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Logo of nihpaAbout Author manuscriptsSubmit a manuscriptHHS Public Access; Author Manuscript; Accepted for publication in peer reviewed journal;
 
Prev Med. Author manuscript; available in PMC 2011 January 1.
Published in final edited form as:
PMCID: PMC2813890
NIHMSID: NIHMS165421

The Benefits and Challenges of Multiple Health Behavior Change in Research and in Practice

Abstract

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 emailed 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; 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 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.

Keywords: multiple risks, health behavior change, interventions

Risky behaviors such as smoking, alcohol abuse, physical inactivity, and poor diet are detrimental to health and often co-occur. Most US adults meet criteria for multiple risk behaviors (Fine et al., 2004). Multiple risks multiply the healthcare burden both in terms of medical consequences and costs (Edington et al., 1997, Shinton, 1997).

There is an identified need for theoretical models, research paradigms and intervention infrastructure that cut across health behaviors (Orleans, 2004). A recent review concluded that “large gaps remain in our knowledge about the efficacy of interventions to address multiple behavioral risk factors” (Goldstein et al., 2004).

Intervening on single behaviors can be complex and challenging – treating multiple behaviors is even more so. To adequately inform new investigators and address barriers systematically, an understanding is needed of the benefits and challenges to multiple health behavior change (MHBC) interventions. Knowledge of the benefits serves to strengthen one’s rationale and commitment, whereas knowledge of the barriers serves to prepare one for the anticipated challenges (Janis and Mann, 1977). We define MHBC interventions as efforts to treat two or more health behaviors either simultaneously or sequentially within a limited time period (Prochaska and Prochaska, 2008). In working to identify a consensus, the findings may be useful for informing future research needs and facilitative efforts in the MHBC field.

Given the early stage of MHBC research, the study aims were primarily descriptive. We anticipated respondents who address multiple health behaviors would (1) rate the benefits of MHBC research more highly than respondents focused solely on singular risks and (2) weight the benefits of MHBC research significantly higher than the challenges.

Methods

Measurement Development

Members of the Society of Behavioral Medicine’s (SBM) Special Interest Group (SIG) on MHBC contributed to the initial list of benefits and challenges via group nominations during a SIG meeting and were invited to provide additional suggestions via the MHBC SIG listserv. Three experts in MHBC (JJP, CRN, BS) reviewed the complete list, identified main themes, deleted redundancies, and edited items to minimize double-barreled and unclear statements. The resulting survey was pilot tested with six individuals from the intended audience, and the survey was revised in response to pilot feedback.

The final measure consisted of 31 challenge items and 24 benefit items rated using 5-point Likert scales ranging from “not important” (coded 1) to “extremely important” (coded 5). For survey organization, the items were grouped into categories of Outreach and Approach, Settings and Systems, Client/Target Market, Theory Development and Testing, and Research Implementation. For analyses, the items were averaged in two scales with high internal consistency: Cronbach alphas .93 for benefits and .95 for challenges.

Data Collection

The University of California, San Francisco Institutional Review Board approved conduct of the study. Data were collected via a secure online survey between May 2006 and May 2007. Item ordering was random for each participant to prevent response bias. The online survey link was emailed to listservs for SBM’s MHBC, Physical Activity, Evidence-Based Behavioral Medicine, Obesity, and Cancer SIGS and to researchers identified as publishing on MHBC. Respondents could answer the survey anonymously.

Results

Sample Characteristics

Of the 83 individuals who started the online survey, 71 completed all rating scale items, and 69 finished the survey in entirety. The sample was 83% female, 88% Caucasian, 9% Hispanic, and 3% Asian/Pacific Islander; 94% held a doctoral degree. The sample averaged 10.1 years (SD = 9.4, Range 0–37) since completing their terminal degree and 8.9 years (SD = 9.6, Range 0–42) of addressing MHBC in their research or practice. Less than half (42.9%) were MHBC SIG members; an additional 11% expressed interest in joining. Respondents identified their discipline(s) as psychology (64%), public health (24%), nursing (9%), medicine (3%), social work (1%), or other (10%). Primary work responsibilities were research (87%), teaching (24%), clinical practice (14%), and other (4%).

Respondents targeted a range of behaviors with most (83%) engaged in MHBC research or practice (Table 1). Compared to individuals focused on singular risks, individuals focused on MHBC were significantly more likely to target tobacco (χ2(1) = 7.61, p<.01), nutrition (χ2(1) = 11.66, p<.01), and stress management (χ2(1) = 10.77, p<.001). Respondents focused on MHBC were significantly more likely to apply the Transtheoretical Model than respondents focused solely on single behaviors (χ2(1) = 4.87, p<.05). No other theoretical approach distinguished MHBC versus single behavior change researchers (Table 1). Among the 58 respondents engaged in MHBC, 26 (44.8%) targeted MHBC with individuals, 16 (27.6%) with populations, and 16 (27.6%) with both individuals and populations. Among those engaged in MHBC, 28 (48.3%) also did work focused on single behavior change.

Table 1
Percent of Respondents to an Online Survey Conducted May 2006–2007 Endorsing Application of Specific Theories and Targeting Specific Health Behaviors by Whether Respondents’ Focus Includes Multiple Health Behavior Change or is Solely on ...

Ratings of Benefits and Challenges

Table 2 presents the mean ratings of each of the 55 benefit and challenge items shown in order from highest rated to lowest and the percent of the sample rating the item a 4 or 5 (very to extremely important). The highest rated 19 items were perceived benefits and the lowest rated 16 items were perceived challenges. A majority of respondents rated 23 of the 24 benefits and 1 of the 31 challenges as very to extremely important.

Table 2
Benefits (B) and Challenges (C) to Multiple Health Behavior Change Interventions Identified by Individuals Engaged in Behavioral Medicine Research and Practice Responding to an Online Survey Conducted May 2006–2007

Respondents engaged in MHBC research or practice rated the total benefits of MHBC interventions (M = 3.81, SD = .48) significantly higher than those focused on single behavior change (M = 3.46, SD = .78), F(1,69) = 4.21, p<.05. There was no significant difference in rated challenges: M = 2.98, SD = .74 for MHBC respondents and M = 3.11, SD = .61 for respondents focused on single behavior change, F(1,69) = 0.32, ns.

Correlations between the benefits and challenges total scales approached zero for respondents focused on MHBC (r = .08) and those focused on single behavior change (r = -.01), indicating the two scales measured different constructs.

The benefits of MHBC interventions were rated significantly higher than the challenges, paired samples t(70) = 7.06, p<.001. When examined by group, the finding was specific to respondents engaged in MHBC: t(57) = 7.50, p<.001 for MHBC respondents and t(11) = 1.23, p = .246 for respondents focused on single behavior change.

The rated benefits and challenges did not differ by whether respondents were MHBC SIG members (p-values>.450).

Discussion

Risk behaviors tend to co-occur. Strategies that target multiple health behaviors for change may optimize delivery efficiency and impacts on health. The current study identified leading benefits and challenges to MHBC interventions as perceived by individuals engaged in behavioral medicine research and practice. The developed measure had an identifiable factor structure that corresponded to the benefits and challenges of MHBC. The findings may be useful for informing future research needs and directions.

Professionals engaged in MHBC gave significantly higher ratings to the benefits of this area of investigation relative to individuals focused on single behavior change. The two groups did not differ in their ratings of the perceived challenges. It appears that individuals focused solely on single behavior change have not fully bought into the benefits that impress MHBC researchers; it is not that there are substantial barriers holding them back. Respondents focused on single behavior change rated the benefits and challenges of MHBC equally; whereas, respondents engaged in MHBC rated the benefits significantly higher than the challenges.

Overall, a sample majority rated nearly all the benefits as very to extremely important, whereas, only one barrier was rated as very to extremely important – the challenge of developing integrated delivery systems for health behavior change. The highest rated benefits centered on the potential for greater real-world applicability for patients, healthcare, and affiliated systems; greater health improvements; and providing information on effective treatments for behaviors that co-occur. Though individuals engaged in MHBC rated the benefits as greatly outweighing the challenges, it is noteworthy that the MHBC SIG members nominated a greater number of challenges (31 items) than benefits (24 items).

In terms of theory, respondents engaged in MHBC were more likely to apply the Transtheoretical Model than those focused solely on singular risks. Developed in the area of smoking cessation, the Transtheoretical Model has demonstrated relevance to over 48 problem or target behaviors (Hall and Rossi, 2008) and may be particularly well suited to MHBC interventions (e.g., Prochaska et al., 2005; Prochaska et al., 2006). Social Cognitive Theory also was highly endorsed with application to both single and multiple risk behavior change.

Study limitations were the under-recruitment of professionals from health disciplines other than psychology and public health and those focused solely on singular risks. No monetary incentive for survey completion was offered. Those focused on singular risks may have been less interested in taking time to participate in a MHBC survey.

MHBC interventions offer great potential for advancing health promotion and disease prevention science and practice. A better understanding of the perspectives of early adopters may help support the growth and expansion of MHBC research. MHBC respondents averaged 8 years of experience in targeting multiple risks, and the response rate among MHBC SIG members (which numbered 49 in 2006) was 61%. In 2009, the MHBC SIG membership was 239 demonstrating impressive growth in interest in the field aided by support from leading funding agencies and the scientific community provided by groups like SBM. MHBC interventions offer the potential for greater real-world applicability and impacts on health. Broader promotion of the benefits of MHBC interventions may be key to expanding this research area.

Acknowledgments

We acknowledge the Society of Behavioral Medicine Special Interest Group on Multiple Health Behavior Change and the survey respondents who shared their perspectives. We acknowledge the funding support of the National Institute on Drug Abuse (#K23 DA018691, #P50 DA09253, #R01 DA020112, #R01 DA022291), the National Institute of Mental Health (#R01MH083684), the National Cancer Institute (#R01 CA109941, #R01 CA119195, #R01 CA85807), the National Institute on Aging (R01AG024490), and the State of California Tobacco-Related Disease Research Program (#17RT-0077).

Footnotes

Publisher's Disclaimer: This is a PDF file of an unedited manuscript that has been accepted for publication. As a service to our customers we are providing this early version of the manuscript. The manuscript will undergo copyediting, typesetting, and review of the resulting proof before it is published in its final citable form. Please note that during the production process errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain.

Contributor Information

Judith J. Prochaska, Founding chair of the Society of Behavioral Medicine’s (SBM) Special Interest Group on Multiple Health Behavior Change (MHBC), is in the Department of Psychiatry at the University of California, San Francisco.

Claudio R. Nigg, Co-chair of the SBM Special Interest Group on MHBC and is in the Department of Public Health Sciences at the University of Hawaii at Manoa.

Bonnie Spring, Former co-chair of the SBM Special Interest Group on MHBC and former SBM President, is in the Departments of Preventive Medicine, Psychology, and Psychiatry at Northwestern University.

Wayne F. Velicer, Founding chair of the SBM Special Interest Group on MHBC is with the Cancer Prevention Research Center at the University of Rhode Island.

James O. Prochaska, Cancer Prevention Research Center at the University of Rhode Island.

References

  • EDINGTON DW, YEN LT, WITTING P. The financial impact of changes in personal health practices. J Occup Environ Med. 1997;39:1037–46. [PubMed]
  • FINE LJ, PHILOGENE GS, GRAMLING R, COUPS EJ, SINHA S. Prevalence of multiple chronic disease risk factors. 2001 National Health Interview Survey. Am J Prev Med. 2004;27:18–24. [PubMed]
  • GOLDSTEIN MG, WHITLOCK EP, DEPUE J. Multiple behavioral risk factor interventions in primary care. Summary of research evidence. Am J Prev Med. 2004;27:61–79. [PubMed]
  • HALL KL, ROSSI JS. Meta-analytic examination of the strong and weak principles across 48 health behaviors. Prev Med. 2008;46:266–74. [PubMed]
  • JANIS IL, MANN L. Decision-Making: A Psychological Analysis of Conflict, Choice and Commitment. New York: Free Press; 1977.
  • ORLEANS CT. Addressing multiple behavioral health risks in primary care. Broadening the focus of health behavior change research and practice. American Journal of Preventive Medicine. 2004;27:1–3. [PubMed]
  • PROCHASKA JJ, PROCHASKA JM. Multiple risk behavior change: what most individuals need. In: OKENE J, RIEKERT K, SHUMAKER S, editors. The Handbook of Health Behavior Change. 3. New York: Springer Publishers; 2008.
  • PROCHASKA JJ, VELICER WF, PROCHASKA JO, DELUCCHI K, HALL SM. Comparing intervention outcomes in smokers treated for single versus multiple behavioral risks. Health Psychol. 2006;25:380–8. [PubMed]
  • PROCHASKA JO, VELICER WF, REDDING C, ROSSI JS, GOLDSTEIN M, DEPUE J, GREENE GW, ROSSI SR, SUN X, FAVA JL, LAFORGE R, RAKOWSKI W, PLUMMER BA. Stage-based expert systems to guide a population of primary care patients to quit smoking, eat healthier, prevent skin cancer, and receive regular mammograms. Preventive Medicine. 2005;41:406–16. [PubMed]
  • SHINTON R. Lifelong exposures and the potential for stroke prevention: the contribution of cigarette smoking, exercise, and body fat. J Epidemiol Community Health. 1997;51:138–43. [PMC free article] [PubMed]