Daily Motivational Text Messages to Promote Physical Activity in University Students: Results From a Microrandomized Trial

Physical activity measurement tools among college students in intervention studies: A systematic review

BACKGROUND

Assessing the impact of interventions on college students' physical activity (PA) requires the use of reliable and valid measurement tools. However, the tools employed in existing studies and their respective reliability and validity are not well-documented. This review aims to systematically evaluate the PA measurement tools utilized in interventions targeting college students and to assess the quality of their measurement properties.

METHODS

A comprehensive search was conducted across five databases (MEDLINE, Cochrane, Embase, Web of Science, PsycInfo) to identify studies on PA interventions among college students, using specific inclusion criteria. The screening of literature and data extraction were independently performed by two authors, focusing on the types of PA measurements used and their measurement properties.

RESULTS

A total of 52 studies, involving 63 different PA measurement tools, were included. Of these, 28 studies used self-report tools, 14 employed objective tools (with one study using two different objective tools), and 10 combined both methods. The International Physical Activity Questionnaire (IPAQ) emerged as the most frequently used self-report tool, while pedometers and accelerometers were the primary objective tools. Despite frequent references to reliability and validity, few studies provided specific evidence regarding measurement properties such as internal consistency and criterion validity, particularly those tailored to the studied population.

CONCLUSION

The majority of PA measurement tools for college students rely on self-reported data, with limited verification of their reliability and validity. For a more accurate assessment of PA intervention effects, it is recommended to adapt the widely recognized IPAQ to specific contexts and incorporate objective tools like accelerometers, which offer practical and precise measurement within college settings.

Towards the Developing and Designing of an Intervention to Promote Prenatal Physical Activity Using MomConnect (mHealth): A Formative Protocol

BACKGROUND AND AIM

The use of mHealth, especially short-message text (SMS), has proven to be an effective intervention in promoting behavioral health outcomes in populations across different contexts and settings. While MomConnect, an mHealth technological device designed to enhance maternal and child health services in South Africa, offers various health-related contents aimed at improving maternal outcomes for pregnant and postpartum women, it currently lacks information on prenatal physical activity. However, physical activity and exercise during pregnancy is safe and beneficial for both the mother and the baby. This article outlines the protocol for designing and developing a prenatal physical activity and exercise text messaging content for the MomConnect device. To achieve this, the protocol aims to elucidate the preferences of prenatal physical activity and exercise text messages and ascertain the preferred amount of SMS messaging to inform the design of an intervention for the incorporation of prenatal physical activity and exercise text messages into the MomConnect device in South Africa.

METHODS

We will apply a user-centred design approach conducted in three phases. First, a scoping literature review and interviews with pregnant women will be conducted to inform the formative stage for developing a desirable prototype SMS. Secondly, healthcare providers and pregnant women will be interviewed to collate data on the preferred SMS. Lastly, a cross-sectional survey will be conducted to determine the preferred quantity of SMS messaging to be incorporated in the MomConnect device.

EXPECTED OUTCOMES

A preferred or desirable prenatal physical activity and exercise SMS text message will inform the design of SMS text messages to be incorporated into the content of the MomConnect device to promote prenatal physical activity and exercise participation among women in the Eastern Cape Province. This study will develop a tailored mHealth intervention to improve prenatal physical activity participation and health behaviors among pregnant women in South Africa.

Machine Learning Methods to Personalize Persuasive Strategies in mHealth Interventions That Promote Physical Activity: Scoping Review and Categorization Overview

BACKGROUND

Although physical activity (PA) has positive effects on health and well-being, physical inactivity is a worldwide problem. Mobile health interventions have been shown to be effective in promoting PA. Personalizing persuasive strategies improves intervention success and can be conducted using machine learning (ML). For PA, several studies have addressed personalized persuasive strategies without ML, whereas others have included personalization using ML without focusing on persuasive strategies. An overview of studies discussing ML to personalize persuasive strategies in PA-promoting interventions and corresponding categorizations could be helpful for such interventions to be designed in the future but is still missing.

OBJECTIVE

First, we aimed to provide an overview of implemented ML techniques to personalize persuasive strategies in mobile health interventions promoting PA. Moreover, we aimed to present a categorization overview as a starting point for applying ML techniques in this field.

METHODS

A scoping review was conducted based on the framework by Arksey and O'Malley and the PRISMA-ScR (Preferred Reporting Items for Systematic Reviews and Meta-Analyses extension for Scoping Reviews) criteria. Scopus, Web of Science, and PubMed were searched for studies that included ML to personalize persuasive strategies in interventions promoting PA. Papers were screened using the ASReview software. From the included papers, categorized by the research project they belonged to, we extracted data regarding general study information, target group, PA intervention, implemented technology, and study details. On the basis of the analysis of these data, a categorization overview was given.

RESULTS

In total, 40 papers belonging to 27 different projects were included. These papers could be categorized in 4 groups based on their dimension of personalization. Then, for each dimension, 1 or 2 persuasive strategy categories were found together with a type of ML. The overview resulted in a categorization consisting of 3 levels: dimension of personalization, persuasive strategy, and type of ML. When personalizing the timing of the messages, most projects implemented reinforcement learning to personalize the timing of reminders and supervised learning (SL) to personalize the timing of feedback, monitoring, and goal-setting messages. Regarding the content of the messages, most projects implemented SL to personalize PA suggestions and feedback or educational messages. For personalizing PA suggestions, SL can be implemented either alone or combined with a recommender system. Finally, reinforcement learning was mostly used to personalize the type of feedback messages.

CONCLUSIONS

The overview of all implemented persuasive strategies and their corresponding ML methods is insightful for this interdisciplinary field. Moreover, it led to a categorization overview that provides insights into the design and development of personalized persuasive strategies to promote PA. In future papers, the categorization overview might be expanded with additional layers to specify ML methods or additional dimensions of personalization and persuasive strategies.

Text Messages to Promote Physical Activity in Patients With Cardiovascular Disease: A Micro-Randomized Trial of a Just-In-Time Adaptive Intervention

BACKGROUND

Text messages may enhance physical activity levels in patients with cardiovascular disease, including those enrolled in cardiac rehabilitation. However, the independent and long-term effects of text messages remain uncertain.

METHODS

The VALENTINE study (Virtual Application-supported Environment to Increase Exercise) was a micro-randomized trial that delivered text messages through a smartwatch (Apple Watch or Fitbit Versa) to participants initiating cardiac rehabilitation. Participants were randomized 4× per day over 6-months to receive no text message or a message encouraging low-level physical activity. Text messages were tailored on contextual factors (eg, weather). Our primary outcome was step count 60 minutes following a text message, and we used a centered and weighted least squares mean method to estimate causal effects. Given potential measurement differences between devices determined a priori, data were assessed separately for Apple Watch and Fitbit Versa users over 3 time periods corresponding to the initiation (0-30 days), maintenance (31-120 days), and completion (121-182 days) of cardiac rehabilitation.

RESULTS

One hundred eight participants were included with 70 552 randomizations over 6 months; mean age was 59.5 (SD, 10.7) years with 36 (32.4%) female and 68 (63.0%) Apple Watch participants. For Apple Watch participants, text messages led to a trend in increased step count by 10% in the 60-minutes following a message during days 1 to 30 (95% CI, -1% to +20%), with no effect from days 31 to 120 (+1% [95% CI, -4% to +5%]), and a significant 6% increase during days 121 to 182 (95% CI, +0% to +11%). For Fitbit users, text messages significantly increased step count by 17% (95% CI, +7% to +28%) in the 60-minutes following a message in the first 30 days of the study with no effect subsequently.

CONCLUSIONS

In patients undergoing cardiac rehabilitation, contextually tailored text messages may increase physical activity, but this effect varies over time and by device.

REGISTRATION

URL: https://www.clinicaltrials.gov; Unique identifier: NCT04587882.

Gamification of Behavior Change: Mathematical Principle and Proof-of-Concept Study

BACKGROUND

Many people want to build good habits to become healthier, live longer, or become happier but struggle to change their behavior. Gamification can make behavior change easier by awarding points for the desired behavior and deducting points for its omission.

OBJECTIVE

In this study, we introduced a principled mathematical method for determining how many points should be awarded or deducted for the enactment or omission of the desired behavior, depending on when and how often the person has succeeded versus failed to enact it in the past. We called this approach optimized gamification of behavior change.

METHODS

As a proof of concept, we designed a chatbot that applies our optimized gamification method to help people build healthy water-drinking habits. We evaluated the effectiveness of this gamified intervention in a 40-day field experiment with 1 experimental group (n=43) that used the chatbot with optimized gamification and 2 active control groups for which the chatbot's optimized gamification feature was disabled. For the first control group (n=48), all other features were available, including verbal feedback. The second control group (n=51) received no feedback or reminders. We measured the strength of all participants' water-drinking habits before, during, and after the intervention using the Self-Report Habit Index and by asking participants on how many days of the previous week they enacted the desired habit. In addition, all participants provided daily reports on whether they enacted their water-drinking intention that day.

RESULTS

A Poisson regression analysis revealed that, during the intervention, users who received feedback based on optimized gamification enacted the desired behavior more often (mean 14.71, SD 6.57 times) than the active (mean 11.64, SD 6.38 times; P<.001; incidence rate ratio=0.80, 95% CI 0.71-0.91) or passive (mean 11.64, SD 5.43 times; P=.001; incidence rate ratio=0.78, 95% CI 0.69-0.89) control groups. The Self-Report Habit Index score significantly increased in all conditions (P<.001 in all cases) but did not differ between the experimental and control conditions (P>.11 in all cases). After the intervention, the experimental group performed the desired behavior as often as the 2 control groups (P≥.17 in all cases).

CONCLUSIONS

Our findings suggest that optimized gamification can be used to make digital behavior change interventions more effective.

TRIAL REGISTRATION

Open Science Framework (OSF) H7JN8; https://osf.io/h7jn8.

The effect of cognitive behavioral therapy text messages on mood: A micro-randomized trial

The StayWell at Home intervention, a 60-day text-messaging program based on Cognitive Behavioral Therapy (CBT) principles, was developed to help adults cope with the adverse effects of the global pandemic. Participants in StayWell at Home were found to show reduced depressive and anxiety symptoms after participation. However, it remains unclear whether the intervention improved mood and which intervention components were most effective at improving user mood during the pandemic. Thus, utilizing a micro-randomized trial (MRT) design, we examined two intervention components to inform the mechanisms of action that improve mood: 1) text messages delivering CBT-informed coping strategies (i.e., behavioral activation, other coping skills, or social support); 2) time at which messages were sent. Data from two independent trials of StayWell are included in this paper. The first trial included 303 adults aged 18 or older, and the second included 266 adults aged 18 or older. Participants were recruited via online platforms (e.g., Facebook ads) and partnerships with community-based agencies aiming to reach diverse populations, including low-income individuals and people of color. The results of this paper indicate that participating in the program improved and sustained self-reported mood ratings among participants. We did not find significant differences between the type of message delivered and mood ratings. On the other hand, the results from Phase 1 indicated that delivering any type of message in the 3 pm-6 pm time window improved mood significantly over sending a message in the 9 am-12 pm time window. The StayWell at Home program increases in mood ratings appeared more pronounced during the first two to three weeks of the intervention and were maintained for the remainder of the study period. The current paper provides evidence that low-burden text-message interventions may effectively address behavioral health concerns among diverse communities.

Promotion of Physical Activity Among University Students With Social Media Or Text Messaging: A Systematic Review

Regular physical exercise lowers the risk of all-cause mortality and various chronic diseases. New technologies, such as smartphones and social media, have been used successfully as health promotion tools in college populations. The purpose of this study was to conduct a systematic review of studies examining the effectiveness of interventions that used modern technologies, as with social media or text messaging, to promote physical activity or reducing sedentary behavior in college students. The systematic review was conducted on the PubMed and SCOPUS databases, considering studies published from 2012 to 2022. For a total of 19 articles selected, an evidence table was drawn up, and the quality of the studies was assessed using the PRISMA checklist. The interventions differed enormously in design, from the strategies implemented to the types of outcome considered. Fifteen of the 19 studies demonstrated an improvement in participants' physical activity levels, 3 studies found no such improvement, and 1 reported a worsening of baseline activity levels. Interventions to improve college students' physical activity levels through the use of social media and/or text messaging tend to be effective. However, many factors can influence the effectiveness of such interventions. For example, a gender-related difference emerged in student participation, and the interventions proved more effective if they were accompanied by the creation of social groups.

Handling of outcome missing data dependent on measured or unmeasured background factors in micro-randomized trial: Simulation and application study

Background

Micro-randomized trials (MRTs) enhance the effects of mHealth by determining the optimal components, timings, and frequency of interventions. Appropriate handling of missing values is crucial in clinical research; however, it remains insufficiently explored in the context of MRTs. Our study aimed to investigate appropriate methods for missing data in simple MRTs with uniform intervention randomization and no time-dependent covariates. We focused on outcome missing data depending on the participants' background factors.

Methods

We evaluated the performance of the available data analysis (AD) and the multiple imputation in generalized estimating equations (GEE) and random effects model (RE) through simulations. The scenarios were examined based on the presence of unmeasured background factors and the presence of interaction effects. We conducted the regression and propensity score methods as multiple imputation. These missing data handling methods were also applied to actual MRT data.

Results

Without the interaction effect, AD was biased for GEE, but there was almost no bias for RE. With the interaction effect, estimates were biased for both. For multiple imputation, regression methods estimated without bias when the imputation models were correct, but bias occurred when the models were incorrect. However, this bias was reduced by including the random effects in the imputation model. In the propensity score method, bias occurred even when the missing probability model was correct.

Conclusions

Without the interaction effect, AD of RE was preferable. When employing GEE or anticipating interactions, we recommend the multiple imputation, especially with regression methods, including individual-level random effects.

Testing the Effects of App-Based Motivational Messages on Physical Activity and Resting Heart Rate Through Smartphone App Compliance in Patients With Vulnerable Coronary Artery Plaques: Protocol for a Microrandomized Trial

BACKGROUND

Achieving the weekly physical activity recommendations of at least 150-300 minutes of moderate-intensity or 75-150 minutes of vigorous-intensity aerobic exercise is important for reducing cardiometabolic risk, but evidence shows that most people struggle to meet these goals, particularly in the mid to long term.

OBJECTIVE

The Messages Improving Resting Heart Health (MIRTH) study aims to determine if (1) sending daily motivational messages through a research app is effective in improving motivation and in promoting adherence to physical activity recommendations in men and women with coronary heart disease randomized to a 12-month intensive lifestyle intervention, and (2) the time of the day when the message is delivered impacts compliance with exercise training.

METHODS

We will conduct a single-center, microrandomized trial. Participants will be randomized daily to either receive or not receive motivational messages over two 90-day periods at the beginning (phase 1: months 4-6) and at the end (phase 2: months 10-12) of the Lifestyle Vulnerable Plaque Study. Wrist-worn devices (Fitbit Inspire 2) and Bluetooth pairing with smartphones will be used to passively collect data for proximal (ie, physical activity duration, steps walked, and heart rate within 180 minutes of receiving messages) and distal (ie, change values for resting heart rate and total steps walked within and across both phases 1 and 2 of the trial) outcomes. Participants will be recruited from a large academic cardiology office practice (Central Sydney Cardiology) and the Royal Prince Alfred Hospital Departments of Cardiology and Radiology. All clinical investigations will be undertaken at the Charles Perkins Centre Royal Prince Alfred clinic. Individuals aged 18-80 years (n=58) with stable coronary heart disease who have low attenuation plaques based on a coronary computed tomography angiography within the past 3 months and have been randomized to an intensive lifestyle intervention program will be included in MIRTH.

RESULTS

The Lifestyle Vulnerable Plaque Study was funded in 2020 and started enrolling participants in February 2022. Recruitment for MIRTH commenced in November 2022. As of September 2023, 2 participants were enrolled in the MIRTH study and provided baseline data.

CONCLUSIONS

This MIRTH microrandomized trial will represent the single most detailed and integrated analysis of the effects of a comprehensive lifestyle intervention delivered through a customized mobile health app on smart devices on time-based motivational messaging for patients with coronary heart disease. This study will also help inform future studies optimizing for just-in-time adaptive interventions.

TRIAL REGISTRATION

Australian New Zealand Clinical Trials Registry ACTRN12622000731796; https://www.anzctr.org.au/Trial/Registration/TrialReview.aspx?id=382861.

INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID)

DERR1-10.2196/46082.

Feasibility of generating structured motivational messages for tailored physical activity coaching

Tailored motivational messages are helpful to motivate people in eHealth applications for increasing physical activity, but it is not sufficiently clear how such messages can be effectively generated in advance. We, therefore, put forward a theory-driven approach to generating tailored motivational messages for eHealth applications for behavior change, and we examine its feasibility by assessing how motivating the resulting messages are perceived. For this, we designed motivational messages with a specific structure that was based on an adaptation of an existing ontology for tailoring motivational messages in the context of physical activity. To obtain tailored messages, experts in health psychology and coaching successfully wrote messages with this structure for personas in scenarios that differed with regard to the persona's mood, self-efficacy, and progress. Based on an experiment in which 60 participants each rated the perceived motivational impact of six generic and six tailored messages based on scenarios, we found credible support for our hypothesis that messages tailored to mood, self-efficacy, and progress are perceived as more motivating. A thematic analysis of people's free-text responses about what they found motivating and demotivating about motivational messages further supports the use of tailored messages, as well as messages that are encouraging and empathetic, give feedback about people's progress, and mention the benefits of physical activity. To aid future work on motivational messages, we make our motivational messages and corresponding scenarios publicly available.

A flexible micro-randomized trial design and sample size considerations

Technological advancements have made it possible to deliver mobile health interventions to individuals. A novel framework that has emerged from such advancements is the just-in-time adaptive intervention, which aims to suggest the right support to the individuals when their needs arise. The micro-randomized trial design has been proposed recently to test the proximal effects of the components of these just-in-time adaptive interventions. However, the extant micro-randomized trial framework only considers components with a fixed number of categories added at the beginning of the study. We propose a more flexible micro-randomized trial design which allows addition of more categories to the components during the study. Note that the number and timing of the categories added during the study need to be fixed initially. The proposed design is motivated by collaboration on the Diabetes and Mental Health Adaptive Notification Tracking and Evaluation study, which learns to deliver effective text messages to encourage physical activity among patients with diabetes and depression. We developed a new test statistic and the corresponding sample size calculator for the flexible micro-randomized trial using an approach similar to the generalized estimating equation for longitudinal data. Simulation studies were conducted to evaluate the sample size calculators and an R shiny application for the calculators was developed.

StepAdd: A personalized mHealth intervention based on social cognitive theory to increase physical activity among type 2 diabetes patients

OBJECTIVE

Investigate the preliminary efficacy and feasibility of a personalized mobile health (mHealth) intervention based on social cognitive theory (SCT) to promote physical activity among type 2 diabetes patients via self-monitoring, goal setting, and automatic feedback.

METHODS

We conducted a pilot study involving 33 type 2 diabetes patients attending Mitsui Memorial Hospital in Japan using a pre-post evaluation design over 12 weeks. Participants measured daily step count, body weight, and blood pressure at home, with the measurements synchronized with the StepAdd application (app) automatically. Participants used the app to review daily results, update personalized step goals, identify individualized barriers to achieving the step goals, find coping strategies to overcome each barrier, and implement these strategies, thereby building effective coping skills to meet the goals. Pharmacists examined the usage of the app and provided coaching on lifestyle modifications. Ultimately, patients established skills to enhance diabetes self-care by using the app.

RESULTS

Daily step count increased dramatically with high statistical significance (p < 0.0001), from a mean of 5436 steps/day to 10,150 steps/day, an 86.7 % increase. HbA1c (p = 0.0001) and BMI (p = 0.0038) also improved. Diabetes self-care in diet, exercise, and foot care as well as self-management behavior, self-regulation, and self-efficacy in achieving daily step goals showed significant improvements. The retention rate of the study was very high, at 97.0 % (n = 32).

CONCLUSIONS

A personalized smartphone-based mHealth intervention based on SCT is feasible and effective at promoting physical activity among type 2 diabetes patients. The methodology of the intervention could be readily applied to other patient populations.

Participant Engagement in Microrandomized Trials of mHealth Interventions: Scoping Review

BACKGROUND

Microrandomized trials (MRTs) have emerged as the gold standard for the development and evaluation of multicomponent, adaptive mobile health (mHealth) interventions. However, not much is known about the state of participant engagement measurement in MRTs of mHealth interventions.

OBJECTIVE

In this scoping review, we aimed to quantify the proportion of existing or planned MRTs of mHealth interventions to date that have assessed (or have planned to assess) engagement. In addition, for the trials that have explicitly assessed (or have planned to assess) engagement, we aimed to investigate how engagement has been operationalized and to identify the factors that have been studied as determinants of engagement in MRTs of mHealth interventions.

METHODS

We conducted a broad search for MRTs of mHealth interventions in 5 databases and manually searched preprint servers and trial registries. Study characteristics of each included evidence source were extracted. We coded and categorized these data to identify how engagement has been operationalized and which determinants, moderators, and covariates have been assessed in existing MRTs.

RESULTS

Our database and manual search yielded 22 eligible evidence sources. Most of these studies (14/22, 64%) were designed to evaluate the effects of intervention components. The median sample size of the included MRTs was 110.5. At least 1 explicit measure of engagement was included in 91% (20/22) of the included MRTs. We found that objective measures such as system usage data (16/20, 80%) and sensor data (7/20, 35%) are the most common methods of measuring engagement. All studies included at least 1 measure of the physical facet of engagement, but the affective and cognitive facets of engagement have largely been neglected (only measured by 1 study each). Most studies measured engagement with the mHealth intervention (Little e) and not with the health behavior of interest (Big E). Only 6 (30%) of the 20 studies that measured engagement assessed the determinants of engagement in MRTs of mHealth interventions; notification-related variables were the most common determinants of engagement assessed (4/6, 67% studies). Of the 6 studies, 3 (50%) examined the moderators of participant engagement-2 studies investigated time-related moderators exclusively, and 1 study planned to investigate a comprehensive set of physiological and psychosocial moderators in addition to time-related moderators.

CONCLUSIONS

Although the measurement of participant engagement in MRTs of mHealth interventions is prevalent, there is a need for future trials to diversify the measurement of engagement. There is also a need for researchers to address the lack of attention to how engagement is determined and moderated. We hope that by mapping the state of engagement measurement in existing MRTs of mHealth interventions, this review will encourage researchers to pay more attention to these issues when planning for engagement measurement in future trials.

Investigating the Role of Context in the Delivery of Text Messages for Supporting Psychological Wellbeing

Without a nuanced understanding of users' perspectives and contexts, text messaging tools for supporting psychological wellbeing risk delivering interventions that are mismatched to users' dynamic needs. We investigated the contextual factors that influence young adults' day-to-day experiences when interacting with such tools. Through interviews and focus group discussions with 36 participants, we identified that people's daily schedules and affective states were dominant factors that shape their messaging preferences. We developed two messaging dialogues centered around these factors, which we deployed to 42 participants to test and extend our initial understanding of users' needs. Across both studies, participants provided diverse opinions of how they could be best supported by messages, particularly around when to engage users in more passive versus active ways. They also proposed ways of adjusting message length and content during periods of low mood. Our findings provide design implications and opportunities for context-aware mental health management systems.

A self-liberation intervention using a pedometer to encourage physical activity among sedentary nursing staff: A randomized controlled trial

Objective

Nurses make up the majority of the workforce in any healthcare system. Physical inactivity due to heavy workloads has been widely reported among nurses. This study aimed to examine whether a self-liberation intervention could help nurses increase their physical activity levels that would result in other health benefits.

Methods

A two-armed randomized controlled trial was implemented among 40 nurses (20 per arm). The control arm received information about the benefits of physical activity, but with no intervention. The intervention arm received the same information and were given pedometers for 12 weeks to record their daily steps while also receiving weekly reminders. Measurements were taken for anthropometric data, self-reported physical activity, exercise stage-of-change, exercise self-efficacy, and pedometer steps (intervention arm only). All statistical analyses were two-sided, with p ⩽ 0.05.

Results

The respondents' mean age was 47.9 ± 7.02 years with 90% being female. After the intervention, the intervention arm achieved a higher self-efficacy score (4.60 ± 1.75 to 5.63 ± 2.48) while a decline was observed in the control arm (5.02 ± 2.08 to 4.50 ± 1.90). At baseline, 16.7% (n = 3) of the control arm and 27.8% (n = 5) of the intervention arm were classified as moderately physically active (McNemar's test = 1.20, p = 0.549). After 12 weeks, this proportion increased to 27.7% (n = 5) in the control arm and 50.0% (n = 9) in the intervention arm (McNemar's test = 5.00, p = 0.172). For the intervention arm, mean daily step counts rose from 8889 ± 579.84 at week 1 to 9930 ± 986.52 at week 12 and reached the level of statistical significance (p < 0.01). Waist circumference of the intervention arm decreased significantly more than that of the control group (p < 0.01).

Conclusion

The self-liberation intervention using a pedometer had positive effects on assisting sedentary nursing staff to progress through the stages of health behavior change and on their exercise self-efficacy, which could further help increase their exercise adherence and overall physical and mental wellbeing.

Ratings and experiences in using a mobile application to increase physical activity among university students: implications for future design

University students have low levels of physical activity and are at risk of mental health disorders. Mobile apps to encourage physical activity can help students, who are frequent smartphone-users, to improve their physical and mental health. Here we report students' qualitative feedback on a physical activity smartphone app with motivational text messaging. We provide recommendations for the design of future apps. 103 students used the app for 6 weeks in the context of a clinical trial (NCT04440553) and answered open-ended questions before the start of the study and at follow-up. A subsample (n = 39) provided additional feedback via text message, and a phone interview (n = 8). Questions focused on the perceived encouragement and support by the app, text messaging content, and recommendations for future applications. We analyzed all transcripts for emerging themes using qualitative coding in Dedoose. The majority of participants were female (69.9%), Asian or Pacific Islander (53.4%), with a mean age of 20.2 years, and 63% had elevated depressive symptoms. 26% felt encouraged or neutral toward the app motivating them to be more physically active. Participants liked messages on physical activity benefits on (mental) health, encouraging them to complete their goal, and feedback on their activity. Participants disliked messages that did not match their motivations for physical activity and their daily context (e.g., time, weekday, stress). Physical activity apps for students should be adapted to their motivations, changing daily context, and mental health issues. Feedback from this sample suggests a key to effectiveness is finding effective ways to personalize digital interventions.

Microrandomized Trials: Developing Just-in-Time Adaptive Interventions for Better Public Health

Just-in-time adaptive interventions (JITAIs) represent an intervention design that adapts the provision and type of support over time to an individual's changing status and contexts, intending to deliver the right support on the right occasion. As a novel strategy for delivering mobile health interventions, JITAIs have the potential to improve access to quality care in underserved communities and, thus, alleviate health disparities, a significant public health concern. Valid experimental designs and analysis methods are required to inform the development of JITAIs. Here, we briefly review the cutting-edge design of microrandomized trials (MRTs), covering both the classical MRT design and its outcome-adaptive counterpart. Associated statistical challenges related to the design and analysis of MRTs are also discussed. Two case studies are provided to illustrate the aforementioned concepts and designs throughout the article. We hope our work leads to better design and application of JITAIs, advancing public health research and practice. (Am J Public Health. 2023;113(1):60-69. https://doi.org/10.2105/AJPH.2022.307150).

Use of mobile app to enhance functional outcomes and adherence of home-based rehabilitation program for elderly with hip fracture: A randomized controlled trial

BACKGROUND

Mobile app has been used to improve exercise adherence and outcomes in populations with different health conditions. However, the effectiveness of mobile app in delivering home-based rehabilitation program to elderly patients with hip fracture is unclear.

OBJECTIVE

The aim of this study was to test the effectiveness of mobile app in delivering home-based rehabilitation program for improving functional outcomes and reducing caregiver stress with enhancing adherence among the elderly patients with hip fracture.

METHODS

A randomized controlled trial with an intervention period of two months was performed. Eligible participants were randomized into either experimental group with home-based rehabilitation program using a mobile app or control group with home-based rehabilitation program using an exercise pamphlet. Primary outcomes were Modified Functional Ambulatory Category (MFAC), Elderly Mobility Scale (EMS) and Lower Extremity Functional Scale (LEFS). Secondary outcomes were exercise adherence and Modified Caregiver Strain Index (M-CSI). The outcomes were collected at pre-discharge training session, one month and two months after hospital discharge.

RESULTS

A total of 50 participants were enrolled, with 19 participants in the experimental group and 20 participants in the control group. Eleven participants had withdrawn from the study. The experimental group showed higher exercise adherence than the control group in first month (p = 0 . 03 ). There were no between-group differences in MFAC, EMS, LEFS and M-CSI at the first month and second month.

CONCLUSION

Use of the mobile app improved exercise adherence, yet it did not improve physical performance, self-efficacy and reduce caregiver stress when compared to a standard home rehabilitation program for elderly patients with hip fracture. Further studies to investigate the benefits of mobile apps are required. (ClinicalTrials.gov ID: NCT04053348.).

Text messages promoting healthy lifestyle and linked with activity monitors stimulate an immediate increase in physical activity among women after gestational diabetes

AIMS

To evaluate the immediate effect of text messages promoting healthy lifestyle and supporting parenting on physical activity amongst women with recent gestational diabetes (GDM).

METHODS

Analysis of data from a pilot randomised controlled trial of a healthy lifestyle program for women with recent GDM. Intervention subjects received text messages providing motivation, reminders, information and feedback as well as an activity monitor. This sub-study examined step count in the 4 h after receipt of a text message, compared to the same time of day on other days among intervention subjects.

RESULTS

Data from 7326 days where step counts were recorded, from 31 women were analysed. The median steps in the 4 h following a text message was 1237 (IQR 18-2240) and it was 1063 (IQR 0-2038) over the same time period on comparison days where there was no message (p < 0.001). The effect was similar whether the messages pertained to physical activity or not. There was no attenuation of the response over 36-38 weeks.

CONCLUSIONS

Women with recent GDM increase their step count in the hours following positive and supportive text messages. This suggests that text messaging programs can facilitate healthy lifestyle and diabetes prevention in this population.

Hybrid Experimental Designs for Intervention Development: What, Why, and How

Advances in mobile and wireless technologies offer tremendous opportunities for extending the reach and impact of psychological interventions and for adapting interventions to the unique and changing needs of individuals. However, insufficient engagement remains a critical barrier to the effectiveness of digital interventions. Human delivery of interventions (e.g., by clinical staff) can be more engaging but potentially more expensive and burdensome. Hence, the integration of digital and human-delivered components is critical to building effective and scalable psychological interventions. Existing experimental designs can be used to answer questions either about human-delivered components that are typically sequenced and adapted at relatively slow timescales (e.g., monthly) or about digital components that are typically sequenced and adapted at much faster timescales (e.g., daily). However, these methodologies do not accommodate sequencing and adaptation of components at multiple timescales and hence cannot be used to empirically inform the joint sequencing and adaptation of human-delivered and digital components. Here, we introduce the hybrid experimental design (HED)-a new experimental approach that can be used to answer scientific questions about building psychological interventions in which human-delivered and digital components are integrated and adapted at multiple timescales. We describe the key characteristics of HEDs (i.e., what they are), explain their scientific rationale (i.e., why they are needed), and provide guidelines for their design and corresponding data analysis (i.e., how can data arising from HEDs be used to inform effective and scalable psychological interventions).

The need for feminist intersectionality in digital health

Digital health, including the use of mobile health apps, telemedicine, and data analytics to improve health systems, has surged during the COVID-19 pandemic. The social and economic fallout from COVID-19 has further exacerbated gender inequities, through increased domestic violence against women, soaring unemployment rates in women, and increased unpaid familial care taken up by women-all factors that can worsen women's health. Digital health can bolster gender equity through increased access to health care, empowerment of one's own health data, and reduced burden of unpaid care work. Yet, digital health is rarely designed from a gender equity perspective. In this Viewpoint, we show that because of lower access and exclusion from app design, gender imbalance in digital health leadership, and harmful gender stereotypes, digital health is disadvantaging women-especially women with racial or ethnic minority backgrounds. Tackling digital health's gender inequities is more crucial than ever. We explain our feminist intersectionality framework to tackle digital health's gender inequities and provide recommendations for future research.