Psychological distress, wellbeing and resilience: modelling adolescent mental health profiles during the COVID-19 pandemic

Sarah Butter, M Shevlin, Jilly Gibson‐Miller, Orla McBride, Todd K. Hartman, Richard P. Bentall, Kate Bennett, Jamie Murphy, Liam Mason, Anton P. Martinez, Liat Levita

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Abstract

There has been concern about adolescent mental health during the pandemic. The current study examined adolescent mental health during the initial phase of the COVID-19 pandemic in the UK. Using indicator of psychological distress, wellbeing and resilience, latent profile analysis was used to identify homogeneous mental health groups among young people aged 13–24 (N = 1971). Multinomial logistic regression was then used to examine which sociodemographic and psychosocial variables predicted latent class membership. Four classes were found. The largest class (Class 1, 37.2%) was characterised by moderate symptomology and moderate wellbeing. Class 2 (34.2%) was characterised by low symptomology and high wellbeing, while Class 3 (25.4%) was characterised by moderate symptomology and high wellbeing. Finally, Class 4 was the smallest (3.2%) and was characterised by high symptomology and low wellbeing. Compared to the low symptomology, high wellbeing class, all other classes were associated with less social engagement with friends, poorer family functioning, greater somatic symptoms, and a less positive model of self. A number of unique associations between the classes and predictor variables were identified. Although around two-thirds of adolescents reported moderate-to-high symptomology, most of these individuals also reported concurrent moderate-to-high levels of wellbeing, reflecting resilience. Furthermore, these findings demonstrate how a more comprehensive picture of mental health can be gained through adopting a dual-continua conceptualisation of mental health that incorporates both pathology and well-being. In this way, at-risk youth can be identified and interventions and resources targeted appropriately.
Original languageEnglish
Article number16
Pages (from-to)1-14
Number of pages15
JournalDiscover Mental Health
Volume4
Issue number1
Early online date23 May 2024
DOIs
Publication statusPublished online - 23 May 2024

Bibliographical note

Publisher Copyright:
© The Author(s) 2024.

Data Access Statement

Data availability
All data generated or analysed during this study are included in this published article and its supplementary information files.

Keywords

  • Young people
  • Resilience
  • Mental health
  • Latent variable modelling
  • COVID-19
  • Adolescents

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