For a structured response to the psychosocial consequences of the restrictive measures imposed by the global COVID-19 health pandemic: the MAVIPAN longitudinal prospective cohort study protocol
Bibliographic record
Abstract
INTRODUCTION: The COVID-19 pandemic and associated restrictive measures have caused important disruptions in economies and labour markets, changed the way we work and socialise, forced schools to close and healthcare and social services to reorganise. This unprecedented crisis forces individuals to make considerable efforts to adapt and will have psychological and social consequences, mainly on vulnerable individuals, that will remain once the pandemic is contained and will most likely exacerbate existing social and gender health inequalities. This crisis also puts a toll on the capacity of our healthcare and social services structures to provide timely and adequate care. The MAVIPAN (Ma vie et la pandémie/ My Life and the Pandemic) study aims to document how individuals, families, healthcare workers and health organisations are affected by the pandemic and how they adapt. METHODS AND ANALYSIS: MAVIPAN is a 5-year longitudinal prospective cohort study launched in April 2020 across the province of Quebec (Canada). Quantitative data will be collected through online questionnaires (4-6 times/year) according to the evolution of the pandemic. Qualitative data will be collected with individual and group interviews and will seek to deepen our understanding of coping strategies. Analysis will be conducted under a mixed-method umbrella, with both sequential and simultaneous analyses of quantitative and qualitative data. ETHICS AND DISSEMINATION: MAVIPAN aims to support the healthcare and social services system response by providing high-quality, real-time information needed to identify those who are most affected by the pandemic and by guiding public health authorities' decision making regarding intervention and resource allocation to mitigate these impacts. MAVIPAN was approved by the Ethics Committees of the Primary Care and Population Health Research Sector of CIUSSS de la Capitale-Nationale (Committee of record) and of the additional participating institutions. TRIAL REGISTRATION NUMBER: NCT04575571.
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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 | 0.031 | 0.040 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.003 | 0.003 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.005 | 0.001 |
| Scholarly communication | 0.003 | 0.004 |
| Open science | 0.004 | 0.002 |
| Research integrity | 0.006 | 0.005 |
| Insufficient payload (model declined to judge) | 0.093 | 0.031 |
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".