Impacts of Confinement on Mental Health and Health Behaviours of Individuals with Multimorbidity during Covid-19 Pandemic
Bibliographic record
Abstract
Background: Confinement and its possible impact on lifestyle make people with multimorbidity more vulnerable to modifications of their mental health and health behaviours that could persist beyond confinement.Objective: To understand the mental health status and health behaviour modifications among individuals with multimorbidity during and post COVID-19 confinement.Methods: Longitudinal multinational cohort study consisting of two online questionnaires with its first wave taken place during the first COVID-19 confinement (May 2020) and its second wave post-deconfinement (November 2020). Including 559 (wave 1) and 144 (wave 2) participants with an average age of 34.30±12.35 and 36.21±13.07 years old. Mostly females living in Canada, France, India and Lebanon. Results: The prevalence of multimorbidity was 27.68%. During confinement, people with multimorbidity were 2 to 3 times more likely to experience psychological distress, depressive symptoms, increased stress or isolation, and the prevalence of stress and psychological distress increased post-deconfinement. Health behaviours were also modified during confinement with people with multimorbidity being more likely to reduce their physical activity and increased their fruit and vegetable consumption. Post-deconfinement, people with multimorbidity had increased sleep problems. Also, regardless of multimorbidity status, sexual desire continuously decreased post-deconfinement. Conclusion: Mental health and health behaviours modifications occurred during the COVID-19 confinement period and people with multimorbidity were more severely impacted on these two outcomes than those without multimorbidity, indicating a need for a more adapted approach of care to future confinement periods or pandemic for this population.
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
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".