Comparing strategies to assess multiple behavior change in behavioral intervention studies

Factors Reducing the Use of a Persuasive mHealth App and How to Mitigate Them: Thematic Analysis

BACKGROUND

Studies on which persuasive features may work for different users in health contexts are rare. The participants in this study were microentrepreneurs. We built a persuasive mobile app to help them to recover from work. Representatives of this target group tend to be very busy due to work, which was reflected in their use of the app during the randomized controlled trial intervention. Microentrepreneurs also often have dual roles; they are professionals in their line of work as well as entrepreneurs managing their own business, which may add to their workload.

OBJECTIVE

This study aimed to present users' views on the factors that hinder their use of the mobile health app that we developed and how these factors could be mitigated.

METHODS

We interviewed 59 users and conducted both data-driven and theory-driven analyses on the interviews.

RESULTS

Factors reducing app use could be divided into 3 categories: use context (problem domain-related issues, eg, the lack of time due to work), user context (user-related issues, eg, concurrent use of other apps), and technology context (technology-related issues, eg, bugs and usability). Due to the nature of the participants' entrepreneurship, which often interferes with personal life, it became clear that designs targeting similar target groups should avoid steep learning curves and should be easy (quick) to use.

CONCLUSIONS

Personalized tunneling-guiding the user through a system via personalized solutions-could help similar target groups with similar issues better engage with and keep using health apps because of the easy learning curve. When developing health apps for interventions, background theories should not be interpreted too strictly. Applying theory in practice may require rethinking approaches for adaptation as technology has evolved rapidly and continues to evolve.

TRIAL REGISTRATION

ClinicalTrials.gov NCT03648593; https://clinicaltrials.gov/ct2/show/NCT03648593.

Quantifying the overall impact of an early childhood multi-behavioural lifestyle intervention

BACKGROUND

The overall impact of interventions targeting multiple behaviours remains largely unexplored.

OBJECTIVES

This study adopted an integrative lifestyle pattern analysis approach to assess the overall effectiveness of an early childhood intervention on change across multiple behaviours.

METHODS

The Melbourne INFANT program was a 15-month cluster-randomized controlled trial involving 4-month-old infants and their parents at baseline in 2008 (n = 542). The intervention included six education sessions helping parents to promote a healthy diet, physical activity and limit sedentary behaviour in their infants. Participants were followed-up twice post-intervention, at ages 3.6 (2011) and 5 years (2013), to assess sustained effects of the intervention. Previous principal component analyses identified two lifestyle patterns from dietary intake, outdoor time and television viewing time. Random effect linear regression models were conducted to assess the impact of the intervention on lifestyle patterns.

RESULTS

The intervention group had a lower 'Discretionary consumption and TV' lifestyle pattern score than the control group at all time points with adjusted mean difference: -0.29, 95% CI -0.49, -0.09, p = 0.004 post-intervention at age 1.5 years; -0.29, 95% CI -0.54, -0.04, p = 0.02 at the first follow-up (age 3.6 years); and -0.21, 95% CI -0.43, 0.01, p = 0.06 at the second follow-up (age 5.0 years). No evidence of between-group differences was found for the 'Fruit, vegetables and outdoor' lifestyle pattern score.

CONCLUSION

This early childhood intervention designed to promote change in more than one obesity-related behaviour was effective in improving correlated unhealthy lifestyle behaviours. Lifestyle pattern analysis is a useful and interpretable approach for evaluating multi-behavioural interventions.

Effect of a physical activity and sleep m-health intervention on a composite activity-sleep behaviour score and mental health: a mediation analysis of two randomised controlled trials

BACKGROUND

To examine if a composite activity-sleep behaviour index (ASI) mediates the effects of a combined physical activity and sleep intervention on symptoms of depression, anxiety, or stress, quality of life (QOL), energy and fatigue in adults.

METHODS

This analysis used data pooled from two studies: Synergy and Refresh. Synergy: Physically inactive adults (18-65 years) who reported poor sleep quality were recruited for a two-arm Randomised Controlled Trial (RCT) (Physical Activity and Sleep Health (PAS; n = 80), or Wait-list Control (CON; n = 80) groups). Refresh: Physically inactive adults (40-65 years) who reported poor sleep quality were recruited for a three-arm RCT (PAS (n = 110), Sleep Health-Only (SO; n = 110) or CON (n = 55) groups). The SO group was omitted from this study. The PAS groups received a pedometer, and accessed a smartphone/tablet "app" using behaviour change strategies (e.g., self-monitoring, goal setting, action planning), with additional email/SMS support. The ASI score comprised self-reported moderate-to-vigorous-intensity physical activity, resistance training, sitting time, sleep duration, efficiency, quality and timing. Outcomes were assessed using DASS-21 (depression, anxiety, stress), SF-12 (QOL-physical, QOL-mental) and SF-36 (Energy & Fatigue). Assessments were conducted at baseline, 3 months (primary time-point), and 6 months. Mediation effects were examined using Structural Equation Modelling and the product of coefficients approach (AB), with significance set at 0.05.

RESULTS

At 3 months there were no direct intervention effects on mental health, QOL or energy and fatigue (all p > 0.05), and the intervention significantly improved the ASI (all p < 0.05). A more favourable ASI score was associated with improved symptoms of depression, anxiety, stress, QOL-mental and of energy and fatigue (all p < 0.05). The intervention effects on symptoms of depression ([AB; 95%CI] -0.31; - 0.60,-0.11), anxiety (- 0.11; - 0.27,-0.01), stress (- 0.37; - 0.65,-0.174), QOL-mental (0.53; 0.22, 1.01) and ratings of energy and fatigue (0.85; 0.33, 1.63) were mediated by ASI. At 6 months the magnitude of association was larger although the overall pattern of results remained similar.

CONCLUSIONS

Improvements in the overall physical activity and sleep behaviours of adults partially mediated the intervention effects on mental health and quality of life outcomes. This highlights the potential benefit of improving the overall pattern of physical activity and sleep on these outcomes.

TRIAL REGISTRATION

Australian New Zealand Clinical Trial Registry: ACTRN12617000680369 ; ACTRN12617000376347 . Universal Trial number: U1111-1194-2680; U1111-1186-6588. Human Research Ethics Committee Approval: H-2016-0267; H-2016-0181.

A Web-Based Computer-Tailored Program to Improve Treatment Adherence in Patients With Type 2 Diabetes: Randomized Controlled Trial

Background

Adherence to core type 2 diabetes mellitus (T2DM) treatment behaviors is suboptimal, and nonadherence is generally not limited to one treatment behavior. The internet holds promise for programs that aim to improve adherence. We developed a computer-tailored eHealth program for patients with T2DM to improve their treatment adherence, that is, adherence to both a healthy lifestyle and medical behaviors.

Objective

The objective of this study is to examine the effectiveness of the eHealth program in a randomized controlled trial.

Methods

Patients with T2DM were recruited by their health professionals and randomized into either the intervention group, that is, access to the eHealth program for 6 months, or a waiting-list control group. In total, 478 participants completed the baseline questionnaire, of which 234 gained access to the eHealth program. Of the 478 participants, 323 were male and 155 were female, the mean age was 60 years, and the participants had unfavorable BMI and HbA_1c levels on average. Outcome data were collected through web-based assessments on physical activity (PA) levels, caloric intake from unhealthy snacks, and adherence to oral hypoglycemic agents (OHAs) and insulin therapy. Changes to separate behaviors were standardized and summed into a composite change score representing changes in the overall treatment adherence. Further standardization of this composite change score yielded the primary outcome, which can be interpreted as Cohen d (effect size). Standardized change scores observed in separate behaviors acted as secondary outcomes. Mixed linear regression analyses were conducted to examine the effectiveness of the intervention on overall and separate treatment behavior adherence, accommodating relevant covariates and patient nesting.

Results

After the 6-month follow-up assessment, 47.4% (111/234) of participants in the intervention group and 72.5% (177/244) of participants in the control group were retained. The overall treatment adherence improved significantly in the intervention group compared with the control group, reflected by a small effect size (d=0.27; 95% CI 0.032 to 0.509; P=.03). When considering changes in separate treatment behaviors, a significant decrease was observed only in caloric intake from unhealthy snacks in comparison with the control group (d=0.36; 95% CI 0.136 to 0.584; P=.002). For adherence to PA (d=−0.14; 95% CI −0.388 to 0.109; P=.27), OHAs (d=0.27; 95% CI −0.027 to 0.457; P=.08), and insulin therapy (d=0.35; 95% CI −0.066 to 0.773; P=.10), no significant changes were observed. These results from the unadjusted analyses were comparable with the results of the adjusted analyses, the per-protocol analyses, and the sensitivity analyses.

Conclusions

Our multibehavior program significantly improved the overall treatment adherence compared with the control group. To further enhance the impact of the intervention in the personal, societal, and economic areas, a wide-scale implementation of our eHealth intervention is suggested.

Trial Registration

Netherlands Trial Register NL664; https://www.trialregister.nl/trial/6664

Adherence to multiple health behaviours in cancer survivors: a systematic review and meta-analysis

PURPOSE

Multiple health behaviours (not smoking, minimal alcohol consumption, and maintaining a healthy weight by having a healthy diet and regular physical activity) improve quality of life and longevity of cancer survivors. Despite international guidelines, there are no existing reviews that synthesise cancer survivors' adherence to healthy lifestyle recommendations.

METHOD

Five databases (Embase, MEDLINE, PsycINFO, Web of Science, and Google Scholar) were searched for relevant articles published from 2007 until January 2018. Studies reporting adult cancer survivors' adherence to at least two lifestyle behaviours (body mass index, physical activity, smoking, fruit and vegetable intake, fiber intake, red meat intake, caloric intake, sodium intake, and alcohol consumption) based on the World Cancer Research Fund/American Institute for Cancer Research (WCRF/AICR) recommendations were included in the review. The pooled prevalence of adherence to single and multiple behaviours was calculated using a random-effects model. Subgroup analysis (mean years of survival and publication year) was undertaken.

RESULTS

A total of 3322 articles were identified. Of these, 51 studies matched the inclusion criteria, presenting data from 2,620,586 adult cancer survivors. Adherence to single behaviours, which was estimated from studies that assessed at least two health behaviours, was highest for not smoking (PE 87%; 95% CI, 85%, 88%) and low or no alcohol intake (PE 83%; 95% CI, 81%, 86%), and lowest for fiber intake (PE 31%; 95% CI, 21%, 40%). Adherence to multiple healthy behaviours (13 studies), ranged from 7 to 40% (pooled estimate (PE) 23%; 95% CI, 17%, 30%). Recent survivors (< 5-year survival time) had relatively better adherence to multiple behaviours (PE 31%; 95% CI, 27%, 35%) than long-term (> 5 years) survivors (PE 25%; 95% CI, 14%, 36%). Adherence to multiple behaviours improved over time since 2007.

CONCLUSION

Adherence to physical activity, dietary, and multiple lifestyle behaviours recommendations was low amongst cancer survivors. Recent cancer survivors were relatively more adherent to WCRF/AICR recommendations compared to long-term survivors.

IMPLICATIONS FOR CANCER SURVIVORS

Health promotion programs help support healthy lifestyle behaviours of cancer survivors. PROSPERO registration number: CRD42018091663.

Compliance with Multiple Health Behaviour Recommendations: A Cross-Sectional Comparison between Female Cancer Survivors and Those with no Cancer History

Lifestyle behaviours have an important role in preventing cancer, reducing treatment side effects, and improving survival and quality of life for cancer survivors. This study investigated adherence to multiple lifestyle behaviours among women with and without a cancer history. From the Australian Longitudinal Study on Women’s Health (ALSWH) surveys, 2407 cancer survivors and 3896 controls (cancer free population) were identified. Based on the World Cancer Research Fund/American Institute for Cancer Research (WCRF/AICR) recommendations, adherence to six health behaviours (smoking, physical activity, fruit and vegetable intake, alcohol consumption, sugary drink intake, and Body Mass Index [BMI]) were assessed. Overall adherence was low, and there were no differences between survivors and controls on adherence to any of the six individual health behaviours. However, both recent and long-term cancer survivors were more likely than controls to adhere to multiple health behaviours (p < 0.05). When participants with melanoma or non-melanoma skin cancer were excluded, adherence was less likely (but not significant) in the cancer group than controls. Higher education (p < 0.01), being married (p < 0.01), and lower comorbidity of chronic illnesses (p < 0.01) were significantly associated with adherence to multiple lifestyle behaviours. Overall, the findings suggest that a cancer diagnosis may result in increased compliance with multiple health behaviour guidelines.

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.

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.

Text Message and Internet Support for Coronary Heart Disease Self-Management: Results From the Text4Heart Randomized Controlled Trial

BACKGROUND

Mobile technology has the potential to deliver behavior change interventions (mHealth) to reduce coronary heart disease (CHD) at modest cost. Previous studies have focused on single behaviors; however, cardiac rehabilitation (CR), a component of CHD self-management, needs to address multiple risk factors.

OBJECTIVE

The aim was to investigate the effectiveness of a mHealth-delivered comprehensive CR program (Text4Heart) to improve adherence to recommended lifestyle behaviors (smoking cessation, physical activity, healthy diet, and nonharmful alcohol use) in addition to usual care (traditional CR).

METHODS

A 2-arm, parallel, randomized controlled trial was conducted in New Zealand adults diagnosed with CHD. Participants were recruited in-hospital and were encouraged to attend center-based CR (usual care control). In addition, the intervention group received a personalized 24-week mHealth program, framed in social cognitive theory, sent by fully automated daily short message service (SMS) text messages and a supporting website. The primary outcome was adherence to healthy lifestyle behaviors measured using a self-reported composite health behavior score (≥3) at 3 and 6 months. Secondary outcomes included clinical outcomes, medication adherence score, self-efficacy, illness perceptions, and anxiety and/or depression at 6 months. Baseline and 6-month follow-up assessments (unblinded) were conducted in person.

RESULTS

Eligible patients (N=123) recruited from 2 large metropolitan hospitals were randomized to the intervention (n=61) or the control (n=62) group. Participants were predominantly male (100/123, 81.3%), New Zealand European (73/123, 59.3%), with a mean age of 59.5 (SD 11.1) years. A significant treatment effect in favor of the intervention was observed for the primary outcome at 3 months (AOR 2.55, 95% CI 1.12-5.84; P=.03), but not at 6 months (AOR 1.93, 95% CI 0.83-4.53; P=.13). The intervention group reported significantly greater medication adherence score (mean difference: 0.58, 95% CI 0.19-0.97; P=.004). The majority of intervention participants reported reading all their text messages (52/61, 85%). The number of visits to the website per person ranged from zero to 100 (median 3) over the 6-month intervention period.

CONCLUSIONS

A mHealth CR intervention plus usual care showed a positive effect on adherence to multiple lifestyle behavior changes at 3 months in New Zealand adults with CHD compared to usual care alone. The effect was not sustained to the end of the 6-month intervention. A larger study is needed to determine the size of the effect in the longer term and whether the change in behavior reduces adverse cardiovascular events.

TRIAL REGISTRATION

ACTRN 12613000901707; https://www.anzctr.org.au/Trial/Registration/TrialReview.aspx?id=364758&isReview=true (Archived by WebCite at http://www.webcitation.org/6c4qhcHKt).

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.

Improving coronary heart disease self-management using mobile technologies (Text4Heart): a randomised controlled trial protocol

Background

Cardiac rehabilitation (CR) is a secondary prevention program that offers education and support to assist patients with coronary heart disease (CHD) make lifestyle changes. Despite the benefits of CR, attendance at centre-based sessions remains low. Mobile technology (mHealth) has potential to reach more patients by delivering CR directly to mobile phones, thus providing an alternative to centre-based CR. The aim of this trial is to evaluate if a mHealth comprehensive CR program can improve adherence to healthy lifestyle behaviours (for example, physically active, fruit and vegetable intake, not smoking, low alcohol consumption) over and above usual CR services in New Zealand adults diagnosed with CHD.

Methods/design

A two-arm, parallel, randomised controlled trial will be conducted at two Auckland hospitals in New Zealand. One hundred twenty participants will be randomised to receive a 24-week evidence- and theory-based personalised text message program and access to a supporting website in addition to usual CR care or usual CR care alone (control). The primary outcome is the proportion of participants adhering to healthy behaviours at 6 months, measured using a composite health behaviour score. Secondary outcomes include overall cardiovascular disease risk, body composition, illness perceptions, self-efficacy, hospital anxiety/depression and medication adherence.

Discussion

This study is one of the first to examine an mHealth-delivered comprehensive CR program. Strengths of the trial include quality research design and in-depth description of the intervention to aid replication. If effective, the trial has potential to augment standard CR practices and to be used as a model for other disease prevention or self-management programs.

Trial registry

Australian New Zealand Clinical Trials Registry: ACTRN12613000901707