RESUMO
Digital phenotyping is a promising method for advancing scalable detection and prediction methods in mental health research and practice. However, little is known about how digital phenotyping data are used to make inferences about youth mental health. We conducted a scoping review of 35 studies to better understand how passive sensing (e.g., Global Positioning System, microphone etc) and electronic usage data (e.g., social media use, device activity etc) collected via smartphones are used in detecting and predicting depression and/or anxiety in young people between 12 and 25 years-of-age. GPS and/or Wifi association logs and accelerometers were the most used sensors, although a wide variety of low-level features were extracted and computed (e.g., transition frequency, time spent in specific locations, uniformity of movement). Mobility and sociability patterns were explored in more studies compared to other behaviours such as sleep, phone use, and circadian movement. Studies used machine learning, statistical regression, and correlation analyses to examine relationships between variables. Results were mixed, but machine learning indicated that models using feature combinations (e.g., mobility, sociability, and sleep features) were better able to predict and detect symptoms of youth anxiety and/or depression when compared to models using single features (e.g., transition frequency). There was inconsistent reporting of age, gender, attrition, and phone characteristics (e.g., operating system, models), and all studies were assessed to have moderate to high risk of bias. To increase translation potential for clinical practice, we recommend the development of a standardised reporting framework to improve transparency and replicability of methodology.
RESUMO
BACKGROUND: More than 50% of people who die by suicide have not been in contact with formal mental health services. The rate of people who fly 'under the radar' of mental health services is higher among men than women, indicating a need to improve engagement strategies targeted towards men who experience suicidal thoughts and/or behaviours. In Australia, a range of mental health support services exist, designed specifically for men, yet, a substantial proportion of men do not use these services. The aim of this study is to evaluate whether a brief online video-based messaging intervention is an effective approach for encouraging men with suicidal thoughts and/or behaviours to engage with existing support services. METHODS: Informed by a literature review, surveys, and consultation with men with a lived experience of suicidal thoughts and/or behaviours, we designed five video-based messages that will be used in this five-arm randomised controlled trial. A total of 380 (76 per arm) men aged 18 years or older with suicidal thoughts who are not currently accessing formal mental health services will be recruited online and randomly assigned to watch one of the five web-based video messages. After viewing the video, men will be presented with information about four existing Australian support services, along with links to these services. The primary outcome will be help-seeking, operationalised as a click on any one of the four support service links, immediately after viewing the video. Secondary outcomes include immediate self-reported help-seeking intentions in addition to self-reported use of the support services during a 1-week follow-up period. We will also use the Discrete Choice Experiment methodology to determine what aspects of support services (e.g. low cost, short appointment wait times) are most valued by this group of men. DISCUSSION: This study is the first to evaluate the effectiveness of a brief web-based video messaging intervention for promoting engagement with existing support services among men with suicidal thoughts who are not currently receiving formal help. If found to be effective, this would represent a scalable, cost-effective approach to promote help-seeking for this at-risk population. Limitations and strengths of this study design are discussed.