Loneliness, coping, suicidal thoughts and self-harm during the COVID-19 pandemic: a repeat cross-sectional UK population survey
Bibliographic record
Abstract
Objectives There has been speculation on the impact of the COVID-19 pandemic and the associated lockdown on suicidal thoughts and self-harm and the factors associated with any change. We aimed to assess the effects and change in effects of risk factors including loneliness and coping, as well as pre-existing mental health conditions on suicidal thoughts and self-harm during the COVID-19 pandemic. Design This study was a repeated cross-sectional online population-based survey. Participants and measures Non-probability quota sampling was adopted on the UK adult population and four waves of data were analysed during the pandemic (17 March 2020 to 29 May 2020). Outcomes were suicidal thoughts and self-harm associated with the pandemic while loneliness, coping, pre-existing mental health conditions, employment status and demographics were covariates. We ran binomial regressions to evaluate the adjusted risks of the studied covariates as well as the changes in effects over time. Results The proportion of individuals who felt lonely increased sharply from 9.8% to 23.9% after the UK lockdown began. Young people (aged 18–24 years), females, students, those who were unemployed and individuals with pre-existing mental health conditions were more likely to report feeling lonely and not coping well. 7.7%–10.0% and 1.9%–2.2% of respondents reported having suicidal thoughts and self-harm associated with the pandemic respectively throughout the period studied. Results from cross-tabulation and adjusted regression analyses showed young adults, coping poorly and with pre-existing mental health conditions were significantly associated with suicidal thoughts and self-harm. Loneliness was significantly associated with suicidal thoughts but not self-harm. Conclusions The association between suicidality, loneliness and coping was evident in young people during the early stages of the pandemic. Developing effective interventions designed and coproduced to address loneliness and promote coping strategies during prolonged social isolation may promote mental health and help mitigate suicidal thoughts and self-harm associated with the pandemic.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".