A randomized trial of sequential and simultaneous multiple behavior change interventions for physical activity and fat intake

Effectiveness of a tailored communication intervention to improve physical activity in hypertensive patients: a twelve-month randomized controlled trial

BACKGROUND

Cardiovascular diseases (CVDs) are a leading cause of morbidity and mortality globally. Arterial hypertension is one of the main cardiovascular risk factors. Despite this, individuals with hypertension often fail to follow medical advice to counteract cardiovascular risks. A physically active lifestyle is one of the most challenging behaviors to adopt. This study aimed to preliminarily investigate the effectiveness of a tailored print message intervention to increase physical activity in patients with arterial hypertension.

METHODS

A sample of 188 patients with hypertension (mean age = 63 years; SD = 10.9; 50% men) participated in a theory-based tailored health communication intervention. Participants were randomly assigned to three parallel groups: (1) the tailored group, which received tailored health brochures; (2) the non-tailored group, which received non-tailored health brochures; or (3) the usual care group, which received no informative print materials. The longitudinal physical activity trajectories (baseline, 6- and 12-month follow-ups) were examined using repeated measures ANOVA and growth curve models.

RESULTS

At the baseline, 38.8% of patients achieved the target physical activity. This percentage rose to 43.0% at 6-month follow-up and 46.0% at 12-month follow-up. The descriptive statistics divided in function of the experimental group suggested differences in the longitudinal trend of the mean physical activity depending on the experimental group. However, statistical significance using repeated measures ANOVA did not support this observation. The analysis of the growth curves suggested that the tailored group showed a progressive increase in physical activity over twelve months (the model that best described the longitudinal trajectory was a linear growth model). The non-tailored group showed an increase in physical activity six months after the beginning of the intervention, followed by a decrease (free time score model). The usual care group did not change over time (no-growth model).

CONCLUSIONS

Findings suggest the effectiveness of the tailored intervention proposed. However, further investigations and empirical confirmations are required.

TRIAL REGISTRATION

ISRCTN13415993 ( https://doi.org/10.1186/ISRCTN13415993 ). Registration date: 08/04/2019.

Multiple Health Behavior Programs in School Settings: Strategies to Promote Transfer-of-Learning Through Life Skills Education

Typically, schools implement health promotion programs that focus on a single behavioral domain. Multiple related health topics may be addressed using separate interventions, potentially producing overlap in program content. However, integrative approaches in health promotion have the potential to produce interventions capable of improving multiple health behaviors. In particular, more research is needed to identify the conditions and the factors that can promote the transfer of learning to broaden the target outcomes of health promotion programs. The present study aims to identify the characteristics of an evidence-based life skills education program that can facilitate the transfer of learning to different health behaviors not initially targeted by the program, and the strategies for achieving successful transfer. A two round Delphi method was used with a diverse group of 21 experts in health promotion, life skills education, and methods of pedagogy for early adolescent students. Questionnaires with open and closed-ended questions were administered on-line. Content qualitative analysis was run, integrating codes, subcategories, and categories of the two rounds of the study. Results showed strong consensus among experts about the potential for promoting the transfer of skills from one health domain to another. Many elements were identified as important factors that facilitate the transfer of learning. Strategies for successful transfer were related to teaching methods, educational approaches, and consistency with the broader school curriculum. Findings suggest that the successful transfer of learning to a new health domain requires that educators recognize its importance and explicitly designate it as an educational aim.

STAR Duodecim eHealth Tool to Recognize Chronic Disease Risk Factors and Change Unhealthy Lifestyle Choices Among the Long-Term Unemployed: Protocol for a Mixed Methods Validation Study

BACKGROUND

Lifestyle choices and socioeconomic status have a significant impact on the expected onset of diseases, age of death, and risk factors concerning long-term illnesses and morbidity. STAR is an online health examination tool, which gives users a report that includes an evaluation of their life expectancy and an estimated risk for developing common long-term illnesses based on questions about health, characteristics, lifestyle, and quality of life.

OBJECTIVE

The goals of this study are to (1) review the capacity of STAR to recognize morbidity risks in comparison to a traditional nurse-led health examination and patient-reported health challenges; (2) evaluate the user experience and usability of STAR; and (3) assess the potential impact of STAR on the health confidence and motivation of patients to make healthier lifestyle choices.

METHODS

This mixed methods validation study will consist of a quantitative part (questionnaires) and a qualitative part (phone interviews and open-ended questions from the questionnaires). The participants will include 100 long-term unemployed individuals attending a health check for the unemployed. The participants will be recruited from three Finnish public health centers in Espoo, Hämeenlinna, and Tampere. At the health centers, the participants will use STAR and attend a nurse's health check. Surveys with multiple-choice and open-ended questions will be collected from the participants, the nurse, and a study assistant. The questionnaires include questions about the participant's background and health challenges from the patient and nurse points of view, as well as questions about how well the health challenges matched the STAR report. The questionnaires also gather data about user experience, health confidence, and usability of STAR. A study assistant will fill out an observer's form containing questions about use time and possible problems encountered while using STAR. A sample of the unemployed participants will be interviewed by telephone subsequently. For the quantitative data, descriptive statistics and a reliability analysis will be performed, and mean sum scores will be computed for the study variables. Thematic analysis of the qualitative data will be performed.

RESULTS

This study was approved by the Ethics Committee of the Expert Responsibility Area of Tampere University Hospital in June 2020 (ETL Code R20067). Data collection will begin in June 2021 and will take approximately 3-6 months.

CONCLUSIONS

Online health examinations can improve the effectiveness of primary prevention in health care by supporting efficient evidence-based morbidity risk estimation and motivating patients to change unhealthy behaviors. A multimethod approach is used to allow for assessment of the tool's usefulness from the points of view of both professionals and patients. This study will further provide a rich understanding of how the tool can be used as part of routine health checks, and how and why the tool may or may not motivate users for making healthier lifestyle choices.

INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID)

PRR1-10.2196/27668.

Mighty men: A faith-based weight loss intervention to reduce cancer risk in African American men

According to the American Cancer Society's guidelines on nutrition and physical activity for cancer prevention, weight control, eating practices and physical activity are second only to tobacco use as modifiable determinants of cancer risk. However, no evidence-based interventions have been targeted to African American men or tailored to individual African American men's preferences, needs or identities. The goal of this chapter is to describe the rationale for the components, aims and setting of Mighty Men: A Faith-Based Weight Loss Intervention for African American Men. We begin by discussing the rationale for focusing on weight loss in the context of cancer prevention, and argue that obesity and obesogenic behaviors are important yet modifiable determinants of cancer risk. Next, we briefly review the scarce literature on interventions to promote healthy eating, physical activity and weight loss in our population of interest, and then discuss the rationale for conducting the intervention in faith- based organizations rather than other common settings for recruiting African American men. We conclude with a discussion of the conceptual foundations and components of Mighty Men, and discuss our focus and goals in the context of the larger literature in this area.

Efficacy of an m-Health Physical Activity and Sleep Health Intervention for Adults: A Randomized Waitlist-Controlled Trial

INTRODUCTION

Interventions that improve both physical activity and sleep quality may be more effective in improving overall health. The purpose of the Synergy Study is to test the efficacy of a mobile health combined behavior intervention targeting physical activity and sleep quality.

STUDY DESIGN

Randomized, waitlist-controlled trial.

SETTING/PARTICIPANTS

This study had an app-based delivery mode, Australia-wide. The participants were 160 adults who reported insufficient physical activity and poor sleep quality in an eligibility survey.

INTERVENTION

The intervention was a mobile app providing educational resources, goal setting, self-monitoring, and feedback strategies. It included 12 weeks of personalized support including weekly reports, tool sheets, and prompts.

MAIN OUTCOME MEASURES

Outcomes were assessed at baseline, 3 months (primary), and 6 months (secondary endpoint). Self-reported minutes of moderate-to-vigorous intensity physical activity and sleep quality were co-primary outcomes. Resistance training; sitting time; sleep hygiene; sleep timing variability; insomnia severity; daytime sleepiness; quality of life; and depression, anxiety, and stress symptoms were secondary outcomes. Data were collected between June 2017 and February 2018 and analyzed in August 2018.

RESULTS

At 3 months, between-group differences in moderate-to-vigorous intensity physical activity were not statistically significant (p=0.139). Significantly more participants in the intervention group engaged in ≥2 days/week (p=0.004) of resistance training. The intervention group reported better overall sleep quality (p=0.009), subjective sleep quality (p=0.017), sleep onset latency (p=0.013), waketime variability (p=0.018), sleep hygiene (p=0.027), insomnia severity (p=0.002), and lower stress symptoms (p=0.032) relative to waitlist controls. At 6 months, group differences were maintained for sleep hygiene (p=0.048), insomnia severity (p=0.002), and stress symptoms (p=0.006). Differences were observed for bedtime variability (p=0.023), sleepiness (p<0.001), daytime dysfunction (p=0.039), and anxiety symptoms (p=0.003) at 6 months, but not 3 months.

CONCLUSIONS

This remotely delivered intervention did not produce statistically significant between-group differences in minutes of moderate-to-vigorous intensity physical activity. Significant short-term differences in resistance training and short- and medium-term differences in sleep health in favor of the intervention were observed.

TRIAL REGISTRATION

This study is registered at anzctr.org.au ACTRN12617000376347.

A randomised controlled trial to test the efficacy of an m-health delivered physical activity and sleep intervention to improve sleep quality in middle-aged adults: The Refresh Study Protocol

INTRODUCTION

Poor sleep health is common and has a substantial negative health impact. Physical activity has been shown to improve sleep health. Many sleep interventions do not explicitly target physical activity, potentially limiting changes in activity and also sleep. Few intervention target those with poor sleep health but without a diagnosed disorder. This study aims to examine the efficacy of a combined physical activity and sleep intervention to improve sleep quality in middle-aged adults and its effect on physical activity, depression and quality of life.

METHODS

A three-arm randomised trial with a three-month primary time-point, will be conducted. Adults (N = 275) aged 40-65 years, who report physical inactivity and poor sleep quality, will be randomly allocated to either a combined Physical Activity and Sleep Health, a Sleep Health-Only or a Wait List Control group. The multi-component m-health intervention will be delivered using a smartphone/tablet "app", supplemented with email and SMS. Participants will use the app to access educational material, set goals, self-monitor and receive feedback about behaviours. Assessments will be conducted at baseline, three-month primary time-point and six-month follow-up. Generalized linear models using an ANCOVA (baseline-adjusted) approach, will be used to identify between-group differences in sleep quality, following an intention-to-treat principle.

DISCUSSION

This study will determine whether the addition of a physical activity intervention enhances the effectiveness of a sleep intervention to improve sleep quality, relative to a sleep-only intervention, in physically inactive middle-aged adults who report poor sleep health, but without a sleep disorder.

The effect of older-person centered and integrated health management model on multiple lifestyle behaviors: A randomized controlled trial from China

OBJECTIVE

To investigate the effectiveness of the older-centered Integrated Health Management Model Project (OPCHMP) for multiple lifestyle behaviours in the elderly.

METHODS

A 2-arm, parallel, randomized controlled trial was conducted in Nanjing. The elderly were recruited from multiple community health service centres. The intervention group was intervened and received a personalized, 2-year OPCHMP. The control group only received usual care. Adherence to healthy lifestyle behaviours (ATHLBS) is the primary outcome, obtained through a self-reported composite health behaviour score. The secondary outcomes were health indicators. General estimating equation models were performed to analyse longitudinal dichotomous data and continuous data.

RESULTS

637 (intervention = 323; control = 314) participants were included in the study. The participants mean age was 70.53 ± 6.07 years. Significant ATHLBS correction was achieved after 24-month follow-up in the intervention group, comparing to controls. And the intervention group reported significantly better health indicators.

CONCLUSION

OPCHMP had positive effect on multiple lifestyle habits in elderly population, which is very encouraging.

Promoting Healthy Eating and Physical Activity Behaviors: A Systematic Review of Multiple Health Behavior Change Interventions Among Cancer Survivors

Multiple health behavior change (MHBC) interventions have great potential for enhancing health and well-being following cancer diagnosis and treatment. However, the characteristics and effects of MHBC interventions remain elusive for cancer survivors. The main purpose of this study was to evaluate the effectiveness of MHBC interventions on healthy eating and physical activity behaviors among cancer survivors. A secondary aim was to examine the effect of using a simultaneous and sequential design approach to MHBC (ie, changing both behaviors at the same time or one after the other). Randomized controlled trials reporting the impact of a MHBC intervention on both healthy eating and physical activity behaviors among cancer survivors were retrieved from MEDLINE, Cochrane Library, and PsycINFO. A total of 27 MHBC interventions were identified; most (92.6%) were designed to promote simultaneous change in both behaviors and assessed end-of-treatment effect among breast cancer survivors. MHBC interventions led by nurses or multidisciplinary teams showed the most compelling evidence for small to moderate improvement in both behaviors, with interventions that lasted ≥17 weeks more likely to improve both behaviors. This study identifies research priorities and provides preliminary evidence for clinical decision making and advancements in MHBC intervention design and delivery for clinical oncology.

Multiple Risk Behavior Interventions: Meta-analyses of RCTs

CONTEXT

Multiple risk behaviors are common and associated with developing chronic conditions such as heart disease, cancer, or Type 2 diabetes. A systematic review, meta-analysis, and meta-regression of the effectiveness of multiple risk behavior interventions was conducted.

EVIDENCE ACQUISITION

Six electronic databases including MEDLINE, EMBASE, and PsycINFO were searched to August 2016. RCTs of non-pharmacologic interventions in general adult populations were selected. Studies targeting specific at-risk groups (such as people screened for cardiovascular risk factors or obesity) were excluded. Studies were screened independently. Study characteristics and outcomes were extracted and risk of bias assessed by one researcher and checked by another. The Behaviour Change Wheel and Oxford Implementation Index were used to code intervention content and context.

EVIDENCE SYNTHESIS

Random-effects meta-analyses were conducted. Sixty-nine trials involving 73,873 individuals were included. Interventions mainly comprised education and skills training and were associated with modest improvements in most risk behaviors: increased fruit and vegetable intake (0.31 portions, 95% CI=0.17, 0.45) and physical activity (standardized mean difference, 0.25; 95% CI=0.13, 0.38), and reduced fat intake (standardized mean difference, -0.24; 95% CI=-0.36, -0.12). Although reductions in smoking were found (OR=0.78, 95% CI=0.68, 0.90), they appeared to be negatively associated with improvement in other behaviors (such as diet and physical activity). Preliminary evidence suggests that sequentially changing smoking alongside other risk behaviors was more effective than simultaneous change. But most studies assessed simultaneous rather than sequential change in risk behaviors; therefore, comparisons are sparse. Follow-up period and intervention characteristics impacted effectiveness for some outcomes.

CONCLUSIONS

Interventions comprising education (e.g., providing information about behaviors associated with health risks) and skills training (e.g., teaching skills that equip participants to engage in less risky behavior) and targeting multiple risk behaviors concurrently are associated with small changes in diet and physical activity. Although on average smoking was reduced, it appeared changes in smoking were negatively associated with changes in other behaviors, suggesting it may not be optimal to target smoking simultaneously with other risk behaviors.

Understanding Multiple Behavioral Risk Factors for Cancer in Rural Women

OBJECTIVES

To examine the demographic and health-related factors associated with risk behaviors that have been linked to cancer including smoking, high BMI, and low physical activity.

DESIGN AND SAMPLE

A secondary analysis was conducted using data from Rural Families Speak about Health, a multistate, epidemiologic study of rural American women and their families (N = 444).

MEASURES

Validated measures for various demographic and health-related items including tobacco use, BMI, physical activity, and depression were used.

RESULTS

Of the total sample with complete data (n = 399), the mean age was 32 years and the majority were White (64%), married (67%), had a high school education or higher (73%), and had an annual household income of less than $40,000 (90%). Regarding cancer risk behaviors, 36% of the sample were smokers, 39% reported low levels of physical activity, and 45% had a calculated BMI over 30. Thirty-five percent of participants reported engaging in two or more risk behaviors. There were significant differences in income, perceived health status, and depression depending on the number of risk behaviors reported.

CONCLUSIONS

Understanding combinations of risk behaviors can assist nurses and other health professionals in tailoring multiple health behavior change interventions to prevent cancer among rural women.

Ready, set, go: a cross-sectional survey to understand priorities and preferences for multiple health behaviour change in a highly disadvantaged group

Background

Socially disadvantaged groups, such as Aboriginal Australians, tend to have a high prevalence of multiple lifestyle risk factors, increasing the risk of disease and underscoring the need for services to address multiple health behaviours. The aims of this study were to explore, among a socially disadvantaged group of people attending an Aboriginal Community Controlled Health Service (ACCHS): a) readiness to change health behaviours; b) acceptability of addressing multiple risk factors sequentially or simultaneously; and c) preferred types of support services.

Methods

People attending an ACCHS in regional New South Wales (NSW) completed a touchscreen survey while waiting for their appointment. The survey assessed participant health risk status, which health risks they would like to change, whether they preferred multiple health changes to be made together or separately, and the types of support they would use.

Results

Of the 211 participants who completed the survey, 94 % reported multiple (two or more) health risks. There was a high willingness to change, with 69 % of current smokers wanting to cut down or quit, 51 % of overweight or obese participants wanting to lose weight and 44 % of those using drugs in the last 12 months wanting to stop or cut down. Of participants who wanted to make more than one health change, over half would be willing to make simultaneous or over-lapping health changes. The most popular types of support were help from a doctor or Health Worker and seeing a specialist, with less than a quarter of participants preferring telephone or electronic (internet or smart phone) forms of assistance. The importance of involving family members was also identified.

Conclusions

Strategies addressing multiple health behaviour changes are likely to be acceptable for people attending an ACCHS, but may need to allow flexibility in the choice of initial target behaviour, timing of changes, and the format of support provided.

Electronic supplementary material

The online version of this article (doi:10.1186/s12913-016-1701-2) contains supplementary material, which is available to authorized users.

Comparative efficacy of simultaneous versus sequential multiple health behavior change interventions among adults: A systematic review of randomised trials

BACKGROUND

Growing evidence points to the benefits of addressing multiple health behaviors rather than single behaviors.

PURPOSE

This review evaluates the relative effectiveness of simultaneous and sequentially delivered multiple health behavior change (MHBC) interventions. Secondary aims were to identify: a) the most effective spacing of sequentially delivered components; b) differences in efficacy of MHBC interventions for adoption/cessation behaviors and lifestyle/addictive behaviors, and; c) differences in trial retention between simultaneously and sequentially delivered interventions.

METHODS

MHBC intervention trials published up to October 2015 were identified through a systematic search. Eligible trials were randomised controlled trials that directly compared simultaneous and sequential delivery of a MHBC intervention. A narrative synthesis was undertaken.

RESULTS

Six trials met the inclusion criteria and across these trials the behaviors targeted were smoking, diet, physical activity, and alcohol consumption. Three trials reported a difference in intervention effect between a sequential and simultaneous approach in at least one behavioral outcome. Of these, two trials favoured a sequential approach on smoking. One trial favoured a simultaneous approach on fat intake. There was no difference in retention between sequential and simultaneous approaches.

CONCLUSIONS

There is limited evidence regarding the relative effectiveness of sequential and simultaneous approaches. Given only three of the six trials observed a difference in intervention effectiveness for one health behavior outcome, and the relatively consistent finding that the sequential and simultaneous approaches were more effective than a usual/minimal care control condition, it appears that both approaches should be considered equally efficacious. PROSPERO registration number: CRD42015027876.

Setting Single or Multiple Goals for Diet and Physical Activity Behaviors Improves Cardiovascular Disease Risk Factors in Adults With Type 2 Diabetes

Purpose

The purpose of this study was to evaluate a 4-month telephone-based goal-setting and decision support intervention among adults with type 2 diabetes mellitus (T2DM) and multiple risk factors for cardiovascular disease (CVD).

Methods

A randomized pretest-posttest control group design was employed. Overweight or obese adults aged 40 to 75 years with T2DM and ≥1 additional CVD risk factor were provided with individualized CVD risk information. At baseline and each biweekly telephone call, the multiple-goal group self-selected both diet- and physical activity–related goals, the single goal group set a single goal, and the control group received information about community health resources. Dietary intake was assessed via a food frequency questionnaire, physical activity via questionnaire, and A1C and blood lipids via fasting fingerstick sample. Between-group differences for clinical (ie, A1C, blood pressure, and blood lipids), physical activity, and dietary variables were evaluated using Kruskal-Wallis, Mann-Whitney U, analysis of variance, and t tests.

Results

From pre- to postintervention, the single-goal group demonstrated significant improvement in systolic blood pressure and intake of servings of fruits, vegetables, and refined grains (all P < .05). The multiple-goal group reported significant reduction in percent energy from total, saturated, monounsaturated, and trans fat intake and significant increase in leisure time walking (all P < .05).

Conclusion

A multiple-goal approach over 4 months can improve dietary and physical activity outcomes, while a single-goal approach may facilitate improvement in one behavioral domain. Additional research is needed to evaluate maintenance of the achieved changes.

Using an eHealth Intervention to Stimulate Health Behavior for the Prevention of Cognitive Decline in Dutch Adults: A Study Protocol for the Brain Aging Monitor

Background

Internet-delivered intervention programs are an effective way of changing health behavior in an aging population. The same population has an increasing number of people with cognitive decline or cognitive impairments. Modifiable lifestyle risk factors such as physical activity, nutrition, smoking, alcohol consumption, sleep, and stress all influence the probability of developing neurodegenerative diseases such as Alzheimer’s disease.

Objective

This study aims to answer two questions: (1) Is the use of a self-motivated, complex eHealth intervention effective in changing multiple health behaviors related to cognitive aging in Dutch adults in the work force, especially those aged 40 and over? and (2) Does this health behavior change result in healthier cognitive aging patterns and contribute to preventing or delaying future onset of neurodegenerative syndromes?

Methods

The Brain Aging Monitor study uses a quasi-experimental 2-year pre-posttest design. The Brain Aging Monitor is an online, self-motivated lifestyle intervention program. Recruitment is done both in medium to large organizations and in the Dutch general population over the age of 40. The main outcome measure is the relationship between lifestyle change and cognitive aging. The program uses different strategies and modalities such as Web content, email, online newsletters, and online games to aid its users in behavior change. To build self-regulatory skills, the Brain Aging Monitor offers its users goal-setting activities, skill-building activities, and self-monitoring.

Results

Study results are expected to be published in early 2016.

Conclusions

This study will add to the body of evidence on the effectiveness of eHealth intervention programs with the combined use of state-of-the-art applied games and established behavior change techniques. This will lead to new insights on how to use behavior change techniques and theory in multidimensional lifestyle eHealth research, and how these techniques and theories apply when they are used in a setting where no professional back-end is available.

Trial Registration

Nederlands Trial Register: NTR4144; http://www.trialregister.nl/trialreg/admin/rctview.asp?TC=4144 (Archived by WebCite at http://www.webcitation.org/6cZzwZSg3)

Who Follows eHealth Interventions as Recommended? A Study of Participants' Personal Characteristics From the Experimental Arm of a Randomized Controlled Trial

BACKGROUND

Computer-tailored eHealth interventions to improve health behavior have been demonstrated to be effective and cost-effective if they are used as recommended. However, different subgroups may use the Internet differently, which might also affect intervention use and effectiveness. To date, there is little research available depicting whether adherence to intervention recommendations differs according to personal characteristics.

OBJECTIVE

The aim was to assess which personal characteristics are associated with using an eHealth intervention as recommended.

METHODS

A randomized controlled trial was conducted among a sample of the adult Dutch population (N=1638) testing an intervention aimed at improving 5 healthy lifestyle behaviors: increasing fruit and vegetable consumption, increasing physical activity, reducing alcohol intake, and promoting smoking cessation. Participants were asked to participate in those specific online modules for which they did not meet the national guideline(s) for the respective behavior(s). Participants who started with fewer than the recommended number of modules of the intervention were defined as users who did not follow the intervention recommendation.

RESULTS

The fewer modules recommended to participants, the better participants adhered to the intervention modules. Following the intervention recommendation increased when participants were older (χ(2)1=39.8, P<.001), female (χ(2)1=15.8, P<.001), unemployed (χ(2)1=7.9, P=.003), ill (χ(2)1=4.5, P=.02), or in a relationship (χ(2)1=7.8, P=.003). No significant relevant differences were found between groups with different levels of education, incomes, or quality of life.

CONCLUSION

Our findings indicate that eHealth interventions were used differently by subgroups. The more frequent as-recommended intervention use by unemployed, older, and ill participants may be an indication that these eHealth interventions are attractive to people with a greater need for health care information. Further research is necessary to make intervention use more attractive for people with unhealthy lifestyle patterns.

Cross-behavior associations and multiple health behavior change: A longitudinal study on physical activity and fruit and vegetable intake

This study aimed to examine the interrelation of physical activity and fruit and vegetable intake. The influence of stage congruence between physical activity and fruit and vegetable intake on multiple behavior change was also investigated. Health behaviors, social-cognitions, and stages of change were assessed in 2693 adults at two points in time. Physical activity and fruit and vegetable intake were assessed 4 weeks after the baseline.

Social-cognitions, stages as well as stage transitions across behavior domains were positively interrelated. Stage congruence was not related to changes in physical activity and fruit and vegetable intake. Physical activity and nutrition appear to facilitate rather than hinder each other. Having intentions to change both behaviors simultaneously does not seem to overburden individuals.

Design and protocol of a randomized multiple behavior change trial: Make Better Choices 2 (MBC2)

BACKGROUND

Suboptimal diet and inactive lifestyle are among the most prevalent preventable causes of premature death. Interventions that target multiple behaviors are potentially efficient; however the optimal way to initiate and maintain multiple health behavior changes is unknown.

OBJECTIVE

The Make Better Choices 2 (MBC2) trial aims to examine whether sustained healthful diet and activity change are best achieved by targeting diet and activity behaviors simultaneously or sequentially. Study design approximately 250 inactive adults with poor quality diet will be randomized to 3 conditions examining the best way to prescribe healthy diet and activity change. The 3 intervention conditions prescribe: 1) an increase in fruit and vegetable consumption (F/V+), decrease in sedentary leisure screen time (Sed-), and increase in physical activity (PA+) simultaneously (Simultaneous); 2) F/V+ and Sed- first, and then sequentially add PA+ (Sequential); or 3) Stress Management Control that addresses stress, relaxation, and sleep. All participants will receive a smartphone application to self-monitor behaviors and regular coaching calls to help facilitate behavior change during the 9 month intervention. Healthy lifestyle change in fruit/vegetable and saturated fat intakes, sedentary leisure screen time, and physical activity will be assessed at 3, 6, and 9 months.

SIGNIFICANCE

MBC2 is a randomized m-Health intervention examining methods to maximize initiation and maintenance of multiple healthful behavior changes. Results from this trial will provide insight about an optimal technology supported approach to promote improvement in diet and physical activity.

Exercise-based treatments for substance use disorders: evidence, theory, and practicality

BACKGROUND

Epidemiological studies reveal that individuals who report risky substance use are generally less likely to meet physical activity guidelines (with the exception of certain population segments, such as adolescents and athletes). A growing body of evidence suggests that individuals with substance use disorders (SUDs) are interested in exercising and that they may derive benefits from regular exercise, in terms of both general health/fitness and SUD recovery.

OBJECTIVES

The aims of this paper were to: (i) summarize the research examining the effects of exercise-based treatments for SUDs; (ii) discuss the theoretical mechanisms and practical reasons for investigating this topic; (iii) identify the outstanding relevant research questions that warrant further inquiry; and (iv) describe potential implications for practice.

METHODS

The following databases were searched for peer-reviewed original and review papers on the topic of substance use and exercise: PubMed Central, MEDLINE, EMBASE, PsycINFO, and CINAHL Plus. Reference lists of these publications were subsequently searched for any missed but relevant manuscripts. Identified papers were reviewed and summarized by both authors.

RESULTS

The limited research conducted suggests that exercise may be an effective adjunctive treatment for SUDs. In contrast to the scarce intervention trials to date, a relative abundance of literature on the theoretical and practical reasons supporting the investigation of this topic has been published.

CONCLUSIONS

Definitive conclusions are difficult to draw due to diverse study protocols and low adherence to exercise programs, among other problems. Despite the currently limited and inconsistent evidence, numerous theoretical and practical reasons support exercise-based treatments for SUDs, including psychological, behavioral, neurobiological, nearly universal safety profile, and overall positive health effects.

Increasing preventive care by primary care nursing and allied health clinicians: a non-randomized controlled trial

BACKGROUND

Although primary care nurse and allied health clinician consultations represent key opportunities for the provision of preventive care, it is provided suboptimally.

PURPOSE

To assess the effectiveness of a practice change intervention in increasing primary care nursing and allied health clinician provision of preventive care for four health risks.

DESIGN

Two-group (intervention versus control), non-randomized controlled study assessing the effectiveness of the intervention in increasing clinician provision of preventive care.

SETTING/PARTICIPANTS

Randomly selected clients from 17 primary healthcare facilities participated in telephone surveys that assessed their receipt of preventive care prior to (September 2009-2010, n=876) and following intervention (October 2011-2012, n=1,113).

INTERVENTION

The intervention involved local leadership and consensus processes, electronic medical record system modification, educational meetings and outreach, provision of practice change resources and support, and performance monitoring and feedback.

MAIN OUTCOME MEASURES

The primary outcome was differential change in client-reported receipt of three elements of preventive care (assessment, brief advice, referral/follow-up) for each of four behavioral risks individually (smoking, inadequate fruit and vegetable consumption, alcohol overconsumption, physical inactivity) and combined. Logistic regression assessed intervention effectiveness.

RESULTS

Analyses conducted in 2013 indicated significant improvements in preventive care delivery in the intervention compared to the control group from baseline to follow-up for assessment of fruit and vegetable consumption (+23.8% vs -1.5%); physical activity (+11.1% vs -0.3%); all four risks combined (+16.9% vs -1.0%) and for brief advice for inadequate fruit and vegetable consumption (+19.3% vs -2.0%); alcohol overconsumption (+14.5% vs -8.9%); and all four risks combined (+14.3% vs +2.2%). The intervention was ineffective in increasing the provision of the remaining forms of preventive care.

CONCLUSIONS

The intervention's impact on the provision of preventive care varied by both care element and risk type. Further intervention is required to increase the consistent provision of preventive care, particularly referral/follow-up.

Patterns and predictors of health behaviors among racially/ethnically diverse residents of low-income housing developments

PURPOSE

To examine behavioral patterns and sociodemographic predictors of diet, inactivity, and tobacco use among a diverse sample of residents from low-income housing developments.

DESIGN

In this cross-sectional survey study, households and residents were randomly selected using multistage cluster sampling. Setting . The study was conducted in 20 low-income housing developments in the Boston, Massachusetts, metropolitan area.

SUBJECTS

Subjects were 828 residents who completed the survey (response rate = 49.3%). Forty-one percent of participants were Hispanic and 38% were non-Hispanic Black. Measures . Outcomes measured were diet, inactivity, and tobacco use. Predictors measured were age, race/ethnicity, gender, education, country in which the subject was born, language spoken, and financial hardship. Analysis . Logistic regression analyses were conducted to examine the association of three health behaviors with sociodemographic factors.

RESULTS

Age, gender, language spoken, and financial hardship showed significant relationships with all three behaviors. For example, those who reported less financial hardship (odds ratio [OR] = 1.75) were more likely to eat healthier. Residents who spoke no English, or at least one language in addition to English, were significantly more likely to report healthier eating (OR = 2.78 and 3.30, respectively) than those who spoke English only. Men were significantly more likely to report less healthy eating (OR = 0.65) than were women. Similar trends emerged for inactivity and tobacco use.

CONCLUSION

Effective health promotion interventions in low-income housing developments that leverage protective factors while addressing risk factors have the potential to reduce income-related health disparities in these concentrated resource-deprived neighborhoods.

Citation searching: a systematic review case study of multiple risk behaviour interventions

BACKGROUND

The value of citation searches as part of the systematic review process is currently unknown. While the major guides to conducting systematic reviews state that citation searching should be carried out in addition to searching bibliographic databases there are still few studies in the literature that support this view. Rather than using a predefined search strategy to retrieve studies, citation searching uses known relevant papers to identify further papers.

METHODS

We describe a case study about the effectiveness of using the citation sources Google Scholar, Scopus, Web of Science and OVIDSP MEDLINE to identify records for inclusion in a systematic review.We used the 40 included studies identified by traditional database searches from one systematic review of interventions for multiple risk behaviours. We searched for each of the included studies in the four citation sources to retrieve the details of all papers that have cited these studies.We carried out two analyses; the first was to examine the overlap between the four citation sources to identify which citation tool was the most useful; the second was to investigate whether the citation searches identified any relevant records in addition to those retrieved by the original database searches.

RESULTS

The highest number of citations was retrieved from Google Scholar (1680), followed by Scopus (1173), then Web of Science (1095) and lastly OVIDSP (213). To retrieve all the records identified by the citation tracking searching all four resources was required. Google Scholar identified the highest number of unique citations.The citation tracking identified 9 studies that met the review's inclusion criteria. Eight of these had already been identified by the traditional databases searches and identified in the screening process while the ninth was not available in any of the databases when the original searches were carried out. It would, however, have been identified by two of the database search strategies if searches had been carried out later.

CONCLUSIONS

Based on the results from this investigation, citation searching as a supplementary search method for systematic reviews may not be the best use of valuable time and resources. It would be useful to verify these findings in other reviews.

Cross-sectional associations between multiple lifestyle behaviors and health-related quality of life in the 10,000 Steps cohort

Background

The independent and combined influence of smoking, alcohol consumption, physical activity, diet, sitting time, and sleep duration and quality on health status is not routinely examined. This study investigates the relationships between these lifestyle behaviors, independently and in combination, and health-related quality of life (HRQOL).

Methods

Adult members of the 10,000 Steps project (n = 159,699) were invited to participate in an online survey in November-December 2011. Participant socio-demographics, lifestyle behaviors, and HRQOL (poor self-rated health; frequent unhealthy days) were assessed by self-report. The combined influence of poor lifestyle behaviors were examined, independently and also as part of two lifestyle behavior indices, one excluding sleep quality (Index 1) and one including sleep quality (Index 2). Adjusted Cox proportional hazard models were used to examine relationships between lifestyle behaviors and HRQOL.

Results

A total of 10,478 participants provided complete data for the current study. For Index 1, the Prevalence Ratio (p value) of poor self-rated health was 1.54 (p = 0.001), 2.07 (p≤0.001), 3.00 (p≤0.001), 3.61 (p≤0.001) and 3.89 (p≤0.001) for people reporting two, three, four, five and six poor lifestyle behaviors, compared to people with 0–1 poor lifestyle behaviors. For Index 2, the Prevalence Ratio (p value) of poor self-rated health was 2.26 (p = 0.007), 3.29 (p≤0.001), 4.68 (p≤0.001), 6.48 (p≤0.001), 7.91 (p≤0.001) and 8.55 (p≤0.001) for people reporting two, three, four, five, six and seven poor lifestyle behaviors, compared to people with 0–1 poor lifestyle behaviors. Associations between the combined lifestyle behavior index and frequent unhealthy days were statistically significant and similar to those observed for poor self-rated health.

Conclusions

Engaging in a greater number of poor lifestyle behaviors was associated with a higher prevalence of poor HRQOL. This association was exacerbated when sleep quality was included in the index.

Clinician assessment, advice and referral for multiple health risk behaviors: prevalence and predictors of delivery by primary health care nurses and allied health professionals

OBJECTIVE

Primary care clinicians have considerable potential to provide preventive care. This study describes their preventive care delivery.

METHODS

A survey of 384 community health nurses and allied health clinicians from in New South Wales, Australia was undertaken (2010-11) to examine the assessment of client risk, provision of brief advice and referral/follow-up regarding smoking inadequate fruit and vegetable consumption, alcohol misuse, and physical inactivity; the existence of preventive care support strategies; and the association between supports and preventive care provision.

RESULTS

Preventive care to 80% or more clients was least often provided for referral/follow-up (24.7-45.6% of clinicians for individual risks, and 24.2% for all risks) and most often for assessment (34.4-69.3% of clinicians for individual risks, and 24.4% for all risks). Approximately 75% reported having 9 or fewer of 17 supports. Provision of care was associated with: availability of a paper screening tool; training; GP referral letter; and number of supports.

CONCLUSION

The delivery of preventive care was limited, and varied according to type of care and risk. Supports were variably associated with elements of preventive care.

PRACTICE IMPLICATIONS

Further research is required to increase routine preventive care delivery and the availability of supports.

Effects of a web-based tailored multiple-lifestyle intervention for adults: a two-year randomized controlled trial comparing sequential and simultaneous delivery modes

Background

Web-based computer-tailored interventions for multiple health behaviors can have a significant public health impact. Yet, few randomized controlled trials have tested this assumption.

Objective

The objective of this paper was to test the effects of a sequential and simultaneous Web-based tailored intervention on multiple lifestyle behaviors.

Methods

A randomized controlled trial was conducted with 3 tailoring conditions (ie, sequential, simultaneous, and control conditions) in the Netherlands in 2009-2012. Follow-up measurements took place after 12 and 24 months. The intervention content was based on the I-Change model. In a health risk appraisal, all respondents (N=5055) received feedback on their lifestyle behaviors that indicated whether they complied with the Dutch guidelines for physical activity, vegetable consumption, fruit consumption, alcohol intake, and smoking. Participants in the sequential (n=1736) and simultaneous (n=1638) conditions received tailored motivational feedback to change unhealthy behaviors one at a time (sequential) or all at the same time (simultaneous). Mixed model analyses were performed as primary analyses; regression analyses were done as sensitivity analyses. An overall risk score was used as outcome measure, then effects on the 5 individual lifestyle behaviors were assessed and a process evaluation was performed regarding exposure to and appreciation of the intervention.

Results

Both tailoring strategies were associated with small self-reported behavioral changes. The sequential condition had the most significant effects compared to the control condition after 12 months (T1, effect size=0.28). After 24 months (T2), the simultaneous condition was most effective (effect size=0.18). All 5 individual lifestyle behaviors changed over time, but few effects differed significantly between the conditions. At both follow-ups, the sequential condition had significant changes in smoking abstinence compared to the simultaneous condition (T1 effect size=0.31; T2 effect size=0.41). The sequential condition was more effective in decreasing alcohol consumption than the control condition at 24 months (effect size=0.27). Change was predicted by the amount of exposure to the intervention (total visiting time: beta=–.06; P=.01; total number of visits: beta=–.11; P<.001). Both interventions were appreciated well by respondents without significant differences between conditions.

Conclusions

Although evidence was found for the effectiveness of both programs, no simple conclusive finding could be drawn about which intervention mode was more effective. The best kind of intervention may depend on the behavior that is targeted or on personal preferences and motivation. Further research is needed to identify moderators of intervention effectiveness. The results need to be interpreted in view of the high and selective dropout rates, multiple comparisons, and modest effect sizes. However, a large number of people were reached at low cost and behavioral change was achieved after 2 years.

Trial Registration

Nederlands Trial Register: NTR 2168; http://www.trialregister.nl/trialreg/admin/rctview.asp?TC=2168 (Archived by WebCite at http://www.webcitation.org/6MbUqttYB).

Sociodemographic and social contextual predictors of multiple health behavior change: data from the Healthy Directions-Small Business study

Multiple modifiable health behaviors contribute to the chronic diseases that are the leading causes of death in the USA. Disparities for meeting recommended health behavior guidelines exist across occupational classes and socioeconomic levels. The purpose of this paper was to investigate sociodemographic and social contextual predictors of multiple health behavior change in a worksite intervention. We analyzed data on four diet and exercise variables from an intervention trial with worksite-level randomization. Eight hundred forty-one employees had complete data from baseline (response rate = 84 %) and follow-up surveys (response rate = 77 %). Multilevel logistic regression estimated associations between least absolute shrinkage and selection operator-selected sociodemographic and social contextual predictor variables and the multiple health behavior change outcome (changing 2+ versus 0 behaviors). Gender, being married/partnered, and perceived discrimination were significantly associated with multiple health behavior change. Sociodemographic and social contextual factors predict multiple health behavior change and could inform the design and delivery of worksite interventions targeting multiple health behaviors.

Multiple behavior change among church members taking part in the faith, activity, and nutrition program

OBJECTIVE

To examine the extent to which participants in a combined physical activity (PA) and dietary intervention achieved changes in multiple health behaviors.

DESIGN

Group randomized trial; includes only participants assigned to the intervention group only.

SETTING

Thirty-six churches in South Carolina.

PARTICIPANTS

Three hundred sixty African American church members.

INTERVENTION

A 15-month PA and dietary intervention, guided by the structural ecological model, targeting environmental (i.e., social, cultural, physical) and organizational (ie, policies, practices) changes within the church.

MAIN OUTCOME MEASURES

Self-reported PA, fruit and vegetable consumption, fat-, and fiber-related behaviors.

ANALYSIS

Change in each behavior was defined as unadjusted pretest-posttest improvement ≥ 0.20 of the baseline standard deviation. The total number and each combination of behaviors changed were calculated.

RESULTS

Up to 19% changed no health behaviors as defined above, 31% changed 1 health behavior, 31% changed 2 health behaviors, 13% changed 3 health behaviors, and 5% changed all 4 of the targeted health behaviors. Combinations of multiple behavior change included PA and dietary behaviors, which suggests that both behaviors can be changed simultaneously.

CONCLUSIONS AND IMPLICATIONS

Nearly half of participants changed at least 2 health behaviors. Faith-based interventions targeting environmental and organizational change can successfully change multiple behaviors, potentially leading to greater improvements in public health.

Prevalence of and intention to change dietary and physical activity health risk behaviours

Poor nutrition and insufficient physical activity contribute to high rates of obesity. Prevalence, intention to change and co-occurrence of four health risk behaviours (inadequate fruit and vegetables, excessive dietary fat, excessive sugary beverages and inadequate physical activity in comparison to public health recommendations) were investigated in an Australian population of working adults. Participants (n=105) completed sociodemographic and stage of change questionnaires. A subsample (n=40) were assessed twice to estimate test-retest repeatability. In the full sample, 73% were female, mean age was 33.8 years and mean BMI was 23.8 kg/m(2). Eighty-seven percent of participants consumed inadequate fruit and vegetables, 43% had excessive dietary fat, 42% had excessive sugary beverages and 29% had inadequate physical activity. The proportions intending to change each behaviour were 57%, 25%, 18% and 24%, respectively. Two-thirds exhibited multiple risk behaviours and 38% intended to change multiple risk behaviours. Fruit and vegetables and dietary fat were the most commonly paired risk behaviours (39%) and the pair most intended to change (19%). Occurrence of multiple risk behaviours was associated with being male (OR 3.10, 95% CI 1.06-9.03) or overweight/obese (OR 2.66, 95% CI 1.02-6.93). Targeting two risk behaviours, particularly fruit and vegetables and dietary fat, may be appropriate when designing health promotion programs in working populations.

Lessons from psychiatry and psychiatric education for medical learners and teachers

Medical learners, teachers, and institutions face significant challenges in health care delivery and in training the next generation of clinicians. We propose that psychiatry offers lessons which may help improve how we take care of patients and how we teach others to care for patients. Our objective is to discuss what learners and teachers can learn from psychiatry, organized around (1) how we make decisions, (2) how we learn, and (3) how we reflect on our practice. Information from clinical care, education, neuroscience and other aspects of life (e.g. business, creativity, and research) help us on these processes. We make 'good' decisions in concert with patients and learners, by listening to their experiences, asking questions and exploring subjective and objective information. Our learning has a neurobiological basis, and is effectively furthered by personalization, reinforcement, acquisition of critical thinking skills, and assessment of our limitations and errors. Our ability to reflect is determined by attitude, skill, tolerating ambiguity or dissonance, and planning for the unexpected. These processes - in addition to knowledge and other skills - will help physicians be successful in practice, learning and teaching, research and leadership.

The web of risk factors for excessive gestational weight gain in low income women

The objective of this study is to gain an in-depth understanding of issues related to gestational weight gain (GWG) including general health, diet, and physical activity among high and low income women and to elucidate socio-ecological and psychosocial risk factors that increase risk for excessive GWG. We conducted 9 focus groups with high (n = 4 groups) and low (n = 5 groups) income pregnant women aged 18-35 years to discuss health, GWG, diet and physical activity following a discussion guide. The constant comparative method was used to code focus group notes and to identify emergent themes. Themes were categorized within the integrative model of behavioral prediction. Low income women, in contrast to high income women, had higher BMIs, had more children, and were African American. Diet and physical activity behaviors reported by low income women were more likely to promote positive energy balance than were those of high income women. The underlying behavioral, efficacy, and normative beliefs described by both groups of women explained most of these behaviors. Experiencing multiple risk factors may lead to (1) engaging in several behavior changes during pregnancy unrelated to weight and (2) holding more weight gain-promoting beliefs than weight maintaining beliefs. These factors could inhibit diet and physical activity behaviors and/or behavior changes that promote energy balance and in combination, result in excessive GWG. Low income women experience multiple risk factors for excessive GWG and successful interventions to prevent excessive GWG and pregnancy related weight gain will need to recognize the complex web of influences.

Improving diet, physical activity and other lifestyle behaviours using computer-tailored advice in general practice: a randomised controlled trial

BACKGROUND

The adoption and maintenance of healthy behaviours is essential in the primary prevention of chronic non-communicable diseases. This study evaluated the effectiveness of a minimal intervention on multiple lifestyle factors such as diet, physical activity, smoking and alcohol, delivered through general practice, using computer-tailored feedback.

METHODS

Adult patients visiting 21 general practitioners in Brisbane, Australia, were surveyed about ten health behaviours that are risk factors for chronic, non-communicable diseases. Those who completed the self-administered baseline questionnaire entered a randomised controlled trial, with the intervention group receiving computer-tailored printed advice, targeting those health behaviours for which respondents were not meeting current recommendations. The primary outcome was change in summary lifestyle score (Prudence Score) and individual health behaviours at three months. A repeated measures analysis compared change in these outcomes in intervention and control groups after adjusting for age and education.

RESULTS

2306 patients were randomised into the trial. 1711 (76%) returned the follow-up questionnaire at 3 months. The Prudence Score (10 items) in the intervention group at baseline was 5.88, improving to 6.25 at 3 months (improvement = 0.37), compared with 5.84 to 5.96 (improvement = 0.12) in the control group (F = 13.3, p = 0.01). The intervention group showed improvement in meeting recommendations for all individual health behaviours compared with the control group. However, these differences were significant only for fish intake (OR 1.37, 95% CI 1.11-1.68), salt intake (OR 1.19, 95% CI 1.05-1.38), and type of spread used (OR 1.28, 95% CI 1.06-1.51).

CONCLUSION

A minimal intervention using computer-tailored feedback to address multiple lifestyle behaviours can facilitate change and improve unhealthy behaviours. Although individual behaviour changes were modest, when implemented on a large scale through general practice, this intervention appears to be an effective and practical tool for population-wide primary prevention.

TRIAL REGISTRATION

The Australian New Zealand Clinical Trials Registry: ACTRN12611001213932.

Interactive computer-based interventions for weight loss or weight maintenance in overweight or obese people

BACKGROUND

The World Health Organization (WHO) estimates that the number of obese or overweight individuals worldwide will increase to 1.5 billion by 2015. Chronic diseases associated with overweight or obesity include diabetes, heart disease, hypertension and stroke.

OBJECTIVES

To assess the effects of interactive computer-based interventions for weight loss or weight maintenance in overweight or obese people.

SEARCH METHODS

We searched several electronic databases, including CENTRAL, MEDLINE, EMBASE, CINAHL, LILACS and PsycINFO, through 25 May 2011. We also searched clinical trials registries to identify studies. We scanned reference lists of included studies and relevant systematic reviews.

SELECTION CRITERIA

Studies were included if they were randomized controlled trials or quasi-randomized controlled trials that evaluated interactive computer-based weight loss or weight maintenance programs in adults with overweight or obesity. We excluded trials if the duration of the intervention was less than four weeks or the loss to follow-up was greater than 20% overall.

DATA COLLECTION AND ANALYSIS

Two authors independently extracted study data and assessed risk of bias. Where interventions, control conditions, outcomes and time frames were similar between studies, we combined study data using meta-analysis.

MAIN RESULTS

We included 14 weight loss studies with a total of 2537 participants, and four weight maintenance studies with a total of 1603 participants. Treatment duration was between four weeks and 30 months. At six months, computer-based interventions led to greater weight loss than minimal interventions (mean difference (MD) -1.5 kg; 95% confidence interval (CI) -2.1 to -0.9; two trials) but less weight loss than in-person treatment (MD 2.1 kg; 95% CI 0.8 to 3.4; one trial). At six months, computer-based interventions were superior to a minimal control intervention in limiting weight regain (MD -0.7 kg; 95% CI -1.2 to -0.2; two trials), but not superior to infrequent in-person treatment (MD 0.5 kg; 95% -0.5 to 1.6; two trials). We did not observe consistent differences in dietary or physical activity behaviors between intervention and control groups in either weight loss or weight maintenance trials. Three weight loss studies estimated the costs of computer-based interventions compared to usual care, however two of the studies were 11 and 28 years old, and recent advances in technology render these estimates unlikely to be applicable to current or future interventions, while the third study was conducted in active duty military personnel, and it is unclear whether the costs are relevant to other settings. One weight loss study reported the cost-effectiveness ratio for a weekly in-person weight loss intervention relative to a computer-based intervention as USD 7177 (EUR 5678) per life year gained (80% CI USD 3055 to USD 60,291 (EUR 2417 to EUR 47,702)). It is unclear whether this could be extrapolated to other studies. No data were identified on adverse events, morbidity, complications or health-related quality of life.

AUTHORS' CONCLUSIONS

Compared to no intervention or minimal interventions (pamphlets, usual care), interactive computer-based interventions are an effective intervention for weight loss and weight maintenance. Compared to in-person interventions, interactive computer-based interventions result in smaller weight losses and lower levels of weight maintenance. The amount of additional weight loss, however, is relatively small and of brief duration, making the clinical significance of these differences unclear.

What predicts patient-reported GP management of smoking, nutrition, alcohol, physical activity and weight?

This study aimed to describe patient-reported management of behavioural risk factors in Australian general practice. Six hundred and ninety-eight eligible patients from 30 general practices in two rural and three urban Divisions of General Practice responded to a mailed invitation to participate and completed a questionnaire. Data were analysed using univariate and multi-level multivariate methods. The prevalence of risk factors varied between 12.6% for smoking and 72.6% for at-risk diet (56.2% were overweight). Most patients were at the action or maintenance phases of their readiness to change their risky behaviours. General practitioners (GPs) provided education or advice to between one-quarter and one-third of those at risk for each risk factor; 9.2% and 9.6% of patients reported having been referred for diet or physical activity interventions. Patient body mass index was associated with increased likelihood of receiving GP advice or referral for diet and physical activity interventions. Having poor diet or physical activity levels and being more ready for change were not associated with the likelihood of GP referral. The major challenge for general practice is to ensure that effective lifestyle interventions are provided to those who will most benefit. Patient-reported GP behavioural risk factor advice and referral is less frequent than is optimal. Priority needs to be given to those most at risk and ready to change their behaviour.

Eating the elephant whole or in slices: views of participants in a smoking cessation intervention trial on multiple behaviour changes as sequential or concurrent tasks

BACKGROUND

This paper explores smoking cessation participants' perceptions of attempting weight management alongside smoking cessation within the context of a health improvement intervention implemented in Glasgow, Scotland.

METHODS

One hundred and thirty-eight participants were recruited from smoking cessation classes in areas of multiple deprivation in Glasgow and randomised to intervention, receiving dietary advice, or to control groups. The primary outcome of the study was to determine the % change in body weight. Semi-structured interviews were conducted with a purposive sample of 15 intervention and 15 control participants at weeks 6 (during the intervention) and 24 (at the end of the intervention). The current paper, though predominantly qualitative, links perceptions of behaviour modification to % weight change and cessation rates at week 24 thereby enabling a better understanding of the mediators influencing multiple behaviour change.

RESULTS

Our findings suggest that participants who perceive separate behaviour changes as part of a broader approach to a healthier lifestyle, and hence attempt behaviour changes concurrently, may be at comparative advantage in positively achieving dual outcomes.

CONCLUSIONS

These findings highlight the need to assess participants' preference for attempting multiple behaviour changes sequentially or simultaneously in addition to assessing their readiness to change. Further testing of this hypothesis is warranted.

TRIAL REGISTRATION

ISRCTN94961361.

A Comprehensive Review of Faith-Based Physical Activity Interventions

This review provides a summary of physical activity interventions delivered in faith-based organizations. Electronic databases were searched to identify relevant studies. After screening, a total of n = 27 articles matched our inclusion criteria; 19 were identified as faith-based interventions (some spiritual or Biblical element included in the intervention) and 8 as faith-placed interventions (no spiritual component). Among all interventions, the most common research design was a randomized controlled trial. African American women were the most commonly targeted population and predominately Black churches were the most common setting. The majority of studies used self-report measures of physical activity. Most of the interventions did not use a theoretical framework to shape the intervention and weekly group sessions were the most frequently reported intervention approach. Overall, 12 of the faith-based and 4 of the faith-placed interventions resulted in increases in physical activity. Recommendations for future faith-based physical activity interventions include more rigorous study design, improved measures of physical activity, larger sample sizes, longer study and follow-up periods, and the use of theory in design and evaluation. Although limited, literature on faith-based physical activity interventions shows significant promise for improving physical activity participation and associated health outcomes.

Program completion of a web-based tailored lifestyle intervention for adults: differences between a sequential and a simultaneous approach

Background

Unhealthy lifestyle behaviors often co-occur and are related to chronic diseases. One effective method to change multiple lifestyle behaviors is web-based computer tailoring. Dropout from Internet interventions, however, is rather high, and it is challenging to retain participants in web-based tailored programs, especially programs targeting multiple behaviors. To date, it is unknown how much information people can handle in one session while taking part in a multiple behavior change intervention, which could be presented either sequentially (one behavior at a time) or simultaneously (all behaviors at once).

Objectives

The first objective was to compare dropout rates of 2 computer-tailored interventions: a sequential and a simultaneous strategy. The second objective was to assess which personal characteristics are associated with completion rates of the 2 interventions.

Methods

Using an RCT design, demographics, health status, physical activity, vegetable consumption, fruit consumption, alcohol intake, and smoking were self-assessed through web-based questionnaires among 3473 adults, recruited through Regional Health Authorities in the Netherlands in the autumn of 2009. First, a health risk appraisal was offered, indicating whether respondents were meeting the 5 national health guidelines. Second, psychosocial determinants of the lifestyle behaviors were assessed and personal advice was provided, about one or more lifestyle behaviors.

Results

Our findings indicate a high non-completion rate for both types of intervention (71.0%; n = 2167), with more incompletes in the simultaneous intervention (77.1%; n = 1169) than in the sequential intervention (65.0%; n = 998). In both conditions, discontinuation was predicted by a lower age (sequential condition: OR = 1.04; P < .001; CI = 1.02-1.05; simultaneous condition: OR = 1.04; P < .001; CI = 1.02-1.05) and an unhealthy lifestyle (sequential condition: OR = 0.86; P = .01; CI = 0.76-0.97; simultaneous condition: OR = 0.49; P < .001; CI = 0.42-0.58). In the sequential intervention, being male (OR = 1.27; P = .04; CI = 1.01-1.59) also predicted dropout. When respondents failed to adhere to at least 2 of the guidelines, those receiving the simultaneous intervention were more inclined to drop out than were those receiving the sequential intervention.

Conclusion

Possible reasons for the higher dropout rate in our simultaneous intervention may be the amount of time required and information overload. Strategies to optimize program completion as well as continued use of computer-tailored interventions should be studied.

Trial Registration

Dutch Trial Register NTR2168

Do participants' preferences for mode of delivery (text, video, or both) influence the effectiveness of a Web-based physical activity intervention?

Background

In randomized controlled trials, participants cannot choose their preferred intervention delivery mode and thus might refuse to participate or not engage fully if assigned to a nonpreferred group. This might underestimate the true effectiveness of behavior-change interventions.

Objective

To examine whether receiving interventions either matched or mismatched with participants’ preferred delivery mode would influence effectiveness of a Web-based physical activity intervention.

Methods

Adults (n = 863), recruited via email, were randomly assigned to one of three intervention delivery modes (text based, video based, or combined) and received fully automated, Internet-delivered personal advice about physical activity. Personalized intervention content, based on the theory of planned behavior and stages of change concept, was identical across groups. Online, self-assessed questionnaires measuring physical activity were completed at baseline, 1 week, and 1 month. Physical activity advice acceptability and website usability were assessed at 1 week. Before randomization, participants were asked which delivery mode they preferred, to categorize them as matched or mismatched. Time spent on the website was measured throughout the intervention. We applied intention-to-treat, repeated-measures analyses of covariance to assess group differences.

Results

Attrition was high (575/863, 66.6%), though equal between groups (t₈₆₃ =1.31, P =.19). At 1-month follow-up, 93 participants were categorized as matched and 195 as mismatched. They preferred text mode (493/803, 61.4%) over combined (216/803, 26.9%) and video modes (94/803, 11.7%). After the intervention, 20% (26/132) of matched-group participants and 34% (96/282) in the mismatched group changed their delivery mode preference. Time effects were significant for all physical activity outcomes (total physical activity: F_2,801 = 5.07, P = .009; number of activity sessions: F_2,801 = 7.52, P < .001; walking: F_2,801 = 8.32, P < .001; moderate physical activity: F_2,801 = 9.53, P < .001; and vigorous physical activity: F_2,801 = 6.04, P = .002), indicating that physical activity increased over time for both matched and mismatched groups. Matched-group participants improved physical activity outcomes slightly more than those in the mismatched group, but interaction effects were not significant. Physical activity advice acceptability (content scale: t₃₆₈ = .10, P = .92; layout scale: t₃₆₈ = 1.53, P = .12) and website usability (layout scale: t₄₂₆ = .05, P = .96; ease of use scale: t₄₂₆ = .21, P = .83) were generally high and did not differ between the matched and mismatched groups. The only significant difference (t₆₂₁ = 2.16, P = .03) was in relation to total time spent on the website: the mismatched group spent significantly more time on the website (14.4 minutes) than the matched group (12.1 minutes).

Conclusion

Participants’ preference regarding delivery mode may not significantly influence intervention outcomes. Consequently, allowing participants to choose their preferred delivery mode may not increase effectiveness of Web-based interventions.

Effect of a tailored behavior change program on a composite lifestyle change score: a randomized controlled trial

To evaluate the effect of a tailored behavior change program on a composite lifestyle change score. A randomized controlled trial conducted in Belgium in 2007-08 with 314 participants allocated to a control and an intervention condition. The intervention was a tailored behavior change program (web-based and individual coaching). The dose of the coaching was chosen by the participants and registered. Outcome measures were weight, saturated fat intake, fruit and vegetable intake, physical activity, smoking status and a composite lifestyle change score. Mann-Whitney U-tests, Kruskal-Wallis tests, t-tests and one-way analyses of variance were used to compare the study conditions and three intervention dose groups (no/low, medium and high intervention dose). There were no significant differences between the study conditions or between the intervention dose groups for the individual lifestyle factors. The composite lifestyle change score was significantly higher in the high intervention dose group compared with the no/low intervention dose group (P = 0.009). The composite lifestyle change score was positively related to the intervention dose, while the individual lifestyle factors were not. Behavior change programs that target multiple lifestyle factors could be evaluated by using a composite lifestyle change score taking into account the intervention dose.

Tailored print communication and telephone motivational interviewing are equally successful in improving multiple lifestyle behaviors in a randomized controlled trial

Background

Computer tailoring and motivational interviewing show promise in promoting lifestyle change, despite few head-to-head comparative studies.

Purpose

Vitalum is a randomized controlled trial in which the efficacy of these methods was compared in changing physical activity and fruit and vegetable consumption in middle-aged Dutch adults.

Methods

Participants (n = 1,629) were recruited via 23 general practices and randomly received either four tailored print letters, four motivational telephone calls, two of each type of intervention, or no information. The primary outcomes were absolute change in self-reported physical activity and fruit and vegetable consumption.

Results

All three intervention groups (i.e., the tailored letters, the motivational calls, and the combined version) were equally and significantly more effective than the control group in increasing physical activity (hours/day), intake of fruit (servings/day), and consumption of vegetables (grams/day) from baseline to the intermediate measurement (week 25), follow-up 1 (week 47) and 2 (week 73). Effect sizes (Cohen’s d) ranged from 0.15 to 0.18. Participants rated the interventions positively; interviews were more positively evaluated than letters.

Conclusions

Tailored print communication and telephone motivational interviewing or their combination are equally successful in changing multiple behaviors.

Electronic supplementary material

The online version of this article (doi:10.1007/s12160-010-9231-3) contains supplementary material, which is available to authorized users.

Characteristics of control group participants who increased their physical activity in a cluster-randomized lifestyle intervention trial

BACKGROUND

Meaningful improvement in physical activity among control group participants in lifestyle intervention trials is not an uncommon finding, and may be partly explained by participant characteristics. This study investigated which baseline demographic, health and behavioural characteristics were predictive of successful improvement in physical activity in usual care group participants recruited into a telephone-delivered physical activity and diet intervention trial, and descriptively compared these characteristics with those that were predictive of improvement among intervention group participants.

METHODS

Data come from the Logan Healthy Living Program, a primary care-based, cluster-randomized controlled trial of a physical activity and diet intervention. Multivariable logistic regression models examined variables predictive of an improvement of at least 60 minutes per week of moderate-to-vigorous intensity physical activity among usual care (n = 166) and intervention group (n = 175) participants.

RESULTS

Baseline variables predictive of a meaningful change in physical activity were different for the usual care and intervention groups. Being retired and completing secondary school (but no further education) were predictive of physical activity improvement for usual care group participants, whereas only baseline level of physical activity was predictive of improvement for intervention group participants. Higher body mass index and being unmarried may also be predictors of physical activity improvement for usual care participants.

CONCLUSION

This is the first study to examine differences in predictors of physical activity improvement between intervention group and control group participants enrolled in a physical activity intervention trial. While further empirical research is necessary to confirm findings, results suggest that participants with certain socio-demographic characteristics may respond favourably to minimal intensity interventions akin to the treatment delivered to participants in a usual care group. In future physical activity intervention trials, it may be possible to screen participants for baseline characteristics in order to target minimal-intensity interventions to those most likely to benefit. (Australian Clinical Trials Registry, http://www.anzctr.org.au/default.aspx, ACTRN012607000195459).

Tailored Health Communication to Change Lifestyle Behaviors

Tailored health communication research represents a very promising line of inquiry that has the potential to produce major impacts on lifestyle behaviors. This study defines tailoring and discusses how tailored interventions operate, including comparing/ contrasting different tailoring channels. Next, the authors review the literature on tailored interventions to change lifestyle behaviors, with a focus on smoking cessation, dietary change, and physical activity, as well as interventions that address multiple lifestyle behaviors. Finally, future directions for tailoring research are discussed. To date, a large literature has amassed showing the promise of tailored programs delivered via print, Internet, local computer/kiosk, telephone, and interpersonal channels. Numerous studies demonstrate that these programs are capable of significant impacts on smoking cessation, dietary change, physical activity, and multiple behavior change. It is concluded that the potential of tailoring will be more fully realized as (a) the field builds a more cumulative science of tailoring and (b) greater dissemination of efficacious tailored programs takes place.

Multiple health behavior changes and co-variation in a telephone counseling trial

BACKGROUND

Delivering effective multiple health behavior interventions to large numbers of adults with chronic conditions via primary care settings is a public health priority.

PURPOSE

Within a 12-month, telephone-delivered diet and physical activity intervention with multiple behavioral outcomes, we examined the extent and co-variation of multiple health behavior change.

METHODS

A cluster-randomized trial with 434 patients with type 2 diabetes or hypertension were recruited from 10 general practices, which were randomized to receive telephone counseling or usual care.

RESULTS

Those receiving telephone counseling were significantly more likely than those in usual care to make greater reductions in multiple behaviors after adjusting for baseline risk behaviors (OR 2.42; 95%CI 1.43, 4.11). Controlling for baseline risk and group allocation, making changes to either physical activity, fat, vegetable, or fiber intake was associated with making significantly more improvements in other behaviors.

CONCLUSIONS

For patients with chronic conditions, telephone counseling can significantly improve multiple health behaviors, with behavioral changes tending to co-vary.

Physical activity trends in Queensland (2002 to 2008): are women becoming more active than men?

OBJECTIVE

Regular monitoring of population levels of physical activity is an effective way to assess change over time towards meeting public health recommendations. The objective of this study was to determine physical activity trends in Central Queensland over the period 2002 to 2008.

METHODS

Data was obtained from the Central Queensland Social Survey (CQSS) conducted annually from 2002 to 2008. A total sample of 8,936 adults aged 18 and over participated in seven cross-sectional surveys. Physical activity was measured using the Active Australia Questionnaire. Binary logistic regression was used to examine trends in sufficient physical activity.

RESULTS

Averaged over all survey years 46.5% of study participants met national physical activity guidelines. A small significant upward trend was found for meeting physical activity recommendations across all years (OR=1.03; 95%CI=1.01-1.05), indicating that the odds of meeting the guidelines increased by an average of 3% per year from 2002 to 2008. Slightly more men than women met the activity guidelines (ns); however a significant positive trend in achieving sufficient activity levels was present in women only (4%).

CONCLUSIONS AND IMPLICATIONS

Although an increasing trend for sufficient physical activity was observed, overall physical activity levels in Central Queensland remain suboptimal and more efforts to increase physical activity are needed. The gender differences in physical activity trends indicate that men and women might need to be targeted differently in health promotion messages. The continuous monitoring of population levels of physical activity in Australia, which allow both state specific and international comparisons, is needed.

A meta-analysis of computer-tailored interventions for health behavior change

OBJECTIVE

Computer-tailored interventions have become increasingly common for facilitating improvement in behaviors related to chronic disease and health promotion. A sufficient number of outcome studies from these interventions are now available to facilitate the quantitative analysis of effect sizes, permitting moderator analyses that were not possible with previous systematic reviews.

METHOD

The present study employs meta-analytic techniques to assess the mean effect for 88 computer-tailored interventions published between 1988 and 2009 focusing on four health behaviors: smoking cessation, physical activity, eating a healthy diet, and receiving regular mammography screening. Effect sizes were calculated using Hedges g. Study, tailoring, and demographic moderators were examined by analyzing between-group variance and meta-regression.

RESULTS

Clinically and statistically significant overall effect sizes were found across each of the four behaviors. While effect sizes decreased after intervention completion, dynamically tailored interventions were found to have increased efficacy over time as compared with tailored interventions based on one assessment only. Study effects did not differ across communication channels nor decline when up to three behaviors were identified for intervention simultaneously.

CONCLUSION

This study demonstrates that computer-tailored interventions have the potential to improve health behaviors and suggests strategies that may lead to greater effectiveness of these techniques.

Improving physical activity and dietary behaviours with single or multiple health behaviour interventions? A synthesis of meta-analyses and reviews

Since multiple health behaviour interventions have gained popularity, it is important to investigate their effectiveness compared to single health behaviour interventions. This synthesis aims to determine whether single intervention (physical activity or dietary) or multiple interventions (physical activity and dietary) are more effective at increasing these behaviours by synthesizing reviews and meta-analyses. A sub-purpose also explored their impact on weight. Overall, reviews/meta-analyses showed that single health behaviour interventions were more effective at increasing the targeted behaviours, while multiple health behaviour interventions resulted in greater weight loss. This review may assist policies aiming at improving physical activity and nutrition and reversing the obesity epidemic.