What does engagement mean to participants in longitudinal cohort studies? A qualitative study
Bibliographic record
Abstract
BACKGROUND: Engagement is important within cohort studies for a number of reasons. It is argued that engaging participants within the studies they are involved in may promote their recruitment and retention within the studies. Participant input can also improve study designs, make them more acceptable for uptake by participants and aid in contextualising research communication to participants. Ultimately it is also argued that engagement needs to provide an avenue for participants to feedback to the cohort study and that this is an ethical imperative. This study sought to explore the participants' experiences and thoughts of their engagement with their birth cohort study. METHODS: Participants were recruited from the Children of the 90s (CO90s) study. Qualitative semi-structured interviews were conducted with 42 participants. The interviews were transcribed verbatim, and uploaded onto Nvivo software. They were then analysed via thematic analysis with a constant comparison technique. RESULTS: Participants' experiences of their engagement with CO90s were broadly based on three aspects: communication they received from CO90s, experiences of ethical conduct from CO90s and receiving rewards from CO90s. The communication received from CO90s, ranged from newsletters explaining study findings and future studies, to more personal forms like annual greeting cards posted to each participant. Ethical conduct from CO90s mainly involved participants understanding that CO90s would keep their information confidential, that it was only involved in 'good' ethical research and their expectation that CO90s would always prioritise participant welfare. Some of the gifts participants said they received at CO90s included toys, shopping vouchers, results from clinical tests, and time off from school to attend data collection (Focus) days. Participants also described a temporality in their engagement with CO90s and the subsequent trust they had developed for the cohort study. CONCLUSION: The experiences of engagement described by participants were theorized as being based on reciprocity which was sometimes overt and other times more nuanced. We further provide empirical evidence of participants' expectation for a reciprocal interaction with their cohort study while highlighting the trust that such an interaction fosters. Our study therefore provides key insights for other cohort studies on what participants value in their interactions with their cohort studies.
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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 | 0.111 | 0.105 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.014 | 0.014 |
| Scholarly communication | 0.007 | 0.009 |
| Open science | 0.003 | 0.009 |
| Research integrity | 0.003 | 0.005 |
| Insufficient payload (model declined to judge) | 0.003 | 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".