Web-Based Video-Coaching to Assist an Automated Computer-Tailored Physical Activity Intervention for Inactive Adults: A Randomized Controlled Trial

Does intervention engagement mediate physical activity change in a web-based computer-tailored physical activity intervention?-Secondary outcomes from a randomised controlled trial

Introduction

The relationship between intervention engagement and behaviour change may vary depending on the specific engagement metric being examined. To counter this composite engagement measures may provide a deeper understanding of the relationship between engagement and behaviour change, though few studies have applied such multidimensional engagement metrics. The aim of this secondary analysis of RCT data was to examine how a composite engagement score mediates the effect of a web-based computer-tailored physical activity intervention.

Methods

501 inactive Australian adults were randomised to a no-treatment control or intervention group. Intervention participants received 8 sessions of web-based personalised physical activity advice over a 12-week intervention period and the ability to complete action plans. Change in physical activity was assessed using Actigraph accelerometers at baseline, 3-months and 9-months. Engagement with the intervention (i.e., a composite score including frequency, intensity, duration and type) was continuously assessed during the intervention period using website tracking software and database metrics. Generalised structural equation models were used to examine how a composite engagement score mediated intervention effects at 3 months and 9 months.

Results

At 3 months, mediation analysis revealed that the intervention group had significantly higher engagement scores than the control group [a-path exp(b) = 6.462, 95% CI = 5.121-7.804, p < 0.001]. Further, increased engagement with the intervention platform was associated with an increased time spent in moderate-to-vigorous physical activity [ab-coefficient exp(b) = 1.008, 95% CI = 1.004-1.014, P < 0.001]; however, the magnitude of this effect was small. There were no significant mediation effects at the 9-month time point.

Discussion

The findings suggest that a composite intervention engagement score has a small positive influence on physical activity changes and that other factors (e.g., behaviour change techniques) are likely to be more important drivers of behaviour change.

Health and Wellness Coaching and Sustained Gains: A Rapid Systematic Review

The Transtheoretical Model of Change identifies key stages in behavior change, including a maintenance stage occurring when a behavior has been upheld for at least 6 months. Health and wellness coaching has demonstrated support for health behavior change, but maintenance of gains has received little attention. Our rapid systematic literature review characterizes both the research exploring sustained gains with health and wellness coaching and what is known about sustained gains after the completion of a health and wellness coaching engagement. Guided by The Cochrane Rapid Reviews Methods Group "Interim Guidance," we drew 231 studies from the 2018 and 2020 Sforzo et al "Compendium of the health and wellness coaching literature," and "Addendum…" appendices. Initial screening and coding for inclusion and exclusion criteria yielded 28 studies for data extraction. We examined studies across outcome categories (physiological, behavioral, psychological, and health risk assessment) to determine whether outcome measures were: not sustained; partially sustained; fully sustained; or improved from immediate post-intervention to a later follow-up period. Twenty-five of the 28 studies reviewed demonstrated partially, or fully, sustained or improved outcomes in one or more variables studied, with sustained gains demonstrated across outcome categories, strengthening confidence in HWC as a facilitator of lasting change.

The Effectiveness of Strategies to Improve User Engagement With Digital Health Interventions Targeting Nutrition, Physical Activity, and Overweight and Obesity: Systematic Review and Meta-Analysis

BACKGROUND

Digital health interventions (DHIs) are effective in improving poor nutrition, physical inactivity, overweight and obesity. There is evidence suggesting that the impact of DHIs may be enhanced by improving user engagement. However, little is known about the overall effectiveness of strategies on engagement with DHIs.

OBJECTIVE

This study aims to assess the overall effectiveness of strategies to improve engagement with DHIs targeting nutrition, physical activity, and overweight or obesity and explore associations between strategies and engagement outcomes. The secondary aim was to explore the impact of these strategies on health risk outcomes.

METHODS

The MEDLINE, Embase, PsycINFO, CINAHL, CENTRAL, Scopus, and Academic Source Complete databases were searched up to July 24, 2023. Eligible studies were randomized controlled trials that evaluated strategies to improve engagement with DHIs and reported on outcomes related to DHI engagement (use or user experience). Strategies were classified according to behavior change techniques (BCTs) and design features (eg, supplementary emails). Multiple-variable meta-analyses of the primary outcomes (usage and user experience) were undertaken to assess the overall effectiveness of strategies. Meta-regressions were conducted to assess associations between strategies and use and user experience outcomes. Synthesis of secondary outcomes followed the "Synthesis Without Meta-Analysis" guidelines. The methodological quality and evidence was assessed using the Cochrane risk-of-bias tool, and the Grading of Recommendations Assessment, Development, and Evaluation tool respectively.

RESULTS

Overall, 54 studies (across 62 publications) were included. Pooled analysis found very low-certainty evidence of a small-to-moderate positive effect of the use of strategies to improve DHI use (standardized mean difference=0.33, 95% CI 0.20-0.46; P<.001) and very low-certainty evidence of a small-to-moderate positive effect on user experience (standardized mean difference=0.29, 95% CI 0.07-0.52; P=.01). A significant positive association was found between the BCTs social support (effect size [ES]=0.40, 95% CI 0.14-0.66; P<.001) and shaping knowledge (ES=0.39, 95% CI 0.03-0.74; P=.03) and DHI use. A significant positive association was found among the BCTs social support (ES=0.70, 95% CI 0.18-1.22; P=.01), repetition and substitution (ES=0.29, 95% CI 0.05-0.53; P=.03), and natural consequences (ES=0.29, 95% CI 0.05-0.53; P=.02); the design features email (ES=0.29, 95% CI 0.05-0.53; P=.02) and SMS text messages (ES=0.34, 95% CI 0.11-0.57; P=.01); and DHI user experience. For secondary outcomes, 47% (7/15) of nutrition-related, 73% (24/33) of physical activity-related, and 41% (14/34) of overweight- and obesity-related outcomes reported an improvement in health outcomes.

CONCLUSIONS

Although findings suggest that the use of strategies may improve engagement with DHIs targeting such health outcomes, the true effect is unknown because of the low quality of evidence. Future research exploring whether specific forms of social support, repetition and substitution, natural consequences, emails, and SMS text messages have a greater impact on DHI engagement is warranted.

TRIAL REGISTRATION

PROSPERO CRD42018077333; https://www.crd.york.ac.uk/prospero/display_record.php?RecordID=77333.

Development and Feasibility Testing of a Multilevel Intervention to Increase Hepatitis C Virus Screening Among Baby Boomers in Primary Care

Chronic infection with hepatitis C virus (HCV) results in an increased risk of cirrhosis and hepatocellular carcinoma (HCC). Only 15% of baby boomers (born 1945-1965) have ever been screened. We aimed to develop a multilevel intervention to increase HCV screening for baby boomers in a primary care setting. This study included two phases: intervention development (phase 1) and feasibility testing (phase 2). In phase 1, we partnered with a Community Advisory Board and a Provider Advisory Board to develop a multilevel intervention to increase HCV screening to be delivered to both providers and patients in primary care. Phase 2 assessed intervention feasibility, acceptability, and usability by conducting Concurrent Think Aloud (CTA) interviews and surveys using previously validated scales with patients (n = 8) and providers (n = 7). Phase 1 results: The patient-level intervention included a mailed reminder letter and CDC pamphlet and a 7-min in-clinic educational video. The provider-level intervention included a 30-min educational session and monthly performance feedback e-mails. Phase 2 results: Qualitatively, both the patient and provider-level intervention were feasible, acceptable, and usable by the target audiences. Quantitatively, on a 1-4 scale, the range of patient-level scores was 3.00-4.00 and provider level was 3.50-4.00 for feasibility, acceptability, and usability. This intervention could improve HCV screening among a high-risk population and therefore reduce HCV-related morbidity and mortality. This project developed a feasible, acceptable, and usable multilevel intervention aimed at increasing HCV screening in primary care.

Piloting an online telecoaching community-based exercise intervention with adults living with HIV: protocol for a mixed-methods implementation science study

INTRODUCTION

Our aim is to evaluate the implementation of an online telecoaching community-based exercise (CBE) intervention with the goal of reducing disability and enhancing physical activity and health among adults living with HIV.

METHODS AND ANALYSIS

We will conduct a prospective longitudinal mixed-methods two-phased intervention study to pilot the implementation of an online CBE intervention with ~30 adults (≥18 years) living with HIV who consider themselves safe to participate in exercise. In the intervention phase (0-6 months), participants will take part in an online CBE intervention involving thrice weekly exercise (aerobic, resistance, balance and flexibility), with supervised biweekly personal training sessions with a fitness instructor, YMCA membership providing access to online exercise classes, wireless physical activity monitor to track physical activity and monthly online educational sessions on topics related to HIV, physical activity and health. In the follow-up phase (6-12 months), participants will be encouraged to continue independent exercise thrice weekly. Quantitative assessment: Bimonthly, we will assess cardiopulmonary fitness, strength, weight, body composition and flexibility, followed by administering self-reported questionnaires to assess disability, contextual factor outcomes (mastery, engagement in care, stigma, social support), implementation factors (cost, feasibility, technology), health status and self-reported physical activity. We will conduct a segmented regression analyses to describe the change in level and trend between the intervention and follow-up phases. Qualitative assessment: We will conduct online interviews with a subsample of ~10 participants and 5 CBE stakeholders at baseline (month 0), postintervention (month 6) and end of follow-up (month 12) to explore experiences, impact and implementation factors for online CBE. Interviews will be audiorecorded and analysed using content analytical techniques.

ETHICS AND DISSEMINATION

Protocol approved by the University of Toronto Research Ethics Board (Protocol # 40410). Knowledge translation will occur in the form of presentations and publications in open-access peer-reviewed journals.

TRIAL REGISTRATION NUMBER

NCT05006391.

Towards multimodal boosting of motivation for fall-preventive physical activity in seniors: An iterative development evaluation study

Background

Many seniors need to increase their physical activity (PA) and participation in fall prevention exercise. Therefore, digital systems have been developed to support fall-preventive PA. Most of them lack video coaching and PA monitoring, two functionalities that may be relevant for increasing PA.

Objective

To develop a prototype of a system to support seniors' fall-preventive PA, which includes also video coaching and PA monitoring, and to evaluate its feasibility and user experience.

Methods

A system prototype was conceived by integrating applications for step-monitoring, behavioural change support, personal calendar, video-coaching and a cloud service for data management and co-ordination. Its feasibility and user experience were evaluated in three consecutive test periods combined with technical development. In total, 11 seniors tested the system at home for four weeks with video coaching from health care professionals.

Results

Initially, the system's feasibility was non-satisfactory due to insufficient stability and usability. However, most problems could be addressed and amended. In the third (last) test period, both seniors and coaches experienced the system prototype to be fun, flexible and awareness-raising. Interestingly, the video coaching which made the system unique compared to similar systems was highly appreciated. Nonetheless, even the users in the last test period highlighted issues due to insufficient usability, stability and flexibility. Further improvements in these areas are needed.

Conclusions

Video coaching in fall-preventive PA can be valuable for both seniors and health care professionals. High reliability, usability and flexibility of systems supporting seniors are essential.

Blended Care Interventions to Promote Physical Activity: A Systematic Review of Randomized Controlled Trials

Background

Blended care interventions combine therapeutic guidance with digital care. Current research results show the promising role of the blended care approach in clinical care. This new way of delivering health care could have the potential to effectively promote physical activity in different public health settings.

Objective

The aim of the systematic review is to investigate the varieties of intervention characteristics of blended care interventions to promote physical activity in terms of structure, behavior change goals, behavior change techniques, and effectiveness of blended care interventions compared to a control group.

Methods

We searched for randomized controlled trials published from 2000 to March 2021 in MEDLINE, CINAHL, Cochrane Central Register of Controlled Trials, SPORTDiscus, PsycINFO, and Web of Science according to the PRISMA guidelines. Risk of bias was assessed using the Cochrane Collaboration tool. Study characteristics, intervention characteristics, and outcome data were extracted. Furthermore, the effect size on the outcome of physical activity was examined or calculated.

Results

In total, the number of reports identified from the database searches was 4828. Of these, 25 studies were included in the review, with a total of 5923 study participants. Results indicated that the characteristics of blended care interventions showed a high heterogeneity. The combinations of therapist-guided interventions and digital interventions allowed the identification of specific subgroups, but they varied in length (range 8–52 weeks, SD 16.6), intensity, and the combination of the components. The most used combination of blended care interventions to promote physical activity was the combination of one-on-one meetings via telephone and Web-based interventions. Motivational models of behavior change were used most frequently as underlying theoretical foundations. Certain behavior change techniques were used consistently across the individual components, e.g., “problem solving” in the therapist-guided component and “feedback on behavior” in the digital component. Considering the effect size of blended care interventions compared with control groups, most studies showed a small effect.

Conclusions

It can be concluded that blended care interventions have potential to promote physical activity. In the future, further high-quality studies should investigate which type of blended care intervention is effective for which target group. Additionally, insights are required on which intervention characteristics are most effective, taking into account new evidence on behavior change.

Registration This systematic literature review was registered in PROSPERO (CRD42020188556).

Supplementary Information

The online version contains supplementary material available at 10.1186/s40798-022-00489-w.

Validity of muscular fitness self-assessments in the ecofit smartphone application: A correlation study

BACKGROUND

Mobile app-based interventions have the potential for wide-reach and therefore may be a useful tool in up-scaling physical activity interventions. In larger-scale interventions, face-to-face assessments are less cost-effective, and researchers often rely on surveys or activity trackers to assess outcomes. However, there is limited evidence of valid muscular fitness assessments that can be self-administered within mHealth interventions. As such, this study will evaluate the concurrent validity of upper and lower body muscular fitness that have been independently assessed by participants via the ecofit app, and face-to-face assessments conducted by a trained researcher.

METHODS

This study compared baseline data from two muscular fitness tests from the ecofit two-armed randomised controlled trial and self-assessed data collected via the ecofit smartphone app (i.e., validated 90-degree push-up and 60-second sit-to-stand test). To assess the concurrent validity, the self-assessed push-up and sit-to-stand tests (i.e., collected via the ecofit app) were correlated using Spearman's correlation coefficient against the researcher-assessed results (i.e., objective results collected during baseline assessment for the ecofit trial). Bland-Altman plots were also used to allow visualisation of the differences between the self- and research-assessed tests.

RESULTS

Participants (N = 54) completed the push-up (24.1%) and sit-to-stand (100%) tests within 14-days of receiving the app. The results revealed a strong significant correlation for the push-up test (0.83, p<0.001) and a moderate significant correlation for the sit-to-stand test (0.63, p<0.001).

CONCLUSION

This study provides support for the concurrent validity of self-reported upper and lower body muscular fitness assessments (i.e., the push-up and sit-to-stand tests) in mHealth. While these tests may be a feasible option for large scale physical activity interventions, more research is needed to determine the generalisability of these results.

Adherence to eHealth-Delivered Exercise in Adults with no Specific Health Conditions: A Scoping Review on a Conceptual Challenge

Adherence has emerged as a focal point and critical determinant of success for physical activity interventions. The term is used for both traditional and digital interventions, and for prescribed and nonprescribed activities. Many other terms for adherence are being used interchangeably, as there is no consensus on its precise conceptualization. This scoping review aimed to advance the definition of adherence to eHealth programs, specifically for the adult population with no specific health conditions. A total of 2983 papers, published between 1 January 2016 and 13 March 2022, were retrieved from different databases (including grey literature). Of those, 13 studies met the eligibility criteria and were included for review. The selected studies used a wide array of technologies and consisted mainly of exercise interventions. Most of the reviewed publications contemplated exercise adherence as a percentage of expected dose. Most (8 out of 13) studies neither assessed nor specified an expected use of the involved technology. Results suggest a need for homogeneity in the conceptualization of adherence to physical activity and exercise, including those interventions delivered digitally.

Investigating psychological variables for technologies promoting physical activity

Background

Many technological interventions designed to promote physical activity (PA) have limited efficacy and appear to lack important factors that could increase engagement. This may be due to a discrepancy between research conducted in this space, and software designers' and developers' use of this research to inform new digital applications.

Objectives

This study aimed to identify (1) what are the variables that act as barriers and facilitators to PA and (2) which PA variables are currently considered in the design of technologies promoting PA including psychological, physical, and personal/contextual ones which are critical in promoting PA. We emphasize psychological variables in this work because of their sparse and often simplistic integration in digital applications for PA.

Methods

We conducted two systematized reviews on PA variables, using PsycInfo and Association for Computing Machinery Digital Libraries for objectives 1 and 2.

Results

We identified 38 PA variables (mostly psychological ones) including barriers/facilitators in the literature. 17 of those variables were considered when developing digital applications for PA. Only few studies evaluate PA levels in relation to these variables. The same barriers are reported for all weight groups, though some barriers are stronger in people with obesity.

Conclusions

We identify PA variables and illustrate the lack of consideration of these in the design of PA technologies. Digital applications to promote PA may have limited efficacy if they do not address variables acting as facilitators or barriers to participation in PA, and that are important to people representing a range of body weight characteristics.

The effect of a single visit to a health coach on perceived health in 50-year old residents in a high-income country - a randomised controlled trial

OBJECTIVE

To evaluate the one-year-effect of a single visit to a health coach on perceived health and exercise level in 50-year-old citizens.

DESIGN

One factor design randomised controlled trial.

SETTING

Participants were randomly selected from the Swedish Population Register.

SUBJECTS

50-year-old residents of the town of Alingsås, Sweden (n = 105).

INTERVENTION

The intervention group (n = 52) received a single one-hour visit to a health coach. The control group (n = 53) received no intervention.

MAIN OUTCOME MEASURES

Change over 12 months in the SF-36 dimensions physical functioning, role-physical, bodily pain, general health, vitality, social functioning, role-emotional, mental health, physical component summary and mental component summary. Reported health transition at follow-up. Change in exercise level.

RESULTS

The control group changed their perceived health more favourable than the intervention group in the following dimensions of the SF-36; general health (p = 0.0055-0.025), role-emotional (p = 0.034-0.040) and mental component summary (p = 0.033-0.073).

CONCLUSION

A single visit to a health coach does not improve perceived health or exercise-level in 50-year-old citizens. On the contrary it may make perceived health worse.Key pointsResearch on health coaching has emerged in the last 20 years, but is diverse and the characteristics of a successful health coaching intervention are still unknown.There is a lack of randomised controlled trials evaluating long-term effectiveness of health coaching.This randomised controlled trial concludes that a single visit to a health coach does not improve, but rather impairs, perceived health in 50-year olds.

Acceptability, usefulness, and satisfaction with a web-based video-tailored physical activity intervention: The TaylorActive randomized controlled trial

PURPOSE

This study aimed to examine the usage, acceptability, usability, perceived usefulness, and satisfaction of a web-based video-tailored physical activity (PA) intervention (TaylorActive) in adults.

METHODS

In 2013-2014, 501 Australian adults aged 18+ years were randomized into a video-tailored intervention, text-tailored intervention, or control group. Over 3 months, the intervention groups received access to 8 sessions of personally tailored PA advice delivered via the TaylorActive website. Only the delivery method differed between the intervention groups: video-tailored vs. text-tailored. Google Analytics and telephone surveys conducted at post intervention (3 months) were used to assess intervention usage, acceptability, usability, perceived usefulness, and satisfaction. Quantitative and qualitative process data were analyzed using descriptive statistics and thematic content analysis.

RESULTS

Of 501 recruited adults, 259 completed the 3-month post-intervention survey (52% retention). Overall, usage of the TaylorActive website with respect to number of website visits, intervention sessions, and action plans completed was modest in both the video-tailored (7.6 ± 7.2 visits, mean ± SD) and text-tailored (7.3 ± 5.4 visits) groups with no significant between-group differences. The majority of participants in all groups used the TaylorActive website less than once in 2 weeks (66.7% video-tailored, 62.7% text-tailored, 87.5% control; p < 0.001). Acceptability was rated mostly high in all groups and, in some instances, significantly higher in the intervention groups compared to the control group (p < 0.010). Usability was also rated high; mean Systems Usability Scores were 77.3 (video-tailored), 75.7 (text-tailored), and 74.1 (control) with no significant between-group differences. Perceived usefulness of the TaylorActive intervention was low, though mostly rated higher in the intervention groups compared to the control group (p < 0.010). Satisfaction with the TaylorActive website was mixed. Participants in both intervention groups liked its ease of use, personalized feedback, and tracking of progress, but also found completing action plans and survey questions for each session repetitive and tedious.

CONCLUSION

Providing personally tailored PA advice on its own (through either video or text) is likely insufficient to ensure good retention, usage, perceived usefulness, and satisfaction with a web-based PA intervention. Strategies to address this may include the incorporation of additional intervention components such as activity trackers, social interactions, gamification, as well as the use of advanced artificial intelligence and machine learning technologies to allow more personalized dialogue with participants.

Describing Transitions in Adherence to Physical Activity Self-monitoring and Goal Attainment in an Online Behavioral Weight Loss Program: Secondary Analysis of a Randomized Controlled Trial

Background

Standard behavioral weight loss interventions often set uniform physical activity (PA) goals and promote PA self-monitoring; however, adherence remains a challenge, and recommendations may not accommodate all individuals. Identifying patterns of PA goal attainment and self-monitoring behavior will offer a deeper understanding of how individuals adhere to different types of commonly prescribed PA recommendations (ie, minutes of moderate-to-vigorous physical activity [MVPA] and daily steps) and guide future recommendations for improved intervention effectiveness.

Objective

This study examined weekly patterns of adherence to step-based and minute-based PA goals and self-monitoring behavior during a 6-month online behavioral weight loss intervention.

Methods

Participants were prescribed weekly PA goals for steps (7000-10,000 steps/day) and minutes of MVPA (50-200 minutes/week) as part of a lifestyle program. Goals gradually increased during the initial 2 months, followed by 4 months of fixed goals. PA was self-reported daily on the study website. For each week, participants were categorized as adherent if they self-monitored their PA and met the program PA goal, suboptimally adherent if they self-monitored but did not meet the program goal, or nonadherent if they did not self-monitor. The probability of transitioning into a less adherent status was examined using multinomial logistic regression.

Results

Participants (N=212) were predominantly middle-aged females with obesity, and 67 (31.6%) self-identified as a racial/ethnic minority. Initially, 73 (34.4%) participants were categorized as adherent to step-based goals, with 110 [51.9%] suboptimally adherent and 29 [13.7%] nonadherent, and there was a high probability of either remaining suboptimally adherent from week to week or transitioning to a nonadherent status. However, 149 (70.3%) participants started out adherent to minute-based goals (34 [16%] suboptimally adherent and 29 [13.7%] nonadherent), with suboptimally adherent seen as the most variable status. During the graded goal phase, participants were more likely to transition to a less adherent status for minute-based goals (odds ratio [OR] 1.39, 95% CI 1.31-1.48) compared to step-based goals (OR 1.24, 95% CI 1.17-1.30); however, no differences were seen during the fixed goal phase (minute-based goals: OR 1.06, 95% CI 1.05-1.08; step-based goals: OR 1.07, 95% CI 1.05-1.08).

Conclusions

States of vulnerability to poor PA adherence can emerge rapidly and early in obesity treatment. There is a window of opportunity within the initial 2 months to bring more people toward adherent behavior, especially those who fail to meet the prescribed goals but engage in self-monitoring. Although this study describes the probability of adhering to step- and minute-based targets, it will be prudent to determine how individual characteristics and contextual states relate to these behavioral patterns, which can inform how best to adapt interventions.

Trial Registration

ClinicalTrials.gov NCT02688621; https://clinicaltrials.gov/ct2/show/NCT02688621

Long-Term Effects of a Video-Based Smartphone App ("VIDEA Bewegt") to Increase the Physical Activity of German Adults: A Single-Armed Observational Follow-Up Study

As physical inactivity is one of the four leading risk factors for mortality, it should be intensively treated. Therefore, this one-year follow-up study aimed to evaluate the long-term effects of a preventive app to increase physical activity in German adults under real-life circumstances. Data collection took place from July 2019 to July 2021 and included six online questionnaires. Physical activity was studied as the primary outcome based on MET-minutes per week (metabolic equivalent). Secondary outcomes included health-related quality of life based on a mental (MCS) and physical health component summary score (PCS). At the time of publication, 46/65 participants completed the study (median 52 years, 81.5% women). A significant increase of physical activity was observed in people with a low/moderate baseline activity during the first four months of follow-up (median increase by 490 MET-minutes per week, p < 0.001, r = 0.649). Both MCS (median increase by 2.8, p = 0.006, r = 0.344) and PCS (median increase by 2.6, p < 0.001, r = 0.521) significantly increased during the first two months and the BMI significantly decreased during the first six months after the intervention (median decrease by 0.96 kg/m2, p < 0.001, r = 0.465). Thus, this study provides evidence for the medium-term impact of the app, since the effects decreased over time. However, due to the chosen study design and a sizeable loss to follow-up, the validity of these findings is limited.

The effectiveness of digital interventions for increasing physical activity in individuals of low socioeconomic status: a systematic review and meta-analysis

BACKGROUND

Digital technologies such as wearables, websites and mobile applications are increasingly used in interventions targeting physical activity (PA). Increasing access to such technologies makes an attractive prospect for helping individuals of low socioeconomic status (SES) in becoming more active and healthier. However, little is known about their effectiveness in such populations. The aim of this systematic review was to explore whether digital interventions were effective in promoting PA in low SES populations, whether interventions are of equal benefit to higher SES individuals and whether the number or type of behaviour change techniques (BCTs) used in digital PA interventions was associated with intervention effects.

METHODS

A systematic search strategy was used to identify eligible studies from MEDLINE, Embase, PsycINFO, Web of Science, Scopus and The Cochrane Library, published between January 1990 and March 2020. Randomised controlled trials, using digital technology as the primary intervention tool, and a control group that did not receive any digital technology-based intervention were included, provided they had a measure of PA as an outcome. Lastly, studies that did not have any measure of SES were excluded from the review. Risk of Bias was assessed using the Cochrane Risk of Bias tool version 2.

RESULTS

Of the 14,589 records initially identified, 19 studies were included in the final meta-analysis. Using random-effects models, in low SES there was a standardised mean difference (SMD (95%CI)) in PA between intervention and control groups of 0.06 (- 0.08,0.20). In high SES the SMD was 0.34 (0.22,0.45). Heterogeneity was modest in both low (I2 = 0.18) and high (I2 = 0) SES groups. The studies used a range of digital technologies and BCTs in their interventions, but the main findings were consistent across all of the sub-group analyses (digital interventions with a PA only focus, country, chronic disease, and duration of intervention) and there was no association with the number or type of BCTs.

DISCUSSION

Digital interventions targeting PA do not show equivalent efficacy for people of low and high SES. For people of low SES, there is no evidence that digital PA interventions are effective, irrespective of the behaviour change techniques used. In contrast, the same interventions in high SES participants do indicate effectiveness. To reduce inequalities and improve effectiveness, future development of digital interventions aimed at improving PA must make more effort to meet the needs of low SES people within the target population.

Getting from Here to There: Motivational Interviewing and Other Techniques to Promote Healthy Aging

Successful health behavior change relies on the autonomy of the individual who is driven toward personally meaningful, positive goals. The medical practitioner and health care team can use several techniques to facilitate such change effectively, including motivational interviewing, cognitive behavioral restructuring, appreciative inquiry, and positive psychology techniques. Older adults can be supported to make change, and may have greater capacity to maintain those changes due to increased levels of conscientiousness. Positive psychology approaches may be effective in older adults, due to evidence that, as individuals age, they tend to prioritize activities that bring them satisfaction and emotional well-being.

Promoting Active Aging: Lessons Learned in an Implementation Pilot in Primary Care

BACKGROUND

Physical activity (PA) preserves mobility, but few practices screen older adults for mobility impairment or counsel on PA.

DESIGN

"Promoting Active Aging" (PAA) was a mixed-methods randomized-controlled pilot, to test the feasibility and acceptability of a video-based PA counseling tool and implementation into practice of two mobility assessment tools.

SETTING

Three primary care practices affiliated with Wake Forest Baptist Health.

PARTICIPANTS

Adults aged 65 years and older who presented for primary care follow-up and were willing and able to answer self-report questions and walk 4 meters (n = 59).

INTERVENTION

Video-based PA counseling intervention versus control video, "Healthy Eating."

MEASUREMENTS

Potential participants completed mobility assessments: self-report (Mobility Assessment Tool-short form (MAT-sf)) and performance based (4-meter walk test). We assessed PAA's implementation-feasibility, acceptability, and value-via interviews and surveys. Effectiveness was measured via participant attendance at a PA information session.

RESULTS

Of 92 patients approached, 89 (96.7%) agreed to mobility assessment. Eighty-nine completed MAT-sf, and 97.8% (87/89) completed 4-meter walk test. Sixty-seven (75%) met eligibility criteria, and 59 (88%) consented to be randomized either to the PA counseling intervention (Video-PA) or to active control (Video-C). Most participants viewed the walk test positively (51/59; 86.4%). Staff reported that completion of patient surveys, MAT-sf, and videos required significant staff time and support (median = 26 minutes for all), resulting in low acceptability of MAT-sf and the videos. Attendance at a PA information session did not differ by randomization group (Video-PA = 11/29 (37.9%); Video-C = 12/30 (40%); 95% confidence interval for difference in proportion = -0.29 to 0.25).

CONCLUSIONS

Mobility assessment, particularly a 4-meter walk test, was feasible in primary care. Tablet-based assessment (MAT-sf) and video counseling tools, selected to reduce staff effort, instead required significant time to implement. Future work to promote PA should identify effective ways to facilitate adoption of PA in sedentary older adults that do not burden staff.

Effectiveness of Individual Real-Time Video Counseling on Smoking, Nutrition, Alcohol, Physical Activity, and Obesity Health Risks: Systematic Review

Background

Real-time video communication technology allows virtual face-to-face interactions between the provider and the user, and can be used to modify risk factors for smoking, nutrition, alcohol consumption, physical activity, and obesity. No systematic reviews have examined the effectiveness of individual real-time video counseling for addressing each of the risk factors for smoking, nutrition, alcohol consumption, physical activity, and obesity.

Objective

This systematic review aims to examine the effectiveness of individually delivered real-time video counseling on risk factors for smoking, nutrition, alcohol consumption, physical activity, and obesity.

Methods

The MEDLINE (Medical Literature Analysis and Retrieval System Online), EMBASE (Excerpta Medica Database), PsycINFO, Cochrane Register of Controlled Trials, and Scopus databases were searched for eligible studies published up to November 21, 2019. Eligible studies were randomized or cluster randomized trials that tested the effectiveness of individual real-time video communication interventions on smoking, nutrition, alcohol, physical activity, and obesity in any population or setting; the comparator was a no-intervention control group or any other mode of support (eg, telephone); and an English-language publication.

Results

A total of 13 studies were eligible. Four studies targeted smoking, 3 alcohol, 3 physical activity, and 3 obesity. In 2 of the physical activity studies, real-time video counseling was found to significantly increase physical activity when compared with usual care at week 9 and after 5 years. Two obesity studies found a significant change in BMI between a video counseling and a documents group, with significantly greater weight loss in the video counseling group than the in-person as well as the control groups. One study found that those in the video counseling group were significantly more likely than those in the telephone counseling group to achieve smoking cessation. The remaining studies found no significant differences between video counseling and telephone counseling or face-to-face counseling for smoking cessation, video counseling and face-to-face treatment on alcohol consumption, video counseling and no counseling for physical activity, and video counseling and face-to-face treatment on BMI. The global methodological quality rating was moderate in 1 physical activity study, whereas 12 studies had a weak global rating.

Conclusions

Video counseling is potentially more effective than a control group or other modes of support in addressing physical inactivity and obesity and is not less effective in modifying smoking and alcohol consumption. Further research is required to determine the relative benefits of video counseling in terms of other policy and practice decision-making factors such as costs and feasibility.

Efficacy of a computer-tailored web-based physical activity intervention using Fitbits for older adults: a randomised controlled trial protocol

INTRODUCTION

Physical activity is an integral part of healthy ageing, yet the majority of older adults 65+ years are not sufficiently active. Web-based physical activity interventions hold much promise to reach older adults. Preliminary evidence suggests that web-based interventions with tailored advice and Fitbits may be well suited for older adults.

METHODS AND ANALYSIS

This study aims to test the effectiveness of 'Active for Life', a 12-week computer-tailored web-based physical activity intervention using Fitbits for older adults. We will recruit 300 participants who will be randomly assigned to one of three trial arms: (1) web-based physical activity intervention with tailored advice only, (2) web-based physical activity intervention with tailored advice and Fitbit or (3) a wait-list control. The primary outcome, objective moderate to vigorous physical activity (MVPA) and secondary outcomes of objective sedentary behaviour, objective sleep, quality of life, social support, physical function and satisfaction with life will be assessed at baseline and week 12. The secondary outcomes of self-reported physical activity, sitting time and sleep will be assessed at baseline, week 6, 12 and 24. Website usability and participant satisfaction will be assessed at week 12 and website usage and intervention fidelity will be assessed from week 1 to 24. Intention-to-treat linear mixed model analyses will be used to test for group (tailoring only, tailoring +Fitbit, control) differences on changes in the main outcome, MVPA and secondary outcomes. Generalised linear models will be used to compare intervention groups (tailoring only, tailoring +Fitbit) on website usability, participant satisfaction, website usage and intervention fidelity.

ETHICS AND DISSEMINATION

The study has received ethics approval from the Central Queensland University Human Research Ethics Committee (H16/12-321). Study outcomes will be disseminated through peer-reviewed publications and academic conferences and used to inform improvements and dissemination of a tailored, web-based physical activity intervention for adults 65+ years.

TRIAL REGISTRATION NUMBER

Australian and New Zealand Clinical Trials Registry Number: ACTRN12618000646246.

Integrating smartphone technology, social support and the outdoor built environment to promote community-based aerobic and resistance-based physical activity: Rationale and study protocol for the 'ecofit' randomized controlled trial

Introduction

Regular physical activity can significantly reduce the risk of numerous chronic diseases, and improve bone density and mental health. Yet, only 50% of Australian adults meet the aerobic physical activity guidelines and 9–19% meet the resistance-based physical activity guidelines. The aim of this study is to enhance community-based aerobic and resistance-based physical activity through the use of publicly available outdoor exercise equipment, social support and smartphone technology.

Research design and methods

The ecofit intervention will be evaluated using a two-arm randomized controlled trial. A total of 240 adults (aged 18–80) will be recruited and randomly allocated to either the ecofit intervention or a ‘wait-list’ control group. Both groups will have access to the two types of outdoor park exercise equipment, but the intervention group will be given access to the purpose-built ecofit app and a 90-min introductory group training session. To promote social support, participants can enrol in a group of up to four individuals and access the ecofit Facebook group. The ecofit app include workout plans that can be tailored to different locations, difficulty levels and workout-types (i.e., resistance-only or combined resistance and aerobic workouts). Outcome assessments will be conducted at baseline, 3- (primary-end point) and 9-months follow-up. The primary outcomes are upper and lower body muscular fitness. The secondary outcomes include physical activity, body composition, aerobic fitness, body mass index, self-report resistance-based physical activity, and mental health outcomes. The cost-effectiveness of the study will also be evaluated.

Discussion

ecofit is an innovative, multi-component physical activity intervention that integrates smartphone technology, social support and the outdoor built environment to promote community-based aerobic and resistance-based physical. The findings will be used to guide future interventions and to support councils to promote community-based physical activity through the use of local outdoor exercise equipment.

Trial registration

ACTRN12619000868189.

Move-It: A Cluster-Randomised Digital Worksite Exercise Intervention in China: Outcome and Process Evaluation

We evaluate the outcomes and processes of a video and web-based worksite exercise intervention for sedentary office workers in China, in a 2-arm cluster-randomised wait-list control trial (n = 282: intervention (INT) n = 196 and wait-list control (WLC) n = 86). Eligible clusters were two sites of a major organisation in China randomly allocated to each group (INT: Guangzhou; WLC: Beijing); eligible participants were site employees (n = 690). A theoretically informed digital workplace intervention (Move-It) involving a 10 min Qigong exercise session (video demonstration via website) was delivered twice a day at set break times during the working day for 12 consecutive weeks. Individual-level outcomes were assessed. Participants' physical activity increased significantly from baseline to post-intervention similarly in both the intervention and the control group. There was a significantly smaller increase in weekday sitting hours in intervention than controls (by 4.66 h/week), and work performance increased only in the control group. Process evaluation (including six focus groups) was conducted using the RE-AIM (reach, effectiveness, adoption, implementation and maintenance) framework. The intervention had wide reach and was successfully marketed to all employees with good uptake. The participatory approach increased perceived organisational support and enhanced adoption. The intervention was implemented broadly as planned. Qigong worksite exercise intervention can be successfully delivered to sedentary office workers in China using video and web-based platforms. It may increase physical activity and does not adversely affect perceived work performance. The study highlights the complexity of conducting health promotion research in real-world organisational settings.

Compendium of Health and Wellness Coaching: 2019 Addendum

The 2019 Addendum, in conjunction with the original health and wellness coaching (HWC) Compendium, organizes HWC literature with the aim of assisting researchers while providing a resource for practitioners. The 2019 Addendum to the HWC Compendium extends the initial work by adding HWC-related literature published in the past 2 years. The 2019 Addendum divides articles retrieved into 8 categories, including a new miscellaneous section complementing categories examining HWC effects on cancer, cholesterol, diabetes, heart disease, hypertension, obesity, and wellness. The 2019 Addendum again provides in-depth information about the nature, quality, and results from each article in a detailed spreadsheet provided as an electronic appendix. The 2019 Addendum contributes another 104 peer-reviewed coaching-related articles to the HWC Compendium. This most recent research again describes HWC as a favorable intervention with treatment potential in all categories, though only 3 new cancer articles were included in the 2019 Addendum. Trends in HWC (ie, e-coaching and group coaching) are identified, and there is also discussion of future research needs. In conclusion, the field of HWC continues to grow, as does the research describing this clinical practice; the 2019 Addendum to the Compendium of HWC organizes and assists understanding of this literature.

User Models for Personalized Physical Activity Interventions: Scoping Review

Background

Fitness devices have spurred the development of apps that aim to motivate users, through interventions, to increase their physical activity (PA). Personalization in the interventions is essential as the target users are diverse with respect to their activity levels, requirements, preferences, and behavior.

Objective

This review aimed to (1) identify different kinds of personalization in interventions for promoting PA among any type of user group, (2) identify user models used for providing personalization, and (3) identify gaps in the current literature and suggest future research directions.

Methods

A scoping review was undertaken by searching the databases PsycINFO, PubMed, Scopus, and Web of Science. The main inclusion criteria were (1) studies that aimed to promote PA; (2) studies that had personalization, with the intention of promoting PA through technology-based interventions; and (3) studies that described user models for personalization.

Results

The literature search resulted in 49 eligible studies. Of these, 67% (33/49) studies focused solely on increasing PA, whereas the remaining studies had other objectives, such as maintaining healthy lifestyle (8 studies), weight loss management (6 studies), and rehabilitation (2 studies). The reviewed studies provide personalization in 6 categories: goal recommendation, activity recommendation, fitness partner recommendation, educational content, motivational content, and intervention timing. With respect to the mode of generation, interventions were found to be semiautomated or automatic. Of these, the automatic interventions were either knowledge-based or data-driven or both. User models in the studies were constructed with parameters from 5 categories: PA profile, demographics, medical data, behavior change technique (BCT) parameters, and contextual information. Only 27 of the eligible studies evaluated the interventions for improvement in PA, and 16 of these concluded that the interventions to increase PA are more effective when they are personalized.

Conclusions

This review investigates personalization in the form of recommendations or feedback for increasing PA. On the basis of the review and gaps identified, research directions for improving the efficacy of personalized interventions are proposed. First, data-driven prediction techniques can facilitate effective personalization. Second, use of BCTs in automated interventions, and in combination with PA guidelines, are yet to be explored, and preliminary studies in this direction are promising. Third, systems with automated interventions also need to be suitably adapted to serve specific needs of patients with clinical conditions. Fourth, previous user models focus on single metric evaluations of PA instead of a potentially more effective, holistic, and multidimensional view. Fifth, with the widespread adoption of activity monitoring devices and mobile phones, personalized and dynamic user models can be created using available user data, including users’ social profile. Finally, the long-term effects of such interventions as well as the technology medium used for the interventions need to be evaluated rigorously.

The Effectiveness of a Web-Based Computer-Tailored Physical Activity Intervention Using Fitbit Activity Trackers: Randomized Trial

BACKGROUND

Web-based interventions that provide personalized physical activity advice have demonstrated good effectiveness but rely on self-reported measures of physical activity, which are prone to overreporting, potentially reducing the accuracy and effectiveness of the advice provided.

OBJECTIVE

This study aimed to examine whether the effectiveness of a Web-based computer-tailored intervention could be improved by integrating Fitbit activity trackers.

METHODS

Participants received the 3-month TaylorActive intervention, which included 8 modules of theory-based, personally tailored physical activity advice and action planning. Participants were randomized to receive the same intervention either with or without Fitbit tracker integration. All intervention materials were delivered on the Web, and there was no face-to-face contact at any time point. Changes in physical activity (Active Australia Survey), sitting time (Workforce Sitting Questionnaire), and body mass index (BMI) were assessed 1 and 3 months post baseline. Advice acceptability, website usability, and module completion were also assessed.

RESULTS

A total of 243 Australian adults participated. Linear mixed model analyses showed a significant increase in total weekly physical activity (adjusted mean increase=163.2; 95% CI 52.0-274.5; P=.004) and moderate-to-vigorous physical activity (adjusted mean increase=78.6; 95% CI 24.4-131.9; P=.004) in the Fitbit group compared with the non-Fitbit group at the 3-month follow-up. The sitting time and BMI decreased more in the Fitbit group, but no significant group × time interaction effects were found. The physical activity advice acceptability and the website usability were consistently rated higher by participants in the Fitbit group. Non-Fitbit group participants completed 2.9 (SD 2.5) modules, and Fitbit group participants completed 4.4 (SD 3.1) modules.

CONCLUSIONS

Integrating physical activity trackers into a Web-based computer-tailored intervention significantly increased intervention effectiveness.

TRIAL REGISTRATION

Australian New Zealand Clinical Trials Registry ACTRN12616001555448; https://www.anzctr.org.au/Trial/Registration/TrialReview.aspx?id=371793 (Archived by WebCite at http://www.webcitation.org/73ioTxQX2).

Examining Changes in Healthy Days After Health Coaching

PURPOSE

To describe changes in health-related quality of life (HRQOL) related to variation in demographic characteristics, program goals, and program participation, among health coaching program participants.

DESIGN

A retrospective observational study of a health coaching program.

SETTING AND PARTICIPANTS

A total of 2169 adults enrolled in an individually purchased or employer-sponsored health plan from a large health and well-being company, who participated in a health coaching program between January 2016 and April 2017.

INTERVENTION

The health coaching program used evidence-based behavior change strategies to encourage skill development, self-monitoring, and goal setting/achievement. Health coaching program modalities included online and telephonic coaching sessions.

MEASURES

Demographic characteristics (gender, age, race, income), goal categories (weight management, fitness, nutrition, stress management, other), program modality (online, telephonic, both), engagement level (low, medium, high), and Healthy Days, a validated HRQOL measure developed by the Centers for Disease Control and Prevention.

ANALYSIS

t Tests, mixed analysis of variance (ANOVA).

RESULTS

There were significant ( P < .05) reductions in average total unhealthy days (UHDs) across all goal categories. Mixed ANOVAs identified a significant main effect for time, for all demographic characteristics ( P values < .05), and a significant effect for program modality ( P < .0001), time ( P < .0001), and interaction effects, between program modality and time, on average UHD ( P = .01).

CONCLUSION

Our findings indicate significant reductions in UHD, following 6 months of health coaching, and support the use of HRQOL measures, which are known to be highly correlated with traditional measures of health, to evaluate health coaching programs.

An mHealth App for Self-Management of Chronic Lower Back Pain (Limbr): Pilot Study

Background

Although mobile health (mHealth) interventions can help improve outcomes among patients with chronic lower back pain (CLBP), many available mHealth apps offer content that is not evidence based. Limbr was designed to enhance self-management of CLBP by packaging self-directed rehabilitation tutorial videos, visual self-report tools, remote health coach support, and activity tracking into a suite of mobile phone apps, including Your Activities of Daily Living, an image-based tool for quantifying pain-related disability.

Objective

The aim is to (1) describe patient engagement with the Limbr program, (2) describe patient-perceived utility of the Limbr program, and (3) assess the validity of the Your Activities of Daily Living module for quantifying functional status among patients with CLBP.

Methods

This was a single-arm trial utilizing a convenience sample of 93 adult patients with discogenic back pain who visited a single physiatrist from January 2016 to February 2017. Eligible patients were enrolled in 3-month physical therapy program and received the Limbr mobile phone app suite for iOS or Android. The program included three daily visual self-reports to assess pain, activity level, and medication/coping mechanisms; rehabilitation video tutorials; passive activity-level measurement; and chat-based health coaching. Patient characteristics, patient engagement, and perceived utility were analyzed descriptively. Associations between participant characteristics and program interaction were analyzed using multiple linear regression. Associations between Your Activities of Daily Living and Oswestry Disability Index (ODI) assessments were examined using Pearson correlation and hierarchical linear modeling.

Results

A total of 93 participants were enrolled; of these, 35 (38%) completed the program (age: mean 46, SD 16 years; female: 22/35, 63%). More than half of completers finished assessments at least every 3 days and 70% (19/27) used the rehabilitation component at least once a week. Among respondents to a Web-based feedback survey, 76% (16/21) found the daily notifications helped them remember to complete their exercises, 81% (17/21) found the system easy to use, and 62% (13/21) rated their overall experience good or excellent. Baseline Your Activities of Daily Living score was a significant predictor of baseline ODI score, with ODI increasing by 0.30 units for every 1-unit increase in Your Activities of Daily Living (P<.001). Similarly, hierarchical linear modeling analysis indicated that Your Activities of Daily Living daily assessment scores were significant predictors of ODI scores over the course of the study (P=.01).

Conclusions

Engagement among participants who completed the Limbr program was high, and program utility was rated positively by most respondents. Your Activities of Daily Living was significantly associated with ODI scores, supporting the validity of this novel tool. Future studies should assess the effect of Limbr on clinical outcomes, evaluate its use among a wider patient sample, and explore strategies for reducing attrition.

Trial Registration

ClinicalTrials.gov NCT03040310; https://clinicaltrials.gov/ct2/show/NCT03040310 (Archived by WebCite at http://www.webcitation.org/722mEvAiv)

Increasing Physical Activity in Mothers Using Video Exercise Groups and Exercise Mobile Apps: Randomized Controlled Trial

Background

Women significantly decrease their activity levels in the transition to motherhood. Digital health technologies are low cost, scalable, and can provide an effective delivery mechanism for behavior change. This is the first study that examines the use of videoconferencing and mobile apps to create exercise groups for mothers.

Objective

The aim of the study was to test the feasibility, acceptability, and effectiveness of an individually adaptive and socially supportive physical activity intervention incorporating videoconferencing and mobile apps for mothers.

Methods

The Moms Online Video Exercise Study was an 8-week, 2-armed, Web-based randomized trial comparing the effectiveness of a group exercise intervention with a waitlist control. Healthy mothers with at least 1 child under the age of 12 years were recruited through Facebook and email listservs. Intervention participants joined exercise groups using videoconferencing (Google Hangouts) every morning on weekdays and exercised together in real time, guided by exercise mobile apps (eg, Nike+, Sworkit) of their choice. Waitlist control participants had access to recommended mobile apps and an invitation to join an exercise group after the 8-week study period. Main outcomes assessed included changes in self-reported moderate, vigorous, and moderate to vigorous physical activity (MVPA) minutes per week in aggregate and stratified by whether women met Centers for Disease Control and Prevention guidelines for sufficient aerobic activity at baseline. Outcomes were measured through self-assessed Web-based questionnaires at baseline and 8 weeks.

Results

The intervention was effective at increasing exercise for inactive women and proved to be feasible and acceptable to all participants. A total of 64 women were randomized, 30 to intervention and 34 to control. Women attended 2.8 sessions per week. There was a strong, but not statistically significant, trend toward increasing moderate, vigorous, and MVPA minutes for all women. As hypothesized, in the prespecified stratum of women who were inactive at baseline (n=51), intervention participants significantly increased their activity by an average of 50 (95% CI 4.0-95.9, P=.03) MVPA minutes per week more than control participants. They had a corresponding statistically significant net increase of 19 (95% CI 3.2-34.8, P=.02) minutes of vigorous activity. Inactive women in the intervention arm also experienced promising reductions in depression, reporting a statistically significant net decrease in their depression score (−3.8, 95% CI −7.0 to −0.6; P=.02).

Conclusions

We found that a group exercise intervention using videoconferencing and mobile apps was a feasible and acceptable way to deliver a physical activity intervention to mothers. The intervention increased physical activity in inactive mothers. Further studies are needed to better establish how long these changes in physical activity can be maintained and whether these findings can be reproduced in a more diverse population.

Trial Registration

ClinicalTrials.gov NCT02805140; https://clinicaltrials.gov/ct2/show/NCT02805140 (Archived by WebCite at http://www.webcitation.org/6yYZwRveg)

Intrapersonal Variation in Goal Setting and Achievement in Health Coaching: Cross-Sectional Retrospective Analysis

Background

Chronic conditions in the United States are among the most costly and preventable of all health problems. Research suggests health coaching is an effective strategy for reducing health risks including decreases in weight, blood pressure, lipids, and blood glucose. Much less is known about how and when coaching works.

Objective

The aim of this study was to conduct an analysis of intrapersonal variations in participants’ progression in health coaching, examining gender and age-related differences.

Methods

This was a cross-sectional, retrospective analysis of 35,333 health coaching participants between 2012 and 2016. Differences in number of goals and activities set and completed, and number of interactions were assessed using negative binomial models. Differences in goal type were assessed using logistic regression for gender and using the Welch test for age to account for unequal variances.

Results

Participants choosing online coaching were more likely to be younger and female (P<.001). Gender and age differences were found for the types of goals set by participants. Regarding program activity, women set and completed 12% more action steps than men (P<.001), averaging 21% more interactions than men (P<.001); no gender differences were found in number of goals completed (P=.12), although the percentage of males and females completing goals was significantly different at 60 and 120 days postenrollment (P<.001). Results indicated significant age-related differences in all aspects of program activity: number of interactions, goals set and completed, action steps set and completed (all P values <.01), as well as significant differences in percentage of individuals completing initial goals within 30 days, with older individuals completing more than younger individuals did (all P values <.001).

Conclusions

This study found significant intrapersonal variation in how people participate in and progress through a coaching program. Age-related variations were found in all aspects of coaching activity, from modality preference and initial choice of goal type (eg, weight management, tobacco cessation) to goal completion, whereas gender-related differences were demonstrated for all program activities except number of goals set and completed. These findings indicate that to maximize behavior change, coaches need to personalize the coaching experience to the individual.

eHealth in Treatment of Offenders in Forensic Mental Health: A Review of the Current State

BACKGROUND

Treatment of offenders in forensic mental health is complex. Often, these in- or outpatients have low treatment motivation, suffer from multiple disorders, and have poor literacy skills. eHealth may be able to improve treatment outcomes because of its potential to increase motivation and engagement, and it can overcome the predominant one-size-fits-all approach by being tailored to individual patients.

OBJECTIVE

To examine its potential, this systematic review studies the way that eHealth has been used and studied in forensic mental health and identifies accompanying advantages and disadvantages for both patients and treatment, including effectiveness.

METHODS

A systematic search in Scopus, PsycINFO, and Web of Science was performed up until December 2017. Studies were included if they focused on technological interventions to improve the treatment of forensic psychiatric patients.

RESULTS

The search resulted in 50 studies in which eHealth was used for treatment purposes. Multiple types of studies and technologies were identified, such as virtual reality, web-based interventions, and videoconferencing. The results confirmed the benefits of technology, for example, the acquisition of unique information about offenders, effectiveness, and tailoring to specific characteristics, but indicated that these are not fully taken advantage of.

DISCUSSION

To overcome the barriers and obtain the benefits, eHealth has to have a good fit with patients and the forensic psychiatric context. It has to be seamlessly integrated in existing care and should not be added as an isolated element. To bridge the gap between the current situation and eHealth's potential, further research on development, implementation, and evaluation should be conducted.

Clarifying the Concept of Adherence to eHealth Technology: Systematic Review on When Usage Becomes Adherence

BACKGROUND

In electronic health (eHealth) evaluations, there is increasing attention for studying the actual usage of a technology in relation to the outcomes found, often by studying the adherence to the technology. On the basis of the definition of adherence, we suggest that the following three elements are necessary to determine adherence to eHealth technology: (1) the ability to measure the usage behavior of individuals; (2) an operationalization of intended use; and (3) an empirical, theoretical, or rational justification of the intended use. However, to date, little is known on how to operationalize the intended usage of and the adherence to different types of eHealth technology.

OBJECTIVE

The study aimed to improve eHealth evaluations by gaining insight into when, how, and by whom the concept of adherence has been used in previous eHealth evaluations and finding a concise way to operationalize adherence to and intended use of different eHealth technologies.

METHODS

A systematic review of eHealth evaluations was conducted to gain insight into how the use of the technology was measured, how adherence to different types of technologies was operationalized, and if and how the intended use of the technology was justified. Differences in variables between the use of the technology and the operationalization of adherence were calculated using a chi-square test of independence.

RESULTS

In total, 62 studies were included in this review. In 34 studies, adherence was operationalized as "the more use, the better," whereas 28 studies described a threshold for intended use of the technology as well. Out of these 28, only 6 reported a justification for the intended use. The proportion of evaluations of mental health technologies reporting a justified operationalization of intended use is lagging behind compared with evaluations of lifestyle and chronic care technologies. The results indicated that a justification of intended use does not require extra measurements to determine adherence to the technology.

CONCLUSIONS

The results of this review showed that to date, justifications for intended use are often missing in evaluations of adherence. Evidently, it is not always possible to estimate the intended use of a technology. However, such measures do not meet the definition of adherence and should therefore be referred to as the actual usage of the technology. Therefore, it can be concluded that adherence to eHealth technology is an underdeveloped and often improperly used concept in the existing body of literature. When defining the intended use of a technology and selecting valid measures for adherence, the goal or the assumed working mechanisms should be leading. Adherence can then be standardized, which will improve the comparison of adherence rates to different technologies with the same goal and will provide insight into how adherence to different elements contributed to the outcomes.

Effectiveness of individual counseling and activity monitors to promote physical activity among university students

BACKGROUND

Physical activity (PA) promotion among university students is important to contribute to a lifelong healthy lifestyle. Nevertheless, research in the field is still limited in quantity, quality and generalizability. This study aimed at evaluating the effectiveness of two individual-based strategies for promoting PA among university students in such university contexts where course-based interventions are difficult to implement.

METHODS

Thirty-three university students were recruited by means of face-to-face interviews and randomly assigned to three groups. The first group attended individual counselling sessions (based on the social cognitive theory and the transtheoretical model of behavior change) via videoconferencing calls, the second used wearable PA monitors designed to motivate to PA, and the third served as control. Interventions lasted 12 weeks. Measures of weekly PA (self-reported by questionnaires and recorded by ActiGraph-GT3X+ monitors) and the stage of change of participants were collected at baseline (t0), immediately after the 12-week intervention (t1), and after a 3-month follow-up (t2).

RESULTS

Students in the individual counselling group increased self-reported energy expenditure between t0 and t1 and maintained this improvement at t2; on the contrary, there was no increase in ActiGraph measures of PA. Progression through stages of changes was observed in the same group at t1, followed by some relapses at t2. No significant differences were found neither in the group of students who used the PA monitors nor in the control group.

CONCLUSIONS

Although measures of self-reported PA and stage of change suggest the effectiveness of the counselling intervention, the results obtained with accelerometers are contrasting, probably due to the fact that some types of PA participants engaged in could not be recorder by accelerometers. Further studies are needed to determine the efficacy of individual counselling to promote PA in university students. The autonomous use of PA monitors had no effects on PA behavior. The low participation rate in the study suggests considering carefully the difficulties in motivating this population and in finding low time-consuming strategies to incentive participation.