eHealth Interventions Research Articles

E-health education intervention to increase dietary adherence among diabetic ulcer patients

Background: Preventing complications of diabetes mellitus requires medical treatment and education. Diabetic ulcer is one of the complications of diabetes mellitus due to traumatized nephropathy. E-health education innovation makes it easy for patients to access education on how to prevent complications from diabetes mellitus. Purpose: Analyzing the effect of e-health education of diabetes mellitus based on the QR model website as a means of dietary compliance in grade 2 diabetic ulcer patients. Method: Employing true experimental pre-test post-test design with control group design. It involved 30 participants who were divided into 2 groups through simple random sampling. Saphiro-Wilk was used for data normality test and Man-Whitney was used for hypothesis testing with score difference test. This research was conducted at the Anak Lanang Wound Care Center Clinic, Semarang. Results: There was an increase in scores on dietary adherence between groups (64.13±2.82 vs 59.07±2.91). Both groups experienced an increase in scores, but the increase was greater in the intervention group given e-health education of diabetes mellitus compared to the control group given the Booklet. Conclusion: There is an effect of e-health education of diabetes mellitus on the level of dietary compliance in grade 2 diabetic ulcer patients. Suggestion: Future researchers are expected to develop database instrumentation and educational content for patients with diabetes mellitus.

Combining user-centered design and behavioral theory to enhance health technologies: A personas-based approach for a primary-care based multifactorial falls risk assessment tool

IntroductionMultifactorial falls risk assessment tools (FRATs) can be an effective falls prevention method for older adults, but are often underutilized by health care professionals (HCPs). This study aims to enhance the use and implementation of multifactorial FRATs by combining behavioral theory with the user-centered design (UCD) method of personas construction. Specifically, the study aimed to (1) construct personas that are based on external (i.e., needs, preferences) and intrinsic user characteristics (i.e., behavioral determinants); and (2) use these insights to inform requirements for optimizing an existing Dutch multifactorial FRAT (i.e., the ‘Valanalyse’). MethodsSurvey data from HCPs (n = 31) was used to construct personas of the ‘Valanalyse.’ To examine differences between clusters on 68 clustering variables, a multivariate cluster analysis technique with non-parametric analyses and computational methods was used. The aggregated external and intrinsic user characteristics of personas were used to inform key design and implementation requirements for the ‘Valanalyse,’ respectively, whereby intrinsic user characteristics were matched with appropriate behavior change techniques to guide implementation. ResultsSignificant differences between clusters were observed in 20 clustering variables (e.g., behavioral beliefs, situations for use). These variables were used to construct six personas representing users of each cluster. Together, the six personas helped operationalize four key design requirements (e.g., guide treatment-related decision making) and 14 implementation strategies (e.g., planning coping responses) for optimizing the ‘Valanalyse’ in Dutch geriatric, primary care settings. ConclusionThe findings suggest that theory- and evidence-based personas that encompass both external and intrinsic user characteristics are a useful method for understanding how the use and implementation of multifactorial FRATs can be optimized with and for HCPs, providing important implications for developers and eHealth interventions with regards to encouraging technology adoption.

The relation between usage of an eHealth intervention for stress urinary incontinence and treatment outcomes: an observational study

BackgroundStress urinary incontinence (SUI), though a prevalent condition among women, is undertreated in primary care. EHealth with pelvic floor muscle training is an evidence-based alternative to care-as-usual. It is unknown, however, how eHealth usage is related to treatment outcome, and this knowledge is required for general practitioners to implement eHealth in their practice. This study examines the relation between usage of eHealth for SUI and treatment outcomes by examining log data. Baseline factors were also explored for associations with treatment success.MethodIn this pre-post study, women with SUI participated in “Baasoverjeblaas.nl”, a web-based intervention translated from the Swedish internet intervention "Tät®-treatment of stress urinary incontinence". Usage was based on log data and divided into three user groups (low, intermediate and high). Online questionnaires were sent before, after treatment and at six-months follow-up. The relation between usage and the primary outcome − treatment success (PGI-) − was studied with a binomial logistic regression analysis. Changes in the secondary outcomes − symptom severity (ICIQ-UI SF) and quality of life (ICIQ-LUTSqol) − were studied per user group with linear mixed model analysis.ResultsIncluded were 515 users with a mean age of 50.5 years (12.0 SD). The majority were low users (n = 295, 57.3%). Treatment success (PGI-I) was reached by one in four women and was more likely in high and intermediate users than in low users (OR 13.2, 95% CI 6.1–28.5, p < 0.001 and OR 2.92, 95% CI 1.35–6.34, p = 0.007, respectively). Symptom severity decreased and quality of life improved significantly over time, especially among high users. The women’s expected ability to train their pelvic floor muscles and the frequency of pelvic floor muscle exercises at baseline were associated with treatment success.ConclusionThis study shows that usage of eHealth for SUI is related to all treatment outcomes. High users are more likely to have treatment success. Treatment success is more likely in women with higher expectations and pelvic floor muscle training at baseline. These findings indicate that general practitioners can select patients that would be more likely to benefit from eHealth treatment, and they can enhance treatment effect by stimulating eHealth usage.Trial registrationLandelijk Trial Register NL6570; https://onderzoekmetmensen.nl/nl/trial/25463.

Effectiveness of a Parent-Based eHealth Intervention for Physical Activity, Dietary Behavior, and Sleep Among Preschoolers: Protocol for a Randomized Controlled Trial.

Preschoolers' lifestyles have become physically inactive and sedentary, their eating habits have become unhealthy, and their sleep routines have become increasingly disturbed. Parent-based interventions have shown promise to improve physical activity (PA), improve dietary behavior (DB), and reduce sleep problems among preschoolers. However, because of the recognized obstacles of face-to-face approaches (eg, travel costs and time commitment), easy access and lower costs make eHealth interventions appealing. Previous studies that examined the effectiveness of parent-based eHealth for preschoolers' PA, DB, and sleep have either emphasized 1 variable or failed to balance PA, DB, and sleep modules and consider the intervention sequence during the intervention period. There is an acknowledged gap in parent-based eHealth interventions that target preschoolers raised in Chinese cultural contexts. This study aims to investigate the effectiveness of a parent-based eHealth intervention for PA, DB, and sleep problems among Chinese preschoolers. This 2-arm, parallel, randomized controlled trial comprises a 12-week intervention with a 12-week follow-up. A total of 206 parent-child dyads will be randomized to either an eHealth intervention group or a control group. Participants allocated to the eHealth intervention group will receive 12 interactive modules on PA, DB, and sleep, with each module delivered on a weekly basis to reduce the sequence effect on variable outcomes. The intervention is grounded in social cognitive theory. It will be delivered through social media, where parents can obtain valid and updated educational information, have a social rapport, and interact with other group members and facilitators. Participants in the control group will receive weekly brochures on PA, DB, and sleep recommendations from kindergarten teachers, but they will not receive any interactive components. Data will be collected at baseline, 3 months, and 6 months. The primary outcome will be preschoolers' PA. The secondary outcomes will be preschoolers' DB, preschoolers' sleep duration, preschoolers' sleep problems, parents' PA, parenting style, and parental feeding style. Parent-child dyads were recruited in September 2023. Baseline and posttest data collection occurred from October 2023 to March 2024. The follow-up data will be obtained in June 2024. The results of the study are expected to be published in 2025. The parent-based eHealth intervention has the potential to overcome the barriers of face-to-face interventions and will offer a novel approach for promoting a healthy lifestyle among preschoolers. If this intervention is found to be efficacious, the prevalence of unhealthy lifestyles among preschoolers may be alleviated at a low cost, which not only has a positive influence on the health of individuals and the well-being of the family but also reduces the financial pressure on society to treat diseases caused by poor lifestyle habits. ClinicalTrials.gov NCT06025019; https://clinicaltrials.gov/study/NCT06025019. DERR1-10.2196/58344.

A Randomized Controlled Trial to Improve Unmet Social Needs and Clinical Outcomes Among Adults with Diabetes.

Adults with type 1 or type 2 diabetes often face financial challenges and other unmet social needs to effective diabetes self-management. Whether a digital intervention focused on addressing socioeconomic determinants of health improves diabetes clinical outcomes more than usual care. Randomized trial from 2019 to 2023. A total of 600 adults with diabetes, HbA1c ≥ 7.5%, and self-reported unmet social needs or financial burden from a health system and randomized to the intervention or standard care. CareAvenue is an automated, e-health intervention with eight videos that address unmet social needs contributing to poor outcomes. Primary outcome was HbA1c, measured at baseline, and 6 and 12months after randomization. Secondary outcomes included systolic blood pressure and reported met social needs, cost-related non-adherence (CRN), and financial burden. We examined main effects and variation in effects across predefined subgroups. Seventy-eight percent of CareAvenue participants completed one or more modules of the website. At 12-month follow-up, there were no significant differences in HbA1c changes between CareAvenue and control group (p = 0.24). There were also no significant between-group differences in systolic blood pressure (p = 0.29), met social needs (p = 0.25), CRN (p = 0.18), and perceived financial burden (p = 0.31). In subgroup analyses, participants with household incomes 100-400% FPL (1.93 (SE = 0.76), p < 0.01), 201-400% FPL (1.30 (SE = 0.62), p < 0.04), and > 400% FPL (1.27 (SE = 0.64), p < 0.05) had significantly less A1c decreases compared to the control group. On average, CareAvenue participants did not achieve better A1c lowering, met needs, CRN, or perceived financial burden compared to control participants. CareAvenue participants with higher incomes achieved significantly less A1c reductions than control. Further research is needed on social needs interventions that consider tailored approaches to population subgroups. ClinicalTrials.gov ID NCT03950973, May 2019.

Smoking cessation in pregnant women: A randomized controlled trial investigating the effectiveness of an eHealth intervention including heart rate variability-biofeedback training

BackgroundPrenatal smoking and stress are associated with adverse health effects for women themselves and are risk factors for adverse outcomes of the child. Effective interventions are needed to support women with smoking cessation and reducing stress. The aims were (1) to test the effectiveness of an 8-week eHealth intervention targeting stress reduction and smoking cessation; (2) to examine whether stress reduction mediated the intervention effect on smoking behavior; (3) to test motivation to quit as a moderator; and (4) to investigate a dose–response effect of program usage. MethodsPregnant women were included if they were >18 years of age, < 28 weeks pregnant at recruitment, and currently smoking. In total, 156 consenting participants were randomly assigned to the intervention or active control condition. Study outcomes on smoking (yes/no, frequency, and quantity) were collected via online questionnaires at pre-intervention (baseline; t0), post-intervention (8 weeks after t0; t1), and follow up at two weeks (t2) and three months (t3) after birth. ResultsSmoking and stress reduced over the 8-week period in both conditions. The intervention effect on smoking was not mediated by stress reduction. Motivation to quit was found to moderate the intervention effect (smoking frequency and quantity) and a dose–response effect was found for program usage in the intervention for the reduction on smoking frequency and quantity. ConclusionProgram usage and motivation to quit are important for smoking reduction in pregnant women. Further research is needed to examine how the intervention could be improved to increase treatment effectiveness.

Needs and Demands for e-Health Interventions in Patients Attending a Psychosomatic Outpatient Clinic: A Baseline Assessment for a User-Centered Design Approach.

Objective: Increased utilization of e-health services can help to meet shortages of psychotherapeutic treatment. e-Health interventions can be effective if tailored according to the individual needs and demands of the target group. To gather comprehensive data for the development of a user-centered e-health intervention, a cross-sectional study was conducted among a heterogeneous cohort of 309 patients seeking treatment or consultation at psychosomatic university hospital in a densely populated region of Germany. Methods: Sociodemographic data, psychometric dimensions of mental burden, as well as needs and demands regarding an e-health intervention were assessed. A descriptive statistical analysis and a cluster analysis were performed to examine distribution of preferences and differences based on level of burden regarding needs and demands for e-health interventions. Results: Two hundred thirty-nine (N = 239) participants were included in the final data analysis. Among this primarily urban target group smartphone availability was favored by 77.8% of the participants. The cluster analysis revealed significant differences dependent on mental burden. 75.2% of participants with a high mental burden preferred longer interventions of 1-4 months compared with 49% in the low burden group, which also considered short interventions of up to 1 month (46%). Differences were also identified for content preferences and daily-life integration and were consistent irrespective of the initial reason for consultation. Conclusion: The findings of this study can provide a foundational framework for developing user-centered psychosomatic interventions. The potential relationship between individual burden and individual needs and demands highlights the crucial role of preliminary research to tailor interventions to effectively address diverse needs and preferences.

Expert Insight Into the Use of eHealth Interventions to Aid Medication Adherence During COVID-19.

The COVID-19 pandemic has transformed the way healthcare is delivered by the increased utilisation of eHealth tools to deliver remote patient consultations. These eHealth tools served various functions during COVID-19 including monitoring and surveillance of patients. Therefore, assessment of digital health interventions for monitoring medication adherence is crucial to maximise the potential benefits of eHealth. The aim of this study is to understand the perspectives of experts in medication adherence around eHealth interventions used to aid adherence during COVID-19. The study was exploratory and utilized a mixed-method approach. Data was gathered from a survey distributed by the International society for Medication Adherence, and from arranging subsequent structured interviews. Purposive sampling was used to collect data from individuals who were rich in knowledge about the field of medication adherence. Template analysis was used to analyse the collected data. Twenty-one participants responded to the survey and 6 completed the interviews. Results showed that eHealth tools reduced barriers to medication adherence by improving health literacy of patients. The main strengths of eHealth technology used in COVID-19 highlighted by participants were convenience and user empowerment. Moreover, weaknesses and barriers included lack of cooperation between technology providers, lack of awareness of doctors about eHealth and patient's digital health literacy. The increased utility of eHealth tools during COVID-19 highlighted their vital role in aiding medication adherence of patients. These technologies have both decreased and increased barriers to medication adherence through numerous ways. Future directions should focus on gaining the perspectives of patients on the use of eHealth interventions and its role in aiding medication adherence.

Creating healthy eating and active environments in early learning settings: protocol of the CHEERS eHealth intervention study.

Early childhood educators through their daily interactions with children, play a central role in shaping young children's health behaviors. Given their influential role, early childhood educators are often targeted in interventions aiming at enhancing their nutrition and physical activity practices. This paper presents the design of the CHEERS eHealth program to improve nutrition and physical activity practices within Early Childhood Education and Care (ECEC) centers. The study has a longitudinal quasi-experimental design with recruitment of ECECs across Alberta Canada. ECEC intervention group educators complete 12 weekly online nutrition and physical activity modules and participate in weekly communities of practice sessions to discuss practical applications within their centers. Outcome assessments are scheduled at baseline (T1), mid-point at 5 months (T2), and end of program after 10 months (T3). Outcome measures include the Creating Healthy Eating and Active Environments survey (CHEERS), Mindful Eating Questionnaire (MEQ), Canadian Behavior, Attitude and Nutrition Knowledge Survey (C-BANKS 2.0), Physical Literacy Knowledge, Attitude, Self-Efficacy, and Behavior (PLKASB-ECE), the Environment and Policy Assessment and Observation (EPAO) derived variables, and an objective measure of children's physical activity using ActiGraph GT3X accelerometers. Linear mixed model analyses will be used to evaluate the effectiveness of the intervention. Qualitative assessments comprise exit interviews and open-response questions embedded within the educational modules. Preliminary baseline data from the 2019 cohort indicate no statistically significant differences between the intervention and control groups for the primary outcome variables, except age. Educators' personal nutrition-related knowledge, attitude and behaviors were positively associated with their self-assessments of the nutrition environment and practices in ECECs. A significant correlation was observed between educators' self-reported physical activity practices and observed activity practices. The CHEERS survey Food Served subscale showed a positive correlation with the objective measures of EPAO-Foods Provided and Nutrition Policy subdomains. We propose that this eHealth intervention would be an effective scaling up approach to enhancing the nutrition and physical activity environments of ECECs by fostering improved nutrition and physical activity-related knowledge, attitudes, and adherence to best practices which will potentially lead to improved outcomes for children in their care.

EmpRess: an eHealth implementation readiness checklist for dementia developed through an interview study of stakeholder needs

Objective This study aimed to create a tool to assess eHealth interventions for dementia by adapting an existing implementation readiness (ImpRess) checklist that assessed manualised interventions. Methods In Part 1, online semi-structured interviews with individual stakeholders (N = 9) with expertise in eHealth and dementia were conducted (response rate 83%). The Nonadoption, Abandonment, and challenges to the Scale-Up, Spread, and Sustainability of Health and care technologies (NASSS) framework was applied, both to guide the construction of the interview guide, as well as to use its subdomains as codes in the deductive qualitative thematic analysis. Respondents were industry professionals (n = 3), researchers (n = 3), policy officers (n = 2), and a clinician (n = 1). In Part 2, the items of the original ImpRess checklist were supplemented by items that covered determinants discussed in the interviews, that were not included in the original checklist. Results The main findings from the interviews included: Participants’ preference for a non-dementia-specific, more general approach to the checklist; the importance of searching for shared values with implementers; and the need for more systematic monitoring of implementation. Conclusions The EmpRess checklist applies an inclusive design approach. The checklist will help evaluate the implementation determinants of eHealth interventions for dementia and provide up-to-date information on what is, and is not, working in eHealth for dementia care.

Effectiveness of eHealth Interventions Promoting Physical Activity in Children and Adolescents: Systematic Review and Meta-Analysis.

eHealth interventions have been postulated as a feasible, acceptable, and possibly effective tool to promote physical activity (PA) among children and adolescents; however, a comprehensive quantitative analysis of the effects of eHealth interventions promoting PA is lacking. This study aims to conduct a systematic review and meta-analysis on experimental studies reporting the effects of eHealth interventions aimed at promoting PA on PA parameters and sedentary behavior parameters in children and adolescents. The CENTRAL, MEDLINE, Embase, and Web of Science databases were searched from inception to February 2022 for randomized controlled trials that analyzed the effects of eHealth interventions aimed at promoting PA on PA and sedentary parameters in children and adolescents. The Hartung-Knapp-Sidik-Jonkman random effects method was used to determine the mean differences (MDs) with their respective 95% CIs. The risk of bias was assessed using the Risk of Bias 2 (RoB2; Cochrane) tool and its extension for cluster randomized controlled trials. The certainty of evidence was evaluated using the Grading of Recommendations, Assessment, Development, and Evaluation (GRADE) tool. A total of 20 trials reporting the effects of different eHealth interventions aimed at promoting PA were included. Results for each parameter were as follows: counts per minute (MD -16.11 counts, 95% CI -122.76 to 90.53; k=3; n=402; I2=69%; favoring control), steps per day (MD 593.46 steps, 95% CI -2102.27 to 3289.19; k=2; n=152; I2=0%; favoring intervention [FI]), moderate to vigorous PA (MD -1.99 min/d, 95% CI -8.95 to 4.96; k=14; n=2336; I2=86%; favoring control), light PA (MD 3.28 min/d, 95% CI -15.48 to 22.04; k=5; n=355; I2=67%; FI), screen time (MD -31.48 min/d, 95% CI -68.62 to 5.65; k=5; n=904; I2=0%; FI), and sedentary time (MD -33.12 min/d, 95% CI -57.27 to -8.97; k=8; n=819; I2=75%; FI). Our results should be interpreted cautiously because of important limitations such as the scarcity of evidence, overall risk of bias, and low to very low certainty of evidence. We did not find conclusive evidence regarding the impact of PA-targeted eHealth interventions on PA parameters, but the very low certainty of evidence suggests that eHealth interventions may reduce sedentary time in children and adolescents. Our results may have important scientific implications as they highlight that the rapid development of eHealth interventions to promote PA lacks robust supporting evidence. PROSPERO CRD42020211020; https://www.crd.york.ac.uk/prospero/display_record.php?RecordID=211020.

Effect of a smart temperature logger on correctly storing biological disease-modifying antirheumatic drugs at home: a pre-post study

ObjectivesBiological disease-modifying antirheumatic drugs (bDMARDs) require specific storage temperatures, but are frequently stored outside the recommended range of 2–8°C. As incorrect storage may affect therapy effectiveness and consequently lead to...

Effects of eHealth Interventions on 24-Hour Movement Behaviors Among Preschoolers: Systematic Review and Meta-Analysis.

The high prevalence of unhealthy movement behaviors among young children remains a global public health issue. eHealth is considered a cost-effective approach that holds great promise for enhancing health and related behaviors. However, previous research on eHealth interventions aimed at promoting behavior change has primarily focused on adolescents and adults, leaving a limited body of evidence specifically pertaining to preschoolers. This review aims to examine the effectiveness of eHealth interventions in promoting 24-hour movement behaviors, specifically focusing on improving physical activity (PA) and sleep duration and reducing sedentary behavior among preschoolers. In addition, we assessed the moderating effects of various study characteristics on intervention effectiveness. We searched 6 electronic databases (PubMed, Ovid, SPORTDiscus, Scopus, Web of Science, and Cochrane Central Register of Controlled Trials) for experimental studies with a randomization procedure that examined the effectiveness of eHealth interventions on 24-hour movement behaviors among preschoolers aged 2 to 6 years in February 2023. The study outcomes included PA, sleep duration, and sedentary time. A meta-analysis was conducted to assess the pooled effect using a random-effects model, and subgroup analyses were conducted to explore the potential effects of moderating factors such as intervention duration, intervention type, and risk of bias (ROB). The included studies underwent a rigorous ROB assessment using the Cochrane ROB tool. Moreover, the certainty of evidence was evaluated using the GRADE (Grading of Recommendations Assessment, Development, and Evaluation) assessment. Of the 7191 identified records, 19 (0.26%) were included in the systematic review. The meta-analysis comprised a sample of 2971 preschoolers, which was derived from 13 included studies. Compared with the control group, eHealth interventions significantly increased moderate to vigorous PA (Hedges g=0.16, 95% CI 0.03-0.30; P=.02) and total PA (Hedges g=0.37, 95% CI 0.02-0.72; P=.04). In addition, eHealth interventions significantly reduced sedentary time (Hedges g=-0.15, 95% CI -0.27 to -0.02; P=.02) and increased sleep duration (Hedges g=0.47, 95% CI 0.18-0.75; P=.002) immediately after the intervention. However, no significant moderating effects were observed for any of the variables assessed (P>.05). The quality of evidence was rated as "moderate" for moderate to vigorous intensity PA and sedentary time outcomes and "low" for sleep outcomes. eHealth interventions may be a promising strategy to increase PA, improve sleep, and reduce sedentary time among preschoolers. To effectively promote healthy behaviors in early childhood, it is imperative for future studies to prioritize the development of rigorous comparative trials with larger sample sizes. In addition, researchers should thoroughly examine the effects of potential moderators. There is also a pressing need to comprehensively explore the long-term effects resulting from these interventions. PROSPERO CRD42022365003; http://tinyurl.com/3nnfdwh3.

Evaluation of the Road Safety Education “E-drive Academy” Interactive Program in Greek Elementary Schools: A Study of 834 Fourth Grade Students

Road safety constitutes a crucial public health issue and there is growing research on road safety school interventions that promote responsible road use. The current experimental study explored the effectiveness of a three-month implementation of the interactive road safety education program “E-drive Academy” with fourth-grade elementary students in Greek schools of Attica prefecture. The sample consisted of 834 students (experimental group: 629; control group: 205). The evaluation questionnaire included demographics and a road safety questionnaire for use by primary education students, specifically designed to test the effectiveness of the taught modules, namely i) walking safely, ii) using the means of transport and being a passenger in a car, iii) riding a bicycle safely, iv) being a passenger in a school bus, v) locus of control, vi) knowing the traffic lights, vii) incorporating movement into daily life, and viii) orienting oneself. The data analysis revealed that the experimental group exhibited significant (p&lt;0.05) improvement in all taught and investigated traffic-related knowledge, skills, and attitudes post-intervention, whereas the control group did not. The present e-health intervention confirms that properly designed universal road safety education could enhance safety skills and help prevent problem behaviours.

A multilevel intervention in pediatric primary care for youth tobacco control: Outcomes of implementing an Ask, Advise, and Connect model.

Multilevel interventions in healthcare settings (e.g. Ask, Advise, and Connect; AAC) can reduce tobacco product use among adult patients: their effectiveness in pediatric practice is largely unknown. We implemented an AAC model in pediatric primary care to deter children's tobacco use, and evaluated its effectiveness in a single-arm trial. At wellness visits, young patients (ages 12-17) completed a tablet-based assessment (Ask) of lifetime and current tobacco use. These data were made available within the electronic health record to pediatric primary care providers for preventive counseling (Advise). Providers then referred patients to an e-health evidence-based tobacco control intervention (Connect). Tobacco control outcomes were examined in the clinic population (N = 2219) and in a sample of patients (N = 388, 62% female, 39% non-White, M age = 15) over time, along with intervention engagement. Population use of tobacco products decreased following introduction of AAC (more than 2-fold). At the patient level, most children (80.9%) engaged with the intervention: those who were Black or African American, who never used tobacco products/were not susceptible to use, and who used fewer non-cigarette tobacco products were more likely to engage, but only after multiple prompts versus a single prompt. Engagement was positively associated with lowering children's susceptibility to using tobacco at follow-up. A pediatric AAC model holds promise in deterring youth tobacco use, including among historically marginalized populations who may require additional support.

Effectiveness of an eHealth-Delivered Program to Empower People With Musculoskeletal Pain in Rural Australia: A Randomized Controlled Trial.

Our objective was to evaluate the effectiveness of a three-month physiotherapist-delivered eHealth physical activity program compared with usual care to improve function in adults with low back pain or knee osteoarthritis in rural Australia. This was a parallel, two-group, pragmatic, superiority, randomized controlled trial involving three- and six-month posttreatment follow-ups. There was a total of 156 adults with chronic nonspecific low back pain (n=97) or knee osteoarthritis (n=59) from rural Australia. The intervention involved an eHealth physical activity and an exercise program that included five to eight teleconsultations with a physiotherapist (primary time point three months) or usual care (eg, general practitioner, physiotherapy, and pain medication). The primary outcome was the Patient-Specific Functional Scale (0-30), with a three-point difference between groups being considered the minimum clinically important difference. Participants receiving the eHealth intervention (n=78) reported significantly greater and clinically worthwhile improvements in function (mean between-group difference 3.6; 95% confidence interval [CI] 1.3-5.9) compared to participants receiving usual care (n=78). Small but statistically significantly greater improvements in disability (7.2 of 100; 95% CI 2.1-12.3) and quality of life (4.5 of 100; 95% CI 0.0-9.0) also favored the eHealth group. No clinical or statistical differences between groups were found for the secondary outcomes of pain, coping skills, and physical activity levels. A physiotherapist-delivered eHealth intervention is effective and provides clinically meaningful improvements in function compared to usual care for people with musculoskeletal pain in rural communities. These findings highlight the potential for eHealth-based programs to improve access to evidence-based exercise interventions for people with musculoskeletal pain in rural communities.

EHealth, family-based interventions, and multilevel approaches to pediatric weight management: a scoping review.

This scoping review examines the current literature on technology-based, eHealth interventions that integrate community and clinical approaches for family-based pediatric weight management. Telehealth and eHealth interventions for weight management are increasingly commonplace; however, it is unclear in the current literature how family-based, pediatric, healthy-weight interventions integrate technology. Additionally, multilevel approaches to address childhood obesity, including working with clinical and community partners, are currently considered best practice and within the socioecological framework for sustainability of outcomes. Little is known how current family based pediatric healthy weight interventions integrate eHealth and multi-level approaches. Guided by Arksey and O'Malley's scoping review framework, a scoping literature review was conducted. Four databases were searched to identify studies conducted between 2010 and 2022 that addressed multilevel, family-based, pediatric weight management interventions that also integrated technology. Studies were excluded that did not include at least 2 of the 4 components and that did not include technology to some degree. A total of 15 articles were included in the scoping review. All articles included some type of technology in the intervention. Twelve articles included a family-based approach, and only 1 article fully used a holistic approach to family-based, pediatric weight management that included technology and integrated clinical and community approaches to address the complexity of childhood obesity. There are several family-based, pediatric weight management interventions that incorporate an eHealth component. There is a gap in the literature about programs that use both technology and integrate multilevel clinical and community approaches for treatment. Additionally, gaps exist in information about adolescent, family-based, weight management interventions, and there are opportunities for nutrition and dietetic professionals to become more involved with technological and multilevel approaches in family-based pediatric weight management.

Software Testing of eHealth Interventions: Existing Practices and the Future of an Iterative Strategy.

eHealth interventions are becoming a part of standard care, with software solutions increasingly created for patients and health care providers. Testing of eHealth software is important to ensure that the software realizes its goals. Software testing, which is comprised of alpha and beta testing, is critical to establish the effectiveness and usability of the software. In this viewpoint, we explore existing practices for testing software in health care settings. We scanned the literature using search terms related to eHealth software testing (eg, "health alpha testing," "eHealth testing," and "health app usability") to identify practices for testing eHealth software. We could not identify a single standard framework for software testing in health care settings; some articles reported frameworks, while others reported none. In addition, some authors misidentified alpha testing as beta testing and vice versa. There were several different objectives (ie, testing for safety, reliability, or usability) and methods of testing (eg, questionnaires, interviews) reported. Implementation of an iterative strategy in testing can introduce flexible and rapid changes when developing eHealth software. Further investigation into the best approach for software testing in health care settings would aid the development of effective and useful eHealth software, particularly for novice eHealth software developers.

The usability and effectiveness of eHealth and mHealth interventions that support self-management and healthcare transition in adolescents and young adults with chronic disease: A systematic review (Preprint)

The usability and effectiveness of eHealth and mHealth interventions that support self-management and healthcare transition in adolescents and young adults with chronic disease: A systematic review (Preprint)

EHealth interventions for psychiatry in Switzerland and Russia: a comparative study.

During the past decade, the use of digital technology to promote mental health has increased dramatically. Additionally, the consequences of the COVID-19 pandemic, such as travel restrictions and the disruption of face-to-face interactions, have led to an increase in the use of digital technologies. A wide variety of technologies have been developed, including messaging chatbots, virtual reality technologies, direct-to-consumer apps, and even technologies that are fully integrated into clinical care tools. The following qualitative study is based on the opinions of mental health specialists in both countries regarding the use of digital health technologies in psychiatry in Switzerland and Russia in 2019-2020. We investigate the state of adoption of digital technologies in the field of mental health, the meaning of such technologies, and the crucial factors in the use of such technologies in psychiatry. Health care professionals in both Russia and Switzerland are well aware of these technologies. However, the use of digital technology to promote mental health has taken different paths in these two health care settings.