[Apps for tinnitus? A systematic review on quality, intervention components, and behavior change techniques]. / Mit Apps gegen den Tinnitus? Ein systematisches Review zu Qualität, Interventionselementen und Techniken der Verhaltensänderung.

BACKGROUND: Various smartphone applications (apps) for people with tinnitus are available and promise tinnitus relief. Yet, it is difficult for people suffering from tinnitus and healthcare professionals to estimate their quality, potential, or risks. The current study aims to generate an overview of available tinnitus apps in the German language and to offer orientation for research and healthcare providers. METHOD: The most prominent stores were searched systematically (November 2020-April 2021; Google Play Store and Apple App Store). Apps specifically developed for tinnitus were evaluated by two independent raters using multiple approaches: a) a quality screening was performed using the German version of the Mobile App Rating Scale (MARS-G), b) intervention components were assessed using a newly developed list of categories, and c) implemented strategies for active tinnitus management were analyzed using behavior change techniques (BCTs). RESULTS: The search yielded 1073 apps, of which 21 apps were analyzed. The apps' overall quality as assessed by MARS­G was average (M = 3.37, SD = 039). A lot of apps offered sounds (n = 18) and information (n = 9) or assessed tinnitus characteristics (n = 13). Out of 93 BCTs, 24 were identified at least once. Only one app was evaluated in non-randomized trials. CONCLUSION: Although a variety of apps are available, most of them focus on a few intervention components (e.g., sounds or information). Therefore, apps do not exploit their potential to impart important evidence-based content for tinnitus management. The app evaluation using multiple approaches points out potential for improvement.

Feasibility and efficacy of a digital resilience training: A pilot study of the strengths-based training RESIST.

Background: Work-related stress is a risk factor for a number of adverse health and work outcomes. Resilience trainings are a promising approach for adequately dealing with work stress and keeping employees mentally healthy. However, results of previous resilience trainings have been heterogeneous, ranging from null findings to large effects. Existing digital resilience interventions show a lack of consistency in terms of an underlying theoretical framework and methods used to foster resilience. Positive Appraisal Style Theory of Resilience offers an innovative conceptualization of resilience. Strengths-based cognitive behavioral therapy is a corresponding therapeutically method reflecting resilience as a resource-oriented process of dealing with stress. Based on this background, a new hybrid web-and app-based digital resilience intervention for employees named RESIST was developed. Objective: The first aim of the study was to investigate the feasibility of the newly developed training RESIST regarding its usability, user behavior, user experience and motivation to use. Second, the study sought to explore preliminary effects of the intervention on reducing stress and enhancing resilience by conducting a pilot randomized controlled trial. Methods: The feasibility study was conducted in three phases. First, the usability of the app was investigated in a pre-test with five participants using a thinking-aloud method. Second, the preliminary efficacy of the training was examined in a pilot randomized controlled trial. A sample of 30 employees were randomized either to receive the resilience training (n = 15) or to be member of a control group (n = 15). The primary outcome was measuring perceived stress. Secondary outcomes included measures of resilience and depressive symptoms. Third, semi-structured interviews were undertaken with six participants of the resilience training group on training content, motivation for use, and user experience. Results: Overall, results indicate that RESIST can be a feasible training for resilience promotion and stress reduction with high user satisfaction. Analysis of covariance showed that, relative to controls, participants who received RESIST reported significantly lower stress scores at post-intervention (F1,27 = 16.91, p < 0.001; Cohen's d = 1.57; 95 % CI 0.71-2.43) than controls. Significant differences, with moderate-to-large effect sizes, were also detected for general resilience and various resilience factors. Conclusions: Results are promising and provide hope that a hybrid web- and app-based resilience intervention based on strengths-based cognitive behavioral therapy can have a positive impact on dealing adequately with stress and improve resilience of employees.

Quality and Adoption of COVID-19 Tracing Apps and Recommendations for Development: Systematic Interdisciplinary Review of European Apps.

BACKGROUND: Simulation study results suggest that COVID-19 contact tracing apps have the potential to achieve pandemic control. Concordantly, high app adoption rates were a stipulated prerequisite for success. Early studies on potential adoption were encouraging. Several factors predicting adoption rates were investigated, especially pertaining to user characteristics. Since then, several countries have released COVID-19 contact tracing apps. OBJECTIVE: This study's primary aim is to investigate the quality characteristics of national European COVID-19 contact tracing apps, thereby shifting attention from user to app characteristics. The secondary aim is to investigate associations between app quality and adoption. Finally, app features contributing to higher app quality were identified. METHODS: Eligible COVID-19 contact tracing apps were those released by national health authorities of European Union member states, former member states, and countries of the European Free Trade Association, all countries with comparable legal standards concerning personal data protection and app use voluntariness. The Mobile App Rating Scale was used to assess app quality. An interdisciplinary team, consisting of two health and two human-computer interaction scientists, independently conducted Mobile App Rating Scale ratings. To investigate associations between app quality and adoption rates and infection rates, Bayesian linear regression analyses were conducted. RESULTS: We discovered 21 national COVID-19 contact tracing apps, all demonstrating high quality overall and high-level functionality, aesthetics, and information quality. However, the average app adoption rate of 22.9% (SD 12.5%) was below the level recommended by simulation studies. Lower levels of engagement-oriented app design were detected, with substantial variations between apps. By regression analyses, the best-case adoption rate was calculated by assuming apps achieve the highest ratings. The mean best-case adoption rates for engagement and overall app quality were 39.5% and 43.6%, respectively. Higher adoption rates were associated with lower cumulative infection rates. Overall, we identified 5 feature categories (symptom assessment and monitoring, regularly updated information, individualization, tracing, and communication) and 14 individual features that contributed to higher app quality. These 14 features were a symptom checker, a symptom diary, statistics on COVID-19, app use, public health instructions and restrictions, information of burden on health care system, assigning personal data, regional updates, control over tracing activity, contact diary, venue check-in, chats, helplines, and app-sharing capacity. CONCLUSIONS: European national health authorities have generally released high quality COVID-19 contact tracing apps, with regard to functionality, aesthetics, and information quality. However, the app's engagement-oriented design generally was of lower quality, even though regression analyses results identify engagement as a promising optimization target to increase adoption rates. Associations between higher app adoption and lower infection rates are consistent with simulation study results, albeit acknowledging that app use might be part of a broader set of protective attitudes and behaviors for self and others. Various features were identified that could guide further engagement-enhancing app development.