The potential of smartphone apps to improve quality and increase access to mental health care is increasingly clear. Yet even in the current global mental health crisis, real-world uptake of ...smartphone apps by clinics or consumers remains low. To understand this dichotomy, this paper reviews current challenges surrounding user engagement with mental health smartphone apps. While smartphone engagement metrics and reporting remains heterogeneous in the literature, focusing on themes offers a framework to identify underlying trends. These themes suggest that apps are not designed with service users in mind, do not solve problems users care most about, do not respect privacy, are not seen as trustworthy and are unhelpful in emergencies. Respecting these current issues surrounding mental health app engagement, we propose several solutions and highlight successful examples of mental health apps with high engagement. Further research is necessary to better characterise engagement with mental health apps and identify best practices for design, testing and implementation.
Inadequate privacy disclosures have repeatedly been identified by cross-sectional surveys of health applications (apps), including apps for mental health and behavior change. However, few studies ...have assessed directly the correspondence between privacy disclosures and how apps handle personal data. Understanding the scope of this discrepancy is particularly important in mental health, given enhanced privacy concerns relating to stigma and negative impacts of inadvertent disclosure. Because most health apps fall outside government regulation, up-to-date technical scrutiny is essential for informed decision making by consumers and health care professionals wishing to prescribe health apps.
To provide a contemporary assessment of the privacy practices of popular apps for depression and smoking cessation by critically evaluating privacy policy content and, specifically, comparing disclosures regarding third-party data transmission to actual behavior.
Cross-sectional assessment of 36 top-ranked (by app store search result ordering in January 2018) apps for depression and smoking cessation for Android and iOS in the United States and Australia. Privacy policy content was evaluated with prespecified criteria. Technical assessment of encrypted and unencrypted data transmission was performed. Analysis took place between April and June 2018.
Correspondence between policies and transmission behavior observed by intercepting sent data.
Twenty-five of 36 apps (69%) incorporated a privacy policy. Twenty-two of 25 apps with a policy (88%) provided information about primary uses of collected data, while only 16 (64%) described secondary uses. While 23 of 25 apps with a privacy policy (92%) stated in a policy that data would be transmitted to a third party, transmission was detected in 33 of all 36 apps (92%). Twenty-nine of 36 apps (81%) transmitted data for advertising and marketing purposes or analytics to just 2 commercial entities, Google and Facebook, but only 12 of 28 (43%) transmitting data to Google and 6 of 12 (50%) transmitting data to Facebook disclosed this.
Data sharing with third parties that includes linkable identifiers is prevalent and focused on services provided by Google and Facebook. Despite this, most apps offer users no way to anticipate that data will be shared in this way. As a result, users are denied an informed choice about whether such sharing is acceptable to them. Privacy assessments that rely solely on disclosures made in policies, or are not regularly updated, are unlikely to uncover these evolving issues. This may limit their ability to offer effective guidance to consumers and health care professionals.
Social network analysis is a prominent approach to investigate interpersonal relationships. Most studies use self-report data to quantify the connections between participants and construct social ...networks. In recent years smartphones have been used as an alternative to map networks by assessing the proximity between participants based on Bluetooth and GPS data. While most studies have handed out specially programmed smartphones to study participants, we developed an application for iOS and Android to collect Bluetooth data from participants' own smartphones. In this study, we compared the networks estimated with the smartphone app to those obtained from sociometric badges and self-report data. Participants (n = 21) installed the app on their phone and wore a sociometric badge during office hours. Proximity data was collected for 4 weeks. A contingency table revealed a significant association between proximity data (ϕ = 0.17, p<0.0001), but the marginal odds were higher for the app (8.6%) than for the badges (1.3%), indicating that dyads were more often detected by the app. We then compared the networks that were estimated using the proximity and self-report data. All three networks were significantly correlated, although the correlation with self-reported data was lower for the app (ρ = 0.25) than for badges (ρ = 0.67). The scanning rates of the app varied considerably between devices and was lower on iOS than on Android. The association between the app and the badges increased when the network was estimated between participants whose app recorded more regularly. These findings suggest that the accuracy of proximity networks can be further improved by reducing missing data and restricting the interpersonal distance at which interactions are detected.
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DOBA, IZUM, KILJ, NUK, PILJ, PNG, SAZU, SIK, UILJ, UKNU, UL, UM, UPUK
Means restriction interventions are recognised as highly effective for the deterrence of suicide attempts by jumping. While such interventions can lead to significant reductions in suicide, it is ...unclear whether these reductions represent a displacement effect, whereby individuals are instead choosing to attempt suicide at other nearby locations which offer the same means. The potential displacement of suicides as an unintended consequence of means restriction has been relatively unexplored to date. The only studies exploring displacement effects have focused on bridges, which are relatively easily contained sites; no studies have yet explored displacement effects at cliff-based high risk suicide locations (hotspots). Using Australian coronial data for the period of 2006–2019, we undertook joinpoint and kernel density analysis of suicides by jumping at a well-known cliff-based hotspot in Sydney, Australia, to determine whether there was evidence of displacement to local and broader surrounding cliffs following the installation of a multi-component harm minimization intervention (the Gap Park Masterplan). While slight decreases were noted in the immediate area subject to the structural intervention in the post-implementation period, alongside slight increases in the surrounding cliffs, there was no evidence for statistically significant changes. While kernel density analyses did not identify the emergence of any new hotspot locations in the post-implementation period, three existing hotspot sites of concern were found in our total area of interest, with greater than expected growth in the density of one of the hotspots. While we found no persuasive evidence of displacement, ongoing monitoring of the cliff-based location where the structural interventions were implemented is needed to ensure the ongoing safety of the area.
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EMUNI, FIS, FZAB, GEOZS, GIS, IJS, IMTLJ, KILJ, KISLJ, MFDPS, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, SBMB, SBNM, UKNU, UL, UM, UPUK, VKSCE, ZAGLJ
Background
Poor engagement has hindered the dissemination of self‐guided digital therapeutics for mental health. Evidence on the efficacy of technology‐supported strategies designed for increasing ...engagement with these interventions is currently inconclusive. Few studies have examined user perceptions of such strategies, which could yield key insights for enhancing their effectiveness.
Methods
Two hundred and eleven participants completed a cross‐sectional online survey. All participants were aged 18 years and above, living in Australia, fluent in English, and self‐reported prior use of digital therapeutics for mental health needs. Survey items elicited participants' views on factor(s) contributing to their engagement/disengagement with digital therapeutics, and perceptions of engagement strategies, including: automated electronic reminders, fun facts, quizzes, and social media platforms. χ2 tests of independence were used to analyse nominal data. Inductive thematic analysis was used to analyse free‐text data.
Results
Factors facilitating engagement included digestible content, assurance of confidentiality, and esthetically appealing design. Factors hindering engagement included lack of time, forgetfulness, and lack of perceived intervention efficacy. Participants had mixed views over the feasibility and acceptability of the strategies explored toward promoting engagement.
Conclusions
Regardless of strategy type, succinct and easily applicable content was identified as an important feature for promoting engagement. Conversely, content that could trigger psychological distress among intervention users should be avoided. Overall, the diverse range of user perspectives highlighted that engagement strategies for any specific digital intervention should be co‐designed with individuals with lived experience of mental health difficulties.
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BFBNIB, DOBA, FZAB, GIS, IJS, IZUM, KILJ, NLZOH, NUK, OILJ, PILJ, PNG, SAZU, SBCE, SBMB, SIK, UILJ, UKNU, UL, UM, UPUK
Data generated within social media platforms may present a new way to identify individuals who are experiencing mental illness. This study aimed to investigate the associations between linguistic ...features in individuals' blog data and their symptoms of depression, generalised anxiety, and suicidal ideation. Individuals who blogged were invited to participate in a longitudinal study in which they completed fortnightly symptom scales for depression and anxiety (PHQ-9, GAD-7) for a period of 36 weeks. Blog data published in the same period was also collected, and linguistic features were analysed using the LIWC tool. Bivariate and multivariate analyses were performed to investigate the correlations between the linguistic features and symptoms between subjects. Multivariate regression models were used to predict longitudinal changes in symptoms within subjects. A total of 153 participants consented to the study. The final sample consisted of the 38 participants who completed the required number of symptom scales and generated blog data during the study period. Between-subject analysis revealed that the linguistic features "tentativeness" and "non-fluencies" were significantly correlated with symptoms of depression and anxiety, but not suicidal thoughts. Within-subject analysis showed no robust correlations between linguistic features and changes in symptoms. The findings may provide evidence of a relationship between some linguistic features in social media data and mental health; however, the study was limited by missing data and other important considerations. The findings also suggest that linguistic features observed at the group level may not generalise to, or be useful for, detecting individual symptom change over time.
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DOBA, IZUM, KILJ, NUK, PILJ, PNG, SAZU, SIK, UILJ, UKNU, UL, UM, UPUK
Digital interventions that deliver psychological self-help provide the opportunity to reach individuals at risk of suicide who do not access traditional health services. Our primary objective was to ...test whether direct (targeting suicidality) and indirect (targeting depression) digital interventions are effective in reducing suicidal ideation and behaviours, and our secondary analyses assessed whether direct interventions were more effective than indirect interventions.
In this systematic review and meta-analysis, we searched online databases MEDLINE, PubMed, PsycINFO, and Cochrane CENTRAL for randomised controlled trials published between database inception to May 21, 2019. Superiority randomised controlled trials of self-guided digital interventions (app or web based, which delivered theory-based therapeutic content) were included if they reported suicidal ideation, suicidal plans, or suicide attempts as an outcome. Non-inferiority randomised controlled trials were excluded to ensure comparability of the effect. Data were extracted from published reports, and intention-to-treat data were used if available. The primary outcome was the difference in mean scores of validated suicidal ideation measures (Hedges'g) with the associated 95% CI for the analysis of digital intervention effectiveness on suicidal ideation. We also present funnel plots of the primary outcome measure (suicidal ideation) for direct and indirect interventions to assess for publication bias. We calculated I2 (with I2 CI) values to test heterogeneity. We used random-effects modelling for the meta-analyses to assess the primary and secondary outcomes. This study is registered with PROSPERO, CRD42018102084.
The literature search yielded 739 articles (including manual searching) for suicidality and 8842 articles for depression. After screening, 14 papers reporting on 16 studies were included in the narrative review and meta-analysis. The 16 studies (ten on direct interventions and six on indirect interventions) provided baseline data for 4398 participants. The primary outcome of overall post-intervention effect for suicidal ideation was small but significant immediately following the active intervention phase (Hedges'g −0·18, 95% CI −0·27 to −0·10, p<0·0001; I2=0%, I2 CI 0·0–47·9). The secondary objective, comparing direct and indirect interventions, showed that direct interventions (targeting suicidality) significantly reduced suicidal ideation at post-intervention (g −0·23, 95% CI −0·35 to −0·11, p<0·0001; I2=17·6%, I2 CI 0·0–58·6), but indirect interventions (targeting depression) failed to reach significance (g −0·12, 95% CI −0·25 to 0·01, p=0·071; I2=0%, I2 CI 0·0–30·7).
Self-guided digital interventions directly targeting suicidal ideation are effective immediately post-intervention. Indirect interventions were not significant for reducing suicidal ideation. Our findings suggest that digital interventions should be promoted and disseminated widely, especially where there is a lack of, or minimal access to, health services.
Australian National Health and Medical Research Council.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UILJ, UL, UM, UPCLJ, UPUK, ZAGLJ, ZRSKP
Purpose of Review
As rates of suicide continue to rise, there is urgent need for innovative approaches to better understand, predict, and care for those at high risk of suicide. Numerous mobile and ...sensor technology solutions have already been proposed, are in development, or are already available today. This review seeks to assess their clinical evidence and help the reader understand the current state of the field.
Recent Findings
Advances in smartphone sensing, machine learning methods, and mobile apps directed towards reducing suicide offer promising evidence; however, most of these innovative approaches are still nascent. Further replication and validation of preliminary results is needed.
Summary
Whereas numerous promising mobile and sensor technology based solutions for real time understanding, predicting, and caring for those at highest risk of suicide are being studied today, their clinical utility remains largely unproven. However, given both the rapid pace and vast scale of current research efforts, we expect clinicians will soon see useful and impactful digital tools for this space within the next 2 to 5 years.
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EMUNI, FIS, FZAB, GEOZS, GIS, IJS, IMTLJ, KILJ, KISLJ, MFDPS, NLZOH, NUK, OBVAL, OILJ, PNG, SAZU, SBCE, SBJE, SBMB, SBNM, UKNU, UL, UM, UPUK, VKSCE, ZAGLJ
Clinical and research interest in the potential of mobile health apps for the management of mental health conditions has recently been given added impetus by growing evidence of consumer adoption. In ...parallel, there is now a developing evidence base that includes meta-analyses demonstrating reductions in symptoms of depression and anxiety, and reduction in suicidal ideation. While these findings are encouraging, recent research continues to identify a number of potential barriers to the widespread adoption of mental health apps. These challenges include poor data governance and data sharing practices; questions of clinical safety relating to the management of adverse events and potentially harmful content; low levels of user engagement and the possibility of ‘digital placebo’ effects; and workforce barriers to integration with clinical practice. Current efforts to address these include the development of new models of care, such as ‘digital clinics’ that integrate health apps. Other contemporary innovations in the field such as digital sensing and just-in-time adaptive interventions are showing early promise for providing accessible and personalised care.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UILJ, UL, UM, UPCLJ, UPUK, ZAGLJ, ZRSKP
Current routes of delivering therapeutics to the brain to treat a variety of neurologic conditions include intracerebral, intrathecal, and intranasal delivery. Though successes have been achieved ...through the use of these methods, each has limitations that warrant a more universal delivery system involving the intravenous pathway. Two main barriers to intravenous delivery are the blood-brain barrier (BBB) and the blood-cerebrospinal fluid barrier. This review discusses potential methods for overcoming barriers of intravenous-mediated brain targeting as well as highlights aspects of the highly restrictive BBB anatomy that are important to consider in the design of successful drug delivery systems. Recent advances in intravenous delivery to the brain have exploited receptor-mediated transcytosis and BBB disruption, as well as control of carrier properties. Currently, three predominant synthetic carriers are being studied to transport therapeutics across the BBB: liposomes, metallic nanoparticles, and polymersomes. This article also focuses on receptors that may be upregulated by brain endothelial cells and their ability to significantly increase brain tissue drug distribution when specific targeting moieties to these receptors are attached to synthetic nanocarriers.