Acceptance towards digital health interventions - Model validation and further development of the Unified Theory of Acceptance and Use of Technology

Predictors of Health Care Practitioners' Intention to Use AI-Enabled Clinical Decision Support Systems: Meta-Analysis Based on the Unified Theory of Acceptance and Use of Technology

BACKGROUND

Artificial intelligence-enabled clinical decision support systems (AI-CDSSs) offer potential for improving health care outcomes, but their adoption among health care practitioners remains limited.

OBJECTIVE

This meta-analysis identified predictors influencing health care practitioners' intention to use AI-CDSSs based on the Unified Theory of Acceptance and Use of Technology (UTAUT). Additional predictors were examined based on existing empirical evidence.

METHODS

The literature search using electronic databases, forward searches, conference programs, and personal correspondence yielded 7731 results, of which 17 (0.22%) studies met the inclusion criteria. Random-effects meta-analysis, relative weight analyses, and meta-analytic moderation and mediation analyses were used to examine the relationships between relevant predictor variables and the intention to use AI-CDSSs.

RESULTS

The meta-analysis results supported the application of the UTAUT to the context of the intention to use AI-CDSSs. The results showed that performance expectancy (r=0.66), effort expectancy (r=0.55), social influence (r=0.66), and facilitating conditions (r=0.66) were positively associated with the intention to use AI-CDSSs, in line with the predictions of the UTAUT. The meta-analysis further identified positive attitude (r=0.63), trust (r=0.73), anxiety (r=-0.41), perceived risk (r=-0.21), and innovativeness (r=0.54) as additional relevant predictors. Trust emerged as the most influential predictor overall. The results of the moderation analyses show that the relationship between social influence and use intention becomes weaker with increasing age. In addition, the relationship between effort expectancy and use intention was stronger for diagnostic AI-CDSSs than for devices that combined diagnostic and treatment recommendations. Finally, the relationship between facilitating conditions and use intention was mediated through performance and effort expectancy.

CONCLUSIONS

This meta-analysis contributes to the understanding of the predictors of intention to use AI-CDSSs based on an extended UTAUT model. More research is needed to substantiate the identified relationships and explain the observed variations in effect sizes by identifying relevant moderating factors. The research findings bear important implications for the design and implementation of training programs for health care practitioners to ease the adoption of AI-CDSSs into their practice.

Attitudes of the general population and mental health practitioners towards blended therapy in Austria

INTRODUCTION

Mental health problems are steadily increasing worldwide. In Austria, the overall supply of mental health services is low, especially in rural areas. Mobile technology and a blended care approach have the potential to overcome problems with service provision. The aim of this study was to map the attitudes of practitioners and people living in Austria towards blended therapy.

METHOD

Two individual online questionnaires (including the Unified Theory of Acceptance and Use of Technology, advantages and disadvantages, useful features) were distributed to practitioners and the general population in Austria.

RESULTS

The questionnaires were answered by 152 members of the general public and 129 practitioners. The general population and practitioners seem to be cautious, but slightly positive about blended therapy. Previous experience of practitioners with blended therapy was low. Practitioners are most worried about the therapeutic process and their work-life balance, while the general population is worried about being overwhelmed by the concept, mainly due to the time investment. Tracking, recording and reminding functions (e.g., for mood, homework) were seen as especially valuable features and accessibility was deemed the biggest advantage by both samples.

CONCLUSION

Practitioners' attitudes are important for implementation of blended therapy. More awareness might help against the cautiousness as well as implementing digital health applications in Austrian health policies.

Measuring electronic health literacy in the context of diabetes care: psychometric evaluation of a Persian version of the condition-specific eHealth literacy scale for diabetes

BACKGROUND

The rise of the internet and social media has led to increased interest among diabetes patients in using technology for information gathering and disease management. However, adequate eHealth literacy is crucial for protecting patients from unreliable diabetes-related information online.

OBJECTIVE

To examine the psychometric characteristics and explore the preliminary validity of the Persian version of the Condition-specific eHealth Literacy Scale for Diabetes (Persian CeHLS-D) to assess eHealth literacy in the context of diabetes care.

METHODS

After adapting, translating, examining content validity, and pilot testing the questionnaire, it was administered to 300 patients with type 2 diabetes mellitus (T2DM). Construct validity was assessed through confirmatory factor analysis, convergent and known-groups validity. The internal consistency (Cronbach's alpha), composite reliability and maximum reliability, and test-retest correlation were assessed.

RESULTS

Factor analysis supported the hypothesized two-factor model with 10 items, and the standardized factor loadings ranged from 0.44 to 0.86 (P-values < 0.001). Cronbach's alpha and test-retest correlation were good for each factor. Convergent validity was confirmed by significant correlations of Persian CeHLS-D with diabetes health literacy, perceived usefulness and importance of using the internet for health information, internet anxiety, and perceived physical and mental health. Know-groups validity determined using groups with different internet-use frequencies, and different attitudes towards providing online healthcare services, were satisfied.

CONCLUSION

This study demonstrated the Persian CeHLS-D as a reliable and valid measure of eHealth literacy among patients with T2DM in Iran. Its satisfactory psychometric properties support its use in research and clinical settings to assess eHealth literacy and inform interventions.

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.

Acceptance of smart sensing, its determinants, and the efficacy of an acceptance-facilitating intervention in people with diabetes: results from a randomized controlled trial

Background

Mental health problems are prevalent among people with diabetes, yet often under-diagnosed. Smart sensing, utilizing passively collected digital markers through digital devices, is an innovative diagnostic approach that can support mental health screening and intervention. However, the acceptance of this technology remains unclear. Grounded on the Unified Theory of Acceptance and Use of Technology (UTAUT), this study aimed to investigate (1) the acceptance of smart sensing in a diabetes sample, (2) the determinants of acceptance, and (3) the effectiveness of an acceptance facilitating intervention (AFI).

Methods

A total of N = 132 participants with diabetes were randomized to an intervention group (IG) or a control group (CG). The IG received a video-based AFI on smart sensing and the CG received an educational video on mindfulness. Acceptance and its potential determinants were assessed through an online questionnaire as a single post-measurement. The self-reported behavioral intention, interest in using a smart sensing application and installation of a smart sensing application were assessed as outcomes. The data were analyzed using latent structural equation modeling and t-tests.

Results

The acceptance of smart sensing at baseline was average (M = 12.64, SD = 4.24) with 27.8% showing low, 40.3% moderate, and 31.9% high acceptance. Performance expectancy (γ = 0.64, p < 0.001), social influence (γ = 0.23, p = .032) and trust (γ = 0.27, p = .040) were identified as potential determinants of acceptance, explaining 84% of the variance. SEM model fit was acceptable (RMSEA = 0.073, SRMR = 0.059). The intervention did not significantly impact acceptance (γ = 0.25, 95%-CI: -0.16-0.65, p = .233), interest (OR = 0.76, 95% CI: 0.38-1.52, p = .445) or app installation rates (OR = 1.13, 95% CI: 0.47-2.73, p = .777).

Discussion

The high variance in acceptance supports a need for acceptance facilitating procedures. The analyzed model supported performance expectancy, social influence, and trust as potential determinants of smart sensing acceptance; perceived benefit was the most influential factor towards acceptance. The AFI was not significant. Future research should further explore factors contributing to smart sensing acceptance and address implementation barriers.

Digital Interventions for Combating Internet Addiction in Young Children: Qualitative Study of Parent and Therapist Perspectives

BACKGROUND

Internet addiction is an emerging mental health issue in this digital age. Nowadays, children start using the internet in early childhood, thus making them vulnerable to addictive use. Previous studies have reported that the risk of internet addiction tends to be higher in lower-income regions with lower quality of life, such as Indonesia. Indonesia has high risks and prevalence of internet addiction, including in children. Digital interventions have been developed as an option to combat internet addiction in children. However, little is known about what parents and therapists in Indonesia perceive about these types of interventions.

OBJECTIVE

This study aims to investigate the experiences, perceptions, and considerations of parents and therapists regarding digital interventions for combating internet addiction in young Indonesian children.

METHODS

This study used a qualitative exploratory approach through semistructured interviews. We involved 22 parents of children aged 7 to 11 years and 6 experienced internet addiction therapists for children. The interview data were transcribed and analyzed using thematic analysis.

RESULTS

Participants in this study recognized 3 existing digital interventions to combat internet addiction: Google Family Link, YouTube Kids, and Apple parental control. They perceived that digital interventions could be beneficial in continuously promoting healthy digital behavior in children and supporting parents in supervision. However, the existing interventions were not highly used due to limitations such as the apps' functionality and usability, parental capability, parent-child relationships, cultural incompatibility, and data privacy.

CONCLUSIONS

The findings suggest that digital interventions should focus not only on restricting and monitoring screen time but also on suggesting substitutive activities for children, developing children's competencies to combat addictive behavior, improving digital literacy in children and parents, and supporting parental decision-making to promote healthy digital behavior in their children. Suggestions for future digital interventions are provided, such as making the existing features more usable and relatable, investigating gamification features to enhance parental motivation and capability in managing their children's internet use, providing tailored or personalized content to suit users' characteristics, and considering the provision of training and information about the use of interventions and privacy agreements.

Enhancing the acceptance of smart sensing in psychotherapy patients: findings from a randomized controlled trial

Objective

Smart sensing has the potential to make psychotherapeutic treatments more effective. It involves the passive analysis and collection of data generated by digital devices. However, acceptance of smart sensing among psychotherapy patients remains unclear. Based on the unified theory of acceptance and use of technology (UTAUT), this study investigated (1) the acceptance toward smart sensing in a sample of psychotherapy patients (2) the effectiveness of an acceptance facilitating intervention (AFI) and (3) the determinants of acceptance.

Methods

Patients (N = 116) were randomly assigned to a control group (CG) or intervention group (IG). The IG received a video AFI on smart sensing, and the CG a control video. An online questionnaire was used to assess acceptance of smart sensing, performance expectancy, effort expectancy, facilitating conditions and social influence. The intervention effects of the AFI on acceptance were investigated. The determinants of acceptance were analyzed with structural equation modeling (SEM).

Results

The IG showed a moderate level of acceptance (M = 3.16, SD = 0.97), while the CG showed a low level (M = 2.76, SD = 1.0). The increase in acceptance showed a moderate effect in the intervention group (p < .05, d = 0.4). For the IG, performance expectancy (M = 3.92, SD = 0.7), effort expectancy (M = 3.90, SD = 0.98) as well as facilitating conditions (M = 3.91, SD = 0.93) achieved high levels. Performance expectancy (γ = 0.63, p < .001) and effort expectancy (γ = 0.36, p < .001) were identified as the core determinants of acceptance explaining 71.1% of its variance. The fit indices supported the model's validity (CFI = .95, TLI = .93, RMSEA = .08).

Discussion

The low acceptance in the CG suggests that enhancing the acceptance should be considered, potentially increasing the use and adherence to the technology. The current AFI was effective in doing so and is thus a promising approach. The IG also showed significantly higher performance expectancy and social influence and, in general, a strong expression of the UTAUT factors. The results support the applicability of the UTAUT in the context of smart sensing in a clinical sample, as the included predictors were able to explain a great amount of the variance of acceptance.

Mental health services for German university students: acceptance of intervention targets and preference for delivery modes

Introduction

Most university students with mental disorders remain untreated. Evaluating the acceptance of intervention targets in mental health treatment, promotion, and prevention, as well as mental health service delivery modes is crucial for reducing potential barriers, increasing healthcare utilization, and efficiently allocating resources in healthcare services.

Aim

The study aimed to evaluate the acceptance of various intervention targets and delivery modes of mental health care services in German first-year university students.

Methods

In total, 1,376 first-year students from two German universities from the 2017-2018 multi-center cross-sectional cohort of the StudiCare project, the German arm of the World Mental Health International College Student Survey initiative, completed a web-based survey assessing their mental health. Mental disorder status was based on self-reported data fulfilling the DSM-IV criteria. We report frequencies of accepted delivery modes [categories: group or in-person therapy with on or off campus services, self-help internet- or mobile-based intervention (IMI) with or without coaching, or a combination of a in-person and IMI (blended)]. In a multinomial logistic regression, we estimate correlates of the preference for in-person vs. IMI vs. a combination of both modes (blended) modalities. Additionally, we report frequencies of intervention targets (disorder specific: e.g., social phobia, depressive mood; study-related: test anxiety, procrastination; general well-being: sleep quality, resilience) their association with mental disorders and sex, and optimal combinations of treatment targets for each mental illness.

Results

German university students' acceptance is high for in-person (71%-76%), moderate for internet- and mobile-based (45%-55%), and low for group delivery modes (31%-36%). In-person treatment (72%) was preferred over IMI (19%) and blended modalities (9%). Having a mental disorder [odds ratio (OR): 1.56], believing that digital treatments are effective (OR: 3.2), and showing no intention to use services (OR: 2.8) were associated with a preference for IMI compared to in-person modes. Students with prior treatment experience preferred in-person modes (OR: 0.46). In general, treatment targets acceptance was higher among female students and students with mental disorders. However, this was not true for targets with the highest (i.e., procrastination) and the lowest (i.e., substance-use disorder) acceptance. If only two intervention targets were offered, a combination of study-related targets (i.e., procrastination, stress, time management) would reach 85%-88% of the students.

Conclusion

In-person services are preferred, yet half of the students consider using IMI, preferably aiming for a combination of at least two study-related intervention targets. Student mental health care services should offer a combination of accepted targets in different delivery modes to maximize service utilization.

A qualitative interview study of patients' attitudes towards and intention to use digital interventions for depressive disorders on prescription

Background

Depressive disorders are an emerging public health topic. Due to their increasing prevalence, patients with depressive disorders suffer from the lack of therapeutic treatment. Digital health interventions may offer an opportunity to bridge waiting times, supplement, or even substitute in-person treatment. Among others, the Unified Theory of Acceptance and Use of Technology (UTAUT) explains that actual technology use is affected by users' behavioural intention. However, patients' perspectives on digital interventions are rarely discussed within the specific context of primary care provided by general practitioners (GP) and need further exploration.

Method

A qualitative study design with semi-structured interviews was used to explore DTx-acceptance of patients with mild or moderate depression (n = 17). The audio-recorded interviews were transcribed verbatim, coded, and thematically analysed by qualitative content analysis.

Results

Patients' performance expectancies reveal that DTx are not perceived as a substitute for face-to-face treatment. Effort expectancies include potential advantages and efforts concerning technical, motivational, and skill-based aspects. Moreover, we identified health status and experience with depressive disorders as other determinants and potential barriers to patients' DTx acceptance: Difficult stages of depression or long-time experience are perceived hurdles for DTx use. GPs' recommendations were just partly relevant for patients and varied according to patients' consultancy preferences. But still, GPs have a crucial role for access due to prescription. GPs' influence on patients' DTx acceptance varies between three situations: (1) pre-use for consultation, (2) pre-use for access and (3) during DTx-use. Further, GPs' guidance could be especially relevant for patients during DTx-use in routine care.

Discussion

The UTAUT-based exploration suggests that acceptance determinants should be considered independently and embedded in personal and situational aspects. DTx require a healthcare professional to prescribe or diagnose the disease, unlike other digital offerings. We identified prescription- and depression-related determinants, exceeding existing theoretical constructs. GPs' guidance can compensate for some barriers to DTx use e.g., by increasing commitment and motivational support to strengthen patients' acceptance.

Conclusion

We argue for a multidimensional integration of acceptance determinants for further development of health technology acceptance research. Future research should specify how DTx can be integrated into routine care to strengthen user acceptance.

Does outcome expectancy predict outcomes in online depression prevention? Secondary analysis of randomised-controlled trials

BACKGROUND

Evidence shows that online interventions could prevent depression. However, to improve the effectiveness of preventive online interventions in individuals with subthreshold depression, it is worthwhile to study factors influencing intervention outcomes. Outcome expectancy has been shown to predict treatment outcomes in psychotherapy for depression. However, little is known about whether this also applies to depression prevention. The aim of this study was to investigate the role of participants' outcome expectancy in an online depression prevention intervention.

METHODS

A secondary data analysis was conducted using data from two randomised-controlled trials (N = 304). Multilevel modelling was used to explore the effect of outcome expectancy on depressive symptoms and close-to-symptom-free status postintervention (6-7 weeks) and at follow-up (3-6 months). In a subsample (n = 102), Cox regression was applied to assess the effect on depression onset within 12 months. Explorative analyses included baseline characteristics as possible moderators. Outcome expectancy did not predict posttreatment outcomes or the onset of depression.

RESULTS

Small effects were observed at follow-up for depressive symptoms (β = -.39, 95% confidence interval [CI]: [-0.75, -0.03], p = .032, padjusted = .130) and close-to-symptom-free status (relative risk = 1.06, 95% CI: [1.01, 1.11], p = .013, padjusted = 0.064), but statistical significance was not maintained when controlling for multiple testing. Moderator analyses indicated that expectancy could be more influential for females and individuals with higher initial symptom severity.

CONCLUSION

More thoroughly designed, predictive studies targeting outcome expectancy are necessary to assess the full impact of the construct for effective depression prevention.

PATIENT OR PUBLIC CONTRIBUTION

This secondary analysis did not involve patients, service users, care-givers, people with lived experience or members of the public. However, the findings incorporate the expectations of participants using the preventive online intervention, and these exploratory findings may inform the future involvement of participants in the design of indicated depression prevention interventions for adults.

CLINICAL TRIAL REGISTRATION

Original studies: DRKS00004709, DRKS00005973; secondary analysis: osf.io/9xj6a.

Acceptance of a Web-Based Intervention in Individuals Who Committed Sexual Offenses Against Children: Cross-Sectional Study

BACKGROUND

Individuals who have committed sexual offenses against children often have difficulties finding treatment, despite its potential effectiveness. Although the development of web-based interventions could enhance therapeutic supply, up to now the acceptance thereof among this target group is unknown.

OBJECTIVE

For the first time, this study assesses the acceptance of a web-based intervention among individuals who committed sexual offenses against children and analyzes variables that predict acceptance. Following the Unified Theory of Acceptance and Use of Technology (UTAUT), it is assumed that acceptance of web-based interventions in individuals who have committed sexual offenses against children follows the same mechanisms as for individuals in general psychiatry.

METHODS

This cross-sectional study is based on the data from an ongoing clinical trial (@myTabu) evaluating the effectiveness of a web-based intervention in individuals who committed sexual offenses against children (N=113). Acceptance level was measured using a questionnaire based on the UTAUT and modified for the target group. Furthermore, predictors of acceptance from the UTAUT (performance expectancy, effort expectancy, and social influence [SI]), attitudes toward web-based interventions, and internet anxiety were assessed at baseline.

RESULTS

Most participants (61.1%, 69/113), reported high acceptance, while 36.3% (41/113) of them indicated moderate acceptance, and 2.7% (3/113) of them expressed low acceptance. In a linear regression model, the predictors explained 41.2% of the variance (F11,101=9.055; P=.01). Attitudes toward web-based interventions (B=0.398, 95% CI 0.16-0.64; P=.001) and SI (B=0.183, 95% CI 0.03-0.38; P=.04) significantly predicted acceptance. Post hoc explorative analysis showed that the participants' belief that people close to them would recommend the use of a web-based intervention is a predictor of acceptance. In contrast, the belief that their community supervisor would recommend the use thereof was not predictive in this respect.

CONCLUSIONS

For the participants of this study, we identified high acceptance of web-based interventions for the majority of participants. SI and the participants' attitudes toward web-based interventions were important in predicting acceptance.

TRIAL REGISTRATION

German Clinical Trial Registration (DRKS, Deutsches Register Klinischer Studien) DRKS 00021256; https://drks.de/search/de/trial/DRKS00021256.

Drivers and barriers of patients' acceptance of video consultation in cancer care

Background

Due to digitization in the medical sector, many healthcare interactions are switched to online services. This study assessed the acceptance of video consultations (VCs) in cancer care, and determined drivers and barriers of acceptance.

Methods

A cross-sectional online-based survey study was conducted in Germany from February 2022 to February 2023. Recruitment took place at oncology outpatient clinics, general practitioners, oncology practices and via cancer-related social media channels. Inclusion criteria were a cancer diagnosis, cancer treatment and internet access. Sociodemographic, medical data, eHealth-related data were acquired via an online assessment. The Unified Theory of Acceptance and Use of Technology (UTAUT) model was used to determine the acceptance of VC and its predictors.

Results

Of N = 350 cancer patients, 56.0% (n = 196) reported high acceptance of VC, 28.0% (n = 98) stated moderate acceptance and 16.0% (n = 56) indicated low acceptance. Factors influencing acceptance were younger age (β = -.28, p < .001), female gender (β = .35, p = .005), stage of disease (β = .11, p = .032), high digital confidence (β = .14, p = .010), low internet anxiety (β = -.21, p = .001), high digital overload (β = -.12, p = .022), high eHealth literacy (β = .14, p = .028), personal trust (β = -.25, p < .001), internet use (β = .17, p = .002), and the UTAUT predictors: performance expectancy (β = .24, p < .001), effort expectancy (β = .26, p < .001), and social influence (β = .34, p < .001).

Conclusions

Patients' acceptance of VC in cancer care is high. Drivers and barriers to acceptance identified should be considered for personalized applications. Considering the growing demand for cancer care establishing digital healthcare solutions is justified.

Home-based exercise interventions delivered by technology in older adults: A scoping review of technological tools usage

BACKGROUND

Despite technology-based systems being considered promising tools to stimulate and increase physical function at home, most older adults are unfamiliar with technology, which may pose some difficulties. Technology-related parameters, such as adherence, acceptance, and acceptability, are crucial to achieving higher efficacy levels of home-based exercise interventions delivered by technology. In this scoping review, we aimed to revise the use of home-based technological tools to improve physical function in the older population, focusing on the user's experience and perspective. Methods This scoping review was conducted following PRISMA guidelines. The search was conducted in April 2022 and updated in April 2023. A total of 45 studies were included in the review. Results Most studies (95.5%) met the technology usage levels defined by the research team or reported satisfactory technology usage levels. Positive health-related outcomes were reported in 80% of studies. Although the existence of guidelines to correctly define and use measures associated with technology use, including adherence, acceptance and acceptability, some terms are still being used interchangeably. Some concerns related to the lack of an international consensus regarding technology usage measures and the exclusion of older adults who did not own or have previous experience with technology in a large percentage of the included studies may have limited the results obtained. Conclusions Altogether, home-based exercise interventions delivered through technology were associated with positive health-related outcomes in older adults, and technology usage levels are considered satisfactory. Older adults are willing and able to use technology autonomously if adequate support is provided.

Hurdles and potentials when implementing internet-delivered Acceptance and commitment therapy for chronic pain: a retrospective appraisal using the Quality implementation framework

OBJECTIVES

Internet-delivered psychological interventions can be regarded as evidence-based practices and have been implemented in psychiatric and somatic care at primary and specialist levels. However, challenges as low adherence and poor routinization, have arisen during attempts to implement internet-delivered interventions in chronic pain settings. Internet-delivered Acceptance and Commitment Therapy (IACT) has been found to be helpful for chronic pain patients and might aid in developing pain rehabilitation services. However, the integration of IACT into standard health care has not yet been described from an implementation science perspective. The aim of this hybrid 1 effectiveness-implementation study was to evaluate the process of implementing IACT in a pain rehabilitation setting, to guide future implementation initiatives.

METHODS

In this retrospective study we described actions taken during an implementation initiative, in which IACT was delivered as part of an interdisciplinary pain rehabilitation program (IPRP) at a specialist level clinic. All documents relevant to the study were reviewed and coded using the Quality Improvement Framework (QIF), focusing on adoption, appropriateness and sustainability.

RESULTS

The QIF-analysis of implementation actions resulted in two categories: facilitators and challenges for implementation. Sustainability may be facilitated by sensitivity to the changing needs of a clinical setting and challenged by unfitting capacity building. Appropriateness might be challenged by an insufficient needs assessment and facilitated by aligning routines for communication with the clinic's existing infrastructure. Adoption may be facilitated by staff key champions and an ability to adapt to occurring hurdles. Possible influential factors, hypotheses and key process challenges are presented in a logic model to guide future initiatives.

CONCLUSIONS

Sustainable implementation may depend on both the continuity of facilitating implementation actions and flexibility to the changing needs and interests of patients, caregivers and organization. We conclude that the use of theories, models and frameworks (TMF) as well as a logic model may ease design, planning and evaluation of an implementation process. Lastly, we suggest that IACT may be appropriate for IPRP when given before or after IPRP, focusing on psychiatric comorbidities.

How to promote usage of telehealth interventions for farmers' mental health? A qualitative study on supporting and hindering aspects for acceptance and satisfaction with a personalized telephone coaching for depression prevention

Low-threshold and remotely delivered preventive interventions, like telephone coaching, are warranted for farmers who experience multiple risk factors for depression, live in underserved areas, and show low help-seeking behavior. Factors facilitating uptake and actual use of effective remote interventions are important to reduce depression disease burden. This study aimed at identifying factors that potentially can influence acceptance of and satisfaction with a telephone coaching in this occupational group.Semi-structured interviews were based on the 'Unified Theory of Acceptance and Use of Technology', the 'Evaluation', and 'Discrepancy' models for satisfaction. Interviews were conducted with 20 of 66 invited participants of a 6-months telephone coaching during an effectiveness or implementation study. Audio-recorded interviews were transcribed and analyzed (deductive-inductive qualitative content analysis). Independent coding by two persons resulted in good agreement (Κ = 0.80). Participants validated results via questionnaire.Overall, 32 supporting (SF) and 14 hindering factors (HF) for acceptance and satisfaction were identified and organized into five dimensions: Coaching result (SF = 9, HF = 3), coach (SF = 9, HF = 1), organization (SF = 5, HF = 2), the telephone as communication medium (SF = 4, HF = 5) and participant characteristics (SF = 5, HF = 3). Most named SFs were 'Flexible appointment arrangement' (n = 19/95 %) and 'low effort' (n = 17/85 %), while most reported HFs were 'lack of visual cues' (n = 12/60 %) and 'social/professional involvement restricts change process' (n = 10/50 %).The perceived changes initiated by coaching, a low effort through telephone conduct, and the indicated personalization were identified as important influencing factors on acceptance and satisfaction based on interviewees' statements. Both may be further enhanced by offering choice and advice for delivery formats (e.g., video-calls) and training of coaches in farm-related issues.

Study registration

German Clinical Trial Registrations: DRKS00017078 and DRKS00015655.

Digital health interventions in dermatology-Mapping technology and study parameters of systematically identified publications

Digital health interventions (DHI) potentially improve the efficiency and effectiveness of dermatological care. Currently, an overview clustering and characterizing the evidence on DHIs is missing. This systematic mapping of the literature aims to analyse published research on DHIs in dermatology to identify trends and gaps in research. For this purpose, a systematic search of the MEDLINE database was conducted in August 2022 to identify original publications on DHIs in dermatology. Data on country, targeted audience, DHI category, indication, outcome parameter and study design were extracted. Out of 12,009 records identified in MEDLINE, 403 studies were included in the final analysis. Studies on DHIs mainly performed in western countries, headed by the United States (n = 133), Germany (n = 32) and Spain (n = 23). Of all identified DHIs, 261 targeted healthcare providers (HCP), 66 clients (e.g. patients, caregivers, healthy individuals) and 67 both clients and HCPs. A majority of DHIs focussed on establishing a diagnosis (n = 254). Every other study analysed store-and-forward teledermatology (n = 187), followed by artificial intelligence applications for image analysis (n = 65). The most often analysed DHI category for clients was a support of health behaviour change (n = 31). Monitoring of clients was targeted by 77 studies. Skin cancer (n = 148), wounds (n = 29) and psoriasis (n = 29) were the most targeted indications by DHIs. Most studies analysed diagnostic performance (n = 166), fewer studies analysed acceptance (n = 92) and effectiveness (n = 98). Usability (n = 32) and efficiency (n = 36) were investigated only to a small extent. Studies on DHIs in dermatology have focused on teledermatology and AI applications, with an emphasis on skin cancer diagnosis. Apart from that, a range of DHIs for different user groups, purposes and indications were identified, demonstrating the broad potential for DHIs in dermatology. Further research with a wider set of outcome parameters is needed to fully understand the potential of DHIs and ensure their sustainable implementation into dermatological care.

AI in medical education: medical student perception, curriculum recommendations and design suggestions

Medical AI has transformed modern medicine and created a new environment for future doctors. However, medical education has failed to keep pace with these advances, and it is essential to provide systematic education on medical AI to current medical undergraduate and postgraduate students. To address this issue, our study utilized the Unified Theory of Acceptance and Use of Technology model to identify key factors that influence the acceptance and intention to use medical AI. We collected data from 1,243 undergraduate and postgraduate students from 13 universities and 33 hospitals, and 54.3% reported prior experience using medical AI. Our findings indicated that medical postgraduate students have a higher level of awareness in using medical AI than undergraduate students. The intention to use medical AI is positively associated with factors such as performance expectancy, habit, hedonic motivation, and trust. Therefore, future medical education should prioritize promoting students' performance in training, and courses should be designed to be both easy to learn and engaging, ensuring that students are equipped with the necessary skills to succeed in their future medical careers.

Digital mental health interventions: A narrative review of what is important from the perspective of LGBTQIA+ people

OBJECTIVES

Digital mental health interventions are a promising therapeutic modality to provide psychological support to LGBTQIA+ (lesbian, gay, bisexual, trans, Queer, intersex, asexual, plus other gender, sexual, and romantic minority identities) people. The aim of this narrative review is to explore how the LGBTQIA+ community has been engaged in the design of digital mental health interventions, how content has been tailored to the LGBTQIA+ community, and features identified as important by LGBTQIA+ participants.

METHODS

A total of 33 studies were included in this review from a larger yield of 1933 identified from systematic searches of five databases (PsycINFO, PubMed, Scopus, CINAHAL, and Medline). Data were analyzed narratively and using content analysis.

RESULTS

Only half of the studies reported engaging the LGBTQIA+ community in intervention designs. Interventions have been tailored in a variety of ways to support LGBTQIA+ individuals-such as through affirming imagery, recruitment through LGBTQIA+ networks, and designing content to focus specifically on LGBTQIA+ issues. A range of features were identified as important for participants, namely how content was tailored to LGBTQIA+ experiences, providing connection to community, and links to other relevant LGBTQIA+ resources. While not a primary aim, results also showed that a wide range of digital modalities can significantly improve a range of mental health problems.

CONCLUSION

Digital interventions are an acceptable and effective form of therapeutic intervention, but future research needs to focus on meaningful engagement of community members to inform design and implementation.

"It's Another Feather in My Hat"-Exploring Factors Influencing the Adoption of Apps With People Living With Dementia

INTRODUCTION

With the growing interest and availability of mobile applications (apps) for people living with dementia, it is desirable to have a broader insight into how technology adoption may be further improved. This paper aims to explore the factors influencing adoption of mobile applications for people living with dementia.

METHODS

The recruitment of participants was facilitated through a dementia advocacy group of people living with dementia. A focus group design was applied to elicit discussion and to explore divergent views on the topic. The data was analysed using thematic analysis.

FINDINGS

The 15 individuals who participated in this study comprised of seven women and eight men within the age range of 60-90 years. This study reports key findings pertaining to the views and experiences of using mobile apps. Data analysis revealed the following four distinct themes; (Theme 1: Living with dementia)-"That's the difficulty there even with apps or anything else." (Theme 2: Motivation)- "It makes me feel good. I feel a little with it [laughs], that its not all gone in there" (Theme 3: Fears and Concerns)- "Can somebody else get into your personal memories?" (Theme 4- Support)- "So it's important that we have that support". Together these themes encapsulate the most influential aspects, as highlighted by the participants influencing the acceptance and adoption of apps.

CONCLUSION

This paper explores the barriers and facilitators to app acceptance and adoption. This includes the importance of "feel good moments" and positive experiences, challenges associated with living with dementia, the importance of ongoing support, and security of the user's information. This study adds to what is already known by capturing the views and experiences of people living with dementia in relation to the factors influencing the adoption of apps.

[Digital personalized health information services from physicians: survey results of patients' and physicians' acceptance and expectations]

BACKGROUND

The acquisition of health information is fundamental for patient empowerment. In order to support this, new ways of providing information must be found. In this article, the digital personalized provision of health information by physicians as well as the intended use and requirements of patients and physicians are examined.

METHODS

An online survey of a sample of patients stratified for the German population (N = 1,000) and an online survey of physicians (N = 364) on the subject of digital personalized health information services were conducted. The type of information provision in the medical setting, the intention to use it, and the requirements for digital information services were assessed.

RESULTS

Digital personalized information services are still rare. However, patients would support such a service, while physicians are more skeptical. Patients value usability and information quality. With regard to the form of presentation, texts tend to be rated more important than videos. For physicians, on the other hand, it is important that the service comes from a trustworthy provider, complies with guidelines, and is free of charge.

DISCUSSION

The potential of the digital transformation of information provision has so far only been utilized to a limited extent. While the basis for successful implementation seems to be given among patients, physicians still need to overcome their reservations, the benefits of such services need to be communicated, and systemic incentives must be created.

Exploring factors that influence the behavioural intention of medical students to use 3D gastroscopic model to learn how to operate gastroscope using UTAUT Model

BACKGROUND

The application of virtual reality (VR) in gastroscopic operation teaching can be safe and effective, but the advantages can be realized only when students accept and use it. This study aims to identify the factors influencing Chinese clinical medical postgraduates on their intention to use the 3D gastroscopic model constructed based on VR technology using Unified Theory of Acceptance and Use of Technology (UTAUT) model. Students' demographic factors are also taken into consideration.

METHODS

All methods were carried out in accordance with relevant guidelines. Data were collected from clinical medical postgraduates students in China using stratified sampling. A total of 292 questionnaires including valid responses were used in this study. Data were processed using Amos 24.0 and SPSS 26.0 software and the statistical analysis technique was based on structural equation modeling (SEM).

RESULTS

The results showed that different from the mediator of home location and year of clinical learning, mediator of gender, university kind and graduate degree did not affect the behavioral intention. In addition, performance expectancy, facilitating condition, and social influence directly and indirectly have effect on behavioral intention. Also, the significance between social influence and performance expectancy, social influence and effort expectancy were verified.

CONCLUSIONS

This study manifested that the proposed framework based on the UTAUT had explanatory power to identify the factors influencing the students' behavioral intention to use the 3D gastroscopic model constructed based on VR technology. Whereas, an important variable of effort expectancy in the frame of the SEM were not certified, thereby indicating that particular attention should be paid to this variable by universities and teachers before applying 3D gastroscopic model constructed based on VR technology in teaching. Added preparatory work is required such as explaining the basic knowledge of the operating steps of VR model and make students adequately understand its accessibility, which can probably improve the intentions of them to use it. The positive effects of social influence on performance expectancy and effort expectancy we proposed was also verified in this study, which provided a direction for future research.

Technologies in Home-Based Digital Rehabilitation: Scoping Review

BACKGROUND

Due to growing pressure on the health care system, a shift in rehabilitation to home settings is essential. However, efficient support for home-based rehabilitation is lacking. The COVID-19 pandemic has further exacerbated these challenges and has affected individuals and health care professionals during rehabilitation. Digital rehabilitation (DR) could support home-based rehabilitation. To develop and implement DR solutions that meet clients' needs and ease the growing pressure on the health care system, it is necessary to provide an overview of existing, relevant, and future solutions shaping the constantly evolving market of technologies for home-based DR.

OBJECTIVE

In this scoping review, we aimed to identify digital technologies for home-based DR, predict new or emerging DR trends, and report on the influences of the COVID-19 pandemic on DR.

METHODS

The scoping review followed the framework of Arksey and O'Malley, with improvements made by Levac et al. A literature search was performed in PubMed, Embase, CINAHL, PsycINFO, and the Cochrane Library. The search spanned January 2015 to January 2022. A bibliometric analysis was performed to provide an overview of the included references, and a co-occurrence analysis identified the technologies for home-based DR. A full-text analysis of all included reviews filtered the trends for home-based DR. A gray literature search supplemented the results of the review analysis and revealed the influences of the COVID-19 pandemic on the development of DR.

RESULTS

A total of 2437 records were included in the bibliometric analysis and 95 in the full-text analysis, and 40 records were included as a result of the gray literature search. Sensors, robotic devices, gamification, virtual and augmented reality, and digital and mobile apps are already used in home-based DR; however, artificial intelligence and machine learning, exoskeletons, and digital and mobile apps represent new and emerging trends. Advantages and disadvantages were displayed for all technologies. The COVID-19 pandemic has led to an increased use of digital technologies as remote approaches but has not led to the development of new technologies.

CONCLUSIONS

Multiple tools are available and implemented for home-based DR; however, some technologies face limitations in the application of home-based rehabilitation. However, artificial intelligence and machine learning could be instrumental in redesigning rehabilitation and addressing future challenges of the health care system, and the rehabilitation sector in particular. The results show the need for feasible and effective approaches to implement DR that meet clients' needs and adhere to framework conditions, regardless of exceptional situations such as the COVID-19 pandemic.

Mapping Factors That Affect the Uptake of Digital Therapeutics Within Health Systems: Scoping Review

BACKGROUND

Digital therapeutics are patient-facing digital health interventions that can significantly alter the health care landscape. Despite digital therapeutics being used to successfully treat a range of conditions, their uptake in health systems remains limited. Understanding the full spectrum of uptake factors is essential to identify ways in which policy makers and providers can facilitate the adoption of effective digital therapeutics within a health system, as well as the steps developers can take to assist in the deployment of products.

OBJECTIVE

In this review, we aimed to map the most frequently discussed factors that determine the integration of digital therapeutics into health systems and practical use of digital therapeutics by patients and professionals.

METHODS

A scoping review was conducted in MEDLINE, Web of Science, Cochrane Database of Systematic Reviews, and Google Scholar. Relevant data were extracted and synthesized using a thematic analysis.

RESULTS

We identified 35,541 academic and 221 gray literature reports, with 244 (0.69%) included in the review, covering 35 countries. Overall, 85 factors that can impact the uptake of digital therapeutics were extracted and pooled into 5 categories: policy and system, patient characteristics, properties of digital therapeutics, characteristics of health professionals, and outcomes. The need for a regulatory framework for digital therapeutics was the most stated factor at the policy level. Demographic characteristics formed the most iterated patient-related factor, whereas digital literacy was considered the most important factor for health professionals. Among the properties of digital therapeutics, their interoperability across the broader health system was most emphasized. Finally, the ability to expand access to health care was the most frequently stated outcome measure.

CONCLUSIONS

The map of factors developed in this review offers a multistakeholder approach to recognizing the uptake factors of digital therapeutics in the health care pathway and provides an analytical tool for policy makers to assess their health system's readiness for digital therapeutics.

Acceptance of smart sensing: a barrier to implementation-results from a randomized controlled trial

Background

Accurate and timely diagnostics are essential for effective mental healthcare. Given a resource- and time-limited mental healthcare system, novel digital and scalable diagnostic approaches such as smart sensing, which utilizes digital markers collected via sensors from digital devices, are explored. While the predictive accuracy of smart sensing is promising, its acceptance remains unclear. Based on the unified theory of acceptance and use of technology, the present study investigated (1) the effectiveness of an acceptance facilitating intervention (AFI), (2) the determinants of acceptance, and (3) the acceptance of adults toward smart sensing.

Methods

The participants (N = 202) were randomly assigned to a control group (CG) or intervention group (IG). The IG received a video AFI on smart sensing, and the CG a video on mindfulness. A reliable online questionnaire was used to assess acceptance, performance expectancy, effort expectancy, facilitating conditions, social influence, and trust. The self-reported interest in using and the installation of a smart sensing app were assessed as behavioral outcomes. The intervention effects were investigated in acceptance using t-tests for observed data and latent structural equation modeling (SEM) with full information maximum likelihood to handle missing data. The behavioral outcomes were analyzed with logistic regression. The determinants of acceptance were analyzed with SEM. The root mean square error of approximation (RMSEA) and standardized root mean square residual (SRMR) were used to evaluate the model fit.

Results

The intervention did not affect the acceptance (p = 0.357), interest (OR = 0.75, 95% CI: 0.42-1.32, p = 0.314), or installation rate (OR = 0.29, 95% CI: 0.01-2.35, p = 0.294). The performance expectancy (γ = 0.45, p < 0.001), trust (γ = 0.24, p = 0.002), and social influence (γ = 0.32, p = 0.008) were identified as the core determinants of acceptance explaining 68% of its variance. The SEM model fit was excellent (RMSEA = 0.06, SRMR = 0.05). The overall acceptance was M = 10.9 (SD = 3.73), with 35.41% of the participants showing a low, 47.92% a moderate, and 10.41% a high acceptance.

Discussion

The present AFI was not effective. The low to moderate acceptance of smart sensing poses a major barrier to its implementation. The performance expectancy, social influence, and trust should be targeted as the core factors of acceptance. Further studies are needed to identify effective ways to foster the acceptance of smart sensing and to develop successful implementation strategies.

Clinical Trial Registration

identifier 10.17605/OSF.IO/GJTPH.

Acceptance, drivers, and barriers to use eHealth interventions in patients with post-COVID-19 syndrome for management of post-COVID-19 symptoms: a cross-sectional study

Background

Post-COVID-19 syndrome is a new and debilitating disease without adequate treatment options. eHealth could be a reasonable approach for symptom management.

Objectives

This study aims to evaluate the acceptance for eHealth interventions for symptom management in individuals with post-COVID-19 syndrome, as well as drivers and barriers influencing acceptance.

Design

Cross-sectional study.

Methods

This study was conducted from January 19 until 24 May 2022. Recruitment took place with a web-based survey. Acceptance and predictors of eHealth interventions were measured by the extended UTAUT model. Included in the model were the core predictor performance expectancy, social influence, and effort expectancy. Previously diagnosed mental illness was estimated and mental health by using the well-established Generalized Anxiety Disorder Scale-7 and the Patient Health Questionnaire Depression Scale. The effect of sociodemographic and medical data was assessed. Multiple hierarchical regression analyses as well as group comparisons were performed.

Results

342 individuals with post-COVID-19 syndrome were examined. The acceptance of eHealth interventions for symptom management was moderate to high (M = 3.60, SD = 0.89). Acceptance was significantly higher in individuals with lower/other education, patients with moderate to severe symptoms during initial COVID-19 infection, still significantly impaired patients, and individuals with a mental illness. Identified predictors of acceptance were age (β = .24, p < .001), current condition including moderate (β = .49, p = .002) and still significantly impaired (β = .67, p < .001), digital confidence (β = .19, p < .001), effort expectancy (β = .26, p < .001), performance expectancy (β = .33, p < .001), and social influence (β = .26, p < .001).

Conclusion

Patients with post-COVID-19 syndrome reported a satisfying level of acceptance and drivers and barriers could be identified. These factors need to be considered for the implementation and future use of eHealth interventions.

Will they or won't they? Understanding New Zealand adults' attitudes towards using digital interventions

Background

Digital interventions deliver healthcare via the internet or smartphone application to support people's well-being and health. Yet uptake is relatively poor. Furthermore, several studies exploring attitudes towards digital interventions have found inconsistent attitudes. In addition to this, regional and cultural nuances may further influence attitudes to digital interventions.

Objective

This study aimed to understand New Zealand adults' attitudes towards digital interventions and their influences.

Results

A mixed-method design consisting of a cross-sectional survey and semi-structured interviews found that New Zealand adults hold varied and complex attitudes towards digital interventions. Attitudes were found to be influenced by group membership and the scenarios in which digital interventions are made available. In addition, beliefs about the benefits and concerns surrounding digital interventions, knowledge, perceived views of others, and previous experience and confidence influenced these attitudes.

Conclusions

Findings indicated that digital interventions would be acceptable if offered as part of the healthcare service rather than a standalone intervention. Key modifiable factors that could positively influence attitudes were identified and could be leveraged to increase the perceived acceptability of digital interventions.

Canadian Older Adults' Intention to Use an Electronic Decision Aid for Housing Decisions: Cross-sectional Web-Based Survey

BACKGROUND

Older adults with disabilities such as loss of autonomy face the decision of whether to stay at home or move to a health care facility such as a nursing home. Therefore, they may need support for this difficult decision.

OBJECTIVE

We assessed the intention of Canadian older adults to use an electronic decision aid (eDA) to make housing decisions and identified the factors that influenced their intention.

METHODS

We conducted a cross-sectional study using a web-based survey targeting older adults across 10 Canadian provinces and 3 territories. We included respondents from a web-based panel who were aged ≥65 years, understood English or French, had access to an electronic device with an internet connection, and had made a housing decision over the past few months or were planning to make a decision in the coming year. We based the web-based survey on the Unified Theory of Acceptance and Use of Technology (UTAUT). We adapted 17 UTAUT items to measure respondents' intention to use the eDA for housing decisions, as well as items measuring 4 intention constructs (performance expectancy, effort expectancy, social influence, and facilitating conditions). We also assessed eHealth literacy using both subjective and objective scales. We used descriptive statistics and multivariable linear regression analyses to identify the factors influencing the intention to use the eDA.

RESULTS

Of the 11,972 invited panelists, 1176 (9.82%) met the eligibility criteria, and 1000 (85.03%) respondents completed the survey. The mean age was 72.5 (SD 5.59) years. Most respondents were male (548/1000, 54.8%), White (906/1000, 90.6%), English speakers (629/1000, 62.9%), and lived in Ontario or Quebec (628/1000, 62.8%) and in urban areas (850/1000, 85%). The mean scores were 27.8 (SD 5.88) out of 40 for subjective eHealth literacy and 3.00 (SD 0.97) out of 5 for objective eHealth literacy. In our sample, the intention score was 4.74 (SD 1.7) out of 7. The mean scores of intention constructs out of 7 were 5.63 (SD 1.28) for facilitating conditions, 4.94 (SD 1.48) for performance expectancy, 5.61 (SD 1.35) for effort expectancy, and 4.76 (SD 1.59) for social influence. In the final model, the factors associated with intention included mother tongue (β=.30; P<.001), objective eHealth literacy (β=-.06; P=.03), performance expectancy (β=.55; P<.001), social influence (β=.37; P<.001), and facilitating conditions (β=.15; P<.001).

CONCLUSIONS

Findings from this pan-Canadian web-based survey on Canadian older adults suggest that their intention to use the eDA to make housing decisions is similar to the findings in other studies using UTAUT. The factors identified as influencing intention were mother tongue, objective eHealth literacy, performance expectancy, social influence, and facilitating conditions. These will guide future strategies for the implementation of the eDA.

Study on factors influencing college students' digital academic reading behavior

Background

Affected by the COVID-19, many colleges have adopted online teaching. Meanwhile, the digital transformation of academic journals has shifted readers' reading habits from traditional paper media to digital media. Digital academic reading has become the main reading method of college students during the COVID-19 pandemic.

Purpose

The purpose of this study was to investigate the behavioral characteristics of college students' digital academic reading and explore the internal factors and external environmental factors affecting the Intention and Use behavior of digital academic reading. At the same time this study provide recommendations to address these influencing factors in terms of the individual, the environment and library resources.

Methods

Based on UTAUT2 model and digital academic reading theories, this paper constructs a digital academic reading information behavior (DARB) model of college students to examine college students' digital academic reading behavior and intention. College students with digital academic reading behavior were recruited as research participants. A multi-stage sampling technique was used to collect representative samples from universities in Nanjing. 239 respondents participated in the questionnaire, with 189 providing valid data. Results: Effort expectancy (EE), social influence (SI), price value (PV), perceived risk (PR) and habit (BH) have a significant impact on behavioral intention (BI), and behavioral intention (BI) and habit (BH) have a significant impact on use behavior (B). However, performance expectancy (PE) and facilitating conditions (FC) have no significant influence on behavioral intention (BI).

Originality/value

The findings of this study will help fill the gap in previous research on the relationship between the influencing factors of digital academic reading and college students' reading intentions and behaviors, so as to provide a basis for improving the academic reading literacy program in colleges and optimizing the current digital academic reading environment.

Promoting participation in remote digital health studies: An expert interview study

Background

Remote digital health studies are on the rise and promise to reduce the operational inefficiencies of in-person research. However, they encounter specific challenges in maintaining participation (enrollment and retention) due to their exclusive reliance on technology across all study phases.

Objective

The goal of this study was to collect experts' opinions on how to facilitate participation in remote digital health studies.

Method

We conducted 13 semi-structured interviews with principal investigators, researchers, and software developers who had recent experiences with remote digital health studies. Informed by the Unified Theory of Acceptance and Use of Technology (UTAUT) framework, we performed a thematic analysis and mapped various approaches to successful study participation.

Results

Our analyses revealed four themes: (1) study planning to increase participation, where experts suggest that remote digital health studies should be planned based on adequate knowledge of what motivates, engages, and disengages a target population; (2) participant enrollment, highlighting that enrollment strategies should be selected carefully, attached to adequate support, and focused on inclusivity; (3) participant retention, with strategies that minimize the effort and complexity of study tasks and ensure that technology is adapted and responsive to participant needs, and (4) requirements for study planning focused on the development of relevant guidelines to foster participation in future studies.

Conclusions

Our findings highlight the significant requirements for seamless technology and researcher involvement in enabling high remote digital health study participation. Future studies can benefit from collected experiences and the development of guidelines to inform planning that balances participant and scientific requirements.

Digital health for chronic disease management: An exploratory method to investigating technology adoption potential

INTRODUCTION

The availability of consumer-facing health technologies for chronic disease management is skyrocketing, yet most are limited by low adoption rates. Improving adoption requires a better understanding of a target population's previous exposure to technology. We propose a low-resource approach of capturing and clustering technology exposure, as a mean to better understand patients and target health technologies.

METHODS

Using Multiple Sclerosis (MS) as a case study, we applied exploratory multivariate factorial analyses to survey data from the Swiss MS Registry. We calculated individual-level factor scorings, aiming to investigate possible technology adoption clusters with similar digital behavior patterns. The resulting clusters were transformed using radar and then compared across sociodemographic and health status characteristics.

RESULTS

Our analysis included data from 990 respondents, resulting in three clusters, which we defined as the (1) average users, (2) health-interested users, and (3) low frequency users. The average user uses consumer-facing technology regularly, mainly for daily, regular activities and less so for health-related purposes. The health-interested user also uses technology regularly, for daily activities as well as health-related purposes. The low-frequency user uses technology infrequently.

CONCLUSIONS

Only about 10% of our sample has been regularly using (adopting) consumer-facing technology for MS and health-related purposes. That might indicate that many of the current consumer-facing technologies for MS are only attractive to a small proportion of patients. The relatively low-resource exploratory analyses proposed here may allow for a better characterization of prospective user populations and ultimately, future patient-facing technologies that will be targeted to a broader audience.

Online consultations in mental healthcare: Modelling determinants of use and experience based on an international survey study at the onset of the pandemic

INTRODUCTION

While online consultations have shown promise to be a means for the effective delivery of high-quality mental healthcare and the first implementations of these digital therapeutic contacts go back nearly two decades, uptake has remained limited over the years. The onset of the COVID-19 pandemic dramatically altered this relative standstill and created a unique turning point, with a massive amount of both professionals and clients having first hands-on experiences with technology in mental healthcare.

OBJECTIVE

The current study aimed to document the uptake of online consultations and explore if specific characteristics of mental health professionals across and beyond Europe could predict this.

METHODS

An international survey was designed to assess mental health professionals' (initial) experiences with online consultations at the onset of the pandemic: their willingness to make use of them and their prior and current experiences, alongside several personal characteristics. Logistic mixed-effects models were used to identify predictors of the use of online consultations, personal experience with this modality, and the sense of telepresence.

RESULTS

A total of 9115 healthcare professionals from 73 countries participated of which about two-thirds used online consultations during the initial COVID-19 outbreak. The current study identifies multiple determinants relating to the use and experience of online consultations, including the professionals' age, experience with the technology before the outbreak, the professional context, and training.

CONCLUSIONS

Despite strong evidence supporting the relevance of training in digital mental health, this is clearly still lacking. Nevertheless, the COVID-19 pandemic presented a first, and potentially transformative, experience with online consultations for many healthcare professionals. The insights from this study can help support professionals and, importantly, (mental) healthcare organisations to create optimal circumstances for selective and high-quality continued use of online consultations.

Determining the Influencing Factors on Acceptance of eHealth Pain Management Interventions Among Patients With Chronic Pain Using the Unified Theory of Acceptance and Use of Technology: Cross-sectional Study

Background

Chronic pain is a complex disease with high prevalence rates, and many individuals who are affected do not receive adequate treatment. As a complement to conventional therapies, eHealth interventions could provide many benefits to a multimodal treatment approach for patients with chronic pain, whereby future use is associated with the acceptance of these interventions.

Objective

This study aims to assess the acceptance of eHealth pain management interventions among patients with chronic pain and identify the influencing factors on acceptance. A further objective of the study is to evaluate the viability of the Unified Theory of Acceptance and Use of Technology (UTAUT) model and compare it with its extended version in terms of explained variance of acceptance.

Methods

We performed a cross-sectional web-based study. In total, 307 participants with chronic pain, as defined according to the International Association for the Study of Pain criteria, were recruited through flyers, posters, and web-based inquiries between December 2020 and July 2021. In addition to sociodemographic and medical data, the assessment included validated psychometric instruments and an extended version of the well-established UTAUT model. For statistical analyses, group comparisons and multiple hierarchical regression analyses were performed.

Results

The acceptance of eHealth pain management interventions among patients with chronic pain was overall moderate to high (mean 3.67, SD 0.89). There was significant difference in acceptance among age groups (W=9674.0; r=0.156; P=.04). Effort expectancy (β=.37; P<.001), performance expectancy (β=.33; P<.001), and social influence (β=.34; P<.001) proved to be the most important predictors of acceptance. The extended UTAUT (including the original UTAUT factors as well as sociodemographic, medical, and eHealth-related factors) model explained 66.4% of the variance in acceptance, thus supporting the viability of the model. Compared with the original UTAUT model (performance expectancy, effort expectancy, and social influence), the extended model explained significantly more variance (F_25,278=1.74; P=.02).

Conclusions

Given the association between acceptance and future use, the knowledge of the influencing factors on acceptance should be used in the development and promotion of eHealth pain management interventions. Overall, the acceptance of eHealth pain management interventions was moderate to high. In total, 8 predictors proved to be significant predictors of acceptance. The UTAUT model is a valuable instrument for determining acceptance as well as the factors that influence acceptance of eHealth pain management interventions among patients with chronic pain. The extended UTAUT model provided the greatest predictive value for acceptance.

Analyzing the determinants to accept a virtual assistant and use cases among cancer patients: a mixed methods study

Background

Technological progress in artificial intelligence has led to the increasing popularity of virtual assistants, i.e., embodied or disembodied conversational agents that allow chatting with a technical system in a natural language. However, only little comprehensive research is conducted about patients' perceptions and possible applications of virtual assistant in healthcare with cancer patients. This research aims to investigate the key acceptance factors and value-adding use cases of a virtual assistant for patients diagnosed with cancer.

Methods

Qualitative interviews with eight former patients and four doctors of a Dutch radiotherapy institute were conducted to determine what acceptance factors they find most important for a virtual assistant and gain insights into value-adding applications. The unified theory of acceptance and use of technology (UTAUT) was used to structure perceptions and was inductively modified as a result of the interviews. The subsequent research model was triangulated via an online survey with 127 respondents diagnosed with cancer. A structural equation model was used to determine the relevance of acceptance factors. Through a multigroup analysis, differences between sample subgroups were compared.

Results

The interviews found support for all factors of the UTAUT: performance expectancy, effort expectancy, social influence and facilitating conditions. Additionally, self-efficacy, trust, and resistance to change, were added as an extension of the UTAUT. Former patients found a virtual assistant helpful in receiving information about logistic questions, treatment procedures, side effects, or scheduling appointments. The quantitative study found that the constructs performance expectancy (ß = 0.399), effort expectancy (ß = 0.258), social influence (ß = 0.114), and trust (ß = 0.210) significantly influenced behavioral intention to use a virtual assistant, explaining 80% of its variance. Self-efficacy (ß = 0.792) acts as antecedent of effort expectancy. Facilitating conditions and resistance to change were not found to have a significant relationship with user intention.

Conclusions

Performance and effort expectancy are the leading determinants of virtual assistant acceptance. The latter is dependent on a patient’s self-efficacy. Therefore, including patients during the development and introduction of a VA in cancer treatment is important. The high relevance of trust indicates the need for a reliable, secure service that should be promoted as such. Social influence suggests using doctors in endorsing the VA.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12913-022-08189-7.

Online ACT intervention for fibromyalgia: An exploratory study of feasibility and preliminary effectiveness with smartphone-delivered experiential sampling assessment

INTRODUCTION

Acceptance and commitment therapy (ACT) is an effective treatment for chronic pain conditions. ACT seeks to produce clinical change by enhancing Psychological Flexibility (PF). This exploratory (feasibility and preliminary effectiveness) study presents a pilot application of an online ACT group intervention for fibromyalgia (FM) with an extensive Experiential Sampling (ES) assessment of outcome and process variables via smartphone.

METHOD

5-weekly ACT online group sessions were applied to 9 female FM patients. Questionnaire-based assessments of several clinical outcomes and PF processes were conducted pre- and post-intervention, and at 6-month follow-up. Extensive (6 weeks pre- and 6 weeks post-intervention) smartphone-delivered ES was implemented to gather process and outcome data in the patients' usual contexts. Clinically significant change was evaluated both at the group level and individually.

RESULTS

This treatment format appears to be feasible and acceptable to participants, with good adoption and completion rates (75 %) and excellent rates of treatment completion and clinical adherence (100 %). Participants showed significant reductions in affective pain, distress and biopsychosocial impact of FM both post-intervention and at 6-month follow-up (as measured with questionnaires), as well as significant improvements in satisfaction with actions and emotional discomfort (as measured through ES). Multilevel regression analyses indicated that PF-related processes assessed through ES had a significant impact on clinical outcomes and predicted the impact of FM at the 6-month follow-up.

CONCLUSIONS

A brief online group ACT intervention for FM was both feasible and acceptable to participants. Also, there was preliminary evidence of effectiveness in enhancing pain-related PF and producing clinical benefits in FM.

Acceptance of E-mental health interventions and its determinants among psychotherapists-in-training during the first phase of COVID-19

BACKGROUND

Although E-mental health (EMH) interventions have been shown to be effective in the treatment of mental health problems and empirical knowledge regarding EMH acceptance for different occupations in health care is established, little is known regarding EMH and psychotherapists-in-training. This seems particularly relevant as psychotherapists-in-training will shape the future health care system since they are as being the next generation of psychotherapists. With social distancing measures in place, COVID-19 has led to an increased demand for EMH, which is broadening the way psychological treatments are delivered.

OBJECTIVE

The present study aims to assess the acceptance of EMH and its determinants among psychotherapists-in-training of different EMH modalities and to retrospectively compare current acceptance with pre-COVID-19 times.

METHODS

Altogether, 29 training institutions in Switzerland and 232 training institutions in Germany were contacted, resulting in a sample of N = 216 psychotherapists-in-training (88.4 % female) who filled out the self-administered web-based questionnaire in summer 2020. The acceptance of EMH was assessed considering several different modalities (e.g., videoconference, guided self-help programs) as well as further possible predictors of EMH acceptance based on the Unified Theory of Acceptance and Use of Technology. Acceptance scores were categorized as low, moderate or high based on prior research and predicted using multiple regression.

RESULTS

Acceptance of EMH was moderate (M = 3.40, SD = 1.11) and increased significantly (t(215) = 12.03, p < .01; d = 0.88) compared to pre-COVID-19 (M = 2.67, SD = 1.11); however, acceptance varied significantly between modalities (F(2.6, 561.7) = 62.93, p < .01, partial η² = 0.23), with videoconferencing being the most accepted and unguided programs the least. Stepwise regression including three of 14 variables (R² = 0.55, F (14, 201) = 17.68, p < .001) identified performance expectancy, social influence and concerns about the therapeutic alliance as significant determinants of EMH acceptance.

DISCUSSION

Acceptance by psychotherapists-in-training was moderate and in line with prior research and comparable with other clinicians' acceptance scores. Performance expectancy, social influence and concerns about the therapeutic alliance were predictive of EMH acceptance, indicating their significance in the implementation of EMH in health care.

CONCLUSION

These findings underline the importance of the aforementioned determinants of EMH acceptance and the need for further studies investigating EMH acceptance in order to derive adequate educational programs and to facilitate dissemination among psychotherapists-in-training.

Effectiveness and cost-effectiveness of a web-based routine assessment with integrated recommendations for action for depression and anxiety (RehaCAT+): protocol for a cluster randomised controlled trial for patients with elevated depressive symptoms in rehabilitation facilities

INTRODUCTION

The integration of a web-based computer-adaptive patient-reported outcome test (CAT) platform with persuasive design optimised features including recommendations for action into routine healthcare could provide a promising way to translate reliable diagnostic results into action. This study aims to evaluate the effectiveness and cost-effectiveness of such a platform for depression and anxiety (RehaCAT+) compared with the standard diagnostic system (RehaCAT) in cardiological and orthopaedic health clinics in routine care.

METHODS AND ANALYSIS

A two-arm, pragmatic, cluster-randomised controlled trial will be conducted. Twelve participating rehabilitation clinics in Germany will be randomly assigned to a control (RehaCAT) or experimental group (RehaCAT+) in a 1:1 design. A total sample of 1848 participants will be recruited across all clinics. The primary outcome, depression severity at 12 months follow-up (T3), will be assessed using the CAT Patient-Reported Outcome Measurement Information System Emotional Distress-Depression Item set. Secondary outcomes are depression at discharge (T1) and 6 months follow-up (T2) as well as anxiety, satisfaction with participation in social roles and activities, pain impairment, fatigue, sleep, health-related quality of life, self-efficacy, physical functioning, alcohol, personality and health economic-specific general quality of life and socioeconomic cost and benefits at T1-3. User behaviour, acceptance, facilitating and hindering factors will be assessed with semistructured qualitative interviews. Additionally, a smart sensing substudy will be conducted, with daily ecological momentary assessments and passive collection of smartphone usage variables. Data analysis will follow the intention-to-treat principle with additional per-protocol analyses. Cost-effectiveness analyses will be conducted from a societal perspective and the perspective of the statutory pension insurance.

ETHICS AND DISSEMINATION

The study will be conducted according to the Declaration of Helsinki. The Ethics Committee of Ulm University, has approved the study (on 24 February 2021 ref. 509/20). Written informed consent will be obtained for all participants. Results will be published via peer-reviewed journals.

TRIAL REGISTRATION NUMBER

DRKS00027447.

Determinants of Acceptance of Weight Management Applications in Overweight and Obese Individuals: Using an Extended Unified Theory of Acceptance and Use of Technology Model

Overweight and obesity carry a tremendous burden in terms of physiological and psychological comorbidities. There is a great variety of weight management applications to support weight reduction, but a systematical analysis of individuals’ needs and requirements to adopt sustaining lifestyle changes is missing so far. This study aimed to assess the acceptance of such applications and its underlying predictors in individuals with overweight/obesity. A cross-sectional study was conducted, including 439 overweight/obese individuals. Health-related internet use and acceptance of weight management applications were examined using a modified questionnaire based on the Unified Theory of Acceptance and Use of Technology (UTAUT). The general acceptance of weight management applications was high, with significant age differences. Compared to older individuals, younger ones showed a higher acceptance. BMI was not significantly associated with acceptance. Besides psychometric data and eHealth-related data, performance expectancy, effort expectancy, and social influence proved to be significant predictors for acceptance. The total variance explanation provided by the extended UTAUT model was 61.2%. The knowledge of the influencing factors on acceptance might be useful in developing, optimizing, and establishing weight management applications. For determining acceptance and its predictors of weight management applications, the UTAUT model is a valid approach.

Engagement, Predictors, and Outcomes of a Trauma Recovery Digital Mental Health Intervention: Longitudinal Study

BACKGROUND

Worldwide, exposure to potentially traumatic events is extremely common, and many individuals develop posttraumatic stress disorder (PTSD) along with other disorders. Unfortunately, considerable barriers to treatment exist. A promising approach to overcoming treatment barriers is a digital mental health intervention (DMHI). However, engagement with DMHIs is a concern, and theoretically based research in this area is sparse and often inconclusive.

OBJECTIVE

The focus of this study is on the complex issue of DMHI engagement. On the basis of the social cognitive theory framework, the conceptualization of engagement and a theoretically based model of predictors and outcomes were investigated using a DMHI for trauma recovery.

METHODS

A 6-week longitudinal study with a national sample of survivors of trauma was conducted to measure engagement, predictors of engagement, and mediational pathways to symptom reduction while using a trauma recovery DMHI (time 1: N=915; time 2: N=350; time 3: N=168; and time 4: N=101).

RESULTS

Confirmatory factor analysis of the engagement latent constructs of duration, frequency, interest, attention, and affect produced an acceptable model fit (χ²₂=8.3; P=.02; comparative fit index 0.973; root mean square error of approximation 0.059; 90% CI 0.022-0.103). Using the latent construct, the longitudinal theoretical model demonstrated adequate model fit (comparative fit index 0.929; root mean square error of approximation 0.052; 90% CI 0.040-0.064), indicating that engagement self-efficacy (β=.35; P<.001) and outcome expectations (β=.37; P<.001) were significant predictors of engagement (R²=39%). The overall indirect effect between engagement and PTSD symptom reduction was significant (β=-.065; P<.001; 90% CI -0.071 to -0.058). This relationship was serially mediated by both skill activation self-efficacy (β=.80; P<.001) and trauma coping self-efficacy (β=.40; P<.001), which predicted a reduction in PTSD symptoms (β=-.20; P=.02).

CONCLUSIONS

The results of this study may provide a solid foundation for formalizing the nascent science of engagement. Engagement conceptualization comprised general measures of attention, interest, affect, and use that could be applied to other applications. The longitudinal research model supported 2 theoretically based predictors of engagement: engagement self-efficacy and outcome expectancies. A total of 2 task-specific self-efficacies-skill activation and trauma coping-proved to be significant mediators between engagement and symptom reduction. Taken together, this model can be applied to other DMHIs to understand engagement, as well as predictors and mechanisms of action. Ultimately, this could help improve the design and development of engaging and effective trauma recovery DMHIs.

Usability Testing and Technology Acceptance of an mHealth App at the Point of Care During Simulated Pediatric In- and Out-of-Hospital Cardiopulmonary Resuscitations: Study Nested Within 2 Multicenter Randomized Controlled Trials

BACKGROUND

Mobile apps are increasingly being used in various domains of medicine. Few are evidence-based, and their benefits can only be achieved if end users intend to adopt and use them. To date, only a small fraction of mobile apps have published data on their field usability and end user acceptance results, especially in emergency medicine.

OBJECTIVE

This study aims to determine the usability and acceptance of an evidence-based mobile app while safely preparing emergency drugs at the point of care during pediatric in- and out-of-hospital cardiopulmonary resuscitations by frontline caregivers.

METHODS

In 2 multicenter randomized controlled parent trials conducted at 6 pediatric emergency departments from March 1 to December 31, 2017, and 14 emergency medical services from September 3, 2019, to January 21, 2020, the usability and technology acceptance of the PedAMINES (Pediatric Accurate Medication in Emergency Situations) app were evaluated among skilled pediatric emergency nurses and advanced paramedics when preparing continuous infusions of vasoactive drugs and direct intravenous emergency drugs at pediatric dosages during standardized, simulation-based, pediatric in- and out-of-hospital cardiac arrest scenarios, respectively. Usability was measured using the 10-item System Usability Scale. A 26-item technology acceptance self-administered survey (5-point Likert-type scales), adapted from the Unified Theory of Acceptance and Use of Technology model, was used to measure app acceptance and intention to use.

RESULTS

All 100% (128/128) of nurses (crossover trial) and 49.3% (74/150) of paramedics (parallel trial) were assigned to the mobile app. Mean total scores on the System Usability Scale were excellent and reached 89.5 (SD 8.8; 95% CI 88.0-91.1) for nurses and 89.7 (SD 8.7; 95% CI 87.7-91.7) for paramedics. Acceptance of the technology was very good and rated on average >4.5/5 for 5 of the 8 independent constructs evaluated. Only the image construct scored between 3.2 and 3.5 by both participant populations.

CONCLUSIONS

The results provide evidence that dedicated mobile apps can be easy to use and highly accepted at the point of care during in- and out-of-hospital cardiopulmonary resuscitations by frontline emergency caregivers. These findings can contribute to the implementation and valorization of studies aimed at evaluating the usability and acceptance of mobile apps in the field by caregivers, even in critical situations.

TRIAL REGISTRATION

ClinicalTrials.gov NCT03021122; https://clinicaltrials.gov/ct2/show/NCT03021122. ClinicalTrials.gov NCT03921346; https://clinicaltrials.gov/ct2/show/NCT03921346.

INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID)

RR2-10.1186/s13063-019-3726-4.

Acceptance of E-Mental Health Services for Different Application Purposes Among Psychotherapists in Clinical Training in Germany and Switzerland: Secondary Analysis of a Cross-Sectional Survey

Background

Despite solid evidence supporting the efficacy of electronic mental health (EMH) services, their acceptance among psychotherapists is limited and uptake rates remain low. However, the acceptance of different EMH services has yet barely been examined in future generations of psychotherapists in a differentiated manner. The aims of this study were (1) to elaborate the intention to use various EMH services for different application purposes and (2) to determine predictors of EMH service acceptance among psychotherapists in clinical training (PiT).

Materials and Methods

Our paper is based on a secondary data analysis of a cross-sectional survey. Respondents were recruited via recognized educational institutions for psychotherapy within Germany and the German-speaking part of Switzerland between June and July of 2020. The survey contained items on the intention to use different EMH services (i.e., guided and unguided programs, virtual reality, psychotherapy by telephone and videoconference) for various application purposes (i.e., prevention, treatment addition, treatment substitute, aftercare). Potential predictors of EMH service acceptance (e.g., barriers and advantages) were examined based on an extension of the Unified Theory of Acceptance and Use of Technology (UTAUT).

Results

Most of the n = 216 respondents were female (88.4%) and located in Germany (72.2%). General acceptance of EMH was moderate (M = 3.4, SD = 1.12, range 1-5), while acceptance of psychotherapy via videoconference was highest (M = 3.7, SD = 1.15) and acceptance of unguided programs was lowest (M = 2.55, SD = 1.14). There was an interaction effect of EMH service and application purpose (η2 = 0.21). Barriers and advantages both had a uniform influence on EMH service acceptance (Pr > 0.999), while impersonality, legal concerns, concerns about therapeutic alliance, simplified information provision, simplified contact maintenance, time flexibility, and geographic flexibility were significant predictors (all p < 0.05). Results showed that the extended UTAUT model was the best fitting model to predict EMH service acceptance (Pr > 0.999).

Conclusions

The intention to use different EMH services varied between application purposes among PiT. To increase acceptance of EMH services and reduce misconceptions, we identified predictors that should be addressed in future acceptance-facilitating interventions when educating PiT.

Diagnostic Performance of an App-Based Symptom Checker in Mental Disorders: Comparative Study in Psychotherapy Outpatients

BACKGROUND

Digital technologies have become a common starting point for health-related information-seeking. Web- or app-based symptom checkers aim to provide rapid and accurate condition suggestions and triage advice but have not yet been investigated for mental disorders in routine health care settings.

OBJECTIVE

This study aims to test the diagnostic performance of a widely available symptom checker in the context of formal diagnosis of mental disorders when compared with therapists' diagnoses based on structured clinical interviews.

METHODS

Adult patients from an outpatient psychotherapy clinic used the app-based symptom checker Ada-check your health (ADA; Ada Health GmbH) at intake. Accuracy was assessed as the agreement of the first and 1 of the first 5 condition suggestions of ADA with at least one of the interview-based therapist diagnoses. In addition, sensitivity, specificity, and interrater reliabilities (Gwet first-order agreement coefficient [AC1]) were calculated for the 3 most prevalent disorder categories. Self-reported usability (assessed using the System Usability Scale) and acceptance of ADA (assessed using an adapted feedback questionnaire) were evaluated.

RESULTS

A total of 49 patients (30/49, 61% women; mean age 33.41, SD 12.79 years) were included in this study. Across all patients, the interview-based diagnoses matched ADA's first condition suggestion in 51% (25/49; 95% CI 37.5-64.4) of cases and 1 of the first 5 condition suggestions in 69% (34/49; 95% CI 55.4-80.6) of cases. Within the main disorder categories, the accuracy of ADA's first condition suggestion was 0.82 for somatoform and associated disorders, 0.65 for affective disorders, and 0.53 for anxiety disorders. Interrater reliabilities ranged from low (AC1=0.15 for anxiety disorders) to good (AC1=0.76 for somatoform and associated disorders). The usability of ADA was rated as high in the System Usability Scale (mean 81.51, SD 11.82, score range 0-100). Approximately 71% (35/49) of participants would have preferred a face-to-face over an app-based diagnostic.

CONCLUSIONS

Overall, our findings suggest that a widely available symptom checker used in the formal diagnosis of mental disorders could provide clinicians with a list of condition suggestions with moderate-to-good accuracy. However, diagnostic performance was heterogeneous between disorder categories and included low interrater reliability. Although symptom checkers have some potential to complement the diagnostic process as a screening tool, the diagnostic performance should be tested in larger samples and in comparison with further diagnostic instruments.

Adolescent Perspectives on How an Adjunctive Mobile App for Social Anxiety Treatment Impacts Treatment Engagement in Telehealth Group Therapy

Adjunctive mobile mental health apps to supplement mental health treatment have been growing in recent years given their ability to address treatment engagement barriers. However, few studies have explicitly examined how these mobile apps impact treatment engagement, and even fewer have investigated this topic through adolescents’ perspectives. To this end, we conducted semi-structured interviews with five adolescents who used an adjunctive mobile mental health app in combination with telehealth cognitive behavioral group therapy for social anxiety. Using a multidimensional framework of treatment engagement, we elicited their perspectives on how the app impacted their engagement in telehealth group therapy and gathered their suggestions for improving the app. Using a consensual qualitative research approach, we learned that adolescents felt the app increased their comfort with others in therapy and their expectations about the effectiveness of mental health apps. They also indicated that the app prepared them for in-session participation and facilitated out-of-session skills practice. Adolescents had valuable suggestions such as adding app features to facilitate social connectedness between group members and adding appointment reminders in the app. This preliminary study highlights implications for future adjunctive mobile mental health app developers and researchers to increase adolescents’ treatment engagement in mental health services.

Bridging the ‘digital divide’ in psychological therapies: Engagement with the SlowMo mobile app for paranoia in psychosis (Preprint)

Background

Marginalized groups are more likely to experience problems with technology-related access, motivation, and skills. This is known as the “digital divide.” Technology-related exclusion is a potential barrier to the equitable implementation of digital health. SlowMo therapy was developed with an inclusive, human-centered design to optimize accessibility and bridge the “digital divide.” SlowMo is an effective, blended digital psychological therapy for paranoia in psychosis.

Objective

This study explores the “digital divide” and mobile app engagement in the SlowMo randomized controlled trial.

Methods

Digital literacy was assessed at baseline, and a multidimensional assessment of engagement (ie, adherence [via system analytics and self-report] and self-reported user experience) was conducted at 12 weeks after therapy. Engagement was investigated in relation to demographics (ie, gender, age, ethnicity, and paranoia severity).

Results

Digital literacy data demonstrated that technology use and confidence were lower in Black people and older people (n=168). The engagement findings indicated that 80.7% (96/119) of therapy completers met the a priori analytics adherence criteria. However, analytics adherence did not differ by demographics. High rates of user experience were reported overall (overall score: mean 75%, SD 17.1%; n=82). No differences in user experience were found for ethnicity, age, or paranoia severity, although self-reported app use, enjoyment, and usefulness were higher in women than in men.

Conclusions

This study identified technology-related inequalities related to age and ethnicity, which did not influence engagement with SlowMo, suggesting that the therapy design bridged the “digital divide.” Intervention design may moderate the influence of individual differences on engagement. We recommend the adoption of inclusive, human-centered design to reduce the impact of the “digital divide” on therapy outcomes.

Trial Registration

ISRCTN Registry ISRCTN32448671; https://www.isrctn.com/ISRCTN32448671