Goal feedback from whom? A physical activity intervention using an N-of-1 RCT

StudyMe: a new mobile app for user-centric N-of-1 trials

N-of-1 trials are multi-crossover self-experiments that allow individuals to systematically evaluate the effect of interventions on their personal health goals. Although several tools for N-of-1 trials exist, there is a gap in supporting non-experts in conducting their own user-centric trials. In this study, we present StudyMe, an open-source mobile application that is freely available from https://play.google.com/store/apps/details?id=health.studyu.me and offers users flexibility and guidance in configuring every component of their trials. We also present research that informed the development of StudyMe, focusing on trial creation. Through an initial survey with 272 participants, we learned that individuals are interested in a variety of personal health aspects and have unique ideas on how to improve them. In an iterative, user-centered development process with intermediate user tests, we developed StudyMe that features an educational part to communicate N-of-1 trial concepts. A final empirical evaluation of StudyMe showed that all participants were able to create their own trials successfully using StudyMe and the app achieved a very good usability rating. Our findings suggest that StudyMe provides a significant step towards enabling individuals to apply a systematic science-oriented approach to personalize health-related interventions and behavior modifications in their everyday lives.

A Systematic Review of the Scope of Study of mHealth Interventions for Wellness and Related Challenges in Pediatric and Young Adult Populations

Background

Despite the purported advantages and potential efficacy of mHealth interventions to promote wellness in children, adolescents, and young adults, it is not clear what areas have been explored and the challenges reported in the biomedical literature.

Methods

We conducted a scoping review of publications between 2015 and 2019.

Results

We identified 54 papers that met our inclusion criteria. Studies were conducted in 21 countries and ranged in size from six to 9851 participants (median: 184). A total of 41% of studies enrolled adolescents only (n = 19). Of the seven types of mHealth interventions identified, apps were the most common intervention (59%; n = 32) evaluated and 44% of the studies evaluated two or more interventions. The most common topic of the studies reviewed was sexual and reproductive health (24%; n = 13).

Conclusion

Most pediatric mHealth intervention studies are conducted in adolescents in large part, and sexual and reproductive health is the most commonly studied topic. With the easy and widespread accessibility to smartphone technology, the use of mobile apps for wellness interventions will likely continue to expand to other wellness topics.

Evaluation of the Healthy Living after Cancer text message-delivered, extended contact intervention using the RE-AIM framework

Background

Text message-delivered interventions have potential to prevent weight regain and maintain diet and physical activity behaviours through extending contact with participants following initial weight loss, lifestyle interventions. Using the RE-AIM Framework, this study evaluated the adoption, reach, implementation, effectiveness, and maintenance of an extended contact text-message intervention following the Healthy Living after Cancer (HLaC) program. HLaC was a 6-month, telephone-delivered intervention targeting healthy diet, physical activity and weight loss for adult cancer survivors, offered by Cancer Councils (CCs) in Australia.

Methods

HLaC completers (n = 182) were offered extended contact via text messages for 6-months (HLaC+Txt). Text message content/frequency was individually tailored to participant’s preferences, ascertained through two telephone-tailoring interviews with CC staff. Adoption (HLaC+Txt uptake among eligible CCs), reach (uptake by HLaC completers) and implementation (intervention cost/length; text dose) were assessed. The effectiveness of extended contact relative to historic controls was quantified by pre-to-post HLaC+Txt changes in self-reported: weight, moderate-vigorous physical activity (MVPA), fruit and vegetable intake, fat and fibre behaviour. Maintenance, following 6-months of noncontact for the intervention cohort, was assessed for these same variables. Semi-structured interviews with CC staff and participants contextualised outcomes.

Results

HLaC+Txt was adopted by all four CCs who had delivered HLaC. In total, 115 participants commenced HLaC+Txt, with reach ranging across CCs from 47 to 80% of eligible participants. The mean number of weeks participants received the text message intervention ranged across CCs from 18.5–22.2 weeks. Participants received (median, 25th,75th percentile) 83 (48, 119) texts, ranging across CCs from 40 to 112. The total cost of HLaC+Txt delivery was on average $AUD85.00/participant. No meaningful (p < 0.05) differences in self-reported outcomes were seen between HLaC+Txt and control cohorts. After 6-months no contact the intervention cohort had maintained weight, fruit intake, fat and fibre index scores relative to end of HLaC+Txt outcomes. Participants/CC staff perceived an important intervention component was maintaining accountability.

Conclusions

While feasible to implement, HLaC+Txt was not effective in the short term. However, intervention effects during the non-contact period suggest the program supports longer term maintenance of weight and diet behaviour. Intervention delivery in this real-world context highlighted key considerations for future implementation.

Trial registration

Australian and New Zealand Clinical Trials Registry (ANZCTR) - ACTRN12615000882527 (registered on 24/08/2015).

Supplementary Information

The online version contains supplementary material available at 10.1186/s12885-021-08806-4.

Adaptive mHealth Intervention for Adolescent Physical Activity Promotion

OBJECTIVE

The present nonrandomized controlled trial aimed to evaluate feasibility, acceptability, and preliminary efficacy of a tailored text message intervention for increasing adolescent physical activity, as compared with passive monitoring.

METHODS

Forty adolescents (13-18 years old) received either a tailored text messaging intervention (Network Underwritten Dynamic Goals Engine [NUDGE]; N = 20), or participated in an attention-control condition (N = 20), for 20 days. Physical activity was measured for all participants via continuous accelerometry. Frequency analyses were conducted on program usage and satisfaction ratings to evaluate feasibility and acceptability, and multilevel models were used to evaluate the efficacy hypotheses.

RESULTS

The vast majority of participants (90%) reported being very or mostly satisfied with the NUDGE program and rated their enjoyment as above average. The intervention group was estimated to spend an average of 20.84 more minutes per day in moderate-to-vigorous physical activity relative to the attention-control group (β = 20.84, SE = 8.19). Exploratory analyses revealed that the intervention group also engaged in 82 fewer minutes of sedentary time per day on average, although this effect was not significant due to the large variability in sedentary time (β = -81.98, SE = 46.86).

CONCLUSIONS

The NUDGE tailored text messaging intervention was feasible, acceptable, and efficacious in increasing physical activity in this sample. Findings warrant additional evaluation of NUDGE as both a standalone physical activity intervention or as part of a multicomponent package.

Caregiver involvement in interventions for improving children's dietary intake and physical activity behaviors

BACKGROUND

Poor diet and insufficient physical activity are major risk factors for non-communicable diseases. Developing healthy diet and physical activity behaviors early in life is important as these behaviors track between childhood and adulthood. Parents and other adult caregivers have important influences on children's health behaviors, but whether their involvement in children's nutrition and physical activity interventions contributes to intervention effectiveness is not known.

OBJECTIVES

• To assess effects of caregiver involvement in interventions for improving children's dietary intake and physical activity behaviors, including those intended to prevent overweight and obesity • To describe intervention content and behavior change techniques employed, drawing from a behavior change technique taxonomy developed and advanced by Abraham, Michie, and colleagues (Abraham 2008; Michie 2011; Michie 2013; Michie 2015) • To identify content and techniques related to reported outcomes when such information was reported in included studies SEARCH METHODS: In January 2019, we searched CENTRAL, MEDLINE, Embase, 11 other databases, and three trials registers. We also searched the references lists of relevant reports and systematic reviews.

SELECTION CRITERIA

Randomised controlled trials (RCTs) and quasi-RCTs evaluating the effects of interventions to improve children's dietary intake or physical activity behavior, or both, with children aged 2 to 18 years as active participants and at least one component involving caregivers versus the same interventions but without the caregiver component(s). We excluded interventions meant as treatment or targeting children with pre-existing conditions, as well as caregiver-child units residing in orphanages and school hostel environments.

DATA COLLECTION AND ANALYSIS

We used standard methodological procedures outlined by Cochrane.

MAIN RESULTS

We included 23 trials with approximately 12,192 children in eligible intervention arms. With the exception of two studies, all were conducted in high-income countries, with more than half performed in North America. Most studies were school-based and involved the addition of healthy eating or physical education classes, or both, sometimes in tandem with other changes to the school environment. The specific intervention strategies used were not always reported completely. However, based on available reports, the behavior change techniques used most commonly in the child-only arm were "shaping knowledge," "comparison of behavior," "feedback and monitoring," and "repetition and substitution." In the child + caregiver arm, the strategies used most commonly included additional "shaping knowledge" or "feedback and monitoring" techniques, as well as "social support" and "natural consequences." We considered all trials to be at high risk of bias for at least one design factor. Seven trials did not contribute any data to analyses. The quality of reporting of intervention content varied between studies, and there was limited scope for meta-analysis. Both validated and non-validated instruments were used to measure outcomes of interest. Outcomes measured and reported differed between studies, with 16 studies contributing data to the meta-analyses. About three-quarters of studies reported their funding sources; no studies reported industry funding. We assessed the quality of evidence to be low or very low. Dietary behavior change interventions with a caregiver component versus interventions without a caregiver component Seven studies compared dietary behavior change interventions with and without a caregiver component. At the end of the intervention, we did not detect a difference between intervention arms in children's percentage of total energy intake from saturated fat (mean difference [MD] -0.42%, 95% confidence interval [CI] -1.25 to 0.41, 1 study, n = 207; low-quality evidence) or from sodium intake (MD -0.12 g/d, 95% CI -0.36 to 0.12, 1 study, n = 207; low-quality evidence). No trial in this comparison reported data for children's combined fruit and vegetable intake, sugar-sweetened beverage (SSB) intake, or physical activity levels, nor for adverse effects of interventions. Physical activity interventions with a caregiver component versus interventions without a caregiver component Six studies compared physical activity interventions with and without a caregiver component. At the end of the intervention, we did not detect a difference between intervention arms in children's total physical activity (MD 0.20 min/h, 95% CI -1.19 to 1.59, 1 study, n = 54; low-quality evidence) or moderate to vigorous physical activity (MVPA) (standard mean difference [SMD] 0.04, 95% CI -0.41 to 0.49, 2 studies, n = 80; moderate-quality evidence). No trial in this comparison reported data for percentage of children's total energy intake from saturated fat, sodium intake, fruit and vegetable intake, or SSB intake, nor for adverse effects of interventions. Combined dietary and physical activity interventions with a caregiver component versus interventions without a caregiver component Ten studies compared dietary and physical activity interventions with and without a caregiver component. At the end of the intervention, we detected a small positive impact of a caregiver component on children's SSB intake (SMD -0.28, 95% CI -0.44 to -0.12, 3 studies, n = 651; moderate-quality evidence). We did not detect a difference between intervention arms in children's percentage of total energy intake from saturated fat (MD 0.06%, 95% CI -0.67 to 0.80, 2 studies, n = 216; very low-quality evidence), sodium intake (MD 35.94 mg/d, 95% CI -322.60 to 394.47, 2 studies, n = 315; very low-quality evidence), fruit and vegetable intake (MD 0.38 servings/d, 95% CI -0.51 to 1.27, 1 study, n = 134; very low-quality evidence), total physical activity (MD 1.81 min/d, 95% CI -15.18 to 18.80, 2 studies, n = 573; low-quality evidence), or MVPA (MD -0.05 min/d, 95% CI -18.57 to 18.47, 1 study, n = 622; very low-quality evidence). One trial indicated that no adverse events were reported by study participants but did not provide data.

AUTHORS' CONCLUSIONS

Current evidence is insufficient to support the inclusion of caregiver involvement in interventions to improve children's dietary intake or physical activity behavior, or both. For most outcomes, the quality of the evidence is adversely impacted by the small number of studies with available data, limited effective sample sizes, risk of bias, and imprecision. To establish the value of caregiver involvement, additional studies measuring clinically important outcomes using valid and reliable measures, employing appropriate design and power, and following established reporting guidelines are needed, as is evidence on how such interventions might contribute to health equity.

Challenges and solutions for N-of-1 design studies in health psychology

Theories of behaviour change and health behaviour change interventions are most often evaluated in between-person designs. However, behaviour change theories apply to individuals not groups and behavioural interventions ultimately aim to achieve within-person rather than between-group change. Within-person methodology, such as N-of-1 (also known as single case design), can circumvent this issue, though has multiple design-specific challenges. This paper provides a conceptual review of the challenges and potential solutions for undertaking N-of-1 studies in health psychology. Key challenges identified include participant adherence to within-person protocols, carry-over and slow onset effects, suitability of behaviour change techniques for evaluation in N-of-1 experimental studies, optimal allocation sequencing and blinding, calculating power/sample size, and choosing the most suitable analysis approach. Key solutions include involving users in study design, employing recent technologies for unobtrusive data collection and problem solving by design. Within-person designs share common methodological requirements with conventional between-person designs but require specific methodological considerations. N-of-1 evaluation designs are appropriate for many though not all types of interventions. A greater understanding of patterns of behaviours and factors influencing behaviour change at the within-person level is required to progress health psychology into a precision science. Video abstract: Supplementary Material 1.

Text Messaging Interventions for Improvement in Physical Activity and Sedentary Behavior in Youth: Systematic Review

BACKGROUND

The use of text messages (short message service, SMS) to change physical activity and sedentary behavior in youth is of interest due to the need for novel, more effective intervention approaches. Previous reviews have examined a variety of technology-based interventions and their impact on different health behaviors, but evidence regarding the impact of just SMS on physical activity and sedentary behavior is lacking.

OBJECTIVE

The aim of this study was to assess the effectiveness and use of theory of SMS interventions for improving physical activity and sedentary behavior in youth.

METHODS

Authors systematically searched electronic databases from March to November 2017. Citations were sifted using additional reviewers, and a qualitative synthesis of eligible studies was conducted using piloted data extraction forms. To be eligible for inclusion, studies had to be of a randomized controlled or quasi-experimental design, incorporate SMS, involve adolescents between the ages of 10 and 19 years, and assess at least one physical activity or sedentary behavior outcome. Risk of bias was assessed using the Cochrane Collaboration's Risk of Bias tool.

RESULTS

A total of 13 studies reporting 11 interventions were included in the qualitative analysis. Studies included interventions that were conducted in schools, online, or face-to-face. Studies were of high heterogeneity with regard to study duration, participant characteristics, intervention content, and outcome measures. Findings were equivocal with regard to intervention effectiveness for physical activity and sedentary behavior. Overall, 7 interventions resulted in an improvement for physical activity and 6 for sedentary behavior. All studies were judged to be of high risk of bias for at least 1 item.

CONCLUSIONS

Some studies in this review showed promising results for using SMS to improve physical activity and sedentary behavior in youth. High heterogeneity of design and outcome measures precluded data pooling and conclusions as to which specific intervention elements are linked to increased effectiveness cannot be drawn. The authors propose incorporating the following elements in future studies: specific focus on desired health behavior; mixed-methods design; include long-term follow-up; include self-monitoring, goal setting, and feedback; combine SMS with a mobile app; and send 3 or more SMS text messages per week. More rigorous studies are needed to explore the relationship between intervention effectiveness and specific intervention components such as content and delivery.