Dropout, nonusage attrition, and pretreatment predictors of nonusage attrition in a commercial Web-based weight loss program

How people with persistent pain experience in-person physiotherapy blended with biopsychosocial digital health - A qualitative study on participants' experiences with Back2Action

Background

A blended intervention consisting of in-person physiotherapy and psychologically-informed digital health, called Back2Action, was developed to optimise the management of people with persistent spinal pain who also have psychosocial risk factors associated with the development or maintenance of persistent pain. This study aimed to gain insights in how participants experienced this blended intervention.

Methods

A qualitative study using semi-structured interviews was conducted. Eleven people with persistent non-specific spinal pain who received the blended intervention within a randomised clinical trial were included. All interviews were recorded, transcribed verbatim and analysed independently by two researchers. Data were analysed using a thematic analysis.

Results

The analysis identified four themes: (1) Experiencing a better understanding of the relationship between own physical and mental health; (2) Importance of the physiotherapist's active involvement in biopsychosocial blended care, which describes the crucial role of physiotherapists in supporting participants in this; (3) Appreciation of digital health, to better understand persistent pain and make meaningful lifestyle changes; and (4) Trials and triumphs, revealing gains such as better coping, but also challenges with implementation of changes into long-term routines.

Conclusion

Participants of the blended intervention experienced positive changes in thoughts and behaviours, which highlights the feasibility and acceptability of the blended intervention as a more holistic treatment within pain management. The differences in personal preferences for receiving psychologically-informed digital health poses challenges for implementation of blended biopsychosocial care in evidence-based practice.

Pragmatic Implementation of Online Obesity Treatment and Maintenance Interventions in Primary Care: A Randomized Clinical Trial

Importance

Behavioral weight loss interventions have achieved success in primary care; however, to our knowledge, pragmatic implementation of a fully automated treatment that requires little researcher oversight has not been tested. Moreover, weight loss maintenance remains a challenge.

Objective

To evaluate the long-term effectiveness of an automated, online, behavioral obesity treatment program (Rx Weight Loss [RxWL]) at 12 months (primary end point) and 24 months when delivered pragmatically in primary care and to compare the effectiveness of 3 weight loss maintenance approaches.

Design, Setting, and Participants

This randomized clinical trial of RxWL, an online weight loss program, recruited patients from a Rhode Island primary care network with approximately 60 practices and 100 physicians. Eligible participants were primary care patients aged 18 to 75 years with overweight or obesity who were referred by their nurse care manager and enrolled between 2018 and 2020. All participants were included in the intention-to-treat analysis, whereas only those who engaged with maintenance intervention were included in the per-protocol analysis. Data were analyzed from August 2022 to September 2023.

Interventions

All participants were offered the same 3-month weight loss program, with randomization to one of three 9-month maintenance programs: control intervention (monthly online newsletters), monthly intervention (9 monthly video lessons and 1 week of self-monitoring per month), or refresher intervention (an introductory session and two 4-week periods of lessons and self-monitoring at 7 and 10 months).

Main Outcomes and Measures

The primary outcome was weight change at 12 months using height and weight data collected from electronic medical records through 24 months.

Results

Among the 540 participants (mean [SD] age, 52.8 [13.4] years; 384 females [71.1%]) in the intention-to-treat analysis, mean estimated 3-month weight loss was 3.60 (95% CI, -4.32 to -2.88) kg. At the 12-month primary end point, the amount of weight regained in the monthly (0.37 [95% CI, -0.06 to 0.81] kg) and refresher (0.45 [95% CI, 0.27 to 0.87] kg) maintenance groups was significantly less than that in the newsletter control maintenance group (1.28 [95% CI, 0.85 to 1.71] kg; P = .004). The difference in weight regain between the monthly and refresher maintenance groups was not statistically significant. This pattern persisted at 24 months. In the per-protocol analysis of 253 participants, mean weight loss at the end of the initial 3-month intervention was 6.19 (95% CI, -7.25 to -5.13) kg. Similarly, at 12 months there was less weight regain in the monthly (0.61 kg) and refresher (0.96 kg) maintenance groups than in the newsletter control maintenance group (1.86 kg).

Conclusions and Relevance

Results of this randomized clinical trial indicate that pragmatic implementation of a 12-month automated, online, behavioral obesity treatment that includes 9 months of active maintenance produces clinically significant weight loss over 2 years in primary care patients with overweight or obesity. These findings underscore the importance of providing ongoing maintenance intervention to prevent weight regain.

Trial Registration

ClinicalTrials.gov Identifier: NCT03488212.

Feasibility and preliminary efficacy of iConquerFear: a self-guided digital intervention for fear of cancer recurrence

PURPOSE

Approximately 50% of cancer survivors experience moderate-severe fear of cancer recurrence (FCR). Self-guided digital interventions have potential to address the high level of FCR-related unmet needs at scale, but existing digital interventions have demonstrated variable engagement and efficacy. This study aimed to evaluate the feasibility and preliminary efficacy of iConquerFear, a five-module self-guided digital FCR intervention.

METHODS

Eligible curatively treated breast cancer survivors were recruited. Participants reporting clinically significant FCR (≥ 13 on the Fear of Cancer Recurrence Inventory-Short Form; FCRI-SF) were given access to iConquerFear. Feasibility was indicated by > 50% of eligible participants enrolling in iConquerFear and recording moderate (≥ 120 min) or greater usage. Preliminary efficacy was evaluated via changes in self-reported FCR severity, anxiety, depression, intrusions and metacognitions from baseline to immediately and 3 months post-intervention.

RESULTS

Fifty-four (83%) of 65 eligible participants enrolled in iConquerFear; six subsequently withdrew. Thirty-nine (83%) participants recorded moderate (n = 24; 120-599 min) or high (n = 15; ≥ 600 min) usage. Engagement levels increased with participant age (p = 0.043), but were lower in participants with higher baseline FCR (p = 0.028). Qualitative feedback indicated engagement was sometimes limited by difficulties with navigation and relating to featured survivors. Participants reported significantly improved FCR (mean reduction (95%CI): baseline to post-intervention - 3.44 (- 5.18, - 1.71), baseline to 3-month follow-up - 4.52 (- 6.25, - 2.78), p =  < 0.001).

CONCLUSION

iConquerFear is a feasible and potentially efficacious intervention for reducing FCR in breast cancer survivors. Easier navigation and more relatable examples may enhance engagement.

IMPLICATIONS FOR CANCER SURVIVORS

iConquerFear may help address moderate but burdensome FCR levels in cancer survivors.

Improved resilience following digital cognitive behavioral therapy for insomnia protects against insomnia and depression one year later

BACKGROUND

While the negative consequences of insomnia are well-documented, a strengths-based understanding of how sleep can increase health promotion is still emerging and much-needed. Correlational evidence has connected sleep and insomnia to resilience; however, this relationship has not yet been experimentally tested. This study examined resilience as a mediator of treatment outcomes in a randomized clinical trial with insomnia patients.

METHODS

Participants were randomized to either digital cognitive behavioral therapy for insomnia (dCBT-I; n = 358) or sleep education control (n = 300), and assessed at pre-treatment, post-treatment, and 1-year follow-up. A structural equation modeling framework was utilized to test resilience as a mediator of insomnia and depression. Risk for insomnia and depression was also tested in the model, operationalized as a latent factor with sleep reactivity, stress, and rumination as indicators (aligned with the 3-P model). Sensitivity analyses tested the impact of change in resilience on the insomnia relapse and incident depression at 1-year follow-up.

RESULTS

dCBT-I resulted in greater improvements in resilience compared to the sleep education control. Furthermore, improved resilience following dCBT-I lowered latent risk, which was further associated with reduced insomnia and depression at 1-year follow-up. Sensitivity analyses indicated that each point improvement in resilience following treatment reduced the odds of insomnia relapse and incident depression 1 year later by 76% and 65%, respectively.

CONCLUSIONS

Improved resilience is likely a contributing mechanism to treatment gains following insomnia therapy, which may then reduce longer-term risk for insomnia relapse and depression.

Predicting Disengagement to Better Support Outcomes in a Web-Based Weight Loss Program Using Machine Learning Models: Cross-Sectional Study

BACKGROUND

Engagement is key to interventions that achieve successful behavior change and improvements in health. There is limited literature on the application of predictive machine learning (ML) models to data from commercially available weight loss programs to predict disengagement. Such data could help participants achieve their goals.

OBJECTIVE

This study aimed to use explainable ML to predict the risk of member disengagement week by week over 12 weeks on a commercially available web-based weight loss program.

METHODS

Data were available from 59,686 adults who participated in the weight loss program between October 2014 and September 2019. Data included year of birth, sex, height, weight, motivation to join the program, use statistics (eg, weight entries, entries into the food diary, views of the menu, and program content), program type, and weight loss. Random forest, extreme gradient boosting, and logistic regression with L1 regularization models were developed and validated using a 10-fold cross-validation approach. In addition, temporal validation was performed on a test cohort of 16,947 members who participated in the program between April 2018 and September 2019, and the remaining data were used for model development. Shapley values were used to identify globally relevant features and explain individual predictions.

RESULTS

The average age of the participants was 49.60 (SD 12.54) years, the average starting BMI was 32.43 (SD 6.19), and 81.46% (39,594/48,604) of the participants were female. The class distributions (active and inactive members) changed from 39,369 and 9235 in week 2 to 31,602 and 17,002 in week 12, respectively. With 10-fold-cross-validation, extreme gradient boosting models had the best predictive performance, which ranged from 0.85 (95% CI 0.84-0.85) to 0.93 (95% CI 0.93-0.93) for area under the receiver operating characteristic curve and from 0.57 (95% CI 0.56-0.58) to 0.95 (95% CI 0.95-0.96) for area under the precision-recall curve (across 12 weeks of the program). They also presented a good calibration. Results obtained with temporal validation ranged from 0.51 to 0.95 for area under a precision-recall curve and 0.84 to 0.93 for area under the receiver operating characteristic curve across the 12 weeks. There was a considerable improvement in area under a precision-recall curve of 20% in week 3 of the program. On the basis of the computed Shapley values, the most important features for predicting disengagement in the following week were those related to the total activity on the platform and entering a weight in the previous weeks.

CONCLUSIONS

This study showed the potential of applying ML predictive algorithms to help predict and understand participants' disengagement with a web-based weight loss program. Given the association between engagement and health outcomes, these findings can prove valuable in providing better support to individuals to enhance their engagement and potentially achieve greater weight loss.

Factors influencing adults to drop out of intensive lifestyle interventions for weight loss

Reducing ≥5% of body weight can decrease the risk of developing chronic diseases in adults with excess weight. Although Intensive Lifestyle Interventions (ILIs) that include cognitive-behavioral techniques to improve physical activity and eating habits are the best approach for losing weight, the failure to retain participants is a barrier to their successful implementation. We aimed to investigate the factors influencing adults to drop out of ILIs for weight loss at six months. We conducted retrospective multiple logistic regression analysis of 268 participants with excess weight (body mass index ≥ 25 kg/m2) from a multicenter study (n = 237, in-person ILI in five clinics, delivered by nutrition interns), and a randomized controlled trial (n = 31, one online ILI, delivered by a master's degree student). The same research team conducted both studies in Northern Mexico, using the same intervention components, and identical instruments and techniques to collect the data. We found that older participants (≥50 years) were less likely to drop out of the ILI for weight loss compared to participants <35 years old (OR = 0.34, 95% CI = 0.16-0.70). For each unit increase in the bodily pain scale of the SF-36 (less perceived pain), the risk of dropping out decreased by 2% (OR = 0.98, 95% CI = 0.97, 0.996), while a change in the interventionist during the 6-month intervention more than doubled the risk of dropping out (OR 2.25, 95% CI = 1.23-4.14). Retention in ILIs may be improved by ensuring that the same interventionist remains during the six-month intervention. In addition, ILIs may need further tailoring for younger ages and for participants with higher perceived pain.

Effectiveness of a bite-sized web-based intervention to improve healthcare worker wellbeing: A randomized clinical trial of WISER

Importance

Problems with the wellbeing of healthcare workers (HCWs) are widespread and associated with detrimental consequences for the workforce, organizations, and patients.

Objective

This study tested the effectiveness of the Web-based Implementation for the Science of Enhancing Resilience (WISER) intervention, a positive psychology program, to improve six dimensions of the wellbeing of HCWs.

Design

We conducted a randomized controlled trial of HCWs between 1 April 2018 and 22 July 2019. Cohort 1 received WISER daily for 10 days. Cohort 2 acted as a waitlist control before receiving WISER.

Setting

Web-based intervention for actively employed HCWs across the United States.

Participants

Eligibility criteria included being ≥18 years old and working as a HCW. Each participant was randomized to start the intervention or serve as a waitlist control for 14 days before starting the intervention.

Interventions

Cohorts received links via 10 texts exposing them to introductory videos and positive psychology exercises (3 good things, cultivating awe, random acts of kindness, cultivating relationships, and gratitude letters).

Main outcomes and measures

The primary outcome was emotional exhaustion; secondary outcomes included depressive symptoms, work-life integration, happiness, emotional thriving, and emotional recovery. All outcomes were assessed at baseline, 1-week post-intervention (primary endpoint), and 1, 6, and 12-month post-intervention. Outcomes were measured using six validated wellbeing instruments, rescaled to 100-point scales for comparison. Six items assessed participants' WISER experience. The analysis employed mixed-effects models.

Results

In cohorts 1 and 2, 241 and 241 initiated WISER, and 178 (74%) and 186 (77%) completed the 6-month follow-up, respectively. Cohort populations were similar at baseline, mostly female (81; 76%) and nurses (34; 32%) or physicians (22; 23%), with 1-10 years of experience in their current position (54; 52%). Relative to control, WISER significantly improved depressive symptoms [-7.5 (95%CI: -11.0, -4.0), p < 0.001], work-life integration [6.5 (95%CI: 4.1, 8.9), p < 0.001], happiness [5.7 (95%CI: 3.0, 8.4), p < 0.001], emotional thriving [6.4 (95%CI: 2.5, 10.3), p = 0.001], and emotional recovery [5.3 (95%CI: 1.7, 8.9), p = 0.004], but not emotional exhaustion [-3.7 (95%CI: -8.2, 0.8), p = 0.11] at 1 week. Combined cohort results at 1, 6, and 12 months showed that all six wellbeing outcomes were significantly improved relative to baseline (p < 0.05 for all). Favorable impressions of WISER were reported by 87% of participants at the 6-month post-assessment.

Conclusion and relevance

WISER improved HCW depressive symptoms, work-life integration, happiness, emotional thriving, and emotional recovery. Improvements in all HCW wellbeing outcomes endured at the 1-, 6-, and 12-month follow-ups. HCW's impressions of WISER were positive.

Clinical trials number

https://clinicaltrials.gov/ct2/show/, identifier: NCT02603133. Web-based Implementation for the Science of Enhancing Resilience Study (WISER).

Identifying Personality Characteristics and Indicators of Psychological Well-Being Associated With Attrition in the Motivation Makes the Move! Physical Activity Intervention: Randomized Technology-Supported Trial

BACKGROUND

Data attrition has been a common problem in longitudinal lifestyle interventions. The contributors to attrition in technology-supported physical activity interventions have not been thoroughly studied.

OBJECTIVE

The present study examined the roles of personality characteristics and indicators of psychological well-being in data attrition within a technology-supported, longitudinal intervention study with overweight adults.

METHODS

Participants (N=89) were adults from the Motivation Makes the Move! intervention study. Data attrition was studied after a 3-month follow-up. Participants' personality characteristics were studied using the Short Five self-report questionnaire. Psychological well-being indicators were assessed with the RAND 36-item health survey, Positive and Negative Affect Schedule, and Beck Depression Inventory. Logistic regression analyses were conducted to assess the risk of discontinuing the study. The analyses were adjusted for sex, age, study group, and educational status.

RESULTS

At the 3-month follow-up, 65 of 89 participants (73% of the initial sample) had continued in the study. Participants' personality characteristics and indicators of psychological well-being were not associated with the risk of dropping out of the study (all P values >.05). The results remained the same after covariate controls.

CONCLUSIONS

Participant attrition was not attributable to personality characteristics or psychological well-being in the Motivation Makes the Move! study conducted with overweight adults. As attrition remains a challenge within longitudinal, technology-supported lifestyle interventions, attention should be paid to the potentially dynamic natures of personality and psychological well-being, as well as other elements beyond these.

TRIAL REGISTRATION

ClinicalTrials.gov NCT02686502; https://clinicaltrials.gov/ct2/show/NCT02686502.

The effectiveness of technology-based interventions for weight loss maintenance: A systematic review of randomized controlled trials with meta-analysis

OBJECTIVE

To systematically review and meta-analyze randomized controlled trials on the effects of technology-based interventions for maintenance of lost weight.

METHODS

A systematic literature search was performed to identify randomized controlled trials with at least one intervention arm delivered through the internet or mobile application, published in English until September 2021. Weight change at the end of the weight loss maintenance phase was considered the primary outcome.

RESULTS

Twelve manuscripts with 2941 adults were included in the review; 10 studies were meta-analyzed. Included interventions had a duration of 3-30 months and were tested compared with minimum interventions (no contact with the study staff or intervention with only a limited number of features) or in-person groups. Technology-based interventions resulted in similar weight regain when compared with minimum interventions (ES = -0.07 kg; 95% CI = [-0.57, 0.42]; p = 0.770). However, when compared with in-person interventions, technology-based interventions were found to lead in significantly higher weight regain (ES = 1.36 kg; 95% CI = [0.29, 2.43]; p = 0.010).

CONCLUSION

Web- and app-based interventions for weight loss maintenance produced similar results with minimum interventions and resulted in greater weight regain compared with in-person interventions. Appropriate interventions for weight loss maintenance provide benefits against weight regain, only when provided in-person.

The Validated Features of Psychological Interventions for Weight Loss: An Integration

Many psychological inclinations, such as maladaptive beliefs, can diminish the capacity of individuals to manage their weight effectively and sustainably. Yet, interventions that purportedly address these psychological inclinations and improve weight management are not always beneficial. To be effective, these interventions should offer participants several choices, should be devoid of features that have not been validated in isolation, and should arrange the various activities in an efficient and effective sequence. Few if any programs fulfill these criteria. The aim of this paper was to construct an intervention that assimilates all the validated features of interventions that overcome the psychological impediments to weight loss. To achieve this goal, we blended a technique called intervention component analysis with thematic analysis. Specifically, we extracted refereed journal articles about weight loss from PsycInfo, distilled the practical recommendations from these articles, excluded recommendations that had not been validated in isolation of other features, integrated overlapping recommendations, and applied several principles to arrange these recommendations into the most effective sequence. This procedure generated an intervention that could comprise up to 43 features and activities, including self-affirmation to foster openness to change, anecdotes about dramatic improvements, ambitious rather than modest targets, an emphasis on strategies rather than targets, rewards for attempts, implementation intentions with partners, self-hypnosis, cognitive reframing, and distancing. If these features are unsuccessful, practices that demand more resources-such as group disclosure, virtual environments, motivational interviewing, and customized programs-were also recommended.

Combining Persuasive System Design Principles and Behavior Change Techniques in Digital Interventions Supporting Long-term Weight Loss Maintenance: Design and Development of eCHANGE

BACKGROUND

Long-term weight maintenance after weight loss is challenging, and innovative solutions are required. Digital technologies can support behavior change and, therefore, have the potential to be an effective tool for weight loss maintenance. However, to create meaningful and effective digital behavior change interventions that support end user values and needs, a combination of persuasive system design (PSD) principles and behavior change techniques (BCTs) might be needed.

OBJECTIVE

This study aimed to investigate how an evidence-informed digital behavior change intervention can be designed and developed by combining PSD principles and BCTs into design features to support end user values and needs for long-term weight loss maintenance.

METHODS

This study presents a concept for how PSD principles and BCTs can be translated into design features by combining design thinking and Agile methods to develop and deliver an evidence-informed digital behavior change intervention aimed at supporting weight maintenance. Overall, 45 stakeholders participated in the systematic and iterative development process comprising co-design workshops, prototyping, Agile development, and usability testing. This included prospective end users (n=17, 38%; ie, people with obesity who had lost ≥8% of their weight), health care providers (n=9, 20%), healthy volunteers (n=4, 9%), a service designer (n=1, 2%), and stakeholders from the multidisciplinary research and development team (n=14, 31%; ie, software developers; digital designers; and eHealth, behavior change, and obesity experts). Stakeholder input on how to operationalize the design features and optimize the technology was examined through formative evaluation and qualitative analyses using rapid and in-depth analysis approaches.

RESULTS

A total of 17 design features combining PSD principles and BCTs were identified as important to support end user values and needs based on stakeholder input during the design and development of eCHANGE, a digital intervention to support long-term weight loss maintenance. The design features were combined into 4 main intervention components: Week Plan, My Overview, Knowledge and Skills, and Virtual Coach and Smart Feedback System. To support a healthy lifestyle and continued behavior change to maintain weight, PSD principles such as tailoring, personalization, self-monitoring, reminders, rewards, rehearsal, praise, and suggestions were combined and implemented into the design features together with BCTs from the clusters of goals and planning, feedback and monitoring, social support, repetition and substitution, shaping knowledge, natural consequences, associations, antecedents, identity, and self-belief.

CONCLUSIONS

Combining and implementing PSD principles and BCTs in digital interventions aimed at supporting sustainable behavior change may contribute to the design of engaging and motivating interventions in line with end user values and needs. As such, the design and development of the eCHANGE intervention can provide valuable input for future design and tailoring of evidence-informed digital interventions, even beyond digital interventions in support of health behavior change and long-term weight loss maintenance.

TRIAL REGISTRATION

ClinicalTrials.gov NCT04537988; https://clinicaltrials.gov/ct2/show/NCT04537988.

Enrollment and retention of participants in remote digital health studies: a scoping review and framework proposal (Preprint)

Background

Objective

Methods

Results

Conclusions

Participants' perspectives on perceived usefulness of digital and in-person diabetes prevention programs: A qualitative study to inform decisions related to program participation

Objective

Given the effectiveness of both in-person and digital diabetes prevention programs (DPPs), participants have an opportunity to select a delivery mode based on their needs and preferences. The objective of this study was to understand and compare participants' experiences with digital and in-person DPPs to identify factors that affected how useful participants perceived these two program delivery modes.

Methods

Semi-structured interviews with participants who were enrolled in DPPs as either a digital (n = 23) or in-person (n = 20) program within one health care system were conducted. Data were analyzed following the template method using the qualitative software NVivo 12.

Results

Findings from the interviews indicated that creating accountability for weight loss was crucial for all program participants. In the digital program, weight and food tracking played a central role in creating accountability, while in the in-person program, group interactions fostered accountability. The digital program was perceived to encourage self-monitoring, oftentimes resulting in participants' reflection on their habits. The in-person program provided a platform for group support and mutual encouragement.

Conclusions

Participants perceived both programs as similarly useful. Yet program characteristics such as the ability to engage with other participants in-person or to seamlessly track weight on a daily basis appealed to different participants. It may be beneficial to align participants' preferences with programs' characteristics and strengths.

Barriers and Considerations in the Design and Implementation of Digital Behavioral Interventions: Qualitative Analysis

Background

Digital behavioral interventions have become increasingly popular for their ability to support patient diagnosis and treatment, chronic disease self-management, behavior change, and adherence to recommended care. However, digital intervention development is impeded by challenges such as limited technical skills, limited access to developers, and cost. The purpose of this study is to elicit in-depth qualitative feedback from intervention developers who have interest in digital behavioral interventions but lack programming skills regarding the barriers they experience and key considerations in the design and implementation of digital interventions.

Objective

This study aims to understand barriers in the design and implementation of digital behavioral interventions, as well as to identify key considerations for researchers who are developing these interventions.

Methods

We conducted semistructured qualitative interviews with 18 researchers who had experience either designing (but not coding) digital behavioral interventions or running research studies with them. Participants were a convenience sample of users of the Computerized Intervention Authoring System platform, an existing no-code development platform for building digital intervention content, and were recruited through either direct email solicitation or snowball sampling. All interviews were conducted and recorded over videoconference between February and April 2020. Recordings from interviews were transcribed and thematically analyzed by multiple coders.

Results

Interviews were completed with 18 participants and lasted between 24 and 65 (mean 46.9, SD 11.3) minutes. Interviewees were predominantly female (17/18, 94%) and represented different job roles, ranging from researcher to project/study staff. Three key barriers in the development of digital behavior interventions were identified during interviews: lack of cross-disciplinary understanding; variability in recipients’ technology access, infrastructure, and literacy; and the idea that evidence-based in-person interactions do not translate directly to digital interactions. Interviewees identified several key considerations that interventionists learned to prioritize, which have the potential to overcome these barriers and lead to successful interventions.

Conclusions

Barriers in the development of digital behavioral interventions are often created by a lack of cross-disciplinary understanding, which can lead to difficulties conceptualizing interventions, unrealistic expectations in terms of cost, and confusion about the development process. Moreover, concerns about research study participant characteristics and access to technology, as well as the translation of in-person interventions to digital, are apparent. Appropriate training in how to work with software development teams may help future digital behavior intervention creators overcome these barriers and may lead to new, exciting innovations in this space.

Weight Loss Trajectories in Healthy Weight Coaching: Cohort Study

Background

As global obesity prevalence continues to increase, there is a need for accessible and affordable weight management interventions, such as web-based programs.

Objective

This paper aims to assess the outcomes of healthy weight coaching (HWC), a web-based obesity management program integrated into standard Finnish clinical care.

Methods

HWC is an ongoing, structured digital 12-month program based on acceptance and commitment therapy. It includes weekly training sessions focused on lifestyle, general health, and psychological factors. Participants received remote one-on-one support from a personal coach. In this real-life, single-arm, prospective cohort study, we examined the total weight loss, weight loss profiles, and variables associated with weight loss success and program retention in 1189 adults (963 women) with a BMI >25 kg/m² among participants of the program between October 2016 and March 2019. Absolute (kg) and relative (%) weight loss from the baseline were the primary outcomes. We also examined the weight loss profiles, clustered based on the dynamic time-warping distance, and the possible variables associated with greater weight loss success and program retention. We compared different groups using the Mann-Whitney test or Kruskal-Wallis test for continuous variables and the chi-squared test for categorical variables. We analyzed changes in medication using the McNemar test.

Results

Among those having reached the 12-month time point (n=173), the mean weight loss was 4.6% (SE 0.5%), with 43% (n=75) achieving clinically relevant weight loss (≥5%). Baseline BMI ≥40 kg/m² was associated with a greater weight loss than a lower BMI (mean 6.6%, SE 0.9%, vs mean 3.2%, SE 0.6%; P=.02). In addition, more frequent weight reporting was associated with greater weight loss. No significant differences in weight loss were observed according to sex, age, baseline disease, or medication use. The total dropout rate was 29.1%. Dropouts were slightly younger than continuers (47.2, SE 0.6 years vs 49.2, SE 0.4 years; P=.01) and reported their weight less frequently (3.0, SE 0.1 entries per month vs 3.3, SE 0.1 entries per month; P<.001).

Conclusions

A comprehensive web-based program such as HWC is a potential addition to the repertoire of obesity management in a clinical setting. Heavier patients lost more weight, but weight loss success was otherwise independent of baseline characteristics.

Primary care clinicians' perspectives on clinical decision support to enhance outcomes of online obesity treatment in primary care: A qualitative formative evaluation

Objective

Online behavioral treatment for obesity produces clinically-meaningful weight losses among many primary care patients. However, some patients experience poor outcomes (i.e., failure to enroll post-referral, poor weight loss, or premature disengagement). This study sought to understand primary care clinicians' perceived utility of a clinical decision support system (CDSS) that would alert clinicians to patients' risk for poor outcome and guide clinician-delivered rescue interventions to reduce risk.

Methods

Qualitative formative evaluation was conducted in the context of an ongoing pragmatic clinical trial implementing online obesity treatment in primary care. Interviews were conducted with 14 nurse care managers (NCMs) overseeing patients' online obesity treatment. Interviews inquired about the potential utility of CDSS in primary care, desired alert frequency/format, and priorities for alert types (non-enrollment, poor weight loss, and/or early disengagement). We used matrix analysis to generate common themes across interviews.

Results

Nearly all NCMs viewed CDSS as potentially helpful in clinical practice. Alerts for patients at risk for disengagement were of highest priority, though all alert types were generally viewed as desirable. Regarding frequency and delivery mode of patient alerts, NCMs wanted to balance the need for prompt patient intervention with minimizing clinician burden. Concerns about CDSS emerged, including insufficient time to respond promptly and adequately to alerts and the need to involve other support staff for patients requiring ongoing rescue intervention.

Conclusions

NCMs view CDSS for online obesity treatment as potentially feasible and clinically useful. For optimal implementation in primary care, CDSS must minimize clinician burden and facilitate collaborative care.

Development of a Mobile Health Application for HIV Prevention Among At-Risk Populations in Urban Settings in East Africa: A Participatory Design Approach

Background

There is limited evidence in Africa on the design and development of mobile health (mHealth) applications to guide best practices and ensure effectiveness. A pragmatic trial for HIV pre-exposure prophylaxis roll-out among key populations in Tanzania is needed.

Objective

We present the results of the development of a mobile app (Jichunge) intended to promote adherence to pre-exposure prophylaxis (PrEP) among men who have sex with men (MSM) and female sex workers (FSW) in Tanzania.

Methods

A participatory design approach was employed and guided by the information system research framework. MSM and FSW were the target populations. A total of 15 MSM and 15 FSW were engaged in the relevance and design cycles, while the piloting phase included 10 MSM and 20 FSW.

Results

The relevance cycle enabled the description of the existing problem, provided the compatible app features for the target population, and identified the need to develop an mHealth app that provides health services in a stigmatizing and discriminating environment. User involvement in the app’s design and evaluation provided an opportunity to incorporate social, cultural, and community-specific features that ensured usability. In addition, the participants suggested valuable information to inform the app, text message services, medication registration, and chat platform designs.

Conclusions

The participatory design approach in the development of mHealth apps is useful in identifying and validating population-specific functional features, improve usability, and ensuring future health impacts. Through this participatory process, the Jichunge app took end-user needs, perspectives, and experiences into account, eliciting enthusiasm regarding its potential role in supporting pre-exposure prophylaxis adherence for HIV and related behavioral change promotion.

Trial Registration

International Clinical Trials Registry Platform PACTR202003823226570; https://trialsearch.who.int/Trial2.aspx?TrialID=PACTR202003823226570

Weight Loss and Usage of an Online Commercial Weight Loss Program (the CSIRO Total Wellbeing Diet Online) Delivered in an Everyday Context: Five-Year Evaluation in a Community Cohort

BACKGROUND

Obesity is a global public health challenge, and there is a need for more evidence-based self-management programs that support longer-term, sustained weight loss.

OBJECTIVE

This study used data from the Commonwealth Scientific and Industrial Research Organisation (CSIRO) Total Wellbeing Diet Online program to determine the reach and weight loss results over its first 5 years.

METHODS

Participants were adults who joined the commercial weight loss program of their own volition between October 2014 and September 2019 (N=61,164). Information collected included year of birth, sex, height, weight, and usage data (eg, entries into the food diary, views of the menu, and program content). Weight loss and percentage of starting body weight lost were calculated. Members were divided into 2 groups for analysis: "stayers" were members who signed up for at least 12 weeks of the program and recorded a weight entry at baseline and at the end of the program, while "starters" began the program but did not record a weight after 12 weeks. Descriptive statistics and multiple linear regression were used to describe weight loss and determine the member and program characteristics associated with weight loss.

RESULTS

Data were available from 59,686 members for analysis. Members were predominately female (48,979/59,686, 82.06%) with an average age of 50 years (SD 12.6). The average starting weight was 90.2 kg (SD 19.7), and over half of all members (34,195/59,688, 57.29%) were classified as obese. At week 12, 94.56% (56,438/59,686) of the members had a paid program membership, which decreased to 41.48% (24,756/59,686) at 24 weeks. At week 12, 52.03% (29,115/55,958) of the remaining members were actively using the platform, and by week 24, 26.59% (14,880/55,958) were using the platform. The average weight loss for all members was 2.8 kg or 3.1% of their starting body weight. Stayers lost 4.9 kg (5.3% of starting body weight) compared to starters, who lost 1.6 kg (1.7% of starting body weight). Almost half (11,082/22,658, 48.91%) the members who stayed on the program lost 5% or more of their starting body weight, and 15.48% (3507/22,658) achieved a weight loss of 10% or more. Of the members who were classified as class 1 obese when they joined the program, 41.39% (3065/7405) who stayed on the program were no longer classified as obese at the end, and across all categories of obesity, 24% (3180/13,319) were no longer classified as obese at the end of the program. Based on multiple linear regression, platform usage was the strongest predictor of weight loss (β=.263; P<.001), with higher usage associated with greater weight loss.

CONCLUSIONS

This comprehensive evaluation of a commercial, online weight loss program showed that it was effective for weight loss, particularly for members who finished the program and were active in using the platform and tools provided. If the results demonstrated here can be achieved at an even greater scale, the potential social and economic benefits will be extremely significant.

Patterns of self-monitoring technology use and weight loss in people with overweight or obesity

Mobile applications and paired devices allow individuals to self-monitor physical activity, dietary intake, and weight fluctuation concurrently. However, little is known regarding patterns of use of these self-monitoring technologies over time and their implications for weight loss. The objectives of this study were to identify distinct patterns of self-monitoring technology use and to investigate the associations between these patterns and weight change. We analyzed data from a 6-month weight loss intervention for school district employees with overweight or obesity (N = 225). We performed repeated measures latent profile analysis (RMLPA) to identify common patterns of self-monitoring technology use and used multiple linear regression to evaluate the relationship between self-monitoring technology use and weight change. RMLPA revealed four distinct profiles: minimal users (n = 65, 29% of sample), activity trackers (n = 124, 55%), dedicated all-around users (n = 25, 11%), and dedicated all-around users with exceptional food logging (n = 11, 5%). The dedicated all-around users with exceptional food logging lost the most weight (X2[1,225] = 5.27, p = .0217). Multiple linear regression revealed that, adjusting for covariates, only percentage of days of wireless weight scale use (B = -0.05, t(212) = -3.79, p < .001) was independently associated with weight loss. We identified distinct patterns in mHealth self-monitoring technology use for tracking weight loss behaviors. Self-monitoring of weight was most consistently linked to weight loss, while exceptional food logging characterized the group with the greatest weight loss. Weight loss interventions should promote self-monitoring of weight and consider encouraging food logging to individuals who have demonstrated consistent use of self-monitoring technologies.

Components of Culturally Tailored Interventions: A Discussion Paper

The purpose of this article is to propose essential components of culturally tailored interventions through analyzing practical issues in 3 studies that tested culturally tailored interventions among Asian American women. Practical issues in the studies were analyzed using a content analysis according to the evaluation criteria for rigor in cross-cultural research. Seven essential components of culturally tailored interventions were identified through the analysis: (a) respecting cultural uniqueness; (b) understanding cultural contexts; (c) using cultural examples; (d) having flexibility; (e) adopting multiple languages; (f) having bilingual and/or culturally matched research team members; and (g) engaging community consultants and research participants. Key words: Asian, culture, intervention, issue, rigor.

Patient use of a self-monitoring app during eating disorder treatment: Naturalistic longitudinal cohort study

OBJECTIVE

To explore patients' use of the self-monitoring app Recovery Record during 26 weeks of naturalistic eating disorder treatment.

METHODS

Selected patient characteristics at baseline were explored as predictors of app use using linear regression. Patients were grouped according to diagnosis (anorexia versus bulimia), and mixed-effects analyses were used to explore differences in app use between diagnoses across four time periods (weeks 1-4; weeks 5-8; weeks 9-12; weeks 13-26).

RESULTS

Eighty-four patients were included of which 41 had anorexia and 43 had bulimia. The total number of logs varied greatly (mean (SD): 592 (628.50)), and patient app activity almost ceased at week 13. Increasing age and no previous eating disorder treatment predicted increased app activity (p = .007; p = .039, respectively). Patients with anorexia logged over four times more often than patients with bulimia in the last time period (median (CI): 4.27 (1.28;14.31); p = .018). Time predicted declining app use (all p ≤ .007).

CONCLUSION

Future research on long-term app engagement should investigate associations between patients' app use and changes in their eating disorder symptom severity over time.

A Remote Nutritional Intervention to Change the Dietary Habits of Patients Undergoing Ablation of Atrial Fibrillation: Randomized Controlled Trial

BACKGROUND

The Prevention With Mediterranean Diet (PREDIMED) trial supported the effectiveness of a nutritional intervention conducted by a dietitian to prevent cardiovascular disease. However, the effect of a remote intervention to follow the Mediterranean diet has been less explored.

OBJECTIVE

This study aims to assess the effectiveness of a remotely provided Mediterranean diet-based nutritional intervention in obtaining favorable dietary changes in the context of a secondary prevention trial of atrial fibrillation (AF).

METHODS

The PREvention of recurrent arrhythmias with Mediterranean diet (PREDIMAR) study is a 2-year multicenter, randomized, controlled, single-blinded trial to assess the effect of the Mediterranean diet enriched with extra virgin olive oil (EVOO) on the prevention of atrial tachyarrhythmia recurrence after catheter ablation. Participants in sinus rhythm after ablation were randomly assigned to an intervention group (Mediterranean diet enriched with EVOO) or a control group (usual clinical care). The remote nutritional intervention included phone contacts (1 per 3 months) and web-based interventions with provision of dietary recommendations, and participants had access to a web page, a mobile app, and printed resources. The information is divided into 6 areas: Recommended foods, Menus, News and Online resources, Practical tips, Mediterranean diet classroom, and Your personal experience. At baseline and at 1-year and 2-year follow-up, the 14-item Mediterranean Diet Adherence Screener (MEDAS) questionnaire and a semiquantitative food frequency questionnaire were collected by a dietitian by phone.

RESULTS

A total of 720 subjects were randomized (365 to the intervention group, 355 to the control group). Up to September 2020, 560 subjects completed the first year (560/574, retention rate 95.6%) and 304 completed the second year (304/322, retention rate 94.4%) of the intervention. After 24 months of follow-up, increased adherence to the Mediterranean diet was observed in both groups, but the improvement was significantly higher in the intervention group than in the control group (net between-group difference: 1.8 points in the MEDAS questionnaire (95% CI 1.4-2.2; P<.001). Compared with the control group, the Mediterranean diet intervention group showed a significant increase in the consumption of fruits (P<.001), olive oil (P<.001), whole grain cereals (P=.002), pulses (P<.001), nuts (P<.001), white fish (P<.001), fatty fish (P<.001), and white meat (P=.007), and a significant reduction in refined cereals (P<.001), red and processed meat (P<.001), and sweets (P<.001) at 2 years of intervention. In terms of nutrients, the intervention group significantly increased their intake of omega-3 (P<.001) and fiber (P<.001), and they decreased their intake of carbohydrates (P=.02) and saturated fatty acids (P<.001) compared with the control group.

CONCLUSIONS

The remote nutritional intervention using a website and phone calls seems to be effective in increasing adherence to the Mediterranean diet pattern among AF patients treated with catheter ablation.

TRIAL REGISTRATION

ClinicalTrials.gov NCT03053843; https://www.clinicaltrials.gov/ct2/show/NCT03053843.

Effect of an Online Weight Management Program Integrated With Population Health Management on Weight Change: A Randomized Clinical Trial

IMPORTANCE

Online programs may help with weight loss but have not been widely implemented in routine primary care.

OBJECTIVE

To compare the effectiveness of a combined intervention, including an online weight management program plus population health management, with the online program only and with usual care.

DESIGN, SETTING, AND PARTICIPANTS

Cluster randomized trial with enrollment from July 19, 2016, through August 10, 2017, at 15 primary care practices in the US. Eligible participants had a scheduled primary care visit and were aged 20 to 70 years, had a body mass index between 27 and less than 40, and had a diagnosis of hypertension or type 2 diabetes. Follow-up ended on May 8, 2019.

INTERVENTIONS

Participants in the usual care group (n = 326) were mailed general information about weight management. Participants in the online program only group (n = 216) and the combined intervention group (n = 298) were registered for the online program. The participants in the combined intervention group also received weight-related population health management, which included additional support from nonclinical staff who monitored their progress in the online program and conducted periodic outreach.

MAIN OUTCOMES AND MEASURES

The primary outcome was weight change at 12 months based on measured weights recorded in the electronic health record. Weight change at 18 months was a secondary outcome.

RESULTS

Among the 840 participants who enrolled (mean age, 59.3 years [SD, 8.6 years]; 60% female; 76.8% White), 732 (87.1%) had a recorded weight at 12 months and the missing weights for the remaining participants were imputed. There was a significant difference in weight change at 12 months by group with a mean weight change of -1.2 kg (95% CI, -2.1 to -0.3 kg) in the usual care group, -1.9 kg (95% CI, -2.6 to -1.1 kg) in the online program only group, and -3.1 kg (95% CI, -3.7 to -2.5 kg) in the combined intervention group (P < .001). The difference in weight change between the combined intervention group and the usual care group was -1.9 kg (97.5% CI, -2.9 to -0.9 kg; P < .001) and the difference between the combined intervention group and the online program only group was -1.2 kg (95% CI, -2.2 to -0.3 kg; P = .01). At 18 months, the mean weight change was -1.9 kg (95% CI, -2.8 to -1.0 kg) in the usual care group, -1.1 kg (95% CI, -2.0 to -0.3 kg) in the online program only group, and -2.8 kg (95% CI, -3.5 to -2.0 kg) in the combined intervention group (P < .001).

CONCLUSIONS AND RELEVANCE

Among primary care patients with overweight or obesity and hypertension or type 2 diabetes, combining population health management with an online program resulted in a small but statistically significant greater weight loss at 12 months compared with usual care or the online program only. Further research is needed to understand the generalizability, scalability, and durability of these findings.

TRIAL REGISTRATION

ClinicalTrials.gov Identifier: NCT02656693.

The Preliminary Efficacy of a Technology-Based Cancer Pain Management Program Among Asian American Breast Cancer Survivors

With few existing technology-based programs to support cancer pain management, the need for culturally tailored programs to support ethnic minority cancer survivors has been highlighted. The purpose of this study was to explore the preliminary efficacy of the technology-based CAncer Pain management support Program for Asian American survivors of breast cancer, a technology-based cancer pain management program, in improving the cancer pain experience of Asian American breast cancer survivors. This pilot study adopted a randomized repeated-measures pretest/posttest control group design with a sample of 94 Asian American breast cancer survivors. Study measures included the Brief Pain Inventory-Short Form, Support Care Needs Survey-34 Short Form, and Mishel Uncertainty in Illness Scale-Community. Data were analyzed using descriptive and inferential statistics including repeated-measures analysis of covariance. Although there were no significant differences in pain, there were significant changes in perceived isolation (F = 9.937, P < .01), personal resources (F = 6.612, P < .05), support care need (F = 8.299, P < .01), and degree of uncertainty (F = 8.722, P < .01) in the intervention group from pretest to posttest. These findings support the positive effects of CAncer Pain management support Program for Asian American survivors of breast cancer on the cancer pain experience of Asian American breast cancer survivors.

Efficacy of a Multi-component m-Health Weight-loss Intervention in Overweight and Obese Adults: A Randomised Controlled Trial

BACKGROUND

This study compared the efficacy of two multi-component m-health interventions with a wait-list control group on body weight (primary outcome), and secondary outcomes of cardiovascular risk factors, lifestyle behaviours, and mental health.

METHODS

Three-arm randomised controlled trial (Enhanced: physical activity, diet, sleep, Traditional: physical activity, diet, Control) with assessments conducted at baseline, 6 and 12 months. Participants (n = 116) were overweight or obese adults aged 19-65 (M = 44.5 [SD = 10.5]). The 6-month intervention was delivered via a smartphone app providing educational materials, goal-setting, self-monitoring and feedback, and also included one face-to-face dietary consultation, a Fitbit and scales. The trial was prospectively registered and conducted between May 2017 and September 2018. Group differences on primary and secondary outcomes were examined between the Pooled Intervention groups (Pooled Intervention = Enhanced and Traditional) and Control groups, and then between Enhanced and Traditional groups.

RESULTS

Nineteen participants (16.4%) formally withdrew from the trial. Compared with the Control group, average body weight of the Pooled Intervention group did not differ at 6 (between-group difference = -0.92, (95% CI -3.33, 1.48)) or 12 months (0.00, (95% CI -2.62, 2.62)). Compared with the Control group, the Pooled Intervention group significantly increased resistance training (OR = 7.83, (95% CI 1.08, 56.63)) and reduced energy intake at 6 months (-1037.03, (-2028.84, -45.22)), and improved insomnia symptoms at 12 months (-2.59, (-4.79, -0.39)). Compared with the Traditional group, the Enhanced group had increased waist circumferences (2.69, (0.20, 5.18)) and sedentary time at 6 months (105.66, (30.83, 180.48)), and improved bed time variability at 12 months (-1.08, (-1.86, -0.29)). No other significant differences were observed between groups.

CONCLUSIONS

Relative to Controls, the Pooled Intervention groups did not differ on body weight but improved resistance training, and reduced energy intake and insomnia symptom severity. No additional weight loss was apparent when targeting improvements in physical activity, diet and sleep in combination compared with physical activity and diet.

Effects of food-related behavioral activation therapy on eating styles, diet quality and body weight change: Results from the MooDFOOD Randomized Clinical Trial

OBJECTIVE

Depression and obesity are bi-directionally related, eating styles and diet quality are two important factors associated with both. It remains uncertain if and how these two factors can be modified. Therefore the current study aims to investigate whether food-related behavioral activation therapy (F-BA), targeting mood, dietary habits and food related behavior, can improve eating styles, and diet quality and reduce body weight in adults with overweight or obesity and subsyndromal depressive symptoms.

METHODS

Data were derived from the MooDFOOD prevention trial, a 2x2 factorial RCT investigating the effect of nutritional strategies on prevention of depression. Changes in emotional, uncontrolled, and cognitive restrained eating (Three Factor Eating Questionnaire Revised), Mediterranean Diet Score (MDS), and body weight were analyzed among 1025 adults who either received F-BA or no intervention for 12 months. Intervention effect was tested by longitudinal analysis of covariance using mixed model analysis.

RESULTS

The F-BA group showed a small decrease in emotional (β=-5.68, p<.001) and uncontrolled eating (β=-4.05, p=.03), and increase in cognitive restrained eating (β=5.53, p<.01), compared to no F-BA. The effect of the F-BA therapy on emotional and uncontrolled eating was stronger in those with higher baseline depressive symptoms (IDS-SR). The F-BA did also lead to small improvements in MDS (β=1.95, p<.001), but not to change in body weight.

CONCLUSION

Our trial showed no reduction in bodyweight, but provides support for the possibility to improve both unhealthy eating styles and diet quality using an intervention targeting these specifically, although effects were small [Trial registration: clinicaltrials.gov NCT02529423].

Feasibility of a stratified blended physiotherapy intervention for patients with non-specific low back pain: a mixed methods study

INTRODUCTION

Integrating web-based or mobile components and face-to-face components within a treatment process is called blended care. As part of the participatory development of a blended physiotherapeutic intervention for patients with low back pain (e-Exercise LBP), a proof of concept study was carried out and showed promising results.

OBJECTIVE

To investigate the feasibility of the e-Exercise LBP prototype for patients and physiotherapists to improve the intervention.

METHODS

A mixed methods study was executed, embedded in the development phase of e-Exercise LBP. 21 physiotherapists treated 41 patients with e-Exercise LBP. Quantitative data consisted of: patients' satisfaction on a five-point Likert Scale; patients' and physiotherapists' experienced usability of the web-based application (System Usability Scale) and; patients' experiences with e-Exercise LBP (closed-ended questions and statements related to the elements and goals of e-Exercise LBP). Semi-structured interviews about experiences with e-Exercise LBP were conducted with seven patients and seven physiotherapists. Qualitative data were analyzed by a phenomenological approach. Quantitative data were analyzed with descriptive statistics.

RESULTS

Patients were satisfied with e-Exercise LBP (mean: 4.0; SD:0.8; range: extreme dissatisfaction (1)-extreme satisfaction (5)). Usability of the web-based application was acceptable (patients: mean: 73.2 (SD:16.3); physiotherapists: mean: 63.3 (SD:12.0); range: 0-100). Interviews revealed that physiotherapists' training is essential to successfully integrate the web-based application and face-to-face sessions within physiotherapy treatment. Also, patients addressed the need of reminder messages to support long-term (exercise) adherence.

CONCLUSION

e-Exercise LBP appeared to be feasible. However, various prerequisites and points of improvement were mentioned to improve physiotherapists' training and the prototype.

Angiotensin Converting Enzyme (ACE): A Marker for Personalized Feedback on Dieting

Angiotensin Converting Enzyme (ACE) expression and activity is associated with obesity. ACE is a circulating factor that predicts sustained weight loss over a time frame of months. Here, we evaluate whether ACE might also be an early marker (over a 24-hour period) for weight loss. 32 participants (78% females; BMI 28.47 ± 4.87kg/m2) followed a 1200KCal diet with an optional daily (<250KCal) snack and were asked to use an in-house generated health platform to provide recordings of food intake, physical activity and urine collection time and volume. Following a day of dieting, ACE levels in urine negatively correlated with weight loss (p = 0.015 ). This reduction in ACE levels was significantly more robust in individuals with a BMI > 25 (p = 0.0025 ). This study demonstrated that ACE levels correlate with BMI and weight loss as early as after 1 day of dieting, and thus ACE could be a potential early "biofeedback" marker for weight loss and diet efficiency.

Predictors of engagement and outcome achievement in a behavioural intervention targeting sugar-sweetened beverage intake among rural adults

OBJECTIVE

To describe relationships among baseline characteristics, engagement indicators and outcomes for rural participants enrolled in SIPsmartER, a behavioural intervention targeting sugar-sweetened beverage (SSB) intake.

DESIGN

A secondary data analysis. Bivariate analyses determined relationships among baseline characteristics (e.g. age, gender, race, education, income), engagement indicators (completion of 6-month health screening, class attendance, call completion) and SSB outcomes (SSB ounce reduction (i.e. US fluid ounces; 1 US fl. oz = 29·57 ml), reduced ≥12 ounces, achieved ≤8 ounce intake). Generalized linear models tested for significant effects of baseline characteristics on engagement indicators and of baseline characteristics and engagement indicators on SSB outcomes.

SETTING

South-west Virginia, USA, a rural, medically underserved region.

PARTICIPANTS

Participants' (n 155) mean age was 41 years; most were female (81 %), White (91 %) and earned ≤$US 20 000 per annum (61 %).

RESULTS

All final models were significant. Engagement models predicted 12-17 % of variance, with age being a significant predictor in all three models. SSB outcome models explained 5-70 % of variance. Number of classes attended was a significant predictor of SSB ounce reduction (β = -6·12, P < 0·01). Baseline SSB intake significantly predicted SSB ounce reduction (β = -0·90, P < 0·001) and achieved ≤8 ounce intake (β = 0·98, P < 0·05).

CONCLUSIONS

The study identifies several participant baseline characteristics that may impact engagement in and outcomes from a community-based intervention targeting SSB intake. Findings suggest greater attendance of SIPsmartER classes is associated with greater reduction in overall SSB intake; yet engagement variables did not predict other outcomes. Findings will inform the future implementation of SIPsmartER and research studies of similar design and intent.

Recruitment and retention of WIC participants in a longitudinal dietary intervention trial

BACKGROUND

This paper describes strategies and outcomes of techniques to recruit and retain low-income women served by the Special Supplemental Nutrition Program for Women, Infants, and Children (WIC) in a longitudinal dietary intervention trial.

METHODS

Community engagement strategies, methods to recruit and retain participants, and recruitment and retention rates are reported. Demographic and lifestyle predictors of loss to follow-up, contacts required to reach participants at each data collection point, participant reactions to the recruitment and retention strategies used, and reasons for drop out (assessed among those who discontinued their study involvement) also were examined.

RESULTS

Of 1281 eligible women, 744 were enrolled (58% recruitment rate); retention rates were 87%, 70%, and 55%, respectively, 2 weeks and 3 and 6 months post-intervention. Being unmarried, younger, and having low baseline vegetable intake predicted loss to follow-up. Between 4 and 5 contact attempts and 1 and 2 completed contacts were required to reach participants at each data collection point. Participants endorsed recruiting women while waiting for WIC appointments (as they were accessible, perceived the information provided as informative, and wanted to pass the time) and by word of mouth. Lacking time and loss of interest were commonly reported reasons for not completing assessments and dropout. To improve retention, shortening telephone assessments, conducting the assessments in person, and increasing the amount of incentives were recommended.

CONCLUSION

Despite using recommended strategies, recruitment and retention rates were modest. Research is needed to identify and test approaches to effectively engage WIC-enrolled adults in health intervention trials.

Improving Adherence to Smoking Cessation Treatment: Smoking Outcomes in a Web-based Randomized Trial

Background

Partial adherence in Internet smoking cessation interventions presents treatment and evaluation challenges. Increasing adherence may improve outcomes.

Purpose

To present smoking outcomes from an Internet randomized trial of two strategies to encourage adherence to tobacco dependence treatment components: (i) a social network (SN) strategy to integrate smokers into an online community and (ii) free nicotine replacement therapy (NRT). In addition to intent-to-treat analyses, we used novel statistical methods to distinguish the impact of treatment assignment from treatment utilization.

Methods

A total of 5,290 current smokers on a cessation website (WEB) were randomized to WEB, WEB + SN, WEB + NRT, or WEB + SN + NRT. The main outcome was 30-day point prevalence abstinence at 3 and 9 months post-randomization. Adherence measures included self-reported medication use (meds), and website metrics of skills training (sk) and community use (comm). Inverse Probability of Retention Weighting and Inverse Probability of Treatment Weighting jointly addressed dropout and treatment selection. Propensity weights were used to calculate Average Treatment effects on the Treated.

Results

Treatment assignment analyses showed no effects on abstinence for either adherence strategy. Abstinence rates were 25.7%-32.2% among participants that used all three treatment components (sk+comm +meds).Treatment utilization analyses revealed that among such participants, sk+comm+meds yielded large percentage point increases in 3-month abstinence rates over sk alone across arms: WEB = 20.6 (95% CI = 10.8, 30.4), WEB + SN = 19.2 (95% CI = 11.1, 27.3), WEB + NRT = 13.1 (95% CI = 4.1, 22.0), and WEB + SN + NRT = 20.0 (95% CI = 12.2, 27.7).

Conclusions

Novel propensity weighting approaches can serve as a model for establishing efficacy of Internet interventions and yield important insights about mechanisms.

Clinical Trials.gov

NCT01544153.

Barriers to participation in web-based and in-person weight management interventions for serious mental illness

OBJECTIVE

This study examines barriers to participation and retention in 2 modalities (web-based and in-person) of a weight-management intervention tailored for individuals with serious mental illness (SMI).

METHOD

Using a mixed-methods approach, we explored the barriers veterans with SMI face when participating in a web-based (WebMOVE) or in-person (MOVE-SMI) version of the same SMI-adapted MOVE weight-management program. Participants in the randomized controlled trial (n = 277) were recruited from specialty mental health clinics at a Veterans Affairs medical center. Barriers were analyzed across treatment condition and program attendance (engagement) at baseline and follow-up using a generalized lineal model. Post hoc analyses assessed whether changes in the trajectory of barriers over time were associated with engagement. A subsample of participants (n = 48) from the WebMOVE and MOVE-SMI treatment conditions completed a qualitative interview, and 2 coders used open coding to analyze the data.

RESULTS

Although barriers specific to treatment modality existed, most barriers cut across intervention modality, including financial hardship, lack of reliable housing and transportation, comorbid physical and mental health issues, and competing demands on personal time. Results of post hoc analyses found the association between engagement and emotional and motivational factors to be statistically significant.

CONCLUSIONS

This study is the 1st to identify barriers in a web-based intervention for SMI. Similar barriers persisted across treatment modalities. Known barriers, particularly socioeconomic barriers, should be addressed to improve engagement and retention of individuals in weight-management interventions adapted for SMI, irrespective of modality. (PsycINFO Database Record (c) 2019 APA, all rights reserved).

A loyalty scheme to encourage physical activity in office workers: a cluster RCT

Background

Increasing physical activity in the workplace can provide physical and mental health benefits for employees and economic benefits for the employer through reduced absenteeism and increased productivity. However, there is limited evidence on effective behaviour change interventions in workplace settings that led to maintained physical activity. This study aimed to address this gap and contribute to the evidence base for effective and cost-effective workplace interventions.

Objectives

To determine the effectiveness and cost-effectiveness of the Physical Activity Loyalty scheme, a multicomponent intervention based on concepts similar to those that underpin a high-street loyalty card, which was aimed at encouraging habitual physical activity behaviour and maintaining increases in mean number of steps per day.

Design

A cluster randomised controlled trial with an embedded economic evaluation, behavioural economic experiments, mediation analyses and process evaluation.

Setting

Office-based employees from public sector organisations in Belfast and Lisburn city centres in Northern Ireland.

Participants

A total of 853 participants [mean age 43.6 years (standard deviation 9.6 years); 71% of participants were female] were randomly allocated by cluster to either the intervention group or the (waiting list) control group.

Intervention

The 6-month intervention consisted of financial incentives (retail vouchers), feedback and other evidence-based behaviour change techniques. Sensors situated in the vicinity of the workplaces allowed participants to monitor their accumulated minutes of physical activity.

Main outcome measures

The primary outcome was mean number of steps per day recorded using a sealed pedometer (Yamax Digiwalker CW-701; Yamax, Tasley, UK) worn on the waist for 7 consecutive days and at 6 and 12 months post intervention. Secondary outcomes included health, mental well-being, quality of life, work absenteeism and presenteeism, and the use of health-care resources.

Results

The mean number of steps per day were significantly lower for the intervention group than the control group [6990 mean number of steps per day (standard deviation 3078) vs. 7576 mean number of steps per day (standard deviation 3345), respectively], with an adjusted mean difference of –336 steps (95% confidence interval –612 to –60 steps; p = 0.02) at 6 months post baseline, but not significantly lower at 12 months post baseline. There was a small but significant enhancement of mental well-being in the intervention group (difference between groups for the Warwick–Edinburgh Mental Wellbeing Scale of 1.34 points, 95% confidence interval 0.48 to 2.20 points), but not for the other secondary outcomes. An economic evaluation suggested that, overall, the scheme was not cost-effective compared with no intervention. The intervention was £25.85 (95% confidence interval –£29.89 to £81.60) more costly per participant than no intervention and had no effect on quality-adjusted life-years (incremental quality-adjusted life-years –0.0000891, 95% confidence interval –0.008 to 0.008).

Limitations

Significant restructuring of participating organisations during the study resulted in lower than anticipated recruitment and retention rates. Technical issues affected intervention fidelity.

Conclusions

Overall, assignment to the intervention group resulted in a small but significant decline in the mean pedometer-measured steps per day at 6 months relative to baseline, compared with the waiting list control group. The Physical Activity Loyalty scheme was deemed not to be cost-effective compared with no intervention, primarily because no additional quality-adjusted life-years were gained through the intervention. Research to better understand the mechanisms of physical activity behaviour change maintenance will help the design of future interventions.

Trial registration

Current Controlled Trials ISRCTN17975376.

Funding

This project was funded by the National Institute for Health Research (NIHR) Public Health Research programme and will be published in full in Public Health Research; Vol. 7, No. 15. See the NIHR Journals Library website for further project information.

Using Mobile Health to Support Clinical Decision-Making to Improve Maternal and Neonatal Health Outcomes in Ghana: Insights of Frontline Health Worker Information Needs

BACKGROUND

Developing and maintaining resilient health systems in low-resource settings like Ghana requires innovative approaches that adapt technology to context to improve health outcomes. One such innovation was a mobile health (mHealth) clinical decision-making support system (mCDMSS) that utilized text messaging (short message service, SMS) of standard emergency maternal and neonatal protocols via an unstructured supplementary service data (USSD) on request of the health care providers. This mCDMSS was implemented in a cluster randomized controlled trial (CRCT) in the Eastern Region of Ghana.

OBJECTIVE

This study aimed to analyze the pattern of requests made to the USSD by health workers (HWs). We assessed the relationship between requests made to the USSD and types of maternal and neonatal morbidities reported in health facilities (HFs).

METHODS

For clusters in the intervention arm of the CRCT, all requests to the USSD during the 18-month intervention period were extracted from a remote server, and maternal and neonatal health outcomes of interest were obtained from the District Health Information System of Ghana. Chi-square and Fisher exact tests were used to compare the proportion and type of requests made to the USSD by cluster, facility type, and location; whether phones accessing the intervention were shared facility phones or individual-use phones (type-of-phone); or whether protocols were accessed during the day or at night (time-of-day). Trends in requests made were analyzed over 3 6-month periods. The relationship between requests made and the number of cases reported in HFs was assessed using Spearman correlation.

RESULTS

In total, 5329 requests from 72 (97%) participating HFs were made to the intervention. The average number of requests made per cluster was 667. Requests declined from the first to the third 6-month period (44.96% [2396/5329], 39.82% [2122/5329], and 15.22% [811/5329], respectively). Maternal conditions accounted for the majority of requests made (66.35% [3536/5329]). The most frequently accessed maternal conditions were postpartum hemorrhage (25.23% [892/3536]), other conditions (17.82% [630/3536]), and hypertension (16.49% [583/3536]), whereas the most frequently accessed neonatal conditions were prematurity (20.08% [360/1793]), sepsis (15.45% [277/1793]), and resuscitation (13.78% [247/1793]). Requests made to the mCDMSS varied significantly by cluster, type of request (maternal or neonatal), facility type and its location, type-of-phone, and time-of-day at 6-month interval (P<.001 for each variable). Trends in maternal and neonatal requests showed varying significance over each 6-month interval. Only asphyxia and sepsis cases showed significant correlations with the number of requests made (r=0.44 and r=0.79; P<.001 and P=.03, respectively).

CONCLUSIONS

There were variations in the pattern of requests made to the mCDMSS over time. Detailed information regarding the use of the mCDMSS provides insight into the information needs of HWs for decision-making and an opportunity to focus support for HW training and ultimately improved maternal and neonatal health.

Predicting Outcomes from Engagement With Specific Components of an Internet-Based Physical Activity Intervention With Financial Incentives: Process Analysis of a Cluster Randomized Controlled Trial

Background

Investigating participant engagement and nonusage attrition can help identify the likely active ingredients of electronic health interventions. Research on engagement can identify which intervention components predict health outcomes. Research on nonusage attrition is important to make recommendations for retaining participants in future studies.

Objective

This study aimed to investigate engagement and nonusage attrition in the Physical Activity Loyalty (PAL) scheme, a 6-month complex physical activity intervention in workplaces in Northern Ireland. The intervention included financial incentives with reward redemption and self-regulation techniques. Specific objectives were (1) to determine whether engagement in specific intervention components predicted physical activity at 6 months, (2) to determine whether engagement in specific intervention components predicted targeted mediators at 6 months, and (3) to investigate predictors of nonusage attrition for participants recording daily activity via the PAL scheme physical activity monitoring system and logging onto the website.

Methods

Physical activity was assessed at baseline and 6 months using pedometers (Yamax Digiwalker CW-701, Japan). Markers of engagement and website use, monitoring system use, and reward redemption were collected throughout the scheme. Random-effects generalized least-squares regressions determined whether engagement with specific intervention components predicted 6-month physical activity and mediators. Cox proportional hazards regressions were used to investigate predictors of nonusage attrition (days until first 2-week lapse).

Results

A multivariable generalized least-squares regression model (n=230) showed that the frequency of hits on the website’s monitoring and feedback component (regression coefficient [b]=50.2; SE=24.5; P=.04) and the percentage of earned points redeemed for financial incentives (b=9.1; SE=3.3; P=.005) were positively related to 6-month pedometer steps per day. The frequency of hits on the discussion forum (b=−69.3; SE=26.6; P=.009) was negatively related to 6-month pedometer steps per day. Reward redemption was not related to levels of more internal forms of motivation. Multivariable Cox proportional hazards regression models identified several baseline predictors associated with nonusage attrition. These included identified regulation (hazard ratio [HR] 0.88, 95% CI 0.81-0.97), recovery self-efficacy (HR 0.88, 95% CI 0.80-0.98), and perceived workplace environment safety (HR 1.07, 95% CI 1.02-1.11) for using the physical activity monitoring system. The EuroQoL health index (HR 0.33, 95% CI 0.12-0.91), financial motivation (HR 0.93, 95% CI 0.87-0.99), and perceived availability of physical activity opportunities in the workplace environment (HR 0.96, 95% CI 0.93-0.99) were associated with website nonusage attrition.

Conclusions

Our results provide evidence opposing one of the main hypotheses of self-determination theory by showing that financial rewards are not necessarily associated with decreases in more internal forms of motivation when offered as part of a complex multicomponent intervention. Identifying baseline predictors of nonusage attrition can help researchers to develop strategies to ensure maximum intervention adherence.

Trial Registration

ISRCTN Registry ISRCTN17975376; http://www.isrctn.com/ISRCTN17975376 (Archived by WebCite at http://www.webcitation.org/76VGZsZug)

Internet-based aftercare for women with bulimia nervosa following inpatient treatment: The role of adherence

Facing poor long-term outcome and high relapse rates in the treatment of bulimia nervosa, we developed an Internet-based aftercare program for women with severe and chronic bulimia nervosa following inpatient treatment based on previous experiences with self-directed targeted prevention and early intervention programs delivered online. The aim of the present study was to examine adherence to the program in detail, to explore potential variables that predict adherence and to analyze whether adherence affects outcomes. We analyzed data from 126 women in the intervention group of a randomized controlled trial. 107 women (85%) logged on to the program platform at least once. These women opened on average 42.8% (SD = 31.9%) of all assigned program pages. Adherence declined during the course of the intervention. Adherence was not associated with the number of outpatient treatment sessions received during the intervention period. Adherence was not related to overall illness severity or duration at baseline. However, excessive exercise at hospital discharge (which may be a sign of insufficient motivation to change eating disorder related behaviors) seems to play some small role in adherence. Adherence did not affect intervention outcomes. Based on our findings, we would like to advocate further research on online aftercare interventions for women with severe and chronic bulimia nervosa.

Factors associated with early dropout in an employer-based commercial weight-loss program

OBJECTIVE

Minimizing program dropout is essential for weight-loss success, but factors that influence dropout among commercial programs are unclear. This study's objective was to determine factors associated with early dropout in a commercial weight-loss program.

METHODS

A retrospective analysis of a remotely delivered, employer-based commercial program from 2013 to 2016 was conducted. The dependent variable was 'early dropout', defined as enrollees who disengaged from telephone coaching by month 2's end. Independent variables included demographics, program website engagement and early weight change. Multivariate logistic regression analyses were used to assess for differences in early dropout by several factors, adjusted for employer clustering.

RESULTS

Of the 5,274 participants, 26.8% dropped out early. Having ≥1 chronic condition (odds ratio [OR] 1.41, p < 0.001) and 'weight-loss failure' defined as ≥0% weight change at month 1's end (OR 1.86, p < 0.001) had significantly increased odds of early dropout. Increasing age by 10-year intervals (OR 0.90, p = 0.002) and 'meeting the website login goal' defined as ≥90 logins in 3 months (OR 0.13, p < 0.001) significantly decreased the odds of early dropout.

CONCLUSIONS

Presence of comorbidities, less online engagement and weight-loss failure were associated with early dropout in a commercial program. Strategies to prevent dropout among high-risk participants, such as increased support or program tailoring, should be developed and tested.

A Behavior-Modification, Clinical-Grade Mobile Application to Improve Breast Cancer Survivors' Accountability and Health Outcomes

PURPOSE

Only 34% of breast cancer survivors engage in the recommended level of physical activity because of a lack of accountability and motivation. Methodist Hospital Cancer Health Application (MOCHA) is a smartphone tool created specifically for self-reinforcement for patients with cancer through the daily accounting of activity and nutrition and direct interaction with clinical dietitians. We hypothesize that use of MOCHA will improve the accountability of breast cancer survivors and help them reach their personalized goals.

PATIENTS AND METHODS

Women with stages I to III breast cancer who were at least 6 months post-active treatment with a body mass index (BMI) greater than 25 kg/m2 were enrolled in a 4-week feasibility trial. The primary objective was to demonstrate adherence during weeks 2 and 3 of the 4-week study period (14 days total). The secondary objective was to determine the usability of MOCHA according to the system usability scale. The exploratory objective was to determine weight loss and dietitian-participant interaction.

RESULTS

We enrolled 33 breast cancer survivors who had an average BMI of 31.6 kg/m2. Twenty-five survivors completed the study, and the average number of daily uses was approximately 3.5 (range, 0 to 12) times/day; participants lost an average of 2 lbs (+4 lbs to -10.6 lbs). The average score of usability (the second objective) was 77.4, which was greater than the acceptable level. More than 90% of patients found MOCHA easy to navigate, and 84% were motivated to use MOCHA daily.

CONCLUSION

This study emphasizes the importance of technology use to improve goal adherence for patients by providing real-time feedback and accountability with the health care team. MOCHA focuses on the engagement of the health care team and is integrated into clinical workflow. Future directions will use MOCHA in a long-term behavior modification study.

What to Consider in a Culturally Tailored Technology-Based Intervention?

The purpose of this article is to identify practical issues in implementing a culturally tailored technology-based intervention among Asian American survivors of breast cancer. In a large-scale technology-based breast cancer intervention study, research team members wrote memos on issues in implementing a culturally tailored technology-based intervention and plausible reasons for the issues. Then, the content of the research diaries was analyzed, along with written records of the research team. The practical issues found in the research process included those related to (1) technology literacy and preferences; (2) language issues; (3) cultural attitudes, beliefs, and values; (4) intervention staff competence; (5) security and confidentiality issues; and (6) time and geographical constraints. Based on the issues, several recommendations are proposed for future research using culturally tailored technology-based interventions among racial and ethnic minorities.

Development of a Mobile Clinical Prediction Tool to Estimate Future Depression Severity and Guide Treatment in Primary Care: User-Centered Design

Background

Around the world, depression is both under- and overtreated. The diamond clinical prediction tool was developed to assist with appropriate treatment allocation by estimating the 3-month prognosis among people with current depressive symptoms. Delivering clinical prediction tools in a way that will enhance their uptake in routine clinical practice remains challenging; however, mobile apps show promise in this respect. To increase the likelihood that an app-delivered clinical prediction tool can be successfully incorporated into clinical practice, it is important to involve end users in the app design process.

Objective

The aim of the study was to maximize patient engagement in an app designed to improve treatment allocation for depression.

Methods

An iterative, user-centered design process was employed. Qualitative data were collected via 2 focus groups with a community sample (n=17) and 7 semistructured interviews with people with depressive symptoms. The results of the focus groups and interviews were used by the computer engineering team to modify subsequent protoypes of the app.

Results

Iterative development resulted in 3 prototypes and a final app. The areas requiring the most substantial changes following end-user input were related to the iconography used and the way that feedback was provided. In particular, communicating risk of future depressive symptoms proved difficult; these messages were consistently misinterpreted and negatively viewed and were ultimately removed. All participants felt positively about seeing their results summarized after completion of the clinical prediction tool, but there was a need for a personalized treatment recommendation made in conjunction with a consultation with a health professional.

Conclusions

User-centered design led to valuable improvements in the content and design of an app designed to improve allocation of and engagement in depression treatment. Iterative design allowed us to develop a tool that allows users to feel hope, engage in self-reflection, and motivate them to treatment. The tool is currently being evaluated in a randomized controlled trial.

Incorporating a Static Versus Supportive Mobile Phone App Into a Partial Meal Replacement Program With Face-to-Face Support: Randomized Controlled Trial

Background

Mobile phone apps may be acceptable to users and could improve retention and adherence over more traditional methods, but there is mixed literature supporting their efficacy. In the weight management space, very little is known about how a mobile phone app integrating features beyond text messaging (short message service) can affect behavior, particularly when combined with face-to-face support.

Objective

The objective of this study was to examine the effectiveness of a mobile phone app when combined with a partial meal replacement program including face-to-face support. This paper compares a static versus supportive app over a 6-month randomized trial for effects on weight loss, weight-related biomarkers, and psychological outcomes.

Methods

Overweight and obese adults (71.2% female, 104/146; mean 48.11, SD 11.75 years) were recruited to participate in the weight loss study, and they were randomized on a 1:1 basis using a computer algorithm. The supportive app (n=75) provided information, food intake recording, rewards, prompts for regular interaction through reminders, and the opportunity to review personal compliance with the dietary program. The static app (n=71) included only recipes and weight loss information. Both groups recieved equal amounts of face-to-face support in addition to app.

Results

The overall reduction in app usage over 24 weeks was lower for the supportive app in comparison with the static app; approximately 39.0% (57/146) of the users were still using the app at week 24. Despite the promising results for app usage, there were no differences in weight loss between groups (F1,128.12=0.83, P=.36). However, it should be noted that almost 60% (49/84) of all participants lost 5% or more of body weight during the trial. No weight-related biomarkers were significantly different between groups. Both groups experienced an increase in positive mood, but this was significantly higher for those who received the static app (F1,118.12=4.93, P=.03).

Conclusions

Although the supportive app was well received by users, we found little evidence of the added benefit of this versus the static app in combination with face-to-face support in a community-delivered weight loss program. Future versions of the app may incorporate more unique behavioral techniques beyond those provided by the consultant to improve the potency of the app.

Trial Registration

Australian New Zealand Clinical Trials Registry ACTRN12613000547741; https://www.anzctr.org.au/Trial/Registration/TrialReview.aspx?id=364187 (Archived by WebCite http://www.webcitation.org/6yivwfMI9)

Wishes and preferences for an online lifestyle program for brain health-A mixed methods study

Introduction

Individuals with subjective cognitive decline (SCD) are at increased risk of Alzheimer's disease and could benefit from a prevention strategy targeting lifestyle factors. Making a program available through the Internet gives a widespread reach at low cost, but suboptimal adherence is a major threat to effectiveness. As a first step in developing an online lifestyle program (OLP), we aimed to identify factors that are barriers and/or facilitators for the use of an OLP in individuals with SCD in three European countries.

Methods

As part of the Euro-SCD project, SCD subjects were recruited at memory clinics in the Netherlands, Germany, and Spain. We combined quantitative and qualitative methods, using a mixed methods approach. We conducted an online 18-item survey on the preferences of SCD patients for an OLP (N = 238). In addition, we held semi-structured interviews (N = 22) to gain in-depth understanding of factors acting as a facilitator and/or barrier for intended use of an OLP. Audio recordings were transcribed verbatim. Content analysis was performed.

Results

One hundred seventy-six individuals completed the survey (response rate 74%). Almost all participants regularly use the Internet (97%). Participants reported trustworthiness (93%), user-friendliness (91%), and up-to-date information (88%) as main facilitators, whereas having contact with other users (26%), needing an account (21%), and assignments (16%) were reported as barriers. Barriers differed slightly between countries, but facilitators were largely similar. In-depth interviews revealed that both program characteristics (e.g., trustworthiness, user-friendliness, and personalization) and personal factors (e.g., expectancy to receive negative feedback) are likely to influence the intended use of an OLP.

Discussion

Involving users provided in-depth understanding of factors associated with the intended use of an OLP for brain health. Both program characteristics and personal factors are likely to influence the use of an OLP. Based on this input from the end-users, we will develop an OLP for individuals with SCD.

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Almost all participants believe that healthy lifestyle contributes to brain health.

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Almost all participants use the Internet daily, on all types of devices.

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Barriers or facilitators can be program characteristics as well as personal factors.

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Trustworthiness, user-friendliness, and personalization are important facilitators.

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One online lifestyle program for different European countries seems feasible.

Evaluation of a Computer-Tailored Healthy Ageing Intervention to Promote Physical Activity among Single Older Adults with a Chronic Disease

This study explores the effectiveness of the Active Plus65 intervention designed to stimulate physical activity among single older adults with a chronic physical impairment. A quasi-experimental pre-test post-test study was performed. The intervention group (n = 411; mean age = 76.75; SD = 7.75) was assessed at baseline, three months, and six months. Data of comparable older adults who completed the original Active Plus intervention served as reference group (n = 87; mean age = 74.36; SD = 6.26). Multilevel regression analyses were applied: outcome measures were weekly minutes of moderate to vigorous physical activity (MVPA) and days per week with at least 30 minutes of MVPA. Although Active Plus65 did not outperform the original intervention, in itself Active Plus65 effectuated a significant increase in the weekly minutes of MVPA (B = 208.26; p < 0.001; Effect Size (ES) = 0.45) and in the days per week with sufficient MVPA (B = 1.20; p < 0.001; ES = 0.61) after three months. After six months, it effectuated a significant increase in the days per week with sufficient MVPA (B = 0.67; p = 0.001; ES = 0.34) but not for the weekly minutes of MVPA (p = 0.745). As Active Plus65 increased MVPA at three months with a higher ES than average interventions for this vulnerable target group, it potentially makes an interesting intervention. Further development should focus on long-term maintenance of effects.

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.

An Overview of Factors Associated with Adherence to Lifestyle Modification Programs for Weight Management in Adults

This review aims to provide an overview of the factors associated with adherence reported in existing literature on lifestyle modification programs for weight management among the adult population. An electronic search was performed using PubMed, Medline, PsycINFO and PsycARTICLE to identify studies that examined the factors of adherence to lifestyle modification programs with explicit definition of adherence indicators. We identified 19 studies published between 2004 and 2016. The most commonly used indicator of adherence was attrition, followed by attendance, self-monitoring and dietary adherence. A broad array of factors has been studied but only few studies exploring each factor. Limited evidence suggested older age, higher education, healthier eating and physical activity behaviours, higher stage of change at baseline and higher initial weight loss may predict better adherence. On the other hand, having depression, stress, strong body shape concern, more previous weight loss attempts and being unemployed may predict poor adherence. Inconsistent findings were obtained for self-efficacy, motivation and male gender. This review highlights the need for more rigorous studies to enhance our knowledge on factors related to adherence. Identification of the factors of adherence could provide important implication for program improvement, ultimately improving the effectiveness and the cost-effectiveness of lifestyle modification program.

A Self-Regulation-Based eHealth Intervention to Promote a Healthy Lifestyle: Investigating User and Website Characteristics Related to Attrition

BACKGROUND

eHealth interventions can reach large populations and are effective in increasing physical activity (PA) and fruit and vegetable intake. Nevertheless, the effects of eHealth interventions are overshadowed by high attrition rates. Examining more closely when users decide to leave the intervention can help eHealth developers to make informed decisions about which intervention components should be reshaped or simply removed. Investigating which users are more likely to quit an intervention can inform developers about whether and how their intervention should be adapted to specific subgroups of users.

OBJECTIVE

This study investigated the pattern of attrition in a Web-based intervention to increase PA, fruit, and vegetable intake. The first aim was to describe attrition rates according to different self-regulation components. A second aim was to investigate whether certain user characteristics are predictors for start session completion, returning to a follow-up session and intervention completion.

METHODS

The sample consisted of 549 adults who participated in an online intervention, based on self-regulation theory, to promote PA and fruit and vegetable intake, called "MyPlan 1.0." Using descriptive analysis, attrition was explored per self-regulation component (eg, action planning and coping planning). To identify which user characteristics predict completion, logistic regression analyses were conducted.

RESULTS

At the end of the intervention program, there was an attrition rate of 78.2% (330/422). Attrition rates were very similar for the different self-regulation components. However, attrition levels were higher for the fulfillment of questionnaires (eg, to generate tailored feedback) than for the more interactive components. The highest amount of attrition could be observed when people were asked to make their own action plan. There were no significant predictors for first session completion. Yet, two subgroups had a lower chance to complete the intervention, namely male users (OR: 2.24, 95% CI=1.23-4.08) and younger adults (OR: 1.02, 95% CI=1.00-1.04). Furthermore, younger adults were less likely to return to the website for the first follow-up after one week (OR: 1.03, 95% CI=1.01-1.04).

CONCLUSIONS

This study informs us that eHealth interventions should avoid the use of extensive questionnaires and that users should be provided with a rationale for several components (eg, making an action plan and completing questions). Furthermore, future interventions should focus first on motivating users for the behavior change before guiding them through action planning. Though, this study provides no evidence for removal of one of the self-regulation techniques based on attrition rates. Finally, strong efforts are needed to motivate male users and younger adults to complete eHealth interventions.

Assessing User Engagement of an mHealth Intervention: Development and Implementation of the Growing Healthy App Engagement Index

BACKGROUND

Childhood obesity is an ongoing problem in developed countries that needs targeted prevention in the youngest age groups. Children in socioeconomically disadvantaged families are most at risk. Mobile health (mHealth) interventions offer a potential route to target these families because of its relatively low cost and high reach. The Growing healthy program was developed to provide evidence-based information on infant feeding from birth to 9 months via app or website. Understanding user engagement with these media is vital to developing successful interventions. Engagement is a complex, multifactorial concept that needs to move beyond simple metrics.

OBJECTIVE

The aim of our study was to describe the development of an engagement index (EI) to monitor participant interaction with the Growing healthy app. The index included a number of subindices and cut-points to categorize engagement.

METHODS

The Growing program was a feasibility study in which 300 mother-infant dyads were provided with an app which included 3 push notifications that was sent each week. Growing healthy participants completed surveys at 3 time points: baseline (T1) (infant age ≤3 months), infant aged 6 months (T2), and infant aged 9 months (T3). In addition, app usage data were captured from the app. The EI was adapted from the Web Analytics Demystified visitor EI. Our EI included 5 subindices: (1) click depth, (2) loyalty, (3) interaction, (4) recency, and (5) feedback. The overall EI summarized the subindices from date of registration through to 39 weeks (9 months) from the infant's date of birth. Basic descriptive data analysis was performed on the metrics and components of the EI as well as the final EI score. Group comparisons used t tests, analysis of variance (ANOVA), Mann-Whitney, Kruskal-Wallis, and Spearman correlation tests as appropriate. Consideration of independent variables associated with the EI score were modeled using linear regression models.

RESULTS

The overall EI mean score was 30.0% (SD 11.5%) with a range of 1.8% - 57.6%. The cut-points used for high engagement were scores greater than 37.1% and for poor engagement were scores less than 21.1%. Significant explanatory variables of the EI score included: parity (P=.005), system type including "app only" users or "both" app and email users (P<.001), recruitment method (P=.02), and baby age at recruitment (P=.005).

CONCLUSIONS

The EI provided a comprehensive understanding of participant behavior with the app over the 9-month period of the Growing healthy program. The use of the EI in this study demonstrates that rich and useful data can be collected and used to inform assessments of the strengths and weaknesses of the app and in turn inform future interventions.