Your browser doesn't support javascript.
loading
Psychological distress, wellbeing and resilience: modelling adolescent mental health profiles during the COVID-19 pandemic.
Butter, Sarah; Shevlin, Mark; Gibson-Miller, Jilly; McBride, Orla; Hartman, Todd K; Bentall, Richard P; Bennett, Kate; Murphy, Jamie; Mason, Liam; Martinez, Anton P; Levita, Liat.
Afiliación
  • Butter S; School of Psychology, Ulster University, Cromore Road, Coleraine, BT52 1SA, Northern Ireland. s.butter@ulster.ac.uk.
  • Shevlin M; School of Psychology, Ulster University, Cromore Road, Coleraine, BT52 1SA, Northern Ireland.
  • Gibson-Miller J; School of Education, University of Sheffield, Sheffield, England.
  • McBride O; School of Psychology, Ulster University, Cromore Road, Coleraine, BT52 1SA, Northern Ireland.
  • Hartman TK; Department of Social Statistics, University of Manchester, Manchester, England.
  • Bentall RP; Department of Psychology, University of Sheffield, Sheffield, England.
  • Bennett K; Department of Psychology, University of Liverpool, Liverpool, England.
  • Murphy J; School of Psychology, Ulster University, Cromore Road, Coleraine, BT52 1SA, Northern Ireland.
  • Mason L; Division of Psychology and Language Sciences, University College London, London, England.
  • Martinez AP; Department of Psychology, University of Sheffield, Sheffield, England.
  • Levita L; School of Psychology, University of Sussex, Falmer, England.
Discov Ment Health ; 4(1): 16, 2024 May 23.
Article en En | MEDLINE | ID: mdl-38780717
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.
Palabras clave

Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Idioma: En Revista: Discov Ment Health Año: 2024 Tipo del documento: Article Pais de publicación: Suiza

Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Idioma: En Revista: Discov Ment Health Año: 2024 Tipo del documento: Article Pais de publicación: Suiza