Literature DB >> 33271497

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

Luke Balcombe1,2, Diego De Leo2.   

Abstract

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: 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 treatment programs in the process. Digital platforms, machine learning, deep learning and artificial intelligence are useful for mental health screening and tracking in various subpopulations. It is necessary to determine appropriate conditions for algorithms for utilization in recommendations. 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 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, combining traditional face-to-face approaches along with innovative and evaluated digital technologies that may be utilized in prevention and early intervention strategies.

Entities:  

Year:  2020        PMID: 33271497     DOI: 10.2196/22755

Source DB:  PubMed          Journal:  JMIR Form Res        ISSN: 2561-326X


  6 in total

1.  Digital Mental Health Challenges and the Horizon Ahead for Solutions.

Authors:  Luke Balcombe; Diego De Leo
Journal:  JMIR Ment Health       Date:  2021-03-29

2.  Impact of the COVID-19 Pandemic on Estonian Elite Athletes: Survey on Mental Health Characteristics, Training Conditions, Competition Possibilities, and Perception of Supportiveness.

Authors:  Ülle Parm; Anu Aluoja; Tuuli Tomingas; Anna-Liisa Tamm
Journal:  Int J Environ Res Public Health       Date:  2021-04-19       Impact factor: 3.390

3.  Learning Agility of Learning and Development Professionals in the Life Sciences Field During the COVID-19 Pandemic: Empirical Study.

Authors:  XinYun Peng; Nicole Wang-Trexler; William Magagna; Susan Land; Kyle Peck
Journal:  Interact J Med Res       Date:  2022-04-26

4.  System Construction of Athlete Health Information Protection Based on Machine Learning Algorithm.

Authors:  Long Liu; Xiaodong Fan
Journal:  Biomed Res Int       Date:  2022-09-28       Impact factor: 3.246

5.  Physical Activity Levels and Psychological Well-Being during COVID-19 Lockdown among University Students and Employees.

Authors:  Adrián De la Rosa; Armando Monterrosa Quintero; María Alejandra Camacho-Villa; Coralie Arc-Chagnaud; André Gustavo Pereira de Andrade; Sergio Reyes-Correa; Ronald Quintero-Bernal; Juan Pedro Fuentes-García
Journal:  Int J Environ Res Public Health       Date:  2022-09-07       Impact factor: 4.614

6.  Anxiety and Depressive Symptoms in the New Life With COVID-19: A Comparative Cross-Sectional Study in Japan Rugby Top League Players.

Authors:  Yasutaka Ojio; Asami Matsunaga; Shin Kawamura; Masanori Horiguchi; Goro Yoshitani; Kensuke Hatakeyama; Rei Amemiya; Ayako Kanie; Chiyo Fujii
Journal:  Int J Public Health       Date:  2022-01-18       Impact factor: 3.380

  6 in total

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