Can an Emoji a Day Keep the Doctor Away? An Explorative Mixed-Methods Feasibility Study to Develop a Self-Help App for Youth With Mental Health Problems.

Today's smartphones allow for a wide range of "big data" measurement, for example, ecological momentary assessment (EMA), whereby behaviours are repeatedly assessed within a person's natural environment. With this type of data, we can better understand - and predict - risk for behavioral and health issues and opportunities for (self-monitoring) interventions. In this mixed-methods feasibility study, through convenience sampling we collected data from 32 participants (aged 16-24) over a period of three months. To gain more insight into the app experiences of youth with mental health problems, we interviewed a subsample of 10 adolescents who received psycthological treatment. The results from this feasibility study indicate that emojis) can be used to identify positive and negative feelings, and individual pattern analyses of emojis may be useful for clinical purposes. While adolescents receiving mental health care are positive about future applications, these findings also highlight some caveats, such as possible drawback of inaccurate representation and incorrect predictions of emotional states. Therefore, at this stage, the app should always be combined with professional counseling. Results from this small pilot study warrant replication with studies of substantially larger sample size.

Upper extremity pain and computer use among engineering graduate students.

BACKGROUND: The objective of this study was to investigate risk factors associated with persistent or recurrent upper extremity and neck pain among engineering graduate students. METHODS: A random sample of 206 Electrical Engineering and Computer Science (EECS) graduate students at a large public university completed an online questionnaire. RESULTS: Approximately 60% of respondents reported upper extremity or neck pain attributed to computer use and reported a mean pain severity score of 4.5 (+/-2.2; scale 0-10). In a final logistic regression model, female gender, years of computer use, and hours of computer use per week were significantly associated with pain. CONCLUSIONS: The high prevalence of upper extremity pain reported by graduate students suggests a public health need to identify interventions that will reduce symptom severity and prevent impairment.