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Background: Uncertainty surrounds the ethical and legal implications of algorithmic and data-driven technologies in the mental health context, including technologies variously characterised as artificial intelligence, machine learning and deep learning. Objective: We aimed to survey scholarly literature on algorithmic and data-driven technologies used in online mental health interventions with a view to identify the legal and ethical issues raised. Methods: We searched for peer-reviewed literature about algorithmic decision systems in mental healthcare used in online platforms. Scopus, Embase and ACM were searched. 1078 relevant peer-reviewed research studies were identified, which were narrowed to 132 empirical research papers for review based on selection criteria. We thematically analysed the papers to address our aims. Results: We grouped the findings into five categories of technology: social media (n=53), smartphones (n=37), sensing technology (n=20), chatbots (n=5), and other/miscellaneous (n=17). Most initiatives were directed toward “detection and diagnosis”. Most papers discussed privacy, principally in terms of respecting research participants” privacy, with relatively little discussion of privacy in context. A small number of studies discussed ethics as an explicit category of concern (n=19). Legal issues were not substantively discussed in any studies, though seven studies noted some legal issues in passing, such as the rights of user-subjects and compliance with relevant privacy and data protection law. Conclusions: Ethics tend not to be explicitly addressed in the broad scholarship on algorithmic and data-driven technologies in online mental health initiatives—even less so legal issues. Scholars may have considered ethical or legal matters at the ethics committee/institutional review board stage of their empirical research but this consideration seldom appears in published material in any detail. We identify several concerns, including the near complete lack of involvement of service users, the scant consideration of ‘algorithmic accountability’, and the potential for over-medicalisation and techno-solutionism. Most papers were published in the computer science field at a pilot or exploratory stage. Thus, these technologies could be appropriated into practice in rarely acknowledged ways, with serious legal and ethical implications.
(Toronto, Sep 22, 2020) We are happy to announce that JMIR Mental Health, which published its first article in 2014, has been accepted for coverage in American Psychological Association’s (APA) PsycINFO.
JMIR Publications is pleased to have the following journals covered in PsycINFO:
Journal of Medical Internet Research
JMIR mHealth and uHealth (approved September 22, 2020)
JMIR Human Factors (approved September 22, 2020)
JMIR Serious Games (approved September 22, 2020)
APA is the leading scientific and professional organization representing psychology in the United States, with more than 121,000 researchers, educators, clinicians, consultants and students as its members worldwide. APA’s PsycINFO is a world-class resource for abstracts and citations of behavioral and social science research and JMIR Publications is glad to be a part of it.
The citations will be searchable once APA does the next quarterly update for PsycINFO.
JMIR Mental Health (JMH, ISSN 2368-7959, Editor-in-Chief: John Torous MD MBI, Impact Factor: 3.54) is a premier SCI/PubMed/Scopus-indexed, peer-reviewed journal which has a unique focus on digital health/digital psychiatry/digital psychology/e-mental health, covering Internet/mobile interventions, technologies and electronic innovations (software and hardware) for mental health, including addictions, online counselling and behaviour change. This includes formative evaluation and system descriptions, theoretical papers, review papers, viewpoint/vision papers, and rigorous evaluations related to digital psychiatry, e-mental health, and clinical informatics in psychiatry/psychology. In June 2020, JMH received an inaugural impact factor of 3.54.
Due to the COVID-19 pandemic, many clinical addiction treatment programs have been required to transition to telephonic or virtual visits. Novel solutions are needed to enhance substance use treatment during a time when many patients are disconnected from clinical care and social support. Digital phenotyping, which leverages the unique functionality of smartphone sensors (GPS, social behavior, and typing patterns), can buttress clinical treatment in a remote, scalable fashion. Specifically, digital phenotyping has the potential to improve relapse prediction and intervention, relapse detection, and overdose intervention. Digital phenotyping may enhance relapse prediction through coupling machine learning algorithms with the enormous amount of collected behavioral data. Activity-based analysis in real time can potentially be used to prevent relapse by warning substance users when they approach locational triggers such as bars or liquor stores. Wearable devices detect when a person has relapsed to substances through measuring physiological changes such as electrodermal activity and locomotion. Despite the initial promise of this approach, privacy, security, and barriers to access are important issues to address.
In recent years, research into internet-based cognitive behavioral therapy (iCBT) has suggested that therapist-guided digital interventions have greater engagement, adherence, and effectiveness than self-directed digital therapies. While research has focused on the effectiveness of, and adherence to, these interventions, less attention has been paid to their implementation in practice and what aspects of the therapist role support success. An understanding of the key factors related to the therapist role and intervention delivery is required if these iCBTs are to be applied in routine clinical care and outcomes optimized. In light of the coronavirus disease 2019 (COVID-19) pandemic, there is greater emphasis on allowing patients access to remote therapies. We report the experiences and reflections of 4 therapists and their 2 supervisors in delivering an online, therapist-supported intervention in a randomized controlled trial for children and young people with tic disorders (the Online Remote Behavioural Intervention for Tics [ORBIT] trial). Themes discussed include the importance of training, supervision, creating support documents/manuals, and record keeping. Alongside this are communication strategies used by therapists to encourage patient adherence and treatment effectiveness. These include rapport building, treatment personalization, and suggestions for overcoming non-engagement. These reflections offer important considerations for the delivery of iCBTs as well as implications associated with the implementation of these interventions in existing services and future research studies. We share thoughts on where iCBTs may sit in a stepped care model, how services may deal with comorbid conditions, and the potential role of iCBTs in collecting clinical data.
Background: Researchers are increasingly using social media advertisements to recruit participants because of their many advantages over traditional methods. Although there is growing evidence for the effectiveness and cost-effectiveness of social media recruitment in the health sciences, no studies have yet examined this in the context of suicide prevention, which remains to be a highly stigmatized and sensitive topic.
Objective: This study aims to recruit a general community sample to complete a survey on suicide literacy, stigma, and risk via Facebook advertisements. Specifically, we aim to establish the performance of the advertisements, cost-effectiveness, sample representativeness, and the impact of gender-specific advertising on recruiting men into the study.
Methods: From June 2017 to March 2019, we released Facebook advertisements targeted at adults 18 years or older, residing in the New South Wales (NSW) trial or control regions, and involved in the LifeSpan suicide prevention trial. Cost-effectiveness was examined descriptively using metrics provided by Facebook. Chi-square analyses were conducted to determine demographic differences between our sample and the general NSW population as well as the impact of gender-specific advertisements on gender engagement.
Results: The 14 Facebook advertisement campaigns reached a total of 675,199 people, yielding 25,993 link clicks and resulting in 9603 individuals initiating the survey (7487 completions) at an overall cost of Aus $2.81 (US $2.01) per participant. There was an overrepresentation of younger (P=.003), female (P=.003), highly educated (P<.001) participants and mental health conditions (P<.001) compared with the total NSW population. The use of male-specific advertisements resulted in a significantly higher proportion of men completing the survey relative to gender-neutral advertisements (38.2% vs 24.6%; P<.001).
Conclusions: This study demonstrates the potential of Facebook to be an effective, low-cost strategy for recruiting a large sample of general community participants for suicide prevention research. Strategies to improve sample representativeness warrant further investigation in future research.
Background: Loneliness is a widespread and significant problem on college campuses. Prolonged loneliness in young adulthood is a risk factor for concurrent and future mental health problems and attrition, making college a critical time for support. Cognitive and behavioral interventions show promise for decreasing loneliness and can be widely disseminated through technology.
Objective: This pilot randomized controlled trial was conducted to examine the initial efficacy, feasibility, and desirability of a smartphone app, Nod, designed to deliver cognitive and behavioral skill-building exercises to reduce loneliness during the transition to college.
Methods: First-year college students (N=221, mean age 18.7 years, 59% female) were recruited online during incoming student orientation, and randomized to either receive immediate access to Nod (experimental group, n=100) or access after 4 weeks (control group, n=121). The app delivered skills via fully automated (1) “social challenges,” suggested activities designed to build social connections; (2) reflections, brief cognitive reframing exercises; and (3) student testimonials that encouraged a growth mindset toward social connection building. Main intention-to-treat analyses were used to compare the conditions on self-assessed loneliness, depressive symptoms, and other mental health and college adjustment outcomes at week 4, controlling for baseline values on those variables. Analyses were also performed to test the hypothesis that the treatment benefits would be particularly pronounced for participants with heightened psychological vulnerability at baseline (ie, higher baseline depressive symptoms and loneliness).
Results: Retention was 97% at week 4, and participants viewed an average 36.7 pages of app content. There were no significant condition differences in loneliness at week 4 (F1, 211=0.05, P=.82; ηp2 <.001). However, there was a significant condition-by-baseline depression interaction to predict week-4 loneliness (F1,209=9.65, P=.002; ηp2 =.04). Simple slope analyses indicated that baseline depression positively predicted week-4 loneliness among control participants (r=0.30, t209=3.81, P<.001), but not among experimental participants (r=–0.09, t209=–0.84, P=.40), suggesting that Nod buffered participants with high baseline depression scores from experiencing heightened midquarter loneliness. Similarly, there were no significant condition differences in other week-4 outcomes. However, moderation by baseline vulnerability was found for week-4 depressive symptoms, sleep quality, and indices of college adjustment (eg, perceived social support and campus belonging).
Conclusions: Although Nod exposure did not impact outcomes for the full sample, these results provide initial evidence of its benefit for vulnerable students. The results of this trial suggest that cognitive and behavioral skills delivered via a mobile app can buffer psychologically vulnerable college students against heightened loneliness and depressive symptoms, as well as other negative college adjustment outcomes. Future work will aim to improve upon app engagement, and to address loneliness among other key populations.
Trial Registration: ClinicalTrials.gov NCT04164654; https://clinicaltrials.gov/ct2/show/NCT04164654
Background: Young people experience a disproportionate burden associated with mental illness that Australia’s mental health care system is ill-equipped to handle. Despite improvements in the provision of mental health services, the rates of service utilization among young people remain suboptimal, and there are still considerable barriers to seeking help. Digital mental health services can overcome a number of barriers and connect young people requiring support; however, the evidence base of digital interventions is limited.
Objective: The aim of this study is to examine the effectiveness of a brief, self-directed, unstructured digital intervention, ReachOut.com (hereafter ReachOut), in reducing depression, anxiety, stress, and risk of suicide.
Methods: A cohort of 1982 ReachOut users participated in a 12-week longitudinal study, with a retention rate of 81.18% (1609/1982) across the duration of the study. Participants completed web-based surveys, with outcome measures of mental health status and suicide risk assessed at 3 time points across the study period.
Results: The results demonstrated that over the 12-week study period, young people using ReachOut experienced modest yet significant reductions in symptoms of depression, anxiety, and stress. Significant, albeit modest, reductions in the proportion of participants at high risk of suicide were also observed.
Conclusions: The findings of this research provide preliminary evidence of the promise of an unstructured digital mental health intervention, ReachOut, in alleviating symptoms of mental ill-health and promoting well-being in young people. These findings are particularly important given that digital services are not only acceptable and accessible but also have the potential to cater to the diverse mental health needs of young people at scale, in a way that other services cannot.
Background: Most people with common mental disorders, including those with severe mental illness, are treated in general practice. Video-based integrated care models featuring mental health specialist video consultations (MHSVC) facilitate the involvement of specialist mental health care. However, the potential uptake by general practitioners (GPs) is unclear.
Objective: This mixed method preimplementation study aims to assess GPs’ intent to adopt MHSVC in their practice, identify predictors for early intent to adopt (quantitative strand), and characterize GPs with early intent to adopt based on the Diffusion of Innovations Theory (DOI) theory (qualitative strand).
Methods: Applying a convergent parallel design, we conducted a survey of 177 GPs and followed it up with focus groups and individual interviews for a sample of 5 early adopters and 1 nonadopter. We identified predictors for intent to adopt through a cumulative logit model for ordinal multicategory responses for data with a proportional odds structure. A total of 2 coders independently analyzed the qualitative data, deriving common characteristics across the 5 early adopters. We interpreted the qualitative findings accounting for the generalized adopter categories of DOI.
Results: This study found that about one in two GPs (87/176, 49.4%) assumed that patients would benefit from an MHSVC service model, about one in three GPs (62/176, 35.2%) intended to adopt such a model, the availability of a designated room was the only significant predictor of intent to adopt in GPs (β=2.03, SE 0.345, P<.001), supporting GPs expected to save time and took a solution-focused perspective on the practical implementation of MHSVC, and characteristics of supporting and nonsupporting GPs in the context of MHSVC corresponded well with the generalized adopter categories conceptualized in the DOI.
Conclusions: A significant proportion of GPs may function as early adopters and key stakeholders to facilitate the spread of MHSVC. Indeed, our findings correspond well with increasing utilization rates of telehealth in primary care and specialist health care services (eg, mental health facilities and community-based, federally qualified health centers in the United States). Future work should focus on specific measures to foster the intention to adopt among hesitant GPs.
Background: In recent years, there has been an increase in symptoms of depression, anxiety, and other mental illnesses in college student populations alongside a steady rise in the demand for counseling services. Digital mental health programs, such as those delivered through mobile apps, can add to the array of available services but must be tested for usability and acceptability before implementation.
Objective: This study aims to examine how students used IntelliCare for College Students over an 8-week period to examine the preliminary associations between app use and psychosocial targets and to gather user feedback about usability issues that need to be remedied before a larger implementation study.
Methods: IntelliCare for College Students is an app-based platform that provides symptom assessments with personalized feedback, information about campus resources, lessons on mental health and wellness topics, and access to the suite of interactive skill–focused IntelliCare apps. A total of 20 students were recruited to participate in an 8-week study. To test for a broad range of potential users, we recruited a mixed sample of students with elevated symptoms of depression or anxiety and students without elevated symptoms. Participants completed psychosocial questionnaires at baseline, week 4, and week 8. Participants also completed user feedback interviews at weeks 4 and 8 in which they provided feedback on their experience using the app and suggestions for changes they would like to be made to the app.
Results: Of the 20 students who downloaded the app, 19 completed the study, indicating a high rate of retention. Over the study period, participants completed an average of 5.85 (SD 2.1; range 1-8) symptom assessments. Significant improvements were observed in the Anxiety Literacy Questionnaire scores (Z=−2.006; P=.045) and in the frequency with which participants used both cognitive (Z=−2.091; P=.04) and behavioral (Z=−2.249; P=.03) coping skills. In the feedback interviews, we identified a high degree of usability with minor bugs in the app software, which were quickly fixed. Furthermore, in feedback interviews, we identified that users found the app to be convenient and appreciated the ability to use the program in short bursts of time.
Conclusions: The findings indicate that the IntelliCare for College Students program was perceived as largely usable and engaging. Although the program demonstrated usability and preliminary benefits to students, further testing is needed to determine its clinical utility among college students.
Trial Registration: ClinicalTrials.gov NCT04035577; https://clinicaltrials.gov/ct2/show/NCT04035577
Background: Tobacco smoking remains the leading cause of preventable death and disease worldwide. Digital interventions delivered through smartphones offer a promising alternative to traditional methods, but little is known about their effectiveness.
Objective: Our objective was to test the preliminary effectiveness of Quit Genius, a novel digital therapeutic intervention for smoking cessation.
Methods: A 2-arm, single-blinded, parallel-group randomized controlled trial design was used. Participants were recruited via referrals from primary care practices and social media advertisements in the United Kingdom. A total of 556 adult smokers (aged 18 years or older) smoking at least 5 cigarettes a day for the past year were recruited. Of these, 530 were included for the final analysis. Participants were randomized to one of 2 interventions. Treatment consisted of a digital therapeutic intervention for smoking cessation consisting of a smartphone app delivering cognitive behavioral therapy content, one-to-one coaching, craving tools, and tracking capabilities. The control intervention was very brief advice along the Ask, Advise, Act model. All participants were offered nicotine replacement therapy for 3 months. Participants in a random half of each arm were pseudorandomly assigned a carbon monoxide device for biochemical verification. Outcomes were self-reported via phone or online. The primary outcome was self-reported 7-day point prevalence abstinence at 4 weeks post quit date.
Results: A total of 556 participants were randomized (treatment: n=277; control: n=279). The intention-to-treat analysis included 530 participants (n=265 in each arm; 11 excluded for randomization before trial registration and 15 for protocol violations at baseline visit). By the quit date (an average of 16 days after randomization), 89.1% (236/265) of those in the treatment arm were still actively engaged. At the time of the primary outcome, 74.0% (196/265) of participants were still engaging with the app. At 4 weeks post quit date, 44.5% (118/265) of participants in the treatment arm had not smoked in the preceding 7 days compared with 28.7% (76/265) in the control group (risk ratio 1.55, 95% CI 1.23-1.96; P<.001; intention-to-treat, n=530). Self-reported 7-day abstinence agreed with carbon monoxide measurement (carbon monoxide <10 ppm) in 96% of cases (80/83) where carbon monoxide readings were available. No harmful effects of the intervention were observed.
Conclusions: The Quit Genius digital therapeutic intervention is a superior treatment in achieving smoking cessation 4 weeks post quit date compared with very brief advice.
Trial Registration: International Standard Randomized Controlled Trial Number (ISRCTN) 65853476; https://www.isrctn.com/ISRCTN65853476
Background: The COVID-19 pandemic has been associated with increased psychological distress, signaling the need for increased mental health services in the context of stay-at-home policies.
Objective: This study aims to characterize how mental health practitioners have changed their practices during the pandemic. The authors hypothesize that mental health practitioners would increase tele–mental health services and that certain provider types would be better able to adapt to tele–mental health than others.
Methods: The study surveyed 903 practitioners, primarily psychologists/doctoral-level (Psych/DL) providers, social workers/master’s-level (SW/ML) providers, and neuropsychologists employed in academic medical centers or private practices. Differences among providers were examined using Bonferroni-adjusted chi-square tests and one-way Bonferroni-adjusted analyses of covariance.
Results: The majority of the 903 mental health practitioners surveyed rapidly adjusted their practices, predominantly by shifting to tele–mental health appointments (n=729, 80.82%). Whereas 80.44% (n=625) were not using tele–mental health in December 2019, only 22.07% (n=188) were not by late March or early April 2020. Only 2.11% (n=19) reported no COVID-19–related practice adjustments. Two-thirds (596/888, 67.10%) reported providing additional therapeutic services specifically to treat COVID-19–related concerns. Neuropsychologists were less likely and Psych/DL providers and SW/ML providers were more likely than expected to transition to tele–mental health (P<.001). Trainees saw fewer patients (P=.01) and worked remotely more than licensed practitioners (P=.03). Despite lower rates of information technology service access (P<.001), private practice providers reported less difficulty implementing tele–mental health than providers in other settings (P<.001). Overall, the majority (530/889, 59.62%) were interested in continuing to provide tele–mental health services in the future.
Conclusions: The vast majority of mental health providers in this study made practice adjustments in response to COVID-19, predominantly by rapidly transitioning to tele–mental health services. Although the majority reported providing additional therapeutic services specifically to treat COVID-19–related concerns, only a small subset endorsed offering such services to medical providers. This has implications for future practical directions, as frontline workers may begin to seek mental health treatment related to the pandemic. Despite differences in tele–mental health uptake based on provider characteristics, the majority were interested in continuing to provide such services in the future. This may help to expand clinical services to those in need via tele–mental health beyond the COVID-19 pandemic.
Background: Suicide is a growing global public health problem that has resulted in an increase in the demand for psychological services to address mental health issues. It is expected that 1 in 6 people on a waiting list for mental health services will attempt suicide. Although suicidal ideation has been shown to be linked to a higher risk of death by suicide, not everybody openly discloses their suicidal thoughts or plans to friends and family or seeks professional help before suicide. Therefore, new methods are needed to track suicide risk in real time together with a better understanding of the ways in which people communicate or express their suicidality. Considering the dynamic nature and challenges in understanding suicide ideation and suicide risk, mobile apps could be better suited to prevent suicide as they have the ability to collect real-time data.
Objective: This study aims to report the practicalities and acceptability of setting up and trialing digital technologies within an inpatient mental health setting in the United Kingdom and highlight their implications for future studies.
Methods: Service users were recruited from 6 inpatient wards in the north west of England. Service users who were eligible to participate and provided consent were given an iPhone and Fitbit for 7 days and were asked to interact with a novel phone app, Strength Within Me (SWiM). Interaction with the app involved journaling (recording daily activities, how this made them feel, and rating their mood) and the option to create safety plans for emotions causing difficulties (identifying strategies that helped with these emotions). Participants also had the option to allow the study to access their personal Facebook account to monitor their social media use and activity. In addition, clinical data (ie, assessments conducted by trained researchers targeting suicidality, depression, and sleep) were also collected.
Results: Overall, 43.0% (80/186 response rate) of eligible participants were recruited for the study. Of the total sample, 67 participants engaged in journaling, with the average number of entries per user being 8.2 (SD 8.7). Overall, only 24 participants created safety plans and the most common difficult emotion to be selected was feeling sad (n=21). This study reports on the engagement with the SWiM app, the technical difficulties the research team faced, the importance of building key relationships, and the implications of using Facebook as a source to detect suicidality.
Conclusions: To develop interventions that can be delivered in a timely manner, prediction of suicidality must be given priority. This paper has raised important issues and highlighted lessons learned from implementing a novel mobile app to detect the risk of suicidality for service users in an inpatient setting.
Background: During pandemics, effective containment and mitigation measures may also negatively influence psychological stability. As knowledge about COVID-19 rapidly evolves, global implementation of containment and mitigation measures has varied greatly, with impacts to mental wellness. Assessing the impact of COVID-19 on the mental health needs of health care workers and other workers may help mitigate mental health impacts and secure sustained delivery of health care and other essential goods and services.
Objective: This study assessed the self-reported prevalence of stress, anxiety, depression, and obsessive-compulsive symptoms in health care workers and other workers seeking support through Text4Hope, an evidence-based SMS text messaging service supporting the mental health of residents of Alberta, Canada, during the COVID-19 pandemic.
Methods: An online cross-sectional survey gathered demographic (age, gender, ethnicity, education, relationship, housing and employment status, employment type, and isolation status) and clinical characteristics using validated tools (self-reported stress, anxiety, depression, and contamination/hand hygiene obsessive-compulsive symptoms). Descriptive statistics and chi-square analysis were used to compare the clinical characteristics of health care workers and other workers. Post hoc analysis was conducted on variables with >3 response categories using adjusted residuals. Logistic regression determined associations between worker type and likelihood of self-reported symptoms of moderate or high stress, generalized anxiety disorder, and major depressive disorder, while controlling for other variables.
Results: Overall, 8267 surveys were submitted by 44,992 Text4Hope subscribers (19.39%). Of these, 5990 respondents were employed (72.5%), 958 (11.6%) were unemployed, 454 (5.5%) were students, 559 (6.8%) were retired, 234 (2.8%) selected “other,” and 72 (0.9%) did not indicate their employment status. Most employed survey respondents were female (n=4621, 86.2%). In the general sample, the 6-week prevalence rates for moderate or high stress, anxiety, and depression symptoms were 85.6%, 47.0%, and 44.0%, respectively. Self-reported symptoms of moderate or high stress, anxiety, and depression were all statistically significantly higher in other workers than in health care workers (P<.001). Other workers reported higher obsessive-compulsive symptoms (worry about contamination and compulsive handwashing behavior) after the onset of the pandemic (P<.001), while health care worker symptoms were statistically significantly higher before and during the COVID-19 pandemic (P<.001). This finding should be interpreted with caution, as it is unclear the extent to which the adaptive behavior of health care workers or the other workers might be misclassified by validated tools during a pandemic.
Conclusions: Assessing symptoms of prevalent stress, anxiety, depression, and obsessive-compulsive behavior in health care workers and other workers may enhance our understanding of COVID-19 mental health needs. Research is needed to understand more fully the relationship between worker type, outbreak phase, and mental health changes over time, as well as the utility of validated tools in health care workers and other workers during pandemics. Our findings underscore the importance of anticipating and mitigating the mental health effects of pandemics using integrated implementation strategies. Finally, we demonstrate the ease of safely and rapidly assessing mental health needs using an SMS text messaging platform during a pandemic.
Background: Homelessness among youth is devastating, with high rates of substance use disorders and mental health comorbidity. Mindfulness-based interventions that include meditation and mindfulness skills training reduce stress and symptoms of anxiety or depression. However, engaging high-risk youth in interventions is challenging. Virtual reality is a more flexible platform for delivering meditation and may be appealing to youth.
Objective: The study objectives were to evaluate the feasibility of delivering virtual reality meditation and of collecting outcome measures, including anxiety and physiologic stress.
Methods: A sample of 30 youth experiencing homelessness was enrolled in the study. Youth were randomized to receive 10 minutes of one of three interventions: (1) virtual reality meditation, (2) audio meditation (through a web-based platform), or (3) virtual reality imagery of historical pictures and text. Subjects who consented to the study attended two research visits. The first visit collected survey measures of demographics, mental health, and substance use, and oriented subjects to the intervention platforms. The second visit (1-3 days later) delivered the intervention and collected pre and post outcome measures of anxiety and physiologic stress (salivary cortisol). Changes in anxiety and cortisol at the second visit were compared across groups using a linear regression model in which the primary analysis compared virtual reality meditation to audio meditation and secondary analyses compared virtual reality meditation to virtual reality imagery.
Results: Anxiety scores decreased in all groups, with a larger reduction among the virtual reality meditation group (difference=10.8) compared to the web-based meditation or virtual reality images groups (difference=5.8 and 5.0, respectively). After controlling for baseline values, there were no significant group differences in changes in anxiety scores or cortisol levels. In comparing virtual reality meditation and audio meditation, the effect size for anxiety was moderate (Cohen d=0.58) while the effect size for cortisol was small (Cohen d=0.08).
Conclusions: Preliminary results suggest that virtual reality meditation has a moderate benefit for anxiety but not physiologic stress. Future research is needed to confirm these results in a larger sample and to investigate whether the effects are sustained or increase with repeated use of virtual reality mediation. Virtual reality meditation appears feasible to deliver among homeless youth and merits further study.
Trial Registration: ClinicalTrials.gov NCT04004520; https://clinicaltrials.gov/ct2/show/NCT04004520
Background: Uncertainty surrounds the ethical and legal implications of algorithmic and data-driven technologies in the mental health context, including technologies variously characterised as artific...
Background: Uncertainty surrounds the ethical and legal implications of algorithmic and data-driven technologies in the mental health context, including technologies variously characterised as artificial intelligence, machine learning and deep learning. Objective: We aimed to survey scholarly literature on algorithmic and data-driven technologies used in online mental health interventions with a view to identify the legal and ethical issues raised. Methods: We searched for peer-reviewed literature about algorithmic decision systems in mental healthcare used in online platforms. Scopus, Embase and ACM were searched. 1078 relevant peer-reviewed research studies were identified, which were narrowed to 132 empirical research papers for review based on selection criteria. We thematically analysed the papers to address our aims. Results: We grouped the findings into five categories of technology: social media (n=53), smartphones (n=37), sensing technology (n=20), chatbots (n=5), and other/miscellaneous (n=17). Most initiatives were directed toward “detection and diagnosis”. Most papers discussed privacy, principally in terms of respecting research participants” privacy, with relatively little discussion of privacy in context. A small number of studies discussed ethics as an explicit category of concern (n=19). Legal issues were not substantively discussed in any studies, though seven studies noted some legal issues in passing, such as the rights of user-subjects and compliance with relevant privacy and data protection law. Conclusions: Ethics tend not to be explicitly addressed in the broad scholarship on algorithmic and data-driven technologies in online mental health initiatives—even less so legal issues. Scholars may have considered ethical or legal matters at the ethics committee/institutional review board stage of their empirical research but this consideration seldom appears in published material in any detail. We identify several concerns, including the near complete lack of involvement of service users, the scant consideration of ‘algorithmic accountability’, and the potential for over-medicalisation and techno-solutionism. Most papers were published in the computer science field at a pilot or exploratory stage. Thus, these technologies could be appropriated into practice in rarely acknowledged ways, with serious legal and ethical implications.
