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

Intention to change multiple health risk behaviors and predictors of behavior change in vocational education students

Objective: No studies have examined vocational education students' intention to change multiple health risk behaviors and whether baseline characteristics predict behavior change. Participants: Paticipants were vocational education students in New South Wales, Australia. Methods: Students in the no-intervention control arm of a cluster randomized controlled trial completed an online survey at baseline and 6 months later. Results: Of 450 participants (83.3%) who reported multiple health risk behaviors at baseline, one-third (33.1%) intended to change at least two risk behaviors within 6 months. Participants experiencing symptoms of anxiety [OR = 7.43, 95% CIs 1.26-43.87; p = 0.03] and who intended to change three to four risk behaviors [OR = 23.30, 95% CIs 4.01-135.40; p = 0.001] rather than one behavior had significantly greater odds of changing at least one behavior in 6 months. Conclusions: Interventions could support vocational education students to change behaviors they wish to as well as motivate them to address other risk behaviors.

Social and Behavioural Correlates of High Physical Activity Levels among Aboriginal Adolescent Participants of the Next Generation: Youth Wellbeing Study

Physical activity typically decreases during teenage years and has been identified as a health priority by Aboriginal adolescents. We examined associations between physical activity levels and sociodemographic, movement and health variables in the Aboriginal led 'Next Generation: Youth Well-being (NextGen) Study' of Aboriginal people aged 10-24 years from Central Australia, Western Australia and New South Wales. Baseline survey data collected by Aboriginal researchers and Aboriginal youth peer recruiters from 2018 to 2020 examined demographics and health-related behaviours. Logistic regression was used to estimate odds ratios (OR) for engaging in high levels of physical activity in the past week (3-7 days; 0-2 days (ref), or 'don't remember') associated with demographic and behavioural factors. Of 1170 adolescents, 524 (41.9%) had high levels of physical activity; 455 (36.4%) had low levels; 191 (15.3%) did not remember. Factors independently associated with higher odds of physical activity 3-7 days/week were low weekday recreational screen time [55.3% vs. 44.0%, OR 1.79 (1.16-2.76)], having non-smoking friends [50.4% vs. 25.0%, OR 2.27 (1.03-5.00)] and having fewer friends that drink alcohol [48.1% vs. 35.2%, OR 2.08 (1.05-4.14)]. Lower odds of high physical activity were independently associated with being female [40.2% vs. 50.9%, OR 0.57 (0.40-0.80)] and some findings differed by sex. The NextGen study provides evidence to inform the co-design and implementation of strategies to increase Aboriginal adolescent physical activity such as focusing on peer influences and co-occurring behaviours such as screen time.

Codeveloping a multibehavioural mobile phone app to enhance social and emotional well-being and reduce health risks among Aboriginal and Torres Strait Islander women during preconception and pregnancy: a three-phased mixed-methods study

OBJECTIVE

Describe the development and pretest of a prototype multibehavioural change app MAMA-EMPOWER.

DESIGN

Mixed-methods study reporting three phases: (1) contextual enquiry included stakeholder engagement and qualitative interviews with Aboriginal women, (2) value specification included user-workshop with an Aboriginal researcher, community members and experts, (3) codesign with Aboriginal researchers and community members, followed by a pretest of the app with Aboriginal women, and feedback from qualitative interviews and the user-Mobile Application Rating Scale (U-MARS) survey tool.

SETTINGS

Aboriginal women and communities in urban and regional New South Wales, Australia.

PARTICIPANTS

Phase 1: interviews, 8 Aboriginal women. Phase 2: workshop, 6 Aboriginal women. Phase 3: app trial, 16 Aboriginal women. U-MARS, 5 Aboriginal women.

RESULTS

Phase 1 interviews revealed three themes: current app use, desired app characteristics and implementation. Phase 2 workshop provided guidance for the user experience. Phase 3 app trial assessed all content areas. The highest ratings were for information (mean score of 3.80 out of 5, SD=0.77) and aesthetics (mean score of 3.87 with SD of 0.74), while functionality, engagement and subjective quality had lower scores. Qualitative interviews revealed the acceptability of the app, however, functionality was problematic.

CONCLUSIONS

Developing a mobile phone app, particularly in an Aboriginal community setting, requires extensive consultation, negotiation and design work. Using a strong theoretical foundation of behavioural change technique's coupled with the consultative approach has added rigour to this process. Using phone apps to implement behavioural interventions in Aboriginal community settings remains a new area for investigation. In the next iteration of the app, we aim to find better ways to personalise the content to women's needs, then ensure full functionality before conducting a larger trial. We predict the process of development will be of interest to other health researchers and practitioners.

Barriers and Facilitators to the Uptake of Online and Telephone Services Targeting Health Risk Behaviours among Vocational Education Students: A Qualitative Study

Uptake of online and telephone services targeting health behaviours is low among vocational education students and barriers and facilitators are unknown. This study aimed to explore barriers and facilitators to uptake of online and telephone services for smoking, nutrition, alcohol, and physical activity (SNAP) risk behaviours via semi-structured individual telephone interviews with fifteen vocational education students. Two authors independently completed thematic analysis, classified themes according to the COM-B (Capability, Opportunity, Motivation, Behaviour) framework, and discussed disagreements until consensus was reached. Facilitators to uptake of online (e.g., desire to learn something new, cost-free, accessible) and telephone services (e.g., prefer to talk to provider, complements online support) primarily related to capability and opportunity. For telephone services, difficulty understanding accent/language was a capability-related barrier. Opportunity-related barriers for online and telephone services were preference for face-to-face interaction and lack of time, while preference for apps/online programs was a barrier for telephone services. For online and telephone services, not wanting to change SNAP behaviours was a motivation-related barrier and being able to change SNAP risk behaviours themselves was a motivation-related barrier for online services. Barriers and facilitators to online and telephone services are relevant for designing interventions vocational education students are more likely to use.

Evaluation of the B.strong Queensland Indigenous Health Worker Brief Intervention Training Program for Multiple Health Risk Behaviours

Queensland’s B.strong brief intervention training program was a complex intervention developed for Aboriginal and Torres Strait Islander health workers to assist clients address multiple health risks of smoking, poor nutrition and physical inactivity. This study evaluates program effectiveness by applying the Kirkpatrick four-level evaluation model: (1) Reaction, participants’ satisfaction; (2) Learning, changes in participants’ knowledge, confidence, attitudes, skills and usual practice; (3) Behaviour, application of learning to practice; and (4) Results, outcomes resulting from training. A retrospective analysis was conducted on data for respondents completing pre-training, post-workshop and follow-up surveys. Changes in domains such as training participant knowledge, confidence, attitudes, and practices between survey times were assessed using paired-samples t-tests. From 2017–2019, B.strong trained 1150 health professionals, reaching targets for workshop and online training. Findings showed statistically significant improvements from baseline to follow-up in: participants’ knowledge, confidence, and some attitudes to conducting brief interventions in each domain of smoking cessation, nutrition and physical activity; and in the frequency of participants providing client brief interventions in each of the three domains. There was a statistically significant improvement in frequency of participants providing brief interventions for multiple health behaviours at the same time from pre-workshop to follow-up. Indigenous Queenslander telephone counselling referrals for smoking cessation increased during the program period. B.strong improved practitioners’ capacity to deliver brief interventions addressing multiple health risks with Indigenous clients.

Barriers and facilitators to the implementation of brief interventions targeting smoking, nutrition, and physical activity for indigenous populations: a narrative review

Objective

This narrative review aimed to identify and categorize the barriers and facilitators to the provision of brief intervention and behavioral change programs that target several risk behaviors among the Indigenous populations of Australia, Canada, and New Zealand.

Methods

A systematic database search was conducted of six databases including PubMeD, Embase, CINAHL, HealthStar, PsycINFO, and Web of Science. Thematic analysis was utilized to analyze qualitative data extracted from the included studies, and a narrative approach was employed to synthesize the common themes that emerged. The quality of studies was assessed in accordance with the Joanna Briggs Institute’s guidelines and using the software SUMARI – The System for the Unified Management, Assessment and Review of Information.

Results

Nine studies were included. The studies were classified at three intervention levels: (1) individual-based brief interventions, (2) family-based interventions, and (3) community-based-interventions. Across the studies, selection of the intervention level was associated with Indigenous priorities and preferences, and approaches with Indigenous collaboration were supported. Barriers and facilitators were grouped under four major categories representing the common themes: (1) characteristics of design, development, and delivery, (2) patient/provider relationship, (3) environmental factors, and (4) organizational capacity and workplace-related factors. Several sub-themes also emerged under the above-mentioned categories including level of intervention, Indigenous leadership and participation, cultural appropriateness, social and economic barriers, and design elements.

Conclusion

To improve the effectiveness of multiple health behavior change interventions among Indigenous populations, collaborative approaches that target different intervention levels are beneficial. Further research to bridge the knowledge gap in this topic will help to improve the quality of preventive health strategies to achieve better outcomes at all levels, and will improve intervention implementation from development and delivery fidelity, to acceptability and sustainability.

Influence of Educational Level on Psychosocial Correlates and Perceived Environmental Correlates of Physical Activity in Adults at Risk for Type 2 Diabetes: The Feel4Diabetes-Study

BACKGROUND

This study aimed to investigate whether the relationship between psychosocial and perceived environmental factors and physical activity (PA) in adults at risk for type 2 diabetes is influenced by educational level.

METHODS

Based on the Finnish Diabetes Risk Score questionnaire, this study selected 164 adults (Mage: 38 (5.34) y, 13.4% men) at type 2 diabetes risk from 11 low socioeconomic neighborhoods in Flanders (Belgium). Participants filled out questionnaires on psychosocial and perceived environmental factors and wore an ActiGraph accelerometer for 5 consecutive days. Statistical analyses were performed using analysis of covariance in SPSS.

RESULTS

Educational level significantly influenced the association between perception of body weight and light PA (P = .01) and total PA (P = .03) on weekend days. Educational level did not influence the associations between other psychosocial and perceived environmental factors (ie, perceived social influence; environmental, time and attitudinal barriers, perceived self-efficacy; knowledge and fatalism) and PA.

CONCLUSIONS

Educational level did not influence the relationship between most psychosocial and perceived environmental factors and PA in this sample of adults at type 2 diabetes risk. This suggests that addressing different psychosocial and perceived environmental correlates in lower and higher educated participants might not be necessary. However, more research in this specific population is needed.

Smoking cessation after hospitalization for myocardial infarction or cardiac surgery: Assessing patient interest, confidence, and physician prescribing practices

Background

Prioritizing and managing multiple behavior changes following a cardiac hospitalization can be difficult, particularly among smokers who must also overcome a serious addiction.

Hypothesis

Hospitalized smokers will report a strong interest in smoking cessation (SC) but will receive little assistance from their physicians.

Methods

We asked current smokers hospitalized for an acute cardiac event to prioritize their health behavior priorities, and inquired about their attitude toward SC therapies. We also assessed SC cessation prescriptions provided by their physicians.

Results

Of the 105 patients approached, 81 (77%) completed the survey. Of these, 72.5% ranked SC as their greatest health change priority, surpassing all other behavior changes, including: taking medications, attending cardiac rehabilitation (CR), dieting, losing weight, and attending doctor appointments. Patients felt that SCM (44%), CR (41%), and starting exercise (35%) would increase their likelihood for SC. While most patients agreed that smoking was harmful, 16% strongly disagreed that smoking was related to their hospitalization. At discharge, medication was prescribed to ~32% of patients, with equal frequency among patients who reported interest and those who reported no interest in using medications.

Conclusion

The majority of hospitalized smokers with cardiac disease want to quit smoking, desire help in doing so, and overwhelmingly rate cessation as their highest health behavior priority, although some believe smoking is unrelated to their disease. The period following an acute cardiac event appears to be a time of great receptivity to SC interventions; however, rates of providing tailored, evidence‐based interventions are disappointingly low.

The Prospective Association Between the Five Factor Personality Model With Health Behaviors and Health Behavior Clusters

To examine the prospective association of personality with individual behavior, multibehavior and clustered health behavior profiles. A prospective study design was employed. Two hundred young adults provided baseline data and 126 (mean age: 21.6 yrs) provide complete data for a 5-month follow-up assessment (63% response rate). Personality and health behaviors (and covariates) were assessed via validated questionnaires. A multibehavior index variable was created ranging from 0-5; two separate health behavior cluster indices were created, including high (4-5 behaviors) vs. low (2 or fewer) behavior adoption and an energy balance cluster (MVPA and diet). When examining MVPA as a continuous variable, the personality trait conscientiousness was prospectively associated with MVPA and a healthy diet. Extraversion was prospectively associated with high (vs. low) behavioral clustering (OR = 1.18; 95% CI: 1.00-1.40) and conscientiousness was prospectively associated with energy balance clustering (OR = 1.09; 95% CI: 1.01-1.17). Extraversion, conscientiousness, openness to experience, and agreeableness were associated with select health-related behaviors. Further, extraversion and conscientiousness were associated with health behavior clustering.