BJPsych Open · 2022 · 12 citations · 24 references
Social SciencesPopulation Health SciencesPsychiatryBehavioral EpidemiologyBehavioral HealthHealth PsychologyAnxiety DisordersCo-occurring Mental DisordersCo-occurring Mental Health ConditionsMental HealthPersonality DisordersPsychiatric EpidemiologyComorbidity Of Mental DisordersMultivariate Linear ModelsWomen's Mental Health
Background Mental health was only modestly affected in adults during the early months of the COVID-19 pandemic on the group level, but interpersonal variation was large. Aims We aim to investigate potential predictors of the differences in changes in mental health. Method Data were aggregated from three Dutch ongoing prospective cohorts with similar methodology for data collection. We included participants with pre-pandemic data gathered during 2006–2016, and who completed online questionnaires at least once during lockdown in The Netherlands between 1 April and 15 May 2020. Sociodemographic, clinical (number of mental health disorders and personality factors) and COVID-19-related variables were analysed as predictors of relative changes in four mental health outcomes (depressive symptoms, anxiety and worry symptoms, and loneliness), using multivariate linear regression analyses. Results We included 1517 participants with ( n = 1181) and without ( n = 336) mental health disorders. Mean age was 56.1 years (s.d. 13.2), and 64.3% were women. Higher neuroticism predicted increases in all four mental health outcomes, especially for worry ( β = 0.172, P = 0.003). Living alone and female gender predicted increases in depressive symptoms and loneliness ( β = 0.05–0.08), whereas quarantine and strict adherence with COVID-19 restrictions predicted increases in anxiety and worry symptoms ( β = 0.07–0.11).Teleworking predicted a decrease in anxiety symptoms ( β = −0.07) and higher age predicted a decrease in anxiety ( β = −0.08) and worry symptoms ( β = −0.10). Conclusions Our study showed neuroticism as a robust predictor of adverse changes in mental health, and identified additional sociodemographic and COVID-19-related predictors that explain longitudinal variability in mental health during the COVID-19 pandemic.
24
An inventory for measuring clinical anxiety: Psychometric properties.
Aaron T. Beck, Norman Epstein, Gary Brown et al. · Journal of Consulting and Clinical Psychology · 1988 · 11.7K citations
Development and validation of the penn state worry questionnaire
Thomas Meyer, Mark L. Miller, R. Metzger et al. · Behaviour Research and Therapy · 1990 · 5.1K citations
A. John Rush, Madhukar H. Trivedi, Hicham M. Ibrahim et al. · Biological Psychiatry · 2003 · 3.9K citations
Mental health problems and social media exposure during COVID-19 outbreak
Junling Gao, Pinpin Zheng, Yingnan Jia et al. · PLoS ONE · 2020 · 2.8K citations · Full text