Influence of recurrent assessments during data collection on caregivers and young children for an agricultural livelihood intervention in Kenya: a qualitative study
Bibliographic record
Abstract
OBJECTIVES: We sought to understand the influence of recurrent assessments on the behaviour of children and caregivers in a 2-year study of an agricultural livelihood intervention. DESIGN: This study used qualitative exit interviews from caregivers in the control arm of a large, cluster-randomised control trial, Shamba Maisha. SETTING: The study was conducted in Western Kenya and involved 12 health facilities between 2016 and 2019. PARTICIPANTS: Participants were 99 caregivers in the control arm who had a child that was 6-36 months in age at the start of the study. INTERVENTIONS: Intervention participants within Shamba Maisha received an irrigation pump, farming lessons and a microloan. Control participants received no intervention but were offered the intervention after completing the 2-year study. RESULTS: Despite receiving no formal benefits, control caregivers reported improved mental health and enhanced knowledge of their child's health compared with the beginning of the study and reported changes in the child's play and diet that they attributed to participation in study assessments. Caregivers in the control arm attributed their changed behaviour to recurrent questioning, instrumental support, interactions with study staff and increased health knowledge. CONCLUSIONS: Recurrent assessments altered participant behaviour, which may have made inference of the intervention's impact more difficult. In designing future, such studies with intervention and control arms, a trade-off between the gains in statistical power provided by recurrent visits and the avoidance of alterations in participants' behaviour that could affect responses to assessments must be considered when deciding on the number of visits for assessment. TRIAL REGISTRATION NUMBERS: NCT03170986; NCT02815579.
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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 | 0.066 | 0.107 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.007 | 0.007 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.001 | 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".