Elsevier

Preventive Medicine

Volume 50, Issues 1–2, January–February 2010, Pages 30-34
Preventive Medicine

Are effects from a brief multiple behavior intervention for college students sustained over time?

https://doi.org/10.1016/j.ypmed.2009.12.010Get rights and content

Abstract

Objective

This study examined whether 3-month outcomes of a brief image-based multiple behavior intervention on health habits and health-related quality of life of college students were sustained at 12-month follow-up without further intervention.

Methods

A randomized control trial was conducted with 303 undergraduates attending a public university in southeastern US. Participants were randomized to receive either a brief intervention or usual care control, with baseline, 3-month, and 12-month data collected during fall of 2007.

Results

A significant omnibus MANOVA interaction effect was found for health-related quality of life, p = 0.01, with univariate interaction effects showing fewer days of poor spiritual health, social health, and restricted recent activity, p's < 0.05, for those receiving the brief intervention. Significant group by time interaction effects were found for driving after drinking, p = 0.04, and moderate exercise, p = 0.04, in favor of the brief intervention. Effect sizes typically increased over time and were small except for moderate size effects for social health-related quality of life.

Conclusion

This study found that 3-month outcomes from a brief image-based multiple behavior intervention for college students were partially sustained at 12-month follow-up.

Introduction

National longitudinal data indicate that the majority of health behaviors and health-related indicators worsen as adolescents age into young adulthood (Harris et al., 2006). Other national epidemiologic data indicate that the majority of adolescents (Eaton et al., 2006) and adults (Fine et al., 2004) are at risk for multiple, simultaneous health damaging behaviors associated with premature morbidity and mortality. In addition, studies show that various adolescent health behaviors are interrelated (Driskell et al., 2008), and that potentially modifiable determinants may link multiple health risk and health promoting behaviors (Peters et al., 2009). Together, these data support the need for, and potential utility of, targeting multiple health habits when developing and implementing behavioral interventions.

Typical prevention and intervention programs targeting individuals focus on single health behavior change, however, effective multiple behavior interventions may have a greater impact on public health (Nigg et al., 2002). There is increasing interest in developing and evaluating integrative interventions targeting multiple risk behaviors (Atkins and Clancy, 2004, Orleans, 2004, Prochaska et al., 2008). In addition, there are a growing number of studies showing that asset-based programs aimed at promoting healthy development involving positive identity and behaviors can improve multiple health habits among youth (Flay, 2003, Roth and Brooks-Gunn, 2003, Tebes et al., 2007).

There are a lack of theoretical models for researchers and practitioners that directly address how to construct interventions targeting multiple health behaviors (Noar et al., 2008, Orleans, 2004). One emerging framework for planning multiple behavior interventions is the Behavior-Image Model (BIM). BIM is based on two principles. First, that activating existing or creating new images of attractive others (i.e., social images or prototypes) and improved possible selves (i.e., future self-images) can integrate and motivate change across divergent health behaviors (Werch, 2007). Second, that BIM-based interventions should involve self-regulatory processes by providing feedback on participants' health behaviors and self-images to increase commitment to goal setting aimed at reducing discrepancy between health behaviors and social/self-images. Several studies have demonstrated that brief interventions using positive social and self-images and health promoting behaviors, in addition to risk behaviors, may simultaneously improve multiple health behaviors among adolescents (Werch et al., 2003, Werch et al., 2005, Werch et al., 2008). Unfortunately, most brief interventions targeting college students have been singularly focused on problem alcohol consumption.

An initial study evaluating three BIM-influenced brief interventions for college students showed the interventions significantly improved a number of health promoting and health risk behaviors and health-related quality of life 1-month post-intervention (Werch et al., 2007). A second study of a BIM-influenced brief image-based intervention for college students found that undergraduates receiving the intervention showed improvements on frequency and heavy use of alcohol; driving after drinking; length, quantity and heavy use of marijuana; 30-day moderate exercise; sleep; and spiritual and social health-related quality of life 3 months post-intervention, compared to students receiving usual care (Werch et al., 2008). The current study examined whether initial 3-month outcomes from the brief image-based multiple behavior intervention for undergraduates were sustained at 12-month follow-up without further intervention.

Section snippets

Participants

Students attending a mid-sized public university in southeastern US were recruited during fall of 2006 to participate in a randomized control trial of a brief health promotion program titled Project Fitness. Of 303 undergraduates recruited, 299 participants provided usable baseline data (99%), and of these 283 provided 3-month data (95%), while 231 provided 12-month data (77%). The majority of participating students were female (59.5%). Average age of participants at baseline was 19.2 years old

Attrition analysis

Twenty-three percent of participants (n = 68) were lost to attrition at 12-month follow-up. No differences were found in the proportion of those who dropped out between experimental groups. Dropouts were more likely to have someone in their immediate family with an alcohol or drug problem (57.3%) than non-dropouts (40.2%), p = 0.01. No other baseline demographic or health behavior differences were found between dropouts and non-dropouts. Factorial ANOVA tests showed no dropout status by

Discussion

Few studies have examined the long-term effects of brief multiple behavior interventions. Such studies are critical to understanding the degree to which short-term brief intervention outcomes are sustained, and whether or not re-interventions may be needed to bolster specific behavioral degradations over time. Results from this study showed that a brief image-based multiple behavior intervention had sustained effects on some health outcomes, but not others. Evidence in favor of longer-term

Conclusions

In conclusion, this study found that initial 3-month outcomes from a brief image-based multiple behavior intervention among college students were partially sustained at 12-month follow-up. In particular, health-related quality of life effects were maintained, as were moderate exercise and driving after drinking. However, effects on alcohol and marijuana use, along with the amount of sleep were not sustained over time. It is these later findings that indicate the need for research to assess

Conflict of interest statement

The authors declare there is no conflict of interest.

Acknowledgments

This manuscript would not have been possible without the financial support from the National Institute on Drug Abuse (Grant #DA018872 and #DA019172), and the National Institute on Alcohol Abuse and Alcoholism (Grant #AA9283). We also wish to also thank those college students who generously agreed to participate in this research and contribute their valuable time making this study possible.

References (43)

  • Centers for Disease Control and Prevention, 2005. State and Local Youth Risk Behavior. Available:...
  • CohenJ.

    Statistical power analysis for the behavioral sciences

    (1998)
  • CollinsL.M. et al.

    A comparison of inclusive and restrictive strategies in modern missing data procedures

    Psychol. Methods

    (2001)
  • DeyoR.A. et al.

    Strategies for improving and expanding the application of health status measures in clinical settings: a researcher-developer viewpoint

    Med. Care

    (1992)
  • EatonD. et al.

    Youth risk behavior surveillance—United States, 2005

    J. Sch. Health

    (2006)
  • EggertL. et al.

    Preventing adolescent drug abuse and high school dropout through an intensive school-based social network development program

    Am. J. Health Promot.

    (1994)
  • EllicksonP. et al.

    Beliefs about resistance self-efficacy and drug prevalence: do they really affect drug use

    Int. J. Addict.

    (1991)
  • FlayB.R.

    Positive youth development is necessary and possible

  • GroegerJ.A. et al.

    Sleep quantity, sleep difficulties and their perceived consequences in a representative sample of some two thousand British adults

    J. Sleep Res.

    (2004)
  • GruenwaldP. et al.

    Outlets, drinking and driving: a multilevel analysis of availability

    J. Stud. Alcohol

    (2002)
  • HarrisK.M. et al.

    Longitudinal trends in race/ethnic disparities in leading health indicators from adolescence to young adulthood

    Arch. Pediatr. Adolesc. Med.

    (2006)
  • Cited by (42)

    • Changes in college students’ health behaviors and substance use after a brief wellness intervention during COVID-19

      2022, Preventive Medicine Reports
      Citation Excerpt :

      For example, Morton et al (Morton et al., 2020) delivered a multi-modal intervention to college students that resulted in significant improvements in participants’ emotional wellbeing. Werch et al (Werch et al., 2010) delivered a multiple behavior intervention to college students and found that certain health outcome effects observed at three months, such as health-related quality of life and moderate exercise, were sustained at 12 months, in absence of the intervention treatment. While our study was not longitudinal in nature, results at second and third follow-up support findings from Werch et al. (2010) Short, Kinman, and Baker (Short et al., 2020) utilized peer coaching to positively influence undergraduates’ wellbeing.

    • Longitudinal assessment of the behavior-changing effect of app-based eco-feedback in residential buildings

      2018, Energy and Buildings
      Citation Excerpt :

      Impacts of behavioral intervention are usually larger in the short term than in the long term [31]. For instance, the durability of behavior intervention on multiple health-related behaviors was studied with baseline, 3-month, and 12-month experiments in [34]. The results showed that some behavior changes, such as moderate exercise, sustained in the post study period (12 month), while other behavior changes, such as alcohol use, decayed in the long term.

    • Multiple Risk Behavior Interventions: Meta-analyses of RCTs

      2017, American Journal of Preventive Medicine
      Citation Excerpt :

      Only four studies reported analyses of intervention fidelity or challenges to implementation.23–26 Most studies that requested participant feedback found high levels of satisfaction both with provided materials (e.g., pedometers, exercise calendars, educational materials) and content of the intervention.27–33 Though some studies did not find differences in satisfaction between participants in the intervention group compared with controls,34–36 these interventions were compared with relatively active control groups.

    View all citing articles on Scopus
    View full text