Psychological screening and tracking of athletes and the potential for digital mental health solutions in a hybrid model of care: A mini review

Luke Balcombe; D De Leo

doi:10.2196/preprints.22755

Background: There is a persistent need for mental ill-health prevention and intervention among ‘at-risk’ and vulnerable subpopulations. Major disruptions to humanity such as the COVID-19 pandemic present an opportunity for a better understanding of the experience of stressors and vulnerability. Faster and better ways of psychological screening and tracking are more generally required in response to the increased demand upon mental health care services. The argument that mental and physical health should be considered together as part of a biopsychosocial approach is garnering acceptance in elite athlete literature. However, the sporting population are unique in that there is an existing stigma of mental health, an under-recognition of mental ill-health as well as engagement difficulties which have hindered research, prevention and intervention efforts. Objective: To summarize and evaluate the literature on athletes’ increased vulnerability to mental ill-health, and digital mental health solutions as a complement to prevention and intervention. To show relationships between athlete mental health problems and resilience as well as digital mental health screening and tracking and faster and better treatment algorithms. Methods: Mini review Results: Recent consensus statements and systematic reviews indicated that elite athletes have comparable rates of mental ill-health prevalence as the general population. However, peculiar subgroups require disentangling. Innovative expansion of data collection and analytics is required to respond to engagement issues and advance research and prevention/intervention programs in the process. Digital platforms, machine learning, deep learning and artificial intelligence are useful for mental health screening and tracking in various sub-populations. It is necessary to determine appropriate conditions for algorithms for utilization in recommendations. An ecological perspective and digital mental health methods are proposed as suitable. Partnered with real-time automation and machine learning models, valid and reliable behavior sensing and digital mental health screening and tracking tools have the potential to drive a consolidated, measurable and balanced risk assessment and management strategy for the prevention and intervention of the sequelae of mental ill-health. Conclusions: Athletes are an ‘at-risk’ subpopulation for mental health problems. However, a subgroup of high-level athletes displayed a resilience which helps them to positively adjust after a period of ‘overwhelming’ stress. Further consideration of stress and adjustments in brief screening tools for elite athletes and general populations is recommended to validate this finding. There is an unrealized potential for broadening the scope of mental health especially symptom and disorder interpretation. Digital platforms for psychological screening and tracking have been widely utilized among general populations but there is yet to be an eminent athlete version. Sport in combination with mental health education should address the barriers to seeking help by increasing awareness of the range of mental ill-health through to positive functioning. A hybrid model of care is recommended for future research and development, combining traditional face-to-face approaches along with innovative and evaluated digital technologies that may be utilized by functional specialists in prevention and early intervention strategies.

Psychological screening and tracking of athletes and the potential for digital mental health solutions in a hybrid model of care: A mini review

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