Experiences of mental health and poverty in high-income countries during COVID-19: A systematic review and meta-aggregation
Bibliographic record
Abstract
Systematic reviews have been published that explore the experiences of living in poverty, yet there are no known studies that have synthesized the findings of research exploring the experiences of mental health and wellbeing of persons living in poverty during COVID-19. To address this gap, we conducted a systematic review and meta-aggregation of qualitative evidence using the method described by the Joanna Briggs Institute (JBI) following the PRISMA guidelines. Of 8391 titles and abstracts screened, we included 23 studies in our review and meta-aggregation. In conducting our meta-aggregation, we generated three synthesized findings: 1) magnification of inequities and marginalization during COVID-19; 2) difficulty accessing resources during the lockdown; and 3) the lockdown causing changes in mental health and wellbeing. The findings of this review suggest that persons living in poverty experienced increased difficulties with mental health and well-being during COVID-19. This was largely influenced by the presence of pandemic restrictions and increasing financial precarity that resulted in rising levels of psychosocial distress. Research regarding the plight of persons living in low income is needed to inform policy and practice for future pandemics in order to decrease the vulnerability of this population. Implementing evidence-informed policies and practices that mitigate the negative psychological effects of physical distancing restrictions on persons living in poverty are needed, and these can be identified through future research efforts.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.005 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".