Dropout Rate in Digital Health Interventions for the Prevention of Skin Cancer: Systematic Review, Meta-analysis, and Metaregression

Dropout rate in clinical trials of smartphone apps for diabetes management: A meta-analysis

Applicability of smartphone-based digital health in diabetes management still face challenges due tolow user retention or engagement. Thus, this systematic and meta-analysis aimed to estimate the dropout rate from the clinical trials. Search of literature was performedon 4 September 2023 through various databases (PubMed, Scilit, Scopus, Embase, and Web of Science). Those reporting clinical trials of smartphone apps for diabetic controls (either type 1 or type 2 diabetes mellitus) were screened and selected in accordance with PRISMA guideline. Of 5,429 identified records, as many as 36 studies were found eligible with a total of 3,327 patients in the intervention group. The overall dropout rate was 29.6 % (95 %CI: 25 %-34.3 %) with high heterogeneity (p-Het < 0.001;I2 = 84.84 %). Sample size, intervention duration, patients' age and gender, and cultural adaptation on the app appeared to be non-significant moderators (p > 0.05). In sub-group levels, notably high dropout rates were observed in studies performing cultural adaptation (34.6 %) and conducted in high-income countries (31.9 %). Given the high dropout rate, the engagement level toward diabetic management apps in real-world setting is expected to be low. High heterogeneity in this study, however, requires careful interpretation of the foregoing results. PROSPERO: CRD42023460365 (14 September 2023).

Effective Communication Supported by an App for Pregnant Women: Quantitative Longitudinal Study

BACKGROUND

In the medical field of obstetrics, communication plays a crucial role, and pregnant women, in particular, can benefit from interventions improving their self-reported communication behavior. Effective communication behavior can be understood as the correct transmission of information without misunderstanding, confusion, or losses. Although effective communication can be trained by patient education, there is limited research testing this systematically with an app-based digital intervention. Thus, little is known about the success of such a digital intervention in the form of a web-app, potential behavioral barriers for engagement, as well as the processes by which such a web-app might improve self-reported communication behavior.

OBJECTIVE

This study fills this research gap by applying a web-app aiming at improving pregnant women's communication behavior in clinical care. The goals of this study were to (1) uncover the potential risk factors for early dropout from the web-app and (2) investigate the social-cognitive factors that predict self-reported communication behavior after having used the web-app.

METHODS

In this study, 1187 pregnant women were recruited. They all started to use a theory-based web-app focusing on intention, planning, self-efficacy, and outcome expectancy to improve communication behavior. Mechanisms of behavior change as a result of exposure to the web-app were explored using stepwise regression and path analysis. Moreover, determinants of dropout were tested using logistic regression.

RESULTS

We found that dropout was associated with younger age (P=.014). Mechanisms of behavior change were consistent with the predictions of the health action process approach. The stepwise regression analysis revealed that action planning was the best predictor for successful behavioral change over the course of the app-based digital intervention (β=.331; P<.001). The path analyses proved that self-efficacy beliefs affected the intention to communicate effectively, which in turn, elicited action planning and thereby improved communication behavior (β=.017; comparative fit index=0.994; Tucker-Lewis index=0.971; root mean square error of approximation=0.055).

CONCLUSIONS

Our findings can guide the development and improvement of apps addressing communication behavior in the following ways in obstetric care. First, such tools would enable action planning to improve communication behavior, as action planning is the key predictor of behavior change. Second, younger women need more attention to keep them from dropping out. However, future research should build upon the gained insights by conducting similar internet interventions in related fields of clinical care. The focus should be on processes of behavior change and strategies to minimize dropout rates, as well as replicating the findings with patient safety measures.

TRIAL REGISTRATION

ClinicalTrials.gov identifier: NCT03855735; https://classic.clinicaltrials.gov/ct2/show/NCT03855735.

Development of a Multiplatform Tool for the Prevention of Prevalent Mental Health Pathologies in Adults: Protocol for a Randomized Control Trial

BACKGROUND

The prevalence of depression and anxiety has increased in recent years, with many individuals having trouble accessing mental health support. Smartphones have become an integral part of modern life, with apps offering new ways to deliver evidence-based self-help strategies to cope with common mental health symptoms. However, most of them do not have empirical evidence of their overall effectiveness or the effectiveness of their components, which could pose a risk for users.

OBJECTIVE

The aim of this study is to evaluate the effectiveness of the modules of evaluation, psychoeducation, and emotional regulation strategies in a multiplatform self-help mental health mobile app in the Maule region of Chile.

METHODS

A sample of 196 adults will be selected, who will be randomly assigned to different components of the app for a fixed period to assess its ability to reduce symptomatology.

RESULTS

The trial is not yet recruiting and is expected to end in October 2024. The first results are expected in April 2024.

CONCLUSIONS

This is the first study in Chile to develop and test the effectiveness of a mobile app to manage anxiety and depression symptoms in adults. The intervention proposed is based on evidence suggesting that the internet or remote intervention tools and self-management of prevalent symptomatology could be the future of mental health care systems in the digital era. If the effects of the intervention are positive, wide implementation in Chile and other Spanish-speaking countries could be possible in the future.

INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID)

PRR1-10.2196/52324.

Challenges in implementing cultural adaptations of digital health interventions

Differences in the access and use of digital health interventions are driven by culture, in addition to economic and physical factors. To avoid the systematic exclusion of traditionally underserved cultural groups, creating inclusive digital health interventions is essential. One way to achieve this is through cultural adaptations, defined as the systematic modification of an existing intervention that aligns with a target audience's cultural norms, beliefs, and values. In theory, cultural adaptations can potentially increase the reach and engagement of digital health interventions. However, the evidence of whether and how that is achieved is limited. Justifying, planning, and implementing an adaptation comes with various challenges and takes time and money. This perspective provides a critical overview of the field's current state and emphasizes the need for technology-specific frameworks that address when and how to culturally adapt digital health interventions.

Digital Health for Oncological Care

ABSTRACT

Digital health tools extend well beyond telemedicine, holding great potential to advance oncological care. We survey digital health and provide recommendations across the health continuum, tailoring them to oncology, including prevention, detection and diagnosis, and treatment and monitoring. Within the prevention realm, we review wellness technologies, cancer screening, mental health solutions, and digital biomarkers. For detection and diagnosis, we describe existing and emerging solutions for remote patient monitoring and various means to capture digital biomarkers, the "digital exam," and "digital outcomes." Treatment and monitoring solutions include telemedicine, chatbots, and digital therapeutics, which are also explored. We also discuss a host of technology enablers that are required for successful implementation and sustainment of digital health-enabled care. Our recommendations pertain to health care systems as well as companies that work with these systems or provide care to patients directly.

Empirical progression criteria thresholds for feasibility outcomes in HIV clinical trials: a methodological study

INTRODUCTION

Pilot and feasibility trials use predetermined thresholds for feasibility outcomes to decide if a larger trial is feasible. These thresholds may be derived from the literature, observational data, or clinical experience. The aim of this study was to determine empirical estimates for feasibility outcomes to inform future HIV pilot randomized trials.

METHODS

We conducted a methodological study of HIV clinical trials indexed in the past 5 years (2017-2021) in the PubMed database. We included trials of people living with HIV individually randomized to any type of intervention and excluded pilot trials and cluster randomized trials. Screening and data extraction were conducted in duplicate. We computed estimates for recruitment, randomization, non-compliance, lost to follow-up, discontinuation, and the proportion analyzed using a random effects meta-analysis of proportions and reported these estimates according to the following subgroups: use of medication, intervention type, trial design, income level, WHO region, participant type, comorbidities, and source of funding. We report estimates with 95% confidence intervals.

RESULTS

We identified 2122 studies in our search, of which 701 full texts were deemed relevant, but only 394 met our inclusion criteria. We found the following estimates: recruitment (64.1%; 95% CI 57.7 to 70.3; 156 trials); randomization (97.1%; 95% CI 95.8 to 98.3; 187 trials); non-compliance (3.8%; 95% CI 2.8 to 4.9; 216 trials); lost to follow-up (5.8%; 95% CI 4.9 to 6.8; 251 trials); discontinuation (6.5%; 95% CI 5.5 to 7.5; 215 trials); analyzed (94.2%; 95% CI 92.9 to 95.3; 367 trials). There were differences in estimates across most subgroups.

CONCLUSION

These estimates may be used to inform the design of HIV pilot randomized trials with careful consideration of variations due to some of the subgroups investigated.