Adoption of Mobile Apps for Depression and Anxiety: Cross-Sectional Survey Study on Patient Interest and Barriers to Engagement

BACKGROUND: Emerging research suggests that mobile apps can be used to effectively treat common mental illnesses like depression and anxiety. Despite promising efficacy results and ease of access to these interventions, adoption of mobile health (mHealth; mobile device-delivered) interventions for mental illness has been limited. More insight into patients\u27 perspectives on mHealth interventions is required to create effective implementation strategies and to adapt existing interventions to facilitate higher rates of adoption. OBJECTIVE: The aim of this study was to examine, from the patient perspective, current use and factors that may impact the use of mHealth interventions for mental illness. METHODS: This was a cross-sectional survey study of veterans who had attended an appointment at a single Veterans Health Administration facility in early 2016 that was associated with one of the following mental health concerns: unipolar depression, any anxiety disorder, or posttraumatic stress disorder. We used the Veteran Affairs Corporate Data Warehouse to create subsets of eligible participants demographically stratified by gender (male or female) and minority status (white or nonwhite). From each subset, 100 participants were selected at random and mailed a paper survey with items addressing the demographics, overall health, mental health, technology ownership or use, interest in mobile app interventions for mental illness, reasons for use or nonuse, and interest in specific features of mobile apps for mental illness. RESULTS: Of the 400 potential participants, 149 (37.3%, 149/400) completed and returned a survey. Most participants (79.9%, 119/149) reported that they owned a smart device and that they use apps in general (71.1%, 106/149). Most participants (73.1%, 87/149) reported interest in using an app for mental illness, but only 10.7% (16/149) had done so. Paired samples t tests indicated that ratings of interest in using an app recommended by a clinician were significantly greater than general interest ratings and even greater when the recommending clinician was a specialty mental health provider. The most frequent concerns related to using an app for mental illness were lacking proof of efficacy (71.8%, 107/149), concerns about data privacy (59.1%, 88/149), and not knowing where to find such an app (51.0%, 76/149). Participants expressed interest in a number of app features with particularly high-interest ratings for context-sensitive apps (85.2%, 127/149), and apps focused on the following areas: increasing exercise (75.8%, 113/149), improving sleep (73.2%, 109/149), changing negative thinking (70.5%, 105/149), and increasing involvement in activities (67.1%, 100/149). CONCLUSIONS: Most respondents had access to devices to use mobile apps for mental illness, already used apps for other purposes, and were interested in mobile apps for mental illness. Key factors that may improve adoption include provider endorsement, greater publicity of efficacious apps, and clear messaging about efficacy and privacy of information. Finally, multifaceted apps that address a range of concerns, from sleep to negative thought patterns, may be best received

Chemical Plants Remain Vulnerable to Terrorists: A Call to Action

U.S. chemical plants currently have potentially catastrophic vulnerabilities as terrorist targets. The possible consequences of these vulnerabilities echo from the tragedies of the Bhopal incident in 1984 to the terrorist attacks on 11 September 2001 and, most recently, Hurricanes Katrina and Rita. Findings from a 2004 nationwide participatory research study of 125 local union leaders at sites with very large volumes of highly hazardous chemicals suggest that voluntary efforts to achieve chemical plant security are not succeeding. Study respondents reported that companies had only infrequently taken actions that are most effective in preventing or in preparing to respond to a terrorist threat. In addition, companies reportedly often failed to involve key stakeholders, including workers, local unions, and the surrounding communities, in these efforts. The environmental health community thus has an opportunity to play a key role in advocating for and supporting improvements in prevention of and preparation for terrorist attacks. Policy-level recommendations to redress chemical site vulnerabilities and the related ongoing threats to the nation’s security are as follows: a) specify detailed requirements for chemical site assessment and security; b) mandate audit inspections supported by significant penalties for cases of noncompliance; c) require progress toward achieving inherently safer processes, including the minimizing of storage of highly hazardous chemicals; d) examine and require additional effective actions in prevention, emergency preparedness, and response and remediation; e) mandate and fund the upgrading of emergency communication systems; and f) involve workers and community members in plan creation and equip and prepare them to prevent and respond effectively to an incident

Microclimate investigation to study the behavior of urban heat islands in the city of Turin

Heatwaves are annually increasing in terms of intensity and frequency. In urban areas, the impact could be further exacerbated by the urban heat island (UHI) effect. This work carries out an urban microclimate analysis to evaluate the behavior of the UHI in the city of Turin during a Heatwave event. Turin is located in the North-West region of Italy, boarded by the Alps mountain ranges in the west and hills in the East. The study utilizes the WRF/MLUCM model and considers the heatwave period in June 2019 [2]. The high- resolution urban land use/land cover data is taken from local climate zone (LCZ) maps provided by the World Urban Database and Access Portal Tools (WUDAPT) repository [3]. The simulation is validated with the data provided by ARPA meteorological stations located over the region[4]. The lower root mean squared error of air temperature and higher index of the agreement show that the simulation is in good agreement with the observational data. The model is then used to analyze the rural-urban temperature distributions over the diurnal cycle. According to the results, the city of Turin has higher near-surface UHI intensity during the night and early morning (with maximum intensity >3 degC), whereas the intensity is diminishing during the mid-day hours. The examination of near-surface air temperature shows that, at some particular day times, the air temperature of the city is less than its rural counterparts indicating a reduction of UHI during Heatwave events as observed by [5