Internet- and mobile-based interventions (IMI) offer an effective way to complement health care. Acceptance of IMI, a key facilitator of their implementation in routine care, is often low. Based on ...the Unified Theory of Acceptance and Use of Technology (UTAUT), this study validates and adapts the UTAUT to digital health care.
Following a systematic literature search, 10 UTAUT-grounded original studies (N = 1588) assessing patients' and health professionals' acceptance of IMI for different somatic and mental health conditions were included. All included studies assessed Performance Expectancy, Effort Expectancy, Social Influence, Facilitating Conditions and acceptance as well as age, gender, internet experience, and internet anxiety via self-report questionnaires. For the model validation primary data was obtained and analyzed using structural equation modeling.
The best fitting model (RMSEA = 0.035, SRMR = 0.029) replicated the basic structure of UTAUT's core predictors of acceptance. Performance Expectancy was the strongest predictor (γ = 0.68, p < .001). Internet anxiety was identified as an additional determinant of acceptance (γ = −0.07, p < .05) and moderated the effects of Social Influence (γ = 0.07, p < .05) and Effort Expectancy (γ = −0.05, p < .05). Age, gender and experience had no moderating effects.
Acceptance is a fundamental prerequisite for harnessing the full potential of IMI. The adapted UTAUT provides a powerful model identifying important factors – primarily Performance Expectancy - to increase the acceptance across patient populations and health professionals.
•Acceptance of digital health interventions, a key determinant of use, is low.•The Unified Theory of Acceptance and Use of Technology was successfully adapted to digital interventions.•Performance Expectancy is the most important determinant of acceptance.•Internet anxiety moderates the effects of Social Influence and Effort Expectancy.
Background
Social communication via instant messaging (IM) and social networking (SN) apps makes up a large part of the time that smartphone users spend on their devices. Previous research has ...indicated that the excessive use of these apps is positively associated with problematic smartphone use behaviors. In particular, image-based SN apps, such as Instagram (Facebook Inc) and Snapchat (Snap Inc), have been shown to exert stronger detrimental effects than those exerted by traditional apps, such as Facebook (Facebook Inc) and Twitter (Twitter Inc).
Objective
In this study, we investigated the correlation between individuals’ tendencies toward smartphone use disorder (SmUD) and objective measures of the frequency of smartphone usage. Additionally, we put to test the hypothesis that the pathway linking the frequency of actual smartphone usage to self-reported tendencies toward SmUD was mediated by the increased frequency of IM and SN app usage.
Methods
We recruited a sample of 124 adult smartphone users (females: 78/124, 62.9%; age: mean 23.84 years, SD 8.29 years) and collected objective information about the frequency of smartphone and SN app usage over 1 week. Participants also filled in a self-report measure for assessing the multiple components of tendencies toward SmUD. Bivariate associations were investigated by using Spearman correlation analyses. A parallel mediation analysis was conducted via multiple regression analysis.
Results
The frequency of smartphone usage, as well as the use of IM apps (Messenger, Telegram, and WhatsApp Facebook Inc), Facebook, and image-based apps (Instagram and Snapchat), had significant positive associations with at least 1 component of SmUD, and the cyberspace-oriented relationships factor exhibited the strongest associations overall. We found support for an indirect effect that linked actual smartphone usage to SmUD tendencies via the frequency of the use of image-based SN apps.
Conclusions
Our novel results shed light on the factors that promote SmUD tendencies and essentially indicate that image-based SN apps seem to be more strongly associated with problematic smartphone behaviors compared to IM apps and traditional SN apps, such as Facebook.
Digital cognitive behavioral therapy (i-CBT) interventions for the treatment of depression have been extensively studied and shown to be effective in the reduction of depressive symptoms. However, ...little is known about their effects on suicidal thoughts and behaviors (STB). Information on the impact of digital interventions on STB are essential for patients' safety because most digital interventions are self-help interventions without direct support options in case of a suicidal crisis. Therefore, we aim to conduct a meta-analysis of individual participant data (IPDMA) to investigate the effects of i-CBT interventions for depression on STB and to explore potential effect moderators.
Data will be retrieved from an established and annually updated IPD database of randomized controlled trials investigating the effectiveness of i-CBT interventions for depression in adults and adolescents. We will conduct a one-stage and a two-stage IPDMA on the effects of these interventions on STB. All types of control conditions are eligible. STB can be measured using specific scales (e.g., Beck scale suicide, BSS) or single items from depression scales (e.g., item 9 of the PHQ-9) or standardized clinical interviews. Multilevel linear regression will be used for specific scales, and multilevel logistic regression will be used for treatment response or deterioration, operationalized as a change in score by at least one quartile from baseline. Exploratory moderator analyses will be conducted at participant, study, and intervention level. Two independent reviewers will assess the risk of bias using the Cochrane Risk of Bias Tool 2.
This IPDMA will harness the available data to assess the effects (response and deterioration) of i-CBT interventions for depression interventions on STB. Information about changes in STB is essential to estimate patients' safety when engaging in digital treatment formats.
We will pre-register this study with the open science framework after article acceptance to ensure consistency between online registration and the published trial protocol.
Objectives
Internet‐ and mobile‐based interventions (IMIs) offer the opportunity to deliver mental health treatments on a large scale. This randomized controlled trial evaluated the efficacy of an ...unguided IMI (StudiCare SAD) for university students with social anxiety disorder (SAD).
Methods
University students (N = 200) diagnosed with SAD were randomly assigned to an IMI or a waitlist control group (WLC) with full access to treatment as usual. StudiCare SAD consists of nine sessions. The primary outcome was SAD symptoms at posttreatment (10 weeks), assessed via the Social Phobia Scale (SPS) and the Social Interaction Anxiety Scale (SIAS). Secondary outcomes included depression, quality of life, fear of positive evaluation, general psychopathology, and interpersonal problems.
Results
Results indicated moderate to large effect sizes in favor of StudiCare SAD compared with WLC for SAD at posttest for the primary outcomes (SPS: d = 0.76; SIAS: d = 0.55, p < 0.001). Effects on all secondary outcomes were significant and in favor of the intervention group.
Conclusion
StudiCare SAD has proven effective in reducing SAD symptoms in university students. Providing IMIs may be a promising way to reach university students with SAD at an early stage with an effective treatment.
Summary
A large number of mobile health applications claiming to target insomnia are available in commercial app stores. However, limited information on the quality of these mobile health ...applications exists. The present study aimed to systematically search the European Google Play and Apple App Store for mobile health applications targeting insomnia, and evaluate the quality, content, evidence base and potential therapeutic benefit. Eligible mobile health applications were evaluated by two independent reviewers using the Mobile Application Rating Scale‐German, which ranges from 1 – inadequate to 5 – excellent. Of 2236 identified mobile health applications, 53 were included in this study. Most mobile health applications (68%) had a moderate overall quality. Concerning the four main subscales of the Mobile Application Rating Scale‐German, functionality was rated highest (M = 4.01, SD = 0.52), followed by information quality (M = 3.49, SD = 0.72), aesthetics (M = 3.31, SD = 1.04) and engagement (M = 3.02, SD = 1.03). While scientific evidence was identified for 10 mobile health applications (19%), only one study employed a randomized controlled design. Fifty mobile health applications featured sleep hygiene/psychoeducation (94%), 27 cognitive therapy (51%), 26 relaxation methods (49%), 24 stimulus control (45%), 16 sleep restriction (30%) and 24 sleep diaries (45%). Mobile health applications may have the potential to improve the care of insomnia. Yet, data on the effectiveness of mobile health applications are scarce, and this study indicates a large variance in the quality of the mobile health applications. Thus, independent information platforms are needed to provide healthcare seekers and providers with reliable information on the quality and content of mobile health applications.
Background: Mobile health applications (apps) are considered to complement traditional psychological treatments for Post-Traumatic Stress Disorder (PTSD). However, the use for clinical practice and ...quality of available apps is unknown.
Objective: To assess the general characteristics, therapeutic background, content, and quality of apps for PTSD and to examine their concordance with established PTSD treatment and self-help methods.
Method: A web crawler systematically searched for apps targeting PTSD in the British Google Play and Apple iTunes stores. Two independent researchers rated the apps using the Mobile App Rating Scale (MARS). The content of high-quality apps was checked for concordance with psychological treatment and self-help methods extracted from current literature on PTSD treatment.
Results: Out of 555 identified apps, 69 met the inclusion criteria. The overall app quality based on the MARS was medium (M = 3.36, SD = 0.65). Most apps (50.7%) were based on cognitive behavioural therapy and offered a wide range of content, including established psychological PTSD treatment methods such as processing of trauma-related emotions and beliefs, relaxation exercises, and psychoeducation. Notably, data protection and privacy standards were poor in most apps and only one app (1.4%) was scientifically evaluated in a randomized controlled trial.
Conclusions: High-quality apps based on established psychological treatment techniques for PTSD are available in commercial app stores. However, users are confronted with great difficulties in identifying useful high-quality apps and most apps lack an evidence-base. Commercial distribution channels do not exploit the potential of apps to complement the psychological treatment of PTSD.
PURPOSE OF REVIEWInternet and mobile-based interventions (IMI) can be used as online delivered forms of psychotherapeutic mental health treatments. These interventions can be an effective as well as ...time and cost-efficient treatment with the potential to scale up mental healthcare. In this review, we map implementation possibilities into routine mental healthcare settings and provide the most recent evidence.
RECENT FINDINGSFourteen articles on digital mental healthcare approaches published in the last 18 months were included. Despite the limited number, the studies provide evidence for the effectiveness of IMI in treating inpatients and outpatients with various disorders in different mental healthcare settings. IMI were investigated as stand-alone interventions, in combination with other treatment forms (blended-care), or as aftercare.
SUMMARYAlthough there is encouraging evidence for the effectiveness of IMI in mental healthcare settings, several limitations have to be considered. The small number of studies conducted within the healthcare system, especially with inpatient samples, calls for more collaboration between researchers and clinical practitioners to unravel barriers and develop efficient protocols for the integration into routine care. Nonetheless, IMI are a promising tool for the endeavour of closing the treatment gap and should, therefore, be further explored in varying settings.
The number of mobile health apps (MHAs), which are developed to promote healthy behaviors, prevent disease onset, manage and cure diseases, or assist with rehabilitation measures, has exploded. App ...store star ratings and descriptions usually provide insufficient or even false information about app quality, although they are popular among end users. A rigorous systematic approach to establish and evaluate the quality of MHAs is urgently needed. The Mobile App Rating Scale (MARS) is an assessment tool that facilitates the objective and systematic evaluation of the quality of MHAs. However, a German MARS is currently not available.
The aim of this study was to translate and validate a German version of the MARS (MARS-G).
The original 19-item MARS was forward and backward translated twice, and the MARS-G was created. App description items were extended, and 104 MHAs were rated twice by eight independent bilingual researchers, using the MARS-G and MARS. The internal consistency, validity, and reliability of both scales were assessed. Mokken scale analysis was used to investigate the scalability of the overall scores.
The retranslated scale showed excellent alignment with the original MARS. Additionally, the properties of the MARS-G were comparable to those of the original MARS. The internal consistency was good for all subscales (ie, omega ranged from 0.72 to 0.91). The correlation coefficients (r) between the dimensions of the MARS-G and MARS ranged from 0.93 to 0.98. The scalability of the MARS (H=0.50) and MARS-G (H=0.48) were good.
The MARS-G is a reliable and valid tool for experts and stakeholders to assess the quality of health apps in German-speaking populations. The overall score is a reliable quality indicator. However, further studies are needed to assess the factorial structure of the MARS and MARS-G.
Mental health (MH) problems in youth are prevalent, burdening, and frequently persistent. Despite the existence of effective treatment, the uptake of professional help is low, particularly due to ...attitudinal barriers.
This study evaluated the effectiveness and acceptability of 2 video-based microinterventions aimed at reducing barriers to MH treatment and increasing the likelihood of seeking professional help in young people.
This study was entirely web based and open access. The interventions addressed 5 MH problems: generalized anxiety disorder, depression, bulimia, nonsuicidal self-injury, and problematic alcohol use. Intervention 1 aimed to destigmatize and improve MH literacy, whereas intervention 2 aimed to induce positive outcome expectancies regarding professional help seeking. Of the 2435 participants who commenced the study, a final sample of 1394 (57.25%) participants aged 14 to 29 years with complete data and sufficient durations of stay on the video pages were randomized in a fully automated manner to 1 of the 5 MH problems and 1 of 3 conditions (control, intervention 1, and intervention 2) in a permuted block design. After the presentation of a video vignette, no further videos were shown to the control group, whereas a second, short intervention video was presented to the intervention 1 and 2 groups. Intervention effects on self-reported potential professional help seeking (primary outcome), stigma, and attitudes toward help seeking were examined using analyses of covariance across and within the 5 MH problems. Furthermore, we assessed video acceptability.
No significant group effects on potential professional help seeking were found in the total sample (F
=0.99; P=.37). However, the groups differed significantly with regard to stigma outcomes and the likelihood of seeking informal help (F
=3.75; P=.02). Furthermore, separate analyses indicated substantial differences in intervention effects among the 5 MH problems.
Interventions to promote help seeking for MH problems may require disorder-specific approaches. The study results can inform future research and public health campaigns addressing adolescents and young adults.
German Clinical Trials Register DRKS00023110; https://drks.de/search/de/trial/DRKS00023110.
Smart sensors and smartphones are becoming increasingly prevalent. Both can be used to gather environmental data (e.g., noise). Importantly, these devices can be connected to each other as well as to ...the Internet to collect large amounts of sensor data, which leads to many new opportunities. In particular, mobile crowdsensing techniques can be used to capture phenomena of common interest. Especially valuable insights can be gained if the collected data are additionally related to the time and place of the measurements. However, many technical solutions still use monolithic backends that are not capable of processing crowdsensing data in a flexible, efficient, and scalable manner. In this work, an architectural design was conceived with the goal to manage geospatial data in challenging crowdsensing healthcare scenarios. It will be shown how the proposed approach can be used to provide users with an interactive map of environmental noise, allowing tinnitus patients and other health-conscious people to avoid locations with harmful sound levels. Technically, the shown approach combines cloud-native applications with Big Data and stream processing concepts. In general, the presented architectural design shall serve as a foundation to implement practical and scalable crowdsensing platforms for various healthcare scenarios beyond the addressed use case.
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