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Item-level analysis of mental health symptom trajectories during the COVID-19 pandemic in the UK: Associations with age, sex and pre-existing psychiatric conditions.
Hampshire, Adam; Trender, William; Grant, Jon E; Mirza, M Berk; Moran, Rosalyn; Hellyer, Peter J; Chamberlain, Samuel R.
  • Hampshire A; Department of Brain Sciences, Imperial College London, London, UK. Electronic address: a.hampshire@imperial.ac.uk.
  • Trender W; Department of Brain Sciences, Imperial College London, London, UK.
  • Grant JE; Department of Psychiatry, University of Chicago, Chicago, USA.
  • Mirza MB; Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, UK.
  • Moran R; Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, UK.
  • Hellyer PJ; Department of Brain Sciences, Imperial College London, London, UK; Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, UK.
  • Chamberlain SR; Department of Psychiatry, University of Southampton, Southampton, UK; Southern Health NHS Foundation Trust, Southampton, UK.
Compr Psychiatry ; 114: 152298, 2022 Jan 31.
Article in English | MEDLINE | ID: covidwho-1719561
ABSTRACT

BACKGROUND:

There is widespread concern regarding how the COVID-19 pandemic has affected mental health. Emerging meta-analyses suggest that the impact on anxiety/depression may have been transient, but much of the included literature has major methodological limitations. Addressing this topic rigorously requires longitudinal data of sufficient scope and scale, controlling for contextual variables, with baseline data immediately pre-pandemic.

AIMS:

To analyse self-report of symptom frequency from two largely UK-based longitudinal cohorts Cohort 1 (N = 10,475, two time-points winter pre-pandemic to UK first winter resurgence), and Cohort 2 (N = 10,391, two time-points, peak first wave to UK first winter resurgence).

METHOD:

Multinomial logistic regression applied at the item level identified sub-populations with greater probability of change in mental health symptoms. Permutation analyses characterised changes in symptom frequency distributions. Cross group differences in symptom stability were evaluated via entropy of response transitions.

RESULTS:

Anxiety was the most affected aspect of mental health. The profiles of change in mood symptoms was less favourable for females and older adults. Those with pre-existing psychiatric diagnoses showed substantially higher probability of very frequent symptoms pre-pandemic and elevated risk of transitioning to the highest levels of symptoms during the pandemic. Elevated mental health symptoms were evident across intra-COVID timepoints in Cohort 2.

CONCLUSIONS:

These findings suggest that mental health has been negatively affected by the pandemic, including in a sustained fashion beyond the first UK lockdown into the first winter resurgence. Women, and older adults, were more affected relative to their own baselines. Those with diagnoses of psychiatric conditions were more likely to experience transition to the highest levels of symptom frequency.
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Full text: Available Collection: International databases Database: MEDLINE Type of study: Cohort study / Experimental Studies / Observational study / Prognostic study / Randomized controlled trials / Reviews Language: English Journal: Compr Psychiatry Year: 2022 Document Type: Article

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Full text: Available Collection: International databases Database: MEDLINE Type of study: Cohort study / Experimental Studies / Observational study / Prognostic study / Randomized controlled trials / Reviews Language: English Journal: Compr Psychiatry Year: 2022 Document Type: Article