Low SES Parents Report More Benefits of Trustworthy Easy-to-read Web-Based Parenting Information: A 4-Year Time Series
Bibliographic record
Abstract
Context: Almost all parents search web-based information for their children. This study focuses on parents with low socioeconomic status (SES), a correlate of health literacy (determinants of child education/health); specifically, their experience of seeking information on the Naître et Grandir (N&G) website (trustworthy information on child development, education and health in clear language). Objectives: To measure the influence of a health literacy intervention on (a) the frequency of the utilization of a questionnaire to understand the perceived outcomes of N&G information, and (b) parents’ expected benefits of this information. Study Design and Analysis: A 4-year prospective time series. Statistical analyses were descriptive and inferential. Setting: For each N&G webpage, parents are invited to complete a questionnaire (Information Assessment Method, IAM) to report their intention to use and expected benefits of the webpage information. Population studied: Quebec parents of 0-8-year-old children who completed at least one IAM questionnaire. Intervention: An improved version of the IAM, the IAM+ was developed with low SES parents and implemented in January 2019. Main outcome measures: IAM data were collected in the pre-intervention (2017-2018) and the post-intervention (2019-2020) periods. Results: Participants completed 10,362 IAM questionnaires. The proportion of responses and reported benefits from low SES participants increased post-intervention. Low SES participants and particularly low SES fathers expected greater benefits from the accessed web information compared to other participants and mothers. Conclusions: Results suggest (a) family physicians recommend trustworthy easy-to-read information resources to all patients when needed, including patients with a low literacy level; (b) web content that incorporates international health literacy standards is associated with greater expected benefits among low SES parents; (c) increasing father awareness and father-inclusive content can lead to greater expected benefits; and (d) the IAM questionnaire that is accessible on all devices, including smartphones, can help low SES parents provide feedback to web editors regarding the outcomes of their content.
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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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".