Designing and applying technology for prevention-Lessons learned in AEQUIPA and its implications for future research and practice.

Almost all Western societies are facing the challenge that their population structure is changing very dynamically. Already in 2019, ten countries had a population share of at least 20 percent in the age group of 64 years and older. Today's society aims to improve population health and help older people live active and independent lives by developing, establishing, and promoting safe and effective interventions. Modern technological approaches offer tremendous opportunities but pose challenges when preventing functional decline. As part of the AEQUIPA Prevention Research Network, the use of technology to promote physical activity in older people over 65 years of age was investigated in different settings and from various interdisciplinary perspectives, including technology development and evaluation for older adults. We present our findings in three main areas: (a) design processes for developing technology interventions, (b) older adults as a user group, and (c) implications for the use of technology in interventions. We find that cross-cutting issues such as time and project management, supervision of participants, ethics, and interdisciplinary collaboration are of vital importance to the success of the work. The lessons learned are discussed based on the experiences gained in the overall AEQUIPA network while building, particularly on the experiences from the AEQUIPA sub-projects TECHNOLOGY and PROMOTE. Our experiences can help researchers of all disciplines, industries, and practices design, study and implement novel technology-based interventions for older adults to avoid pitfalls and create compelling and meaningful solutions.

Mitigating Feelings of Loneliness and Depression by Means of Web-Based or Print-Based Physical Activity Interventions: Pooled Analysis of 2 Community-Based Intervention Trials.

BACKGROUND: Physical activity (PA) is associated with benefits, such as fewer depressive symptoms and loneliness. Web- and print-based PA interventions can help older individuals accordingly. OBJECTIVE: We aimed to test the following research questions: Do PA interventions delivered in a web- or print-based mode improve self-reported PA stage of change, social-cognitive determinants of PA, loneliness, and symptoms of depression? Is subjective age a mediator and stage of change a moderator of this effect? METHODS: Overall, 831 adults aged ≥60 years were recruited and either allocated to a print-based or web-based intervention group or assigned to a wait-list control group (WLCG) in 2 community-based PA intervention trials over 10 weeks. Missing value imputation using an expectation-maximization algorithm was applied. Frequency analyses, multivariate analyses of variance, and moderated mediation analyses were conducted. RESULTS: The web-based intervention outperformed (47/59, 80% of initially inactive individuals being adopters, and 396/411, 96.4% of initially active individuals being maintainers of the recommended PA behavior) the print-based intervention (20/25, 80% of adopters, and 63/69, 91% of maintainers) and the WLCG (5/7, 71% of adopters; 141/150, 94% of maintainers). The pattern regarding adopters was statistically significant (web vs print Z=-1.94; P=.02; WLCG vs web Z=3.8367; P=.01). The pattern was replicated with stages (χ24=79.1; P<.001; contingency coefficient 0.314; P<.001); in the WLCG, 40.1% (63/157) of the study participants moved to or remained in action stage. This number was higher in the groups receiving web-based (357/470, 76%) or print-based interventions (64/94, 68.1%). A significant difference was observed favoring the 2 intervention groups over and above the WLCG (F19, 701=4.778; P<.001; η2=0.098) and a significant interaction of time and group (F19, 701=2.778; P<.001; η2=0.070) for predictors of behavior. The effects of the interventions on subjective age, loneliness, and depression revealed that both between-group effects (F3, 717=8.668; P<.001; η2=0.018) and the interaction between group and time were significant (F3, 717=6.101; P<.001; η2=0.025). In a moderated mediation model, both interventions had a significant direct effect on depression in comparison with the WLCG (web-based: c' path -0.86, 95% CI -1.58 to -0.13, SE 0.38; print-based: c' path -1.96, 95% CI -2.99 to -0.92, SE 0.53). Furthermore, subjective age was positively related to depression (b path 0.14, 95% CI 0.05-0.23; SE 0.05). An indirect effect of the intervention on depression via subjective age was only present for participants who were in actor stage and received the web-based intervention (ab path -0.14, 95% CI -0.34 to -0.01; SE 0.09). CONCLUSIONS: Web-based interventions appear to be as effective as print-based interventions. Both modes might help older individuals remain or become active and experience fewer depression symptoms, especially if they feel younger. TRIAL REGISTRATION: German Registry of Clinical Trials DRKS00010052 (PROMOTE 1); https://tinyurl.com/nnzarpsu and DRKS00016073 (PROMOTE 2); https://tinyurl.com/4fhcvkwy. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): RR2-10.2196/15168.

Availability of open data for spatial public health research.

Background: Preventive and health-promoting policies can guide (place- and space-specific) factors influencing human health, such as the physical and social environment. Required is data that can lead to a more nuanced decision-making process and identify both existing and future challenges. Along with the rise of new technologies, and thus the multiple opportunities to use and process data, new options have emerged to measure and monitor factors that affect health. Thus, in recent years, several gateways for open data (including governmental and geospatial data) have become available. At present, an increasing number of research institutions as well as (state and private) companies and citizens' initiatives are providing data. However, there is a lack of overviews covering the range of such offerings regarding health. In particular, for geographically differentiated analyses, there are challenges related to data availability at different spatial levels and the growing number of data providers. Objectives: This paper aims to provide an overview of open data resources available in the context of space and health to date. It also describes the technical and legal conditions for using open data. Results: An up-to-date summary of results including information on relevant data access and terms of use is provided along with a web visualization. All data is available for further use under an open license.

Impact of Activity Tracker Usage in Combination with a Physical Activity Intervention on Physical and Cognitive Parameters in Healthy Adults Aged 60+: A Randomized Controlled Trial.

Regular physical activity (PA) is of central importance for healthy aging and has a well-known impact on helping older adults maintain their cognitive and physical health. Thus, we aimed to compare the effectiveness of two physical activity interventions primarily conducted at home (print-based or web-based vs. web-based plus the use of an activity tracker) on cognitive and physical health parameters in older adults. Data of participants (n = 551, 60-80 years) were analyzed after being randomly allocated to a waitlist control group (CG), a web-based or print-based intervention group (IG) or a web-based intervention group that also included the use of an activity tracker (AG). Measured parameters were grip strength, endurance (two-minute step test), gait speed (four-meter walk test), cognition (Simon task; balanced integration score (BIS), reaction time and accuracy) and physical self-concept (Physical Self-Description Questionnaire (PSDQ)). We found the highest effect sizes in all measured dimensions for AG (grip strength, endurance, gait speed, reaction time, physical self-concept), followed by IG (endurance, gait speed, reaction time, physical self-concept) and CG (endurance, gait speed, BIS). Findings suggest that a combined web-based and activity tracker intervention may improve physical functions, physical self-concept, and cognition in community-dwelling older adults.

Web-Based Versus Print-Based Physical Activity Intervention for Community-Dwelling Older Adults: Crossover Randomized Trial.

BACKGROUND: Fewer than half of older German adults engage in the recommended levels of endurance training. OBJECTIVE: The study aim is to compare the acceptance and effectiveness of two interventions for physical activity (PA) promotion among initially inactive community-dwelling older adults ≥60 years in a 9-month, crossover randomized trial. METHODS: Participants were recruited in person and randomized to one of the following interventions for self-monitoring PA: a print-based intervention (PRINT: 113/242, 46.7%) or a web-based intervention (WEB: 129/242, 53.3%). Furthermore, 29.5% (38/129) of those in the web-based intervention group received a PA tracker in addition to WEB (WEB+). After randomization, the participants and researchers were not blinded. The participants' baseline intervention preferences were retrospectively assessed. All the intervention groups were offered 10 weekly face-to-face group sessions. Afterward, participants could choose to stay in their group or cross over to one of the other groups, and group sessions were continued monthly for another 6 months. 3D accelerometers to assess PA and sedentary behavior (SB) at baseline (T0), 3-month follow-up (T1), and 9-month follow-up (T2) were used. Adherence to PA recommendations, attendance of group sessions, and intervention acceptance were assessed using self-administered paper-based questionnaires. Linear mixed models were used to calculate differences in moderate to vigorous PA (MVPA) and SB between time points and intervention groups. RESULTS: Of the 242 initially recruited participants, 91 (37.6%) were randomized to the WEB group; 38 (15.7%) to the WEB+ group; and 113 (46.7%) to the PRINT group. Overall, 80.6% (195/242) of the participants completed T1. Only 0.4% (1/242) of the participants changed from the WEB group to the PRINT group and 6.2% (15/242) moved from the PRINT group to the WEB group (WEB-WEB: 103/249, (41.4%); PRINT-PRINT: 76/249, 30.5%) when offered to cross over at T1. Furthermore, 66.1% (160/242) of participants completed T2. MVPA in minutes per day increased between baseline and T1, but these within-group changes disappeared after adjusting for covariates. MVPA decreased by 9 minutes per day between baseline and T2 (ßtime=-9.37, 95% CI -18.58 to -0.16), regardless of the intervention group (WEB vs PRINT: ßgroup*time=-3.76, 95% CI -13.33 to 5.82, WEB+ vs PRINT: ßgroup*time=1.40, 95% CI -11.04 to 13.83). Of the participants, 18.6% (38/204) met the PA recommendations at T0, 16.4% (26/159) at T1, and 20.3% (28/138) at T2. For SB, there were no significant group differences or group-by-time interactions at T1 or T2. Intervention acceptance was generally high. The use of intervention material was high to moderate at T1 and decreased by T2. CONCLUSIONS: There was little movement between intervention groups at T1 when given the choice, and participation was not associated with increases in PA or decreases in SB over time. TRIAL REGISTRATION: German Clinical Trials Register DRKS00016073; https://www.drks.de/drks_web/navigate.do?navigationId=trial.HTML&TRIAL_ID=DRKS00016073.

Ecological Predictors of Older Adults' Participation and Retention in a Physical Activity Intervention.

Research is still lacking regarding the question as to how programs to promote healthy ageing should be organized in order to increase acceptance and thus effectiveness. For older adults, ecological factors, such as the physical distance to program sites, might predict participation and retention. Thus, the key aim of this analysis was to examine these factors in a physical activity intervention trial. Adults (N = 8299) aged 65 to 75 years were invited to participate and n = 589 participants were randomly assigned to one of two intervention groups with 10 weeks of physical activity home practice and exercise classes or a wait-list control group. Response, participation, and dropout data were compared regarding ecological, individual, and study-related variables. Kaplan-Meier curves and Cox regression models were used to determine predictors of dropout. In total, 405 participants completed the study. Weekly class attendance rates were examined regarding significant weather conditions and holiday periods. The highest rates of nonresponse were observed in districts with very high neighborhood levels of socioeconomic status. In this study, ecological factors did not appear to be significant predictors of dropout, whereas certain individual and study-related variables were predictive. Future studies should consider these factors during program planning to mobilize and keep subjects in the program.

Health-related lifestyle and dropout from a web-based physical activity intervention trial in older adults: A latent profile analysis.

OBJECTIVE: Selective study dropout limits manifestation and detection of intervention effects and is a major challenge in behavioral intervention studies. Engaging in health-risk behaviors might make individuals especially dropout-vulnerable. Thus, this theory-based study's aim was to identify health-related lifestyle profiles affecting dropout in a web-based physical activity intervention trial targeting older adults. METHOD: The 12-week intervention trial was conducted between 2016 and 2018 in Germany. Baseline lifestyle profiles consisting of self-reported physical activity, sedentary behavior, alcohol consumption, fruit and vegetable intake, nocturnal sleep, and social activity were assessed with questionnaires and investigated in 589 individuals. The risk of study dropout related to health-related lifestyle profile was tested with Poisson regression in 571 individuals (96.9%). RESULTS: Latent profile analysis identified four latent health-related lifestyle profiles: socially inactive (n = 23, 3.9%), slightly unhealthy (n = 449, 75.2%), health-promoting (n = 81, 13.8%), and highly physically active lifestyle (n = 36, 6.1%). Profiles differed significantly by sex, stage of behavior change, and subjective health. Compared with the average of all profiles, statistically significant study dropout adjusted risk ratios (aRR) were 1.91 for the socially inactive lifestyle, and aRR = 0.73 for the slightly unhealthy lifestyle. There were no statistically significant effects for the highly physically active lifestyle (aRR = 0.94) and the health-promoting lifestyle (aRR = 0.76) on study dropout. CONCLUSIONS: This study highlights the relevance of accounting for the correlation between health-related lifestyle profiles and study participation of older adults in physical activity interventions. (PsycInfo Database Record (c) 2021 APA, all rights reserved).

Measuring the association of objective and perceived neighborhood environment with physical activity in older adults: challenges and implications from a systematic review.

BACKGROUND: A supportive environment is a key factor in addressing the issue of health among older adults. There is already sufficient evidence that objective and self-reported measures of the neighborhood environment should be taken into account as crucial components of active aging, as they have been shown to influence physical activity; particularly in people aged 60+. Thus, both could inform policies and practices that promote successful aging in place. An increasing number of studies meanwhile consider these exposures in analyzing their impact on physical activity in the elderly. However, there is a wide variety of definitions, measurements and methodological approaches, which complicates the process of obtaining comparable estimates of the effects and pooled results. The aim of this review was to identify and summarize these differences in order to emphasize methodological implications for future reviews and meta analyzes in this field and, thus, to create a sound basis for synthesized evidence. METHODS: A systematic literature search across eight databases was conducted to identify peer-reviewed articles examining the association of objective and perceived measures of the neighborhood environment and objectively measured or self-reported physical activity in adults aged ≥ 60 years. Two authors independently screened the articles according to predefined eligibility criteria, extracted data, and assessed study quality. A qualitative synthesis of the findings is provided. RESULTS: Of the 2967 records retrieved, 35 studies met the inclusion criteria. Five categories of methodological approaches, numerous measurement instruments to assess the neighborhood environment and physical activity, as well as several clusters of definitions of neighborhood, were identified. CONCLUSIONS: The strength of evidence of the associations of specific categories of environmental attributes with physical activity varies across measurement types of the outcome and exposures as well as the physical activity domain observed and the operationalization of neighborhood. The latter being of great importance for the targeted age group. In the light of this, future reviews should consider these variations and stratify their summaries according to the different approaches, measures and definitions. Further, underlying mechanisms should be explored.

Requirements for (web-based) physical activity interventions targeting adults above the age of 65 years - qualitative results regarding acceptance and needs of participants and non-participants.

BACKGROUND: It remains unclear how physical activity (PA) interventions need to be designed to reach older adults and to be widely accepted in this target group. The aim of this study was to assess the acceptance of a web-based PA program, including individual intervention components as well as relevant contextual factors, and to specify requirements for future interventions. METHODS: Two hundred sixty-six participants of a PA intervention completed a questionnaire covering individual program components (content, structure, and context). Further, 25 episodic guided interviews focusing on reasons for (non-) participation were conducted with 8 participants and 17 non-participants. Following qualitative content analysis, different requirements were identified and organized based on the social-ecological model, resulting in a profile of requirements. RESULTS: Based on the participants' and non-participants' statements, six different levels of requirements affecting acceptance of and successful participation in a web-based PA intervention were identified. The individual fit was influenced by an interaction of different factors at the intrapersonal, sociocultural, content, spatial, digital and organizational levels. Several age- and gender-specific requirements were noted in the interviewed older adults. Men and women, as well as younger (< 70 years) and older (≥70 years) adults differed in terms of perceived enjoyment and benefits of socializing while exercising together, the time expenditure perceived to be acceptable, previous digital skills, as well as in perceptions that ambience and accessibility of exercise facilities in the neighborhood were important. CONCLUSIONS: To motivate older adults to engage in PA and address different needs in terms of life circumstances and quality of life as well as differences in technical affinity, different requirement profiles should be included in the process of intervention development and implementation. Participatory development loops and modular offer formats are recommended for this.

[Is My Community Ready? The Community Readiness Model and its Exemplary Application in Community-Based Health Promotion]. / Wie bereit ist die Kommune? Das Community Readiness-Modell und die beispielhafte Anwendung in der kommunalen Gesundheitsförderung.

The German Prevention Act adopted in 2015 strengthens setting-based prevention approaches. The aim of this work was the presentation of the Community Readiness Model as an instrument for determining needs and improving health-promoting structures in the community setting, using the example of the promotion of physical activity in older adults. The needs assessment in the context of the model implementation was carried out by Community Readiness assessment, in which guided interviews on health promotion topics were conducted with key persons in communities. The community's stage of readiness was determined based on the interview results, and appropriate public health measures were derived from the respective stage. In our example, the model was adapted to the topic of promoting physical activity among older community-dwelling adults. The assessment was carried out in 2015 in 23 communities in Northwestern Germany. Illustrations such as spider web diagrams and geographical distributions are used to present the assessment results. The Community Readiness approach is a model that enables in-depth assessment as well as targeted development of local structures and capacities. Our experience shows that the method can be implemented well in Community Readiness assessment. The main advantages of this approach are its systematic nature and the analysis of local strengths and weaknesses as a prerequisite for community-specific interventions.

Implementation and Effects of Information Technology-Based and Print-Based Interventions to Promote Physical Activity Among Community-Dwelling Older Adults: Protocol for a Randomized Crossover Trial.

BACKGROUND: Despite the known health benefits of physical activity (PA), less than half and less than one-third of older adults in Germany reach the PA recommendations for endurance training and strength training, respectively, of the World Health Organization. The aim of this study is to investigate the implementation and effectiveness over the course of 9 months of two interventions (information technology [IT]-based vs print-based) for PA promotion among initially inactive older adults in a randomized, crossover trial. This study is part of a large research consortium (2015-2021) investigating different aspects of PA promotion. The IT-based intervention was previously developed and refined, while the print-based intervention was newly developed during this funding phase. OBJECTIVE: We aim to compare the effectiveness and examine the preferences of study participants regarding both delivery modes. METHODS: Our target sample size was 390 initially inactive community-dwelling older adults aged ≥60 years at baseline (3-month follow-up [T1]: expected n=300; 9-month follow-up [T2]: expected n=240) who were randomized to one of two interventions for self-monitoring PA: IT-based (50%) or print-based (50%) intervention. In addition, 30% of the IT-based intervention group received a PA tracker. At T1, participants in both groups could choose whether they prefered to keep their assigned intervention or cross over to the other group for the following 6 months (T2). Participants' intervention preferences at baseline were collected retrospectively to run a post hoc matched-mismatched analysis. During the initial 3-month intervention period, both intervention groups were offered weekly group sessions that were continued monthly between T1 and T2. A self-administered questionnaire and 3D accelerometers were employed to assess changes in PA between baseline, T1, and T2. Adherence to PA recommendations, attendance at group sessions, and acceptance of the interventions were also tracked. RESULTS: The funding period started in February 2018 and ends in January 2021. We obtained institutional review board approval for the study from the Medical Association in Bremen on July 3, 2018. Data collection was completed on January 31, 2020, and data cleaning and analysis started in February 2020. We expect to publish the first results by the end of the funding period. CONCLUSIONS: Strategies to promote active aging are of particular relevance in Germany, as 29% of the population is projected to be ≥65 years old by 2030. Regular PA is a key contributor to healthy aging. This study will provide insights into the acceptance and effectiveness of IT-based vs print-based interventions to promote PA in initially inactive individuals aged ≥60 years. Results obtained in this study will improve the existing evidence base on the effectiveness of community-based PA interventions in Germany and will inform efforts to anchor evidence-based PA interventions in community structures and organizations via an allocation of permanent health insurance funds. TRIAL REGISTRATION: German Registry of Clinical Trials DRKS00016073; https://tinyurl.com/y983586m. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): DERR1-10.2196/15168.

Effects of Two Web-Based Interventions and Mediating Mechanisms on Stage of Change Regarding Physical Activity in Older Adults.

BACKGROUND: Web-based, theory-driven interventions effectively promote older adults' physical activity. Social-cognitive mechanisms of their effect on stage of change need to be further researched. METHODS: Older adults were randomly allocated to intervention group 1 (10-week online physical activity program), intervention group 2 (same program plus activity tracker), or delayed intervention control group; n = 351 were analyzed (59.6% of originally allocated individuals). Stages of change for recommended endurance and strength training and social-cognitive predictors of physical activity were assessed using questionnaires at baseline and follow-up. Intervention effects and mediation were investigated using mixed-effects ANOVA and ordinal least squares regression. RESULTS: Direct effects on stage of change were found for intervention group 1 regarding endurance training (bintervention group 1  = 0.44, 95% confidence interval [0.15, 0.73]), and both groups regarding strength training (bintervention group 1  = 1.02, [0.71, 1.33], bintervention group 2  = 1.24, [0.92, 1.56]). Social-cognitive predictor changes in task self-efficacy, intention, and action planning explained intervention effect on stage of change, but not to the full extent. CONCLUSIONS: The results indicate significant web-based intervention effects on physical activity stage, partly mediated by changes in task self-efficacy, intention, and action planning.

[DEVASYS - Development of an Online Tool to Support Systematic Evaluation of Intervention Projects in Prevention and Health Promotion]. / DEVASYS ­ Entwicklung eines Online-Tools zur Unterstützung der systematischen Evaluation von Interventionsprojekten der Prävention und Gesundheitsförderung.

OBJECTIVES: To date, knowledge about the effects and implementation quality of disease prevention and health promotion projects in Germany is limited. Only a few structured evaluation systems exist that can be easily used and which include features for evaluating research and practice projects. The aim of the current project was to develop and carry out a pilot study of an online evaluation tool that enables structured self-evaluation of projects in disease prevention and health promotion practice and contributes to an improved documentation and cyclical development of projects. METHODS: The mixed-methods approach taken in this project included 2 steps: a) search of literature and database to develop a theoretical framework for the tool and b) adaptation process to test the fit of the tool for practice, including a focus group discussion and a usability test with different disease prevention and health promotion stakeholders (N=12). RESULTS: The resulting documentation and evaluation system (DEVASYS) is comprised of the components "planning", "documentation", and "evaluation" which can be used independently of one another. The conceptual basis of the tool is the RE-AIM framework. To determine the quality of an individual project, dimensions of both the output (reach, acceptance, implementation) and the outcome levels (effectiveness, maintenance) can be documented with the tool. CONCLUSION: DEVASYS is a practice-oriented tool contributing to an improved evaluation of existing practice-related intervention projects and the overall quality of future projects in the area of disease prevention and health promotion. Systematic dissemination and implementation of the tool are the next steps to be taken.

Effects of two web-based interventions promoting physical activity among older adults compared to a delayed intervention control group in Northwestern Germany: Results of the PROMOTE community-based intervention trial.

Regular physical activity (PA) is of central importance for healthy ageing. However, in Germany, only 42% of older adults currently reach the PA recommendations of the World Health Organization. The aim of this study was to examine the effects of two web-based interventions on PA in adults aged 65-75 years living in Northwestern Germany compared to a delayed intervention control group (CG). 589 older adults were randomized to one of the three groups. Participants in intervention group 1 (IG1) received access to a web-based intervention for ten weeks assisting them in self-tracking PA behavior. Participants in IG2 received the intervention of IG1 and additionally an activity tracker to objectively track PA behavior. To analyze differences in objectively measured moderate-to-vigorous PA and sedentary time between baseline and follow-up (12 weeks after baseline), linear mixed models were used. The interaction effects revealed a decrease in minutes spent on moderate-to-vigorous PA in bouts of 10 min by 11 min per week in IG1 participants (ß = -11.08, 95% CI: (-35.03; 12.87)). In comparison, IG2 participants were 7 min more physically active at follow-up (ß = 7.48, 95% CI: (-17.64; 32.60)). Sedentary time in bouts of 30 min per week increased in IG1 participants (ß = 106.77, 95% CI: (-47.69; 261.23)) and decreased in IG2 participants at follow-up (ß = -16.45, 95% CI: (-178.83; 145.94)). Participation in the two web-based interventions did not lead to significant increases in moderate-to-vigorous PA or significant decreases in sedentary time compared to the CG. The study was registered at the German Clinical Trials Register (DRKS00010052, 07-11-2016).

Comparison of three meta-analytic methods using data from digital interventions on type 2 diabetes.

AIMS: Pooling the effect sizes of randomized controlled trials (RCTs) from continuous outcomes, such as glycated hemoglobin level (HbA1c), is an important method in evidence syntheses. However, due to challenges related to baseline imbalances and pre/post correlations, simple analysis of change scores (SACS) and simple analysis of final values (SAFV) meta-analyses result in under- or overestimation of effect estimates. This study was aimed to compare pooled effect sizes estimated by Analysis of Covariance (ANCOVA), SACS, and SAFV meta-analyses, using the example of RCTs of digital interventions with HbA1c as the main outcome. MATERIALS AND METHODS: Three databases were systematically searched for RCTs published from 1993 through June 2017. Two reviewers independently assessed titles and abstracts using predefined eligibility criteria, assessed study quality, and extracted data, with disagreements resolved by arbitration from a third reviewer. RESULTS: ANCOVA, SACS, and SAFV resulted in pooled HbA1c mean differences of -0.39% (95% CI: [-0.51, -0.26]), -0.39% (95% CI: [-0.51, -0.26]), and -0.34% (95% CI: [-0.48-0.19]), respectively. Removing studies with both high baseline imbalance (≥±0.2%) and pre/post correlation of ≥±0.6 resulted in a mean difference of -0.39% (95% CI: [-0.53, -0.26]), -0.40% (95% CI: [-0.54, -0.26]), and -0.33% (95% CI: [-0.48, -0.18]) with ANCOVA, SACS, and SAFV meta-analyses, respectively. Substantial heterogeneity was noted. Egger's test for funnel plot symmetry did not indicate evidence of publication bias for all methods. CONCLUSION: By all meta-analytic methods, digital interventions appear effective in reducing HbA1c in type 2 diabetes. The effort to adjust for baseline imbalance and pre/post correlation using ANCOVA relies on the level of detail reported from individual studies. Reporting detailed summary data and, ideally, access to individual patient data of intervention trials are essential.

Effectiveness of Digital Interventions for Improving Glycemic Control in Persons with Poorly Controlled Type 2 Diabetes: A Systematic Review, Meta-analysis, and Meta-regression Analysis.

BACKGROUND: Digital interventions may assist patients with type 2 diabetes in improving glycemic control. We aimed to synthesize effect sizes of digital interventions on glycated hemoglobin (HbA1c) levels and to identify effective features of digital interventions targeting patients with poorly controlled type 2 diabetes. MATERIALS AND METHODS: MEDLINE, ISI Web of Science, and PsycINFO were searched for randomized controlled trials (RCTs) comparing the effects of digital interventions with usual care. Two reviewers independently assessed studies for eligibility and determined study quality, using the Cochrane Risk of Bias Assessment Tool. The Behavioral Change Technique Taxonomy V1 (BCTTv1) was used to identify BCTs used in interventions. Mean HbA1c differences were pooled using analysis of covariance to adjust for baseline differences and pre-post correlations. To examine effective intervention features and to evaluate differences in effect sizes across groups, meta-regression and subgroup analyses were performed. RESULTS: Twenty-three arms of 21 RCTs were included in the meta-analysis (n = 3787 patients, 52.6% in intervention arms). The mean HbA1c baseline differences ranged from -0.2% to 0.64%. The pooled mean HbA1c change was statistically significant (-0.39 {95% CI: [-0.51 to -0.26]} with substantial heterogeneity [I2 statistic, 80.8%]) and a significant HbA1c reduction was noted for web-based interventions. A baseline HbA1c level above 7.5%, ß = -0.44 (95% CI: [-0.81 to -0.06]), the BCTs "problem solving," ß = -1.30 (95% CI: [-2.05 to -0.54]), and "self-monitoring outcomes of behavior," ß = -1.21 (95% CI: [-1.95 to -0.46]) were significantly associated with reduced HbA1c levels. CONCLUSIONS: Digital interventions appear effective for reducing HbA1c levels in patients with poorly controlled type 2 diabetes.