The effect of the Yara smartphone application on anxiety, sleep quality, and suicidal thoughts in patients with major depressive disorder in Iran: a randomized controlled trial.

BACKGROUND: Depression is one of the most common mental disorders that leads to anxiety, sleep disturbances, and suicidal thoughts. Due to the high cost of treatment and the reluctance of many patients to seek medical help, major depressive disorder (MDD) is becoming more prevalent. Therefore, alternative methods like smartphone applications can help prevent and improve depression symptoms. The present study aimed to determine the effect of the newly developed Yara smartphone application on anxiety, sleep quality, and suicidal thoughts in patients with MDD. METHODS: This randomized controlled trial with a pretest-posttest design was conducted on Iranian patients with MDD in 2022. Sixty-four patients were recruited using convenience sampling and randomly assigned to two control and intervention groups. The intervention was conducted using the Yara smartphone application for three months. Data were collected using the Spielberger State-Trait Anxiety Inventory (STAI), Pittsburgh Sleep Quality Index (PSQI), and Beck Scale for Suicidal Ideation (BSSI). Data were first entered into IBM SPSS Statistics for Windows, version 22 (IBM Corp., Armonk, N.Y., USA) and then analyzed using descriptive and analytical statistics. RESULTS: There was no statistically significant difference in the mean score of anxiety and sleep quality between the intervention and control groups before the intervention (p ≥ .05). However, this difference in the mean score of anxiety and sleep quality was statistically significant in the two groups after the intervention (p < .05). The results showed no statistically significant difference in the mean score of suicidal thoughts between the two groups before and after the intervention (p ≥ .05). The use of the Yara smartphone application had a significant positive effect on anxiety and sleep quality in depressed patients (p < .001). At the same time, it had no significant effect on suicidal thoughts (p ≥ .05). CONCLUSION: Considering the positive effect of using the Yara smartphone application on reducing anxiety and improving sleep quality in depressed patients, this application can help alleviate the problems of depressed patients alongside existing treatment methods. Thus, this application is recommended for this group of patients in psychiatric clinics and departments. The Yara application's effectiveness was not approved on suicidal thoughts in this study so that further investigation would be necessary. TRIAL REGISTRATION: Iranian Registry of Clinical Trial approval code (IRCT# IRCT20131112015390N7).

Exploring weight-related self-monitoring as a potential risk factor for eating disorder symptoms in adults - A systematic review and meta-analysis.

OBJECTIVE: Weight-related self-monitoring (WRSM), which involves the intentional tracking of body weight metrics, has been considered a potential risk factor for eating disorders. Therefore, the aim of this study was to systematically summarize the current state of the literature and to quantify the possible association between WRSM and eating disorder symptoms in adults. METHOD: Preregistration was carried out using PROSPERO (ID CRD42022366133). The PubMed, PsycInfo, and Web of Science databases were searched until December 21, 2023. A study had to be 1) be available in English or German, 2) be peer-reviewed and quantitative, 3) include adult participants (age ≥18 years) from the general population, 4) assess eating disorder symptoms via at least one of the following questionnaires: EDI, EAT, FEV, TFEQ, DEBQ, EDE-Q, Munich ED-Quest or IEG, and 5) include WRSM. Data analyses included descriptive analyses and three-level meta-analysis, corrected for correlations, for the global score and the different subscales of the eating disorder questionnaires. RESULTS: A total of 28 studies (n = 17,370 participants), with an overall fair methodological quality, were included in the systematic review. Out of these studies, nine studies with n = 13,507 participants were ultimately analyzed in the meta-analysis. The three-level meta-analysis did not reveal a significant association between WRSM and the eating disorder global score (r = 0.13, 95% CI [-0.02, 0.28]; p = 0.08), with this pattern also being evident in the subgroup analysis (diet monitoring). DISCUSSION: WRSM alone does not generally translate into an increased risk of disordered eating symptoms in the general population. We assume that individual factors are likely to determine whether the use of WRSM could lead to eating disorder symptoms. These factors should be accounted for in future research.

Smartphone-based scans of palate models of newborns with cleft lip and palate: Outlooks for three-dimensional image capturing and machine learning plate tool.

OBJECTIVES: To evaluate the performance of smartphone scanning applications (apps) in acquiring 3D meshes of cleft palate models. Secondarily, to validate a machine learning (ML) tool for computing automated presurgical plate (PSP). MATERIALS AND METHODS: We conducted a comparative analysis of two apps on 15 cleft palate models: five unilateral cleft lip and palate (UCLP), five bilateral cleft lip and palate (BCLP) and five isolated cleft palate (ICP). The scans were performed with and without a mirror to simulate intraoral acquisition. The 3D reconstructions were compared to control reconstructions acquired using a professional intraoral scanner using open-source software. RESULTS: Thirty 3D scans were acquired by each app, totalling 60 scans. The main findings were in the UCLP sample, where the KIRI scans without a mirror (0.22 ± 0.03 mm) had a good performance with a deviation from the ground truth comparable to the control group (0.14 ± 0.13 mm) (p = .653). Scaniverse scans with a mirror showed the lowest accuracy of all the samples. The ML tool was able to predict the landmarks and automatically generate the plates, except in ICP models. KIRI scans' plates showed better performance with (0.22 ± 0.06 mm) and without mirror (0.18 ± 0.05 mm), being comparable with controls (0.16 ± 0.08 mm) (p = .954 and p = .439, respectively). CONCLUSIONS: KIRI Engine performed better in scanning UCLP models without a mirror. The ML tool showed a high capability for morphology recognition and automated PSP generation.

Supportive eHealth Technologies and Their Effects on Physical Functioning and Quality of Life for People With Lung Cancer: Systematic Review.

BACKGROUND: Despite advancements in treatment and early diagnosis, people with lung cancer are not living as long as those with other cancers. The more common symptoms of lung cancer, such as breathlessness, fatigue, and depression, can be alleviated by improving patients' physical functioning. Therefore, good symptom management and improved health-related quality of life (HRQoL) are priorities in this patient group. However, current health care services have limited capacity to provide this support. One way to address this issue of health care resources is to empower patients to self-manage their condition using eHealth technologies. OBJECTIVE: The purpose of this review was to identify and assess available research on technologies that support persons with lung cancer to improve or maintain their physical functioning, HRQoL, or both. METHODS: Six databases-PubMed, Web of Science, CINAHL, MEDLINE, SPORTDiscus, and PsycINFO-were searched from January 1, 1990, to April 30, 2023. Studies were suitable for inclusion if the participants included people with lung cancer aged >18 years who had been exposed to a physical activity, exercise, or training intervention that was delivered via an electronic or web-based application with or without a comparator. Furthermore, the study had to report on the impact of the intervention on physical functioning and HRQoL. Studies that focused on telemedicine without a digital intervention were excluded. The Grading of Recommendations Assessment, Development, and Evaluation system was used to assess the quality of the included papers. Due to the heterogeneity of the studies, a narrative synthesis was undertaken. RESULTS: This review is reported in accordance with the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) guidelines. A total of 794 papers were initially identified through our search, of which, after screening, 8 (1%) were confirmed suitable for inclusion in the review. As 2 (25%) of the 8 papers reported on different stages of the same study, we included only 7 studies in our analysis. The studies were undertaken between 2010 and 2018 across multiple countries and aimed to develop a technology and test its feasibility or acceptance. The 7 technologies identified included web-based applications, mobile apps, and gaming consoles. The studies demonstrated impact on walking distance, muscle strength, balance, dyspnea symptoms, and cancer-related fatigue. HRQoL scores also showed improvement. CONCLUSIONS: The findings indicate that eHealth technologies can positively impact physical functioning and well-being for people with lung cancer, but there are limited studies that demonstrate the impact of these digital interventions over longer periods. None of the studies reported on the implementation or adoption of a mobile health or eHealth intervention in routine clinical practice, highlighting the need for further research in this area. TRIAL REGISTRATION: PROSPERO CRD42023414094; https://tinyurl.com/39hhbwyx.

Data Visualization Preferences in Remote Measurement Technology for Individuals Living With Depression, Epilepsy, and Multiple Sclerosis: Qualitative Study.

BACKGROUND: Remote measurement technology (RMT) involves the use of wearable devices and smartphone apps to measure health outcomes in everyday life. RMT with feedback in the form of data visual representations can facilitate self-management of chronic health conditions, promote health care engagement, and present opportunities for intervention. Studies to date focus broadly on multiple dimensions of service users' design preferences and RMT user experiences (eg, health variables of perceived importance and perceived quality of medical advice provided) as opposed to data visualization preferences. OBJECTIVE: This study aims to explore data visualization preferences and priorities in RMT, with individuals living with depression, those with epilepsy, and those with multiple sclerosis (MS). METHODS: A triangulated qualitative study comparing and thematically synthesizing focus group discussions with user reviews of existing self-management apps and a systematic review of RMT data visualization preferences. A total of 45 people participated in 6 focus groups across the 3 health conditions (depression, n=17; epilepsy, n=11; and MS, n=17). RESULTS: Thematic analysis validated a major theme around design preferences and recommendations and identified a further four minor themes: (1) data reporting, (2) impact of visualization, (3) moderators of visualization preferences, and (4) system-related factors and features. CONCLUSIONS: When used effectively, data visualizations are valuable, engaging components of RMT. Easy to use and intuitive data visualization design was lauded by individuals with neurological and psychiatric conditions. Apps design needs to consider the unique requirements of service users. Overall, this study offers RMT developers a comprehensive outline of the data visualization preferences of individuals living with depression, epilepsy, and MS.

The Acceptability, Engagement, and Feasibility of Mental Health Apps for Marginalized and Underserved Young People: Systematic Review and Qualitative Study.

BACKGROUND: Smartphone apps may provide an opportunity to deliver mental health resources and interventions in a scalable and cost-effective manner. However, young people from marginalized and underserved groups face numerous and unique challenges to accessing, engaging with, and benefiting from these apps. OBJECTIVE: This study aims to better understand the acceptability (ie, perceived usefulness and satisfaction with an app) and feasibility (ie, the extent to which an app was successfully used) of mental health apps for underserved young people. A secondary aim was to establish whether adaptations can be made to increase the accessibility and inclusivity of apps for these groups. METHODS: We conducted 2 sequential studies, consisting of a systematic literature review of mental health apps for underserved populations followed by a qualitative study with underserved young male participants (n=20; age: mean 19). Following the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) guidelines, an electronic search of 5 databases was conducted in 2021. The search yielded 18,687 results, of which 14 articles met the eligibility criteria. RESULTS: The included studies comprised a range of groups, including those affected by homelessness, having physical health conditions, living in low- and middle-income countries, and those with sexual and gender minority identities. Establishing and maintaining user engagement was a pervasive challenge across mental health apps and populations, and dropout was a reported problem among nearly all the included studies. Positive subjective reports of usability, satisfaction, and acceptability were insufficient to determine users' objective engagement. CONCLUSIONS: Despite the significant amount of funding directed to the development of mental health apps, juxtaposed with only limited empirical evidence to support their effectiveness, few apps have been deliberately developed or adapted to meet the heterogeneous needs of marginalized and underserved young people. Before mental health apps are scaled up, a greater understanding is needed of the types of services that more at-risk young people and those in limited-resource settings prefer (eg, standard vs digital) followed by more rigorous and consistent demonstrations of acceptability, effectiveness, and cost-effectiveness. Adopting an iterative participatory approach by involving young people in the development and evaluation process is an essential step in enhancing the adoption of any intervention, including apps, in "real-world" settings and will support future implementation and sustainability efforts to ensure that marginalized and underserved groups are reached. TRIAL REGISTRATION: PROSPERO CRD42021254241; https://www.crd.york.ac.uk/prospero/display_record.php?RecordID=254241.

Relative Efficacy of an Acceptance and Commitment Therapy-Based Smartphone App with a Standard US Clinical Practice Guidelines-Based App for Smoking Cessation in Dual Users of Combustible and Electronic Cigarettes: Secondary Findings from a Randomized Trial.

BACKGROUND: While smartphone apps for smoking cessation have shown promise for combustible cigarette smoking cessation, their efficacy in helping dual users of combustible and electronic cigarettes (e-cigarettes) to quit cigarettes remains unknown. This study utilized data from a randomized trial to determine if an Acceptance and Commitment Therapy (ACT)-based app (iCanQuit) was more efficacious than a US Clinical Practice Guidelines-based app (QuitGuide) for combustible cigarette smoking cessation among 575 dual users. METHODS: The primary cessation outcome was self-reported, complete-case 30-day abstinence from combustible cigarettes at 12 months. Logistic regression assessed the interaction between dual use and treatment arm on the primary outcome in the full trial sample (N = 2,415). We then compared the primary outcome between arms among dual users (iCanQuit: n = 297; QuitGuide: n = 178). Mediation analyses were conducted to explore mechanisms of action of the intervention: acceptance of cues to smoke and app engagement. Results: There was an interaction between dual use of combustible and e-cigarettes and treatment arm on the primary outcome (p = 0.001). Among dual users, 12-month abstinence from cigarettes did not differ between arms (23% for iCanQuit vs. 27% for QuitGuide, p = 0.40). Mediation analysis revealed a significant positive indirect effect of the iCanQuit app on 12-month abstinence from cigarettes through acceptance of emotions that cue smoking (p = 0.004). CONCLUSIONS: Findings from this study of dual users of combustible and e-cigarettes showed no evidence of a difference in quit rates between arms. Acceptance of emotions that cue smoking is a potential mechanism contributing to cigarette smoking abstinence among dual users.

Target-user preferences, motivations, and acceptance for a dialectical behaviour therapy smartphone application for eating disorders.

PURPOSE: Evidence shows that dialectical behavioural therapy (DBT) is efficacious for eating disorders (ED), yet few people have access to specialized treatments like DBT. Translating key DBT skills for delivery via a smartphone application may broaden the dissemination of evidence-based interventions. However, prior to developing a DBT-based app, it is crucial to gather information on target-user needs and preferences. Assessing overall acceptance and identifying predictors of acceptance, informed by the UTAUT framework, is also important. This process ensures not only a demand for such an app, but also that users receive content and features tailored to their needs. METHOD: This study aimed to understand target-user preferences of DBT-based apps for EDs by assessing willingness to engage, overall acceptance levels, and preferred functionality/content delivery modes (n = 326 symptomatic participants). RESULTS: Eighty-eight percent indicated they would be willing to use a DBT-based ED app if it were available. Acceptance levels of a DBT app were high (64%), which was uniquely predicted by performance expectancy (perceptions of how beneficial an intervention is) and facilitating conditions (expectations of technological infrastructure and support in interventions) in path analysis. Content perceived as important to contain were emotion regulation techniques, tailored intervention strategies, and psychoeducation. CONCLUSION: Findings generate important information about target-user preferences of a DBT-based app for EDs, highlighting necessary design principles for apps of this kind. Level of evidence Level V, cross-sectional descriptive study.

[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.

A novel smartphone App to support the clinical practice of pediatric ophthalmology and strabismus: the validation of visual acuity tests.

This study is aimed at describing the TreC Oculistica novel smartphone App that facilitated the clinical practice of pediatric ophthalmology and strabismus during the COVID-19 pandemic and at reporting on the validation of visual acuity tests in a home setting. The Trec Oculistica smartphone App was prescribed to eligible patients at the Pediatric Ophthalmology and Strabismus Clinic, Ophthalmology Unit of Rovereto Hospital, between September 2020 and March 2022. Four key indicators were identified for monitoring visual and visuo-motor functions remotely: visual acuity, ocular motility, head posture, and color vision. Clinicians selected few mobile applications (iOS, Android) and printable materials within the Trec Oculistica App: the Snellen Chart Visual Acuity App, the 9Gaze App, the eyeTilt App, the Color Blind test App, the LEA Symbols pdf, and the Snellen Chart pdf. All patients, aged 4 and older, were screened at home for visual acuity at 3 m and later in the clinic (LEA Symbols cabinet or Snellen computerized optotype). The 9Gaze, the eyeTilt, and the Color Blind test Apps were only recommended to a subset of patients based on clinical suspicion or diagnosis. The Wilcoxon signed rank sum test and weighted Cohen's kappa coefficient were applied to compare pairs of scores from different settings. The Trec Oculistica App was downloaded and activated by 97 patients or their caregiver. 40 patients were tested at home using the 9Gaze App, 7 used the eyeTilt App, and 11 used the Color-Blind test App. Families reported that all the Apps were easy and intuitive to use; clinicians reported that measurements were reliable. 82 eyes of 41 patients (mean age 5.2 years, SD ± 0.4, range 4.4-6.1) were tested for visual acuity using the self-administered LEA Symbols pdf. 92 eyes of 46 patients (mean age 11.6 years, SD ± 5.2, range 6-35) were evaluated using the self-administered Snellen Chart Visual Acuity App or the Snellen Chart pdf. Home median visual acuity score was statistically different from that registered in clinical setting for both the LEA Symbols pdf (P-value = 0.0074) and the Snellen Chart App and pdf (P-value = 0.0001). The strength of agreement was 0.12 (slight) for the LEA Symbols pdf, 0.50 (moderate) for the Snellen Chart Visual Acuity App, and 0.69 (substantial) for the Snellen Chart pdf. CONCLUSION: The novel TreC Oculistica smartphone App was a useful tool for facilitating the clinical practice of pediatric ophthalmology and strabismus during the COVID-19 pandemic. In the follow-up of strabismus patients and patients with suspected inherited retinal diseases, the 9Gaze, eyeTilt, and Color Blind test applications were deemed to be intuitive and easy to use by families and were considered reliable by clinicians. In a home setting, visual acuity tested by means of Snellen Charts was moderately congruent with the in-office examination. On the contrary, agreement was poor in younger children tested with the LEA Symbols pdf. WHAT IS KNOWN: • Teleophthalmology enables clinicians to evaluate patients' ocular diseases remotely and various tools are helpful for screening, follow-ups and treatment. • Smartphones can currently be used to obtain ocular images and vision measurements of patients' eyes and this information can be shared with the ophthalmologist for further evaluations and medical management (mhealth). WHAT IS NEW: • Smartphone Apps can be successfully used in a hybrid teleophthalmology service concerning first visits and follow-ups. • Apps and printable materials are easy, intuitive to use for patients and  also reliable for  clinicians.

Predicting smoking cessation, reduction and relapse six months after using the Stop-Tabac app for smartphones: a machine learning analysis.

BACKGROUND: An analysis of predictors of smoking behaviour among users of smoking cessation apps can provide useful information beyond what is already known about predictors in other contexts. Therefore, the aim of the present study was to identify the best predictors of smoking cessation, smoking reduction and relapse six months after starting to use the smartphone app Stop-Tabac. METHOD: Secondary analysis of 5293 daily smokers from Switzerland and France who participated in a randomised trial testing the effectiveness of this app in 2020, with follow-up at one and six months. Machine learning algorithms were used to analyse the data. The analyses for smoking cessation included only the 1407 participants who responded after six months; the analysis for smoking reduction included only the 673 smokers at 6-month follow-up; and the analysis for relapse at 6 months included only the 502 individuals who had quit smoking after one month. RESULTS: Smoking cessation after 6 months was predicted by the following factors (in this order): tobacco dependence, motivation to quit smoking, frequency of app use and its perceived usefulness, and nicotine medication use. Among those who were still smoking at follow-up, reduction in cigarettes/day was predicted by tobacco dependence, nicotine medication use, frequency of app use and its perceived usefulness, and e-cigarette use. Among those who had quit smoking after one month, relapse after six months was predicted by intention to quit, frequency of app use, perceived usefulness of the app, level of dependence and nicotine medication use. CONCLUSION: Using machine learning algorithms, we identified independent predictors of smoking cessation, smoking reduction and relapse. Studies on the predictors of smoking behavior among users of smoking cessation apps may provide useful insights for the future development of these apps and future experimental studies. CLINICAL TRIAL REGISTRATION: ISRCTN Registry: ISRCTN11318024, 17 May 2018. http://www.isrctn.com/ISRCTN11318024 .

Can a Single Variable Predict Early Dropout From Digital Health Interventions? Comparison of Predictive Models From Two Large Randomized Trials.

BACKGROUND: A single generalizable metric that accurately predicts early dropout from digital health interventions has the potential to readily inform intervention targets and treatment augmentations that could boost retention and intervention outcomes. We recently identified a type of early dropout from digital health interventions for smoking cessation, specifically, users who logged in during the first week of the intervention and had little to no activity thereafter. These users also had a substantially lower smoking cessation rate with our iCanQuit smoking cessation app compared with users who used the app for longer periods. OBJECTIVE: This study aimed to explore whether log-in count data, using standard statistical methods, can precisely predict whether an individual will become an iCanQuit early dropout while validating the approach using other statistical methods and randomized trial data from 3 other digital interventions for smoking cessation (combined randomized N=4529). METHODS: Standard logistic regression models were used to predict early dropouts for individuals receiving the iCanQuit smoking cessation intervention app, the National Cancer Institute QuitGuide smoking cessation intervention app, the WebQuit.org smoking cessation intervention website, and the Smokefree.gov smoking cessation intervention website. The main predictors were the number of times a participant logged in per day during the first 7 days following randomization. The area under the curve (AUC) assessed the performance of the logistic regression models, which were compared with decision trees, support vector machine, and neural network models. We also examined whether 13 baseline variables that included a variety of demographics (eg, race and ethnicity, gender, and age) and smoking characteristics (eg, use of e-cigarettes and confidence in being smoke free) might improve this prediction. RESULTS: The AUC for each logistic regression model using only the first 7 days of log-in count variables was 0.94 (95% CI 0.90-0.97) for iCanQuit, 0.88 (95% CI 0.83-0.93) for QuitGuide, 0.85 (95% CI 0.80-0.88) for WebQuit.org, and 0.60 (95% CI 0.54-0.66) for Smokefree.gov. Replacing logistic regression models with more complex decision trees, support vector machines, or neural network models did not significantly increase the AUC, nor did including additional baseline variables as predictors. The sensitivity and specificity were generally good, and they were excellent for iCanQuit (ie, 0.91 and 0.85, respectively, at the 0.5 classification threshold). CONCLUSIONS: Logistic regression models using only the first 7 days of log-in count data were generally good at predicting early dropouts. These models performed well when using simple, automated, and readily available log-in count data, whereas including self-reported baseline variables did not improve the prediction. The results will inform the early identification of people at risk of early dropout from digital health interventions with the goal of intervening further by providing them with augmented treatments to increase their retention and, ultimately, their intervention outcomes.

Characterizing Consumer Smartphone Apps for Virtual Reality-Based Exposure Therapy: Content Analysis.

BACKGROUND: In vivo exposure therapy is the most effective treatment for phobias but is often impractical. Virtual reality exposure therapy (VRET) can help overcome critical barriers to in vivo exposure therapy. However, accessible mobile software related to VRET is not well understood. OBJECTIVE: The purpose of our study is to describe the landscape of accessible smartphone apps with potential utility for clinical VRET. METHODS: We conducted a content analysis of publicly available smartphone apps related to virtual reality on the Google Play Store and the Apple App Store as of March 2020. RESULTS: The initial search yielded 525 apps, with 84 apps (52 on the Google Play Store and 32 on the Apple App Store) included for analysis. The most common phobic stimulus depicted was bodies of water or weather events (25/84, 29.8%), followed by heights (24/84, 28.6%), and animals (23/84, 27.4%). More than half of the apps were visually abstract (39/84, 53.5%). Most apps were free to use (48/84, 57.1%), while the rest were free to try (22/84, 26.2%) or required payment for use (14/84, 16.7%), with the highest cost for use being US $6. The average overall app rating was 2.9 stars out of 5, but the number of ratings ranged from 0 to 49,233. None of the 84 apps advertised compliance with the Health Insurance Portability and Accountability Act, offered the ability to monitor data, provided clinician control over variables in the app experiences, or explicitly stated use by or development with clinicians. CONCLUSIONS: None of the smartphone apps reviewed were explicitly developed for phobia therapy. However, 16 of the 84 included apps were considered ideal candidates to investigate further as part of treatment due to their accessibility, depiction of phobia-relevant stimuli, low or no cost, and high user scores. Most of these apps were visually abstract and free to use, making them accessible and potentially flexible as part of clinical exposure hierarchies. However, none of the apps were designed for clinical use, nor did they provide tools for clinician workflows. Formal evaluation of these accessible smartphone apps is needed to understand the clinical potential of accessible VRET solutions.

Conceptualizing the digital therapeutic alliance in the context of fully automated mental health apps: A thematic analysis.

Fully automated mental health apps provide a promising opportunity for increasing access to mental health care and resources. Given this opportunity, continued research into the utility and effectiveness of mental health apps is crucial. Therapeutic alliance (TA) refers to the relationship between a client and a healthcare professional, and has been shown to be an important predictor of clinical outcomes in face-to-face therapy. Given the significance of TA in traditional therapy, it is important to explore whether the notion of a digital therapeutic alliance (DTA) in the context of fully automated mental health apps also plays an important role in clinical outcomes. Current evidence shows that the conceptualization of DTA in the context of fully automated mental health apps can be potentially different to TA in face-to-face therapy. Thus, a new DTA conceptual model is necessary for comprehensively understanding the mechanisms underpinning DTA for fully automated mental health apps. To the best of our knowledge, this is the first study that qualitatively explored the dimensions of a DTA in the context of fully automated mental health apps. We conducted interviews with 20 users of mental health apps to explore the key dimensions comprising DTA in the context of fully automated mental health apps. We found that although conceptualizations of DTA and TA have shared dimensions, flexibility and emotional experiences are unique domains in DTA. On the other hand, although agreement on goals between a therapist and a client is important in face to face therapy, we found that users can have an alliance with an app without a goal. The importance of goal needs further investigations.

Can Digital Health Solutions Fill in the Gap for Effective Guideline Implementation in Cardiovascular Disease Prevention: Hope or Hype?

PURPOSE OF REVIEW: To evaluate the use of digital health solutions in improving the implementation of cardiovascular disease (CVD) prevention guidelines and review current evidence supporting it. RECENT FINDINGS: Healthy diet guideline recommendations can be improved by text-messaging programs and apps for reinforcing healthy food intake and reducing unhealthy nutrients purchase and consumption. Wearable activity trackers are also effective in increasing physical activity levels. Text-messaging programs for smoking cessation have demonstrated benefits in increasing quitting rates; however, evidence on smartphone apps for smoking cessation is still lacking. Smartphone apps have the potential to improve medication adherence; however, better quality evidence is needed. Digital pills are another promising digital solution to improve medication adherence. The use of digital health solutions in CVD prevention is an evolving field and, to date, there is an increasing body of evidence that supports that such technologies are effective in improving CVD prevention guideline implementation.

Determinants of the acceptance and adoption of a digital contact tracing tool during the COVID-19 pandemic in Singapore.

The motivations that govern the adoption of digital contact tracing (DCT) tools are complex and not well understood. Hence, we assessed the factors influencing the acceptance and adoption of Singapore's national DCT tool - TraceTogether - during the COVID-19 pandemic. We surveyed 3943 visitors of Tan Tock Seng Hospital from July 2020 to February 2021 and stratified the analyses into three cohorts. Each cohort was stratified based on the time when significant policy interventions were introduced to increase the adoption of TraceTogether. Binary logistic regression was preceded by principal components analysis to reduce the Likert items. Respondents who 'perceived TraceTogether as useful and necessary' had higher likelihood of accepting it but those with 'Concerns about personal data collected by TraceTogether' had lower likelihood of accepting and adopting the tool. The injunctive and descriptive social norms were also positively associated with both the acceptance and adoption of the tool. Liberal individualism was mixed in the population and negatively associated with the acceptance and adoption of TraceTogether. Policy measures to increase the uptake of a national DCT bridged the digital divide and accelerated its adoption. However, good public communications are crucial to address the barriers of acceptance to improve voluntary uptake widespread adoption.

Eating disorders early app use mediates treatment effect on clinical improvement.

OBJECTIVE: Eating disorders (EDs) contribute considerably to the global burden of disease. However, most affected individuals do not receive treatment. Mobile apps present an enormous opportunity to increase access to mental healthcare services. This study examined whether the degree of usage of a self-help app for EDs mediated the app's effects on the clinical response by individuals with EDs. METHOD: App usage measures included the total number of cognitive-behavioral meal logs, total number of days spent using the app, and the last day the app was used during the study period. Mediation analysis was performed using the MacArthur framework. RESULTS: All usage variables met the analytic requirements for testing mediation (group means (sd) for app and standard app, respectively: logs = 74 (108) vs. 51.4 (88.1), days spent = 14.3 (17.5) vs. 10.6 (15.0), p-values from Wilcox rank sum tests p < .01). Regression coefficients indicated mediation effects. The mediation effects demonstrated support that increased engagement (as measured by logs and time spent on the app) was related to an increased likelihood of achieving a significant clinical change by the end of the trial. DISCUSSION: Greater and longer engagement in an ED app mediates its efficacy in terms of ED remission.

Smartphone apps for eating disorders: An overview of the marketplace and research trends.

OBJECTIVE: Apps purporting to assist with the management of eating disorders are proliferating; although less is known about (a) the safety or efficacy of the apps on the marketplaces and (b) if the research evidence supports dissemination of these apps. In this research forum, we seek to synthesize the current data and provide practical considerations around the use and research of these apps. METHODS: A search of the iOS and Google Play stores was conducted in June 2021 to identify publicly available apps targeting eating disorders. A PubMed search was also conducted in June 2021 to identify relevant publications around smartphone apps for eating disorders. RESULTS: Sixty-five apps that support the treatment of eating disorders were identified and coded across 105 data points on the publicly available mindApps.org website. The literature search revealed 13 articles. Seven percent of marketplaces apps offered any research support and the 13 published studies focused on only four apps. DISCUSSION: There is a need for more translational research on smartphone apps for eating disorders. Current marketplace offerings present risks that may not be balanced by their limited evidence. Research efforts should focus on offering evidenced-based apps for the marketplace. Clinicians should weigh known and emerging risks and benefits of these apps within the context of research gaps when making decisions around use.

Smoking Cessation Smartphone App Use Over Time: Predicting 12-Month Cessation Outcomes in a 2-Arm Randomized Trial.

BACKGROUND: Little is known about how individuals engage over time with smartphone app interventions and whether this engagement predicts health outcomes. OBJECTIVE: In the context of a randomized trial comparing 2 smartphone apps for smoking cessation, this study aimed to determine distinct groups of smartphone app log-in trajectories over a 6-month period, their association with smoking cessation outcomes at 12 months, and baseline user characteristics that predict data-driven trajectory group membership. METHODS: Functional clustering of 182 consecutive days of smoothed log-in data from both arms of a large (N=2415) randomized trial of 2 smartphone apps for smoking cessation (iCanQuit and QuitGuide) was used to identify distinct trajectory groups. Logistic regression was used to determine the association of group membership with the primary outcome of 30-day point prevalence of smoking abstinence at 12 months. Finally, the baseline characteristics associated with group membership were examined using logistic and multinomial logistic regression. The analyses were conducted separately for each app. RESULTS: For iCanQuit, participants were clustered into 3 groups: "1-week users" (610/1069, 57.06%), "4-week users" (303/1069, 28.34%), and "26-week users" (156/1069, 14.59%). For smoking cessation rates at the 12-month follow-up, compared with 1-week users, 4-week users had 50% higher odds of cessation (30% vs 23%; odds ratio [OR] 1.50, 95% CI 1.05-2.14; P=.03), whereas 26-week users had 397% higher odds (56% vs 23%; OR 4.97, 95% CI 3.31-7.52; P<.001). For QuitGuide, participants were clustered into 2 groups: "1-week users" (695/1064, 65.32%) and "3-week users" (369/1064, 34.68%). The difference in the odds of being abstinent at 12 months for 3-week users versus 1-week users was minimal (23% vs 21%; OR 1.16, 95% CI 0.84-1.62; P=.37). Different baseline characteristics predicted the trajectory group membership for each app. CONCLUSIONS: Patterns of 1-, 3-, and 4-week smartphone app use for smoking cessation may be common in how people engage in digital health interventions. There were significantly higher odds of quitting smoking among 4-week users and especially among 26-week users of the iCanQuit app. To improve study outcomes, strategies for detecting users who disengage early from these interventions (1-week users) and proactively offering them a more intensive intervention could be fruitful.

Effectiveness of Digital Counseling Environments on Anxiety, Depression, and Adherence to Treatment Among Patients Who Are Chronically Ill: Systematic Review.

BACKGROUND: Patients who are chronically ill need novel patient counseling methods to support their self-care at different stages of the disease. At present, knowledge of how effective digital counseling is at managing patients' anxiety, depression, and adherence to treatment seems to be fragmented, and the development of digital counseling will require a more comprehensive view of this subset of interventions. OBJECTIVE: This study aims to identify and synthesize the best available evidence on the effectiveness of digital counseling environments at improving anxiety, depression, and adherence to treatment among patients who are chronically ill. METHODS: Systematic searches of the EBSCO (CINAHL), PubMed, Scopus, and Web of Science databases were conducted in May 2019 and complemented in October 2020. The review considered studies that included adult patients aged ≥18 years with chronic diseases; interventions evaluating digital (mobile, web-based, and ubiquitous) counseling interventions; and anxiety, depression, and adherence to treatment, including clinical indicators related to adherence to treatment, as outcomes. Methodological quality was assessed using the standardized Joanna Briggs Institute critical appraisal tool for randomized controlled trials or quasi-experimental studies. As a meta-analysis could not be conducted because of considerable heterogeneity in the reported outcomes, narrative synthesis was used to synthesize the results. RESULTS: Of the 2056 records screened, 20 (0.97%) randomized controlled trials, 4 (0.19%) pilot randomized controlled trials, and 2 (0.09%) quasi-experimental studies were included. Among the 26 included studies, 10 (38%) digital, web-based interventions yielded significantly positive effects on anxiety, depression, adherence to treatment, and the clinical indicators related to adherence to treatment, and another 18 (69%) studies reported positive, albeit statistically nonsignificant, changes among patients who were chronically ill. The results indicate that an effective digital counseling environment comprises high-quality educational materials that are enriched with multimedia elements and activities that engage the participant in self-care. Because of the methodological heterogeneity of the included studies, it is impossible to determine which type of digital intervention is the most effective for managing anxiety, depression, and adherence to treatment. CONCLUSIONS: This study provides compelling evidence that digital, web-based counseling environments for patients who are chronically ill are more effective than, or at least comparable to, standard counseling methods; this suggests that digital environments could complement standard counseling.