Multiple Health Behavior Change Interventions Research Articles

Moderating effects of socioeconomic status and geographical location on the Health4Life school-based intervention

ObjectiveThis study evaluated the moderating effects of socioeconomic status (SES) and geographical location on the efficacy of an eHealth school-based multiple health behaviour change intervention – Health4Life – in targeting alcohol and tobacco use, dietary intake, knowledge, behavioural intentions, and psychological distress over 24-months. MethodsData from the Health4Life cluster-randomised controlled trial conducted from 2019 to 2021 in 71 Australian secondary schools were analysed (N=6639; baseline age 11-14yrs). Schools were from metropolitan (89%) and regional (11%) areas, and participants’ SES was classified as low (15%), mid (37%), and high (48%) relative to the study population. Primary outcomes included alcohol and tobacco use, and a composite indicator of poor diet. Secondary outcomes were knowledge, behavioural intentions, and psychological distress. Latent growth models assessed moderating effects of SES and geographical location on between-group change over 24-months. ResultsGeographical location moderated the intervention’s effect on odds of reporting a poor diet (OR = 1.79, 95% CI = 1.32–2.43, p < 0.001) and diet-related behavioural intentions (OR = 0.71, 95% CI = 0.56–0.89, p = 0.024) over time. Subset analyses indicated that intervention participants in regional areas had higher odds of reporting a poor diet (OR = 1.61, 95% CI = 1.13–2.29, p = 0.008), while those in metropolitan areas had higher odds of improving diet-related behavioural intentions (OR = 1.13, 95% CI = 1.01–1.27, p = 0.041), compared to the control group. No other significant moderation effects were observed. ConclusionsWhile significant disparities were generally not observed, the geographical differences in intervention effects on diet and diet-related intentions suggest that co-designed and tailored approaches may benefit disadvantaged adolescents to address the disproportionately high rates of lifestyle risk behaviours among these priority populations.

The moderating effect of access to food facilities and recreational activity space on mHealth multiple health behavior change intervention.

To evaluate whether the neighborhood social and built environment moderates response to a mobile health multiple health behavior change intervention targeting fruit/vegetable intake, sedentary behavior, and physical activity. Participants were 156 Chicago-residing adults with unhealthy lifestyle behaviors. Using linear mixed models, we evaluated whether access to food facilities (fast food restaurants and grocery stores) and recreational activity spaces (gyms and parks) moderated the difference in behavior change between the active intervention condition relative to control. Using spatial data analysis (cross K functions), we also assessed whether participants who achieved goal levels of behaviors ("responders") were more or less likely than those who did not achieve intervention goals ("non-responders") to reside near fast food restaurants, grocery stores, gyms, or parks. According to linear mixed models, none of the neighborhood social and built environment factors moderated the difference in behavior change between the active intervention condition and the control condition (Likelihood Ratio (χ²[1] = 0.02-2.33, P-values > 0.05). Cross K functions showed that diet behavior change responders were more likely than non-responders to reside near fast food restaurants, but not grocery stores. The results for activity behavior change were more variable. Sedentary screen time responders were more likely to reside around recreational activity spaces than non-responders. Moderate-vigorous physical activity responders had greater and lesser clustering than non-responders around parks, dependent upon distance from the park to participant residence. A complex relationship was observed between residential proximity to Chicago facilities and response to multiple health behavior change intervention. Replication across diverse geographic settings and samples is necessary.

Assessing the Effectiveness of eHealth Interventions to Manage Multiple Lifestyle Risk Behaviors Among Older Adults: Systematic Review and Meta-Analysis.

Developing adverse lifestyle behaviors increases the risk of a variety of chronic age-related diseases, including cardiovascular disease, obesity, and Alzheimer disease. There is limited evidence regarding the effectiveness of eHealth-based multiple health behavior change (MHBC) interventions to manage lifestyle risk behaviors. The purpose of this systematic evaluation was to assess the effectiveness of eHealth MHBC interventions in changing ≥2 major lifestyle risk behaviors in people aged ≥50 years. The literature search was conducted in 6 electronic databases-PubMed, Embase, Web of Science, Scopus, Cochrane Library, and SPORTDiscus-from inception to May 1, 2024. Eligible studies were randomized controlled trials of eHealth interventions targeting ≥2 of 6 behaviors of interest: alcohol use, smoking, diet, physical activity (PA), sedentary behavior, and sleep. A total of 34 articles with 35 studies were included. eHealth-based MHBC interventions significantly increased smoking cessation rates (odds ratio 2.09, 95% CI 1.62-2.70; P<.001), fruit intake (standardized mean difference [SMD] 0.18, 95% CI 0.04-0.32; P=.01), vegetable intake (SMD 0.17, 95% CI 0.05-0.28; P=.003), self-reported total PA (SMD 0.22, 95% CI 0.02-0.43; P=.03), and objectively measured moderate to vigorous PA (SMD 0.25, 95% CI 0.09-0.41; P=.002); in addition, the interventions decreased fat intake (SMD -0.23, 95% CI -0.33 to -0.13; P<.001). No effects were observed for alcohol use, sedentary behavior, or sleep. A sensitivity analysis was conducted to test the robustness of the pooled results. Moreover, the certainty of evidence was evaluated using the GRADE (Grading of Recommendations Assessment, Development, and Evaluation) framework. eHealth-based MHBC interventions may be a promising strategy to increase PA, improve diet, and reduce smoking among older adults. However, the effect sizes were small. Further high-quality, older adult-oriented research is needed to develop eHealth interventions that can change multiple behaviors. PROSPERO International Prospective Register of Systematic Reviews CRD42023444418; https://www.crd.york.ac.uk/prospero/display_record.php?ID=CRD42023444418.

Anxiety, depression and distress outcomes from the Health4Life intervention for adolescent mental health: a cluster-randomized controlled trial

Mental disorders are a leading cause of disease burden worldwide. As onset typically occurs in adolescence, prevention during this period is critical. The Health4Life-school-based multiple health behavior change (MHBC) intervention targets six lifestyle risk factors: diet, sleep, physical activity, screentime, alcohol use and smoking. Health4Life has been evaluated in a cluster-randomized controlled trial in 71 Australian schools (6,639 grade seven students). This study presents intervention effects on secondary outcomes of depressive, anxiety and psychological distress symptoms. Generalized linear mixed-effect analyses of data from baseline, post-intervention (7 weeks), 12 months and 24 months showed that the Health4Life intervention was no more effective than an active control in reducing depressive, anxiety or psychological distress symptoms at a 24 or 12 month follow-up; however, there were short-term benefits for psychological distress and depressive symptoms immediately post-intervention. This study offers new evidence that multiple health behavior change interventions may improve adolescent mental health, but future research should explore methods to address anxiety and sustain effects over the longer term. A priori ANZCTR trial registration: ACTRN12619000431123.

Effectiveness of Interventions for Changing More Than One Behavior at a Time to Manage Chronic Conditions: A Systematic Review and Meta-analysis.

Health behaviors play a significant role in chronic disease management. Rather than being independent of one another, health behaviors often co-occur, suggesting that targeting more than one health behavior in an intervention has the potential to be more effective in promoting better health outcomes. We aimed to conduct a systematic review and meta-analysis of randomized trials of interventions that target more than one behavior to examine the effectiveness of multiple health behavior change interventions in patients with chronic conditions. Five electronic databases (Web of Science, PubMed, CINAHL, EMBASE, and Cochrane) were systematically searched in November 2023, and studies included in previous reviews were also consulted. We included randomized trials of interventions aiming to change more than one health behavior in individuals with chronic conditions. Two independent reviewers screened and extracted data, and used Cochrane's Risk of Bias 2 tool. Meta-analyses were conducted to estimate the effects of interventions on change in health behaviors. Results were presented as Cohen's d for continuous data, and risk ratio for dichotomous data. Sixty-one studies were included spanning a range of chronic diseases: cardiovascular (k = 25), type 2 diabetes (k = 15), hypertension (k = 10), cancer (k = 7), one or more chronic conditions (k = 3), and multiple conditions (k = 1). Most interventions aimed to change more than one behavior simultaneously (rather than in sequence) and most targeted three particular behaviors at once: "physical activity, diet and smoking" (k = 20). Meta-analysis of 43 eligible studies showed for continuous data (k = 29) a small to substantial positive effect on behavior change for all health behaviors (d = 0.081-2.003) except for smoking (d = -0.019). For dichotomous data (k = 23) all analyses showed positive effects of targeting more than one behavior on all behaviors (RR = 1.026-2.247). Targeting more than one behavior at a time is effective in chronic disease management and more research should be directed into developing the science of multiple behavior change.

The Health4Life e-health intervention for modifying lifestyle risk behaviours of adolescents: secondary outcomes of a cluster randomised controlled trial.

To investigate the effectiveness of a school-based multiple health behaviour change e-health intervention for modifying risk factors for chronic disease (secondary outcomes). Cluster randomised controlled trial. Students (at baseline [2019]: year 7, 11-14 years old) at 71 Australian public, independent, and Catholic schools. Health4Life: an e-health school-based multiple health behaviour change intervention for reducing increases in the six major behavioural risk factors for chronic disease: physical inactivity, poor diet, excessive recreational screen time, poor sleep, and use of alcohol and tobacco. It comprises six online video modules during health education class and a smartphone app. Comparison of Health4Life and usual health education with respect to their impact on changes in twelve secondary outcomes related to the six behavioural risk factors, assessed in surveys at baseline, immediately after the intervention, and 12 and 24 months after the intervention: binge drinking, discretionary food consumption risk, inadequate fruit and vegetable intake, difficulty falling asleep, and light physical activity frequency (categorical); tobacco smoking frequency, alcohol drinking frequency, alcohol-related harm, daytime sleepiness, and time spent watching television and using electronic devices (continuous). A total of 6640 year 7 students completed the baseline survey (Health4Life: 3610; control: 3030); 6454 (97.2%) completed at least one follow-up survey, 5698 (85.8%) two or more follow-up surveys. Health4Life was not statistically more effective than usual school health education for influencing changes in any of the twelve outcomes over 24 months; for example: fruit intake inadequate: odds ratio [OR], 1.08 (95% confidence interval [CI], 0.57-2.05); vegetable intake inadequate: OR, 0.97 (95% CI, 0.64-1.47); increased light physical activity: OR, 1.00 (95% CI, 0.72-1.38); tobacco use frequency: relative difference, 0.03 (95% CI, -0.58 to 0.64) days per 30 days; alcohol use frequency: relative difference, -0.34 (95% CI, -1.16 to 0.49) days per 30 days; device use time: relative difference, -0.07 (95% CI, -0.29 to 0.16) hours per day. Health4Life was not more effective than usual school year 7 health education for modifying adolescent risk factors for chronic disease. Future e-health multiple health behaviour change intervention research should examine the timing and length of the intervention, as well as increasing the number of engagement strategies (eg, goal setting) during the intervention. Australian New Zealand Clinical Trials Registry: ACTRN12619000431123 (prospective).

“Healthier health in more ways than one”: Perspectives on a program for changing both smoking and obesity-related health behaviors

IntroductionIndividuals with obesity who smoke cigarettes have increased risk of morbidity and mortality. The goal of the current study was to inform the development of a multiple health behavior change intervention designed to facilitate smoking cessation while also targeting weight gain. MethodsFour qualitative focus groups were conducted with individuals who smoked cigarettes and had overweight or obesity (n = 16) to explore the combined effects of smoking and obesity, past attempts to quit smoking or lose weight, and preferences for a combined health intervention. ResultsFocus groups converged on five themes including: the interactive effects of weight and smoking; lack of experience with evidence-based weight loss approaches; a desire and expectation to lose weight quickly; rapid weight gain during past attempts at smoking cessation; and interest in a multiple health behavior change intervention with weight management preceding smoking cessation and an emphasis on planning for the future and receiving encouragement and support. ConclusionsGroups provided insight into key topics to highlight in a combined intervention and key issues that have interfered with success in both domains.

Potential Mediators of a School-Based Digital Intervention Targeting Six Lifestyle Risk Behaviours in a Cluster Randomised Controlled Trial of Australian Adolescents

Lifestyle risk behaviours—physical inactivity, poor diet, poor sleep, recreational screen time, and alcohol and tobacco use—collectively known as the “Big 6” emerge during adolescence and significantly contribute to chronic disease development into adulthood. To address this issue, the Health4Life program targeted the Big 6 risk behaviours simultaneously via a co-designed eHealth school-based multiple health behaviour change (MHBC) intervention. This study used multiple causal mediation analysis to investigate some potential mediators of Health4Life’s effects on the Big 6 primary outcomes from a cluster randomised controlled trial of Health4Life among Australian school children. Mediators of knowledge, behavioural intentions, self-efficacy, and self-control were assessed. The results revealed a complex pattern of mediation effects across different outcomes. Whilst there was a direct effect of the intervention on reducing moderate-to-vigorous physical activity risk, the impact on sleep duration appeared to occur indirectly through the hypothesised mediators. Conversely, for alcohol and tobacco use, both direct and indirect effects were observed in opposite directions cancelling out the total effect (competitive partial mediation). The intervention’s effects on alcohol and tobacco use highlighted complexities, suggesting the involvement of additional undetected mediators. However, little evidence supported mediation for screen time and sugar-sweetened beverage intake risk. These findings emphasise the need for tailored approaches when addressing different risk behaviours and designing effective interventions to target multiple health risk behaviours. The trial was pre-registered with the Australian and New Zealand Clinical Trials Registry: ACTRN12619000431123.

Digital interventions to moderate alcohol consumption in young people: a Cancer Prevention Europe overview of systematic reviews.

Strategies to reduce alcohol consumption would contribute to substantial health benefits in the population, including reducing cancer risk. The increasing accessibility and applicability of digital technologies make these powerful tools suitable to facilitate changes in behaviour in young people which could then translate into both immediate and long-term improvements to public health. We conducted a review of systematic reviews to assess the available evidence on digital interventions aimed at reducing alcohol consumption in sub-populations of young people [school-aged children, college/university students, young adults only (over 18 years) and both adolescent and young adults (<25 years)]. Searches were conducted across relevant databases including KSR Evidence, Cochrane Database of Systematic Reviews (CDSR) and Database of Abstracts of Reviews of Effects (DARE). Records were independently screened by title and abstract and those that met inclusion criteria were obtained for full text screening by two reviewers. Risk of bias (RoB) was assessed with the ROBIS checklist. We employed a narrative analysis. Twenty-seven systematic reviews were included that addressed relevant interventions in one or more of the sub-populations, but those reviews were mostly assessed as low quality. Definitions of "digital intervention" greatly varied across systematic reviews. Available evidence was limited both by sub-population and type of intervention. No reviews reported cancer incidence or influence on cancer related outcomes. In school-aged children eHealth multiple health behaviour change interventions delivered through a variety of digital methods were not effective in preventing or reducing alcohol consumption with no effect on the prevalence of alcohol use [Odds Ratio (OR) = 1.13, 95% CI: 0.95-1.36, review rated low RoB, minimal heterogeneity]. While in adolescents and/or young adults who were identified as risky drinkers, the use of computer or mobile device-based interventions resulted in reduced alcohol consumption when comparing the digital intervention with no/minimal intervention (-13.4 g/week, 95% CI: -19.3 to -7.6, review rated low RoB, moderate to substantial heterogeneity).In University/College students, a range of E-interventions reduced the number of drinks consumed per week compared to assessment only controls although the overall effect was small [standardised mean difference (SMD): -0.15, 95% CI: -0.21 to -0.09]. Web-based personalised feedback interventions demonstrated a small to medium effect on alcohol consumption (SMD: -0.19, 95% CI: -0.27 to -0.11) (review rated high RoB, minimal heterogeneity). In risky drinkers, stand-alone Computerized interventions reduced short (SMD: -0.17, 95% CI: -0.27 to -0.08) and long term (SMD: -0.17, 95% CI: -0.30 to -0.04) alcohol consumption compared to no intervention, while a small effect (SMD: -0.15, 95% CI: -0.25 to -0.06) in favour of computerised assessment and feedback vs. assessment only was observed. No short-term (SMD: -0.10, 95% CI: -0.30 to 0.11) or long-term effect (SMD: -0.11, 95% CI: -0.53 to 0.32) was demonstrated for computerised brief interventions when compared to counsellor based interventions (review rated low RoB, minimal to considerable heterogeneity). In young adults and adolescents, SMS-based interventions did not significantly reduce the quantity of drinks per occasion from baseline (SMD: 0.28, 95% CI: -0.02 to 0.58) or the average number of standard glasses per week (SMD: -0.05, 95% CI: -0.15 to 0.05) but increased the risk of binge drinking episodes (OR = 2.45, 95% CI: 1.32-4.53, review rated high RoB; minimal to substantial heterogeneity). For all results, interpretation has limitations in terms of risk of bias and heterogeneity. Limited evidence suggests some potential for digital interventions, particularly those with feedback, in reducing alcohol consumption in certain sub-populations of younger people. However, this effect is often small, inconsistent or diminishes when only methodologically robust evidence is considered. There is no systematic review evidence that digital interventions reduce cancer incidence through alcohol moderation in young people. To reduce alcohol consumption, a major cancer risk factor, further methodologically robust research is warranted to explore the full potential of digital interventions and to form the basis of evidence based public health initiatives.

Participant Preferences for the Development of a Digitally Delivered Gardening Intervention to Improve Diet, Physical Activity, and Cardiovascular Health: Cross-sectional Study.

Low dietary intake of fruits and vegetables and physical inactivity are 2 modifiable risk factors for cardiovascular disease. Fruit and vegetable gardening can provide access to fresh produce, and many gardening activities are considered moderate physical activity. This makes gardening interventions a potential strategy for cardiovascular disease risk reduction. Previously developed gardening interventions have relied on in-person delivery models, which limit scalability and reach. The purpose of this study was to ascertain participant insight on intervention components and topics of interest to inform a digitally delivered, gardening-focused, multiple health behavior change intervention. A web-based survey was delivered via Amazon Mechanical Turk (MTurk), including quantitative and open-ended questions. Eligible participants were aged ≥20 years, could read and write in English, were US residents, and had at least a 98% MTurk task approval rating. A multilevel screening process was used to identify and exclude respondents with response inattention, poor language fluency, or suspected automated web robots (bots). Participants were asked about their interest in gardening programming, their preferences for intervention delivery modalities (1-hour expert lectures, a series of brief <5-minute videos, or in-person meetings), and what information is needed to teach new gardeners. Comparisons were made between never gardeners (NG) and ever gardeners (EG) in order to examine differences in perceptions based on prior experience. Quantitative data were summarized, and differences between groups were tested using chi-square tests. Qualitative data were coded and organized into intervention functions based on the Behavior Change Wheel. A total of 465 participants were included (n=212, 45.6% NG and n=253, 54.4% EG). There was a high level of program interest overall (n=355, 76.3%), though interest was higher in EG (142/212, 67% NG; 213/253, 84.2% EG; P<.001). The majority of participants (n=282, 60.7%) preferred a series of brief <5-minute videos (136/212, 64.2% NG; 146/253, 57.7% EG; P=.16) over 1-hour lectures (29/212, 13.7% NG; 50/253, 19.8% EG; P=.08) or in-person delivery modes (47/212, 22.2% NG; 57/253, 22.5% EG; P=.93). Intervention functions identified were education and training (performing fundamental gardening and cooking activities), environmental restructuring (eg, social support), enablement (provision of tools or seeds), persuasion (offering encouragement and highlighting the benefits of gardening), and modeling (using content experts and participant testimonials). Content areas identified included the full lifecycle of gardening activities, from the fundamentals of preparing a garden site, planting and maintenance to harvesting and cooking. In a sample of potential web-based learners, participants were interested in a digitally delivered gardening program. They preferred brief videos for content delivery and suggested content topics that encompassed how to garden from planting to harvesting and cooking. The next step in this line of work is to identify target behavior change techniques and pilot test the intervention to assess participant acceptability and preliminary efficacy.

Health4Life eHealth intervention to modify multiple lifestyle risk behaviours among adolescent students in Australia: a cluster-randomised controlled trial

Lifestyle risk behaviours are prevalent among adolescents and commonly co-occur, but current intervention approaches tend to focus on single risk behaviours. This study aimed to evaluate the efficacy of the eHealth intervention Health4Life in modifying six key lifestyle risk behaviours (ie, alcohol use, tobacco smoking, recreational screen time, physical inactivity, poor diet, and poor sleep, known as the Big 6) among adolescents. We conducted a cluster-randomised controlled trial in secondary schools that had a minimum of 30 year 7 students, in three Australian states. A biostatistician randomly allocated schools (1:1) to Health4Life (a six-module, web-based programme and accompanying smartphone app) or an active control group (usual health education) with the Blockrand function in R, stratified by site and school gender composition. All students aged 11-13 years who were fluent in English and attended participating schools were eligible. Teachers, students, and researchers were not masked to allocation. Primary outcomes were alcohol use, tobacco use, recreational screen time, moderate to vigorous physical activity (MVPA), sugar-sweetened beverage intake, and sleep duration at 24 months, measured by self-report surveys, and analysed in all students who were eligible at baseline. Latent growth models estimated between-group change over time. This trial is registered with the Australian New Zealand Clinical Trials Registry (ACTRN12619000431123). Between April 1, 2019, and Sept 27, 2019, we recruited 85 schools (9280 students), of which 71 schools with 6640 eligible students (36 schools [3610 students] assigned to the intervention and 35 [3030 students] to the control) completed the baseline survey. 14 schools were excluded from the final analysis or withdrew, mostly due to a lack of time. We found no between-group differences for alcohol use (odds ratio 1·24, 95% CI 0·58-2·64), smoking (1·68, 0·76-3·72), screen time (0·79, 0·59-1·06), MVPA (0·82, 0·62-1·09), sugar-sweetened beverage intake (1·02, 0·82-1·26), or sleep (0·91, 0·72-1·14) at 24 months. No adverse events were reported during this trial. Health4Life was not effective in modifying risk behaviours. Our results provide new knowledge about eHealth multiple health behaviour change interventions. However, further research is needed to improve efficacy. Paul Ramsay Foundation, the Australian National Health and Medical Research Council, the Australian Government Department of Health and Aged Care, and the US National Institutes of Health.

A multiple health behaviour change intervention to prevent depression: A randomized controlled trial

ObjectiveTo examine the effectiveness of a 12-month MHBC intervention in the prevention of onset depression in primary health care (PHC). MethodsTwenty-two PHC centres took part in the cluster-randomized controlled trial. Patients were randomized to receive either usual care or an MHBC intervention. The endpoints were onset of major depression and reduction of depressive symptoms in participants without baseline depression at a 12-month follow-up. Results2531 patients agreed and were eligible to participate. At baseline, around 43% were smokers, 82% were non-adherent to the Mediterranean diet and 55% did not perform enough physical activity. The intervention group exhibited a greater positive change in two or more behaviours (OR 1.75 [95%CI: 1.17 to 2.62]; p = 0.006); any behaviour (OR 1.58 [95%CI: 1.13 to 2.20]; p = 0.007); and adherence to the Mediterranean diet (OR 1.94 [95%CI: 1.29 to 2.94]; p = 0.002), while this increase was not statistically significant for smoking and physical activity. The intervention was not effective in preventing major depression (OR 1.17; [95% CI 0.53 to 2.59)]; p = 0.690) or reducing depressive symptoms (Mean difference: 0.30; [95% CI -0.77 to 1.36]; p = 0.726) during follow-up. ConclusionsAs compared to usual care, the MHBC intervention provided a non-significant reduction in the incidence of major depression.Trial registration:ClinicalTrials.gov, NCT03136211.

Diet, Physical Activity, and Stress Among Wheelchair Users With Multiple Sclerosis: Examining Individual and Co-Occurring Behavioral Risk Factors

ObjectiveThis study examined individual and co-occurring behavioral risk factors (diet, exercise, and stress) in wheelchair users with multiple sclerosis (MS) and potential association with MS symptoms (ie, fatigue, depression, anxiety, pain, sleep, and health-related quality of life [HRQOL]). DesignSurvey. SettingGeneral Community. ParticipantsOne hundred twenty-three wheelchair users with MS completed this study (N=123). InterventionsNot applicable. Main Outcome MeasuresParticipants were mailed instructions for accessing online questionnaires (demographic and clinical characteristics, Godin Leisure-Time Exercise Questionnaire, Perceived Stress Scale, Automated Self-Administered 24-Hour Dietary Assessment Tool, and MS symptoms). ResultsStandard cut-points were used to categorize behavioral risk factors and then identify the extent and distribution of these behaviors both individually and co-occurring. We then analyzed the associations between behavioral risk factors and MS symptoms using bivariate correlation analyses and Mann-Whitney U tests. The mean age of participants was 60.6±10.0 years, 76% identified as women, 82% had a progressive disease course, and the mean MS duration was 23.0±9.7 years. Seven participants were classified as having 0 negative health behaviors, 41 participants had 1 negative health behavior, 49 participants had 2 negative health behaviors, and 26 participants had 3 negative health behaviors. The number of negative health behaviors was significantly correlated with HRQOL (physical, r=.30; psychological, r=.47), sleep (r=.25), depressive symptoms (r=.36), and anxiety (r=.43). Mann-Whitney U tests indicated greater fatigue, depression, and anxiety as well as lower sleep quality and HRQOL among participants who reported 2 or 3 behavioral risk factors compared with 0 or 1 behavioral risk factor. ConclusionsFuture research should examine the design and implementation of multiple health behavior change interventions targeting co-occurring behavioral risk factors among wheelchair users with MS.

Psychosocial Mediators of Web-Based Interventions for Promoting a Healthy Lifestyle Among Chinese College Students: Secondary Analysis of a Randomized Controlled Trial.

BackgroundWeb-based multiple health behavior change (MHBC) interventions have demonstrated effectiveness in promoting physical activity (PA) and fruit and vegetable consumption (FVC) among Chinese college students. However, there is limited research examining their effects on promoting a healthy lifestyle (ie, adhering to both PA and FVC behavioral recommendations) among Chinese college students. In addition, the salient psychosocial mediators of successful MHBC interventions need to be researched.ObjectiveThis study aims to examine the effectiveness of a previous 8-week web-based MHBC program for promoting a healthy lifestyle and enhancing the psychosocial determinants (intention, self-efficacy, planning, and social support) of behavior change among Chinese college students. Furthermore, the study aims to identify whether changes in these psychosocial determinants mediate intervention effectiveness on the immediate and sustained lifestyle changes.MethodsThis was a secondary analysis for a 3-arm randomized controlled trial. Chinese college students (N=552) were randomly assigned to 1 of 3 groups: a PA-first group (4-week PA intervention followed by 4-week FVC intervention), an FVC-first group (4-week FVC intervention followed by 4-week PA intervention), and a placebo control group. The intervention content was designed based on the health action process approach model. Data for analyses were collected at baseline (T0), postintervention assessment (T1), and 12-week follow-up assessment (T2).ResultsAt baseline, 13.9% (77/552) of the participants maintained a healthy lifestyle. After 8 weeks, more (200/552, 36.2%) participants achieved a healthy lifestyle. PA-first and FVC-first groups were, respectively, 3.24 times and 5 times more likely to adopt a healthy lifestyle than the control group at T1. After 12 weeks, 35.5% (196/552) of the participants adopted a healthy lifestyle. Intervention groups were approximately 2.99 times (PA first) and 4.07 times (FVC first) more likely to adopt a healthy lifestyle than the control group at T2. Intervention effects favored both intervention groups in self-efficacy and planning for PA and in intention and planning for FVC compared with the control condition. In addition, changes in PA self-efficacy and FVC intention mediated intervention effectiveness on the immediate lifestyle change after 8 weeks. Changes in FVC intention were identified as a salient mediator for facilitating sustained lifestyle change after 12 weeks.ConclusionsThis study provides empirical evidence for the effectiveness of an 8-week theory- and web-based MHBC intervention program on promoting a healthy lifestyle, self-efficacy and planning for PA, and intention and planning for FVC among Chinese college students. These research findings add new knowledge to the underlying psychosocial mechanisms of successful MHBC interventions. Overall, this study has considerable implications for future web-based MHBC research and practice in terms of addressing PA self-efficacy and FVC intention and helping students to adopt and maintain a healthy lifestyle independently of whether PA or FVC is addressed first.Trial RegistrationClinicalTrials.gov NCT03627949; https://clinicaltrials.gov/ct2/show/NCT03627949

Digital multiple health behaviour change intervention targeting online help seekers: protocol for the COACH randomised factorial trial

IntroductionUnhealthy lifestyle behaviours continue to be highly prevalent, including alcohol consumption, unhealthy diets, insufficient physical activity and smoking. There is a lack of effective interventions which have a large enough...

A Community-Based Participatory Action Research with Women from Disadvantaged Populations: Strengths and Weaknesses of a Multiple Health Behaviour Change Intervention.

Disadvantaged populations usually adopt risk behaviours, resulting in obesity and mental health-related disorders. Grounded in the socioecological model and self-determination theory, the aims were firstly to describe and implement a two-year multiple health behaviour change intervention, and secondly, to assess the strengths and weaknesses of the intervention. In total, 11 women from a disadvantaged population participated in this programme, which encompassed 117 sessions. Qualitative techniques were used to collect data and a thematic analysis was conducted. The variety of activities and the group-based intervention were the main strengths, and the decrease in attendance and the programme’s tight schedule were the main weaknesses. This is the first intervention in a disadvantaged population mainly comprised of Roma women. The design described in detail and its assessment provide relevant knowledge to improve their health status and decrease inequalities. The practical implications for future research are useful for replicating interventions in similar contexts.

A Health Behavior and Lifestyle Intervention Pilot Trial for Childbearing Adolescents

We pilot tested a multiple health behavior change (MHBC) intervention to improve breastfeeding rates, healthy eating/active living, and depression prevention among pregnant and parenting adolescent mothers. We also assessed utility of the MHBC mHealth approach by examining health behavior coaction and intervention acceptability. We used a longitudinal randomized controlled trial to compare the tablet-delivered momHealth to a control condition (usual care). Delivered between 32 weeks of pregnancy and one month postpartum, momHealth included nine multi-media education modules, simultaneous daily educational text messaging, and weekly videoconferences for individual and group support. Main outcomes included “any” and “exclusive” breastfeeding initiation and continuation for 5 weeks and 3 months postpartum; number of fruit and vegetable servings; minutes of moderate/vigorous physical activity per day; and depressive symptoms. Sixty-two adolescents aged 16–19 having their first baby were randomized. Compared to Control, more momHealth participants were still breastfeeding at 5 weeks (chi-square = 3.91, df = 1, P = .048). Mothers who breastfed for 3 months were more likely to eat adequate daily fruits/vegetables. Participants positively rated the intervention. momHealth positively affected early breastfeeding continuation and trended toward positive outcomes in healthy living and depressive symptoms. A fully powered trial is planned to test the intervention more effectively.

Multiple lifestyle risk behaviours and hierarchical dimensions of psychopathology in 6640 Australian adolescents.

Physical inactivity, sugar sweetened beverage consumption, alcohol use, smoking, poor sleep and excessive recreational screen time (the 'Big 6' lifestyle risk behaviours) often co-occur and are key risk factors for psychopathology. However, the best fitting latent structure of the Big 6 is unknown and links between multiple lifestyle risk behaviours and hierarchical dimensions of psychopathology have not been explored among adolescents. This study aimed to address these gaps in the literature. Confirmatory factor analysis, latent class analysis and factor mixture models were conducted among 6640 students (Mage = 12.7 years) to identify the latent structure of the Big 6 lifestyle risk behaviours. Structural equation models were then used to examine associations with psychopathology. A mixture model with three classes, capturing mean differences in a single latent factor indexing overall risk behaviours, emerged as the best fitting model. This included relatively low-risk (Class 1: 30%), moderate-risk (Class 2: 67%) and high-risk (Class 3: 3%) classes. Students high on externalizing demonstrated significantly greater odds of membership to the high-risk class (odds ratio = 8.75, 99% confidence interval = [3.30, 23.26]) and moderate-risk class (odds ratio = 2.93, 99% confidence interval = [1.43, 5.97]) in comparison to the low-risk class. Similarly, students high on internalizing demonstrated significantly higher odds of membership to the high-risk class (odds ratio = 1.89, 99% confidence interval = [1.06, 3.37]) and the moderate-risk class (odds ratio = 1.66, 99% confidence interval = [1.03, 2.67]) in comparison to the low-risk class. Associations between lower order factors of psychopathology and lifestyle risk behaviours were mostly accounted for by the more parsimonious higher order factors. Classes representing differences in probabilities of the Big 6 lifestyle risk behaviours relate to varying levels of hierarchical dimensions of psychopathology, suggesting multiple health behaviour change and transdiagnostic intervention approaches may be valuable for reducing risk of psychopathology.

The Effectiveness of Sequentially Delivered Web-Based Interventions on Promoting Physical Activity and Fruit-Vegetable Consumption Among Chinese College Students: Mixed Methods Study.

BackgroundWeb-based interventions for multiple health behavior change (MHBC) appear to be a promising approach to change unhealthy habits. Limited research has tested this assumption in promoting physical activity (PA) and fruit-vegetable consumption (FVC) among Chinese college students. Moreover, the timing of MHBC intervention delivery and the order of components need to be addressed.ObjectiveThis study aims to examine the effectiveness of 2 sequentially delivered 8-week web-based interventions on physical activity, FVC, and health-related outcomes (BMI, depression, and quality of life) and the differences in the intervention effects between the 2 sequential delivery patterns. The study also aims to explore participants’ experiences of participating in the health program.MethodsWe conducted a randomized controlled trial, in which 552 eligible college students (mean 19.99, SD 1.04 years, 322/552, 58.3% female) were randomly assigned to 1 of 3 groups: PA-first group (4 weeks of PA followed by 4 weeks of FVC intervention), FVC-first group (4 weeks of FVC followed by 4 weeks of PA intervention), and a control group (8 weeks of placebo treatment unrelated to PA and FVC). The treatment content of two intervention groups was designed based on the Health Action Process Approach (HAPA) framework. A total of four web-based assessments were conducted: at baseline (T1, n=565), after 4 weeks (T2, after the first behavior intervention, n=486), after 8 weeks (T3, after the second behavior intervention, n=420), and after 12 weeks (T4, 1-month postintervention follow-up, n=348). In addition, after the completion of the entire 8-week intervention, 18 participants (mean 19.56, SD 1.04 years, 10/18, 56% female) who completed the whole program were immediately invited to attend one-to-one and face-to-face semistructured interviews. The entire study was conducted during the fall semester of 2017.ResultsThe quantitative data supported superior effects on physical activity, FVC, and BMI in the 2 sequential intervention groups compared with the control group. There were no significant differences in physical activity, FVC, and health-related outcomes between the 2 intervention groups after 8 weeks. The FVC-first group contributed to more maintenance of FVC compared with the PA-first group after 12 weeks. Four major themes with several subthemes were identified in the qualitative thematic analysis: PA and FVC behavior, health-related outcomes, correlates of behavior change, and contamination detection.ConclusionsThis study provides empirical evidence for the effectiveness of sequentially delivered, web-based MHBC interventions on PA and FVC among Chinese college students. The timing issue of MHBC intervention delivery was preliminarily addressed. Qualitative findings provide an in-depth understanding and supplement the quantitative findings. Overall, this study may contribute considerably to future web-based MHBC interventions.Trial RegistrationClinicalTrials.gov NCT03627949; https://clinicaltrials.gov/ct2/show/NCT03627949International Registered Report Identifier (IRRID)RR2-10.1186/s12889-019-7438-1

Effects of a multiple chronic condition (CC) remote monitoring program on clinical outcomes among older adults

Older adults are faced with an increased risk of comorbid chronic disease such as diabetes. While multiple health behavior change interventions (MHCIs) are known to improve clinical outcomes more than targeted interventions, less is known whether such effects persist in older populations. The objective of the study was to examine the effects of multiple chronic condition (CC) remote monitoring program enrollment and mental health program enrollment on glucose and blood pressure reduction, adjusting for self-monitoring behaviors. In a sample of 594 older adults (age 55+, 14% 65+ years, 46.8% female) evaluated over a 12-month period, statistical models showed that older adults with uncontrolled diabetes (A1c >= 7.0%) had a 7.9 pt. reduction in blood glucose for each additional program enrolled and a 22.7 pt. reduction in blood glucose when enrolled in mental health compared to those not enrolled. Similarly, older adults with uncontrolled hypertension (BP >= 130/80) had a 4.8 pt. reduction in systolic blood pressure for each additional program enrolled and a 7.2 pt. reduction in systolic blood pressure when enrolled in mental health compared to those not enrolled. The findings indicate the potential for multiprogram digital health interventions that incorporate mental health to further improve clinical outcomes in older adults suffering from multiple chronic diseases, namely diabetes and hypertension.