Such impact analyses take into account recruitment, participation, and efficacy rates summed across all treated behaviors. Such impact analyses are best applied over longer term follow-ups to take into account treatment trajectories on different risk behaviors that may be increasing,
Acknowledgment
This study was supported by CDC Grant 1 RO1 DP000103 to Susan Butterworth, Ph.D.
References (38)
- et al.
Evaluating a population-based recruitment approach and a stage-based expert system intervention for smoking cessation
Addict. Behav.
(2001) - et al.
Counselor and stimulus control enhancements of a stage-matched expert system intervention for smokers in a managed care setting
Prev. Med.
(2001) - et al.
Stage-based expert systems to guide a population of primary care patients to quit smoking, eat healthier, prevent skin cancer, and receive regular mammograms
Prev. Med.
(2005) - et al.
Increasing mammography among women aged 40–74 by use of a stage-matched, tailored intervention
Prev. Med.
(1998) - et al.
Transtheoretical individualized multimedia expert systems targeting adolescents' health behaviors
Cogn. Behav. Pract.
(1999) - et al.
Applying the transtheoretical model to regular moderate exercise in an overweight population: validation of a stages of change measure
Prev. Med.
(2001) - et al.
Distribution of smokers by stage in three representative samples
Prev. Med.
(1995) - et al.
Randomized controlled community trial of the efficacy of a multicomponent stage-matched intervention to increase sun protection among beachgoers
Prev. Med.
(2002) - et al.
Distribution of daily smokers by stage of change: Current Population Survey results
Prev. Med.
(2003) - et al.
The efficacy of motivational interviewing: a meta-analysis of controlled clinical trials
J. Consult. Clin. Psychol.
(2003)
The effect of motivational interviewing-based health coaching on employees' physical and mental health status
J. Occup. Health Psychol.
Both smoking reduction with nicotine replacement therapy and motivational advice increase future cessation among smokers unmotivated to quit
J. Consult. Clin. Psychol.
The process of smoking cessation: an analysis of precontemplation, contemplation and preparation stages of change
J. Consult. Clin. Psychol.
A randomized clinical trial of a population- and transtheoretical model-based stress-management intervention
Health Psychol.
Smoking Cessation, Clinical Practice Guideline 18 (No. 96-0692)
Treating Tobacco Use and Dependence, Clinical Practice Guideline
Why don't we see more translation of health promotion research to practice? Rethinking the efficacy-to-effectiveness transition
Am. J. Public Health
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