Mental health clinicians perform complex tasks with patients that potentially could be improved by the massive computing power available through mobile apps. This study aimed to analyse commercially available mobile and computer applications (apps) focused on treating psychiatric disorders. Apps were analysed by two independent raters for whether they took advantage of computer power to process data in a fashion that augments four main elements of clinical treatment including (1) assessment/diagnosis, (2) treatment planning, (3) treatment fidelity monitoring, and (4) outcome tracking. The evidence base for each of these apps was also explored via PsychINFO, Research Gate and Google Scholar. Searches of the Google Play Store, the Apple App Store, and the One Mind PsyberGuide found 722 apps labelled for mental health use, of which 163 apps were judged relevant to clinical work with patients with psychiatric disorders. Fifty-nine of these were determined to contain a computer-driven function for at least one of the four main elements of clinical treatment. The most common element was assessment/diagnosis (55/59 apps), followed by outcome tracking (34/59 apps). Six apps updated treatment plans using user input. Only one app tracked treatment fidelity. None of the apps contained computer-driven functions for all four elements. Twelve apps were supported in randomized clinical trials to show greater efficacy compared with either wait-list or other active treatments. Results showed that these four clinical elements can be meaningfully augmented, but the full potential of computer processing appears unreached in mental health-related apps.
Key learning aims
(1)
To understand what apps are currently available to treat clinical-level psychiatric problems.
(2)
To understand how many of the commercially available mental health-focused apps can be used for the treatment of clinical populations.
(3)
To understand how mental health services can be complemented by utilizing computer processing power within apps.
IntroductionDeinstitutionalisation of the mentally ill is an ongoing process in European countries. Quality of care in residential facilities, however, was seldom assessed in part due to the lack of adequate instruments.ObjectivesTo assess the quality of care in Portuguese residential facilities for long term mental patients.MethodsQuality of care in residential facilities was assessed with the toolkit developed by the DEMoBinc study using interviews with the units’ managers, and the users.ResultsThe 20 units assessed across Portugal were mainly located in the city; 13 were in a hospital setting and 7 in the community. Most of the units (90%) had no maximum length of stay, and 60% were mixed-gender; 85% of the users were not compulsory. Most of the units (60%) had no one-bedrooms, and their aim was rehabilitative in 40%, and rehabilitative plus providing support in 40%. The rate of patients with a bank account was 49.4%, 32.4% were in charge of their finances, while only 14.1% had voted.In hospital vs. community units patients were more frequently men (80.5 vs. 53.8%) and older (51.1 ± 13.7 vs. 43.3 ± 9.6, p < .001). In community units the treatment was more frequently explained (50 vs. 26.3%), patients’ involvement was higher (40.4 vs. 19.5%), while mean GAF scores (64.9 vs. 60.2) did not differ.ConclusionsPortuguese results show that in spite of the effort to create new facilities for the longer term mentally ill, a lot still has to be done to improve the quality of care they provide.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.