Multiple Health Behavior Research represents the future of preventive medicine

doi:10.1016/j.ypmed.2008.01.015

Preventive Medicine

Volume 46, Issue 3, March 2008, Pages 281-285

https://doi.org/10.1016/j.ypmed.2008.01.015 Get rights and content

Abstract

Given the disease and cost burdens, Multiple Health Behavior Research represents the future of preventive medicine. Growing evidence in this special issue and beyond indicates that simultaneous and sequential interventions can be effective. The challenge for the future is to make such interventions more effective, cost effective and less demanding. Co-variation represents one innovative approach in which effective change on one treated behavior increases the odds of effective action on a second targeted behavior. Co-variation can occur when all behaviors received full treatment, when one receives full treatment and the others receive minimal treatment and when only one behavior is treated and others co-vary without treatment. Integrative treatments represent another innovation in which higher order constructs drive change on multiple behaviors related to the construct and treatment has to be only on one higher order behavior. A more integrated approach to research and practice involves new paradigms complementing established paradigms. Multiple behaviors proactively treated in populations at home or work by computer-based and stage-based interventions designed to generate co-variation that produces greater impacts can complement traditional paradigms that treat single behaviors in individual patients in clinics by clinicians with action-oriented modular interventions designed for specific behaviors to produce significant efficacy. More inclusive research to support more inclusive practices can hopefully lead to more inclusive care.

Section snippets

Simultaneous MHBR

Until recently, there was no programmatic research demonstrating the effectiveness of interventions designed to simultaneously change two or more target behaviors. Hyman et al. (2007) found that simultaneous intervention was more effective for physical activity and diet, while Spring et al. (2004) demonstrated sequentially targeting weight after smoking cessation may provide more benefit. In this issue, three articles (Johnson et al., 2008, Prochaska et al., 2008, Prochaska et al., 2007,

Co-variation

Co-variation occurs when taking effective action on one behavior increases the odds of taking effective action on a second behavior. This phenomenon is different from co-occurrence where groups of particular behaviors are more likely to have higher prevalence in particular populations, such as the research in this issue by deVries et al. (2008), Sanchez et al. (2008), and Keller et al. (2008). Co-variation reflects behaviors changing together rather than behaviors occurring together.

Integrative approaches

Most effective MHBR interventions have applied modular approaches, where each target behavior is treated by a module, such as fully tailored communications for each behavior, plus a multiple behavior self-help manual. The assumption is that behavior change is construct-driven and interventions are expected to work best when a construct, such as stage of change, is specific to a given behavior. But a modular approach can be very demanding. With tailored interventions, each construct that is

Common factor approach

In this issue, Noar et al. (2007), discusses a behavior change principle approach which suggests that interventions should teach individuals common principles of behavior change, as well as how to apply those principles to a variety of health behaviors. The common factor approach draws heavily on the type of integrative research of Hall and Rossi (2008) who demonstrate remarkable principles of relating the pros and cons of changing to the stages of change for 48 different behaviors. Another

Toward greater integration

Preventive medicine suffers from fragmentation like the rest of medicine. There is too much information and not enough knowledge. Information is not knowledge; it is the integration of information that is knowledge. In this issue, Hall and Rossi's meta-analysis is a wonderful example of knowledge where hundreds of thousands of bits of information from 140 data sets on 48 behaviors from 10 countries are integrated and presented in one elegant graph. Further integration is provided by two

New paradigms complementing established paradigms

This special issue reflects how new paradigms are beginning to complement established paradigms of preventive medicine and health promotion. Multiple behavior change complements single behavior change. Computer-based interventions are complementary to clinician-based treatment, with three of the studies reported in this issue applying computer-based and two calling on clinicians (DePue et al., 2008, Prochaska et al., 2008). Two studies used clinic-based interventions (DePue et al., 2008,

Conclusion

Multiple Health Behavior Research can help create a more integrated approach to research and practice in which new paradigms complement established paradigms. The new paradigms include multiple behaviors proactively treated in populations at home or work by computer-based and stage-based interventions designed to generate co-variation which can produce greater impacts. More inclusive research to support more inclusive practice can lead to a future of more inclusive care.

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This study identified clusters of chronic disease risks and explored associations between clusters and demographic characteristics and mental health conditions, among people accessing community mental health services. Data from a cross-sectional telephone survey of Australian mental health consumers (n = 567) were analysed. Clusters were identified based on tobacco smoking (53.5%), harmful chronic alcohol consumption (20.1%), harmful acute alcohol consumption (43.5%), inadequate fruit and vegetable intake (66.0%), inadequate physical activity (75.5%), inadequate strength activity (81.8%), and high body mass index (BMI) (67.9%), using latent class analysis. Multinomial logistic regression examined associations between cluster membership and participant characteristics. Three groups were identified: Cluster 1 (19.05%) had < 0.5 probabilities for most risks; Cluster 2 (34.04%) had high probabilities of all risks, particularly tobacco smoking and both types of harmful alcohol consumption; and Cluster 3 (46.91%) had high probabilities of both inadequate physical and strength activity, inadequate fruit and vegetable intake, and high BMI. Compared to Cluster 1 membership, participants with higher education were less likely to be in either Cluster 2 or 3, females or those over 55 were more likely to be in Cluster 3, those with a substance use disorder were more likely to be in Cluster 2, and those with a personality disorder were less likely to be in Cluster 3. The clustering patterns reinforce the importance of addressing multiple chronic disease risks for people with a mental health condition. Preventive care interventions targeting clusters of risks may help reduce the burden of chronic disease among this high-risk population.
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ReviewMultiple Health Behavior Research represents the future of preventive medicine

Abstract

Section snippets

Simultaneous MHBR

Co-variation

Integrative approaches

Common factor approach

Toward greater integration

New paradigms complementing established paradigms

Conclusion

Prev. Med.

Prev. Med.

Prev. Med.

Prev. Med.

Am. J. Prev. Med.

Am. J. Prev. Med.

Prev. Med.

Prev. Med.

Prev. Med.

Prev. Med.

Prev. Med.

Prev. Med.

Review
Multiple Health Behavior Research represents the future of preventive medicine