The Avon Longitudinal Study of Parents and Children - A resource for COVID-19 research: Generation 2 questionnaire data capture May-July 2020
Bibliographic record
Abstract
The Avon Longitudinal Study of Parents and Children (ALSPAC) is a prospective population-based cohort study which recruited pregnant women in 1990-1992 from the Bristol area (UK). ALSPAC has followed these women, their partners (Generation 0; G0) and their offspring (Generation 1; G1) ever since. From 2012, ALSPAC has identified G1 participants who were pregnant (or their partner was) or had become parents, and enrolled them, their partners, and children in the ALSPAC-Generation 2 (ALSPAC-G2) study, providing a unique multi-generational cohort. At present, approximately 1,100 G2 children (excluding those in utero ) from 810 G1 participants have been enrolled. In response to the COVID-19 pandemic, ALSPAC rapidly deployed two online questionnaires; one during the initial lockdown phase in 2020 (9 th April-15 th May), and another when national lockdown restrictions were eased (26 th May-5 th July). As part of this second questionnaire, G1 parents completed a questionnaire about each of their G2 children. This covered: parental reports of children’s feelings and behaviour since lockdown, school attendance, contact patterns, and health. A total of 289 G1 participants completed this questionnaire on behalf of 411 G2 children. This COVID-19 G2 questionnaire data can be combined with pre-pandemic ALSPAC-G2 data, plus ALSPAC-G1 and -G0 data, to understand how children’s health and behaviour has been affected by the pandemic and its management. Data from this questionnaire will be complemented with linkage to health records and results of biological testing as they become available. Prospective studies are necessary to understand the impact of this pandemic on children’s health and development, yet few relevant studies exist; this resource will aid these efforts. Data has been released as: 1) a freely-available dataset containing participant responses with key sociodemographic variables; and 2) an ALSPAC-held dataset which can be combined with existing ALSPAC data, enabling bespoke research across all areas supported by the study.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.006 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 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) | 0.010 | 0.005 |
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".