Assessing and Improving the Use of Online Information About Child Development, Education, Health, and Well-Being in Low-Education, Low-Income Parents: Protocol for a Mixed-Methods Multiphase Study
Bibliographic record
Abstract
BACKGROUND: This study is born from a partnership between Web editors of Naître et grandir (N&G) and AboutKidsHealth (AKH) and researchers who developed and validated the Information Assessment Method (IAM). N&G and AKH are popular Canadian websites with high-quality comprehensive information about child development, education, health, and well-being. IAM allows parents to assess online information and provide feedback to Web editors. High-quality online consumer health information improves knowledge, self-efficacy, and health. However, low-socioeconomic status (SES) parents underuse N&G and IAM, despite these parents being more likely to report decreased worries and increased confidence as outcomes from N&G information. OBJECTIVE: The study is aimed to improve low-SES parents' use of online child information and interaction with Web editors and explore subsequent health outcomes for parents and children. METHODS: Multiphase mixed-methods design. Our general approach is centered on organizational participatory research. In phase 1, we will conduct a qualitative interpretive study to identify barriers and facilitators to using N&G information and to interacting with N&G editors via IAM; interview more than 10 low-SES parents about their experience with N&G and IAM and more than 10 nonusers of N&G and IAM; and use thematic analysis to identify main barriers and facilitators. In phase 2, we will integrate parents' views (phase 1 findings) in N&G and IAM and implement a new version: IAM+N&G+. In phase 3, we will conduct a quantitative prospective longitudinal study (pre-/postimplementation monitoring of knowledge use and outcomes). We will compare the use of original (IAM and N&G) and new (IAM+ and N&G+) versions using Google Analytics variables, IAM variables, a material and social deprivation index, and demographics. We anticipate increased use post implementation (linear mixed modeling). In phase 4, we will conduct a qualitative descriptive study on outcomes of information use. We will interview more than 30 low-SES parents who receive and rate the N&G+ newsletter using IAM+ and analyze data in the form of life histories to describe how parents and children experience perceived outcomes. RESULTS: The project was funded in 2017 by the Canadian Institutes of Health Research and received an ethics approval by the McGill University's institutional review board. Data collection for phase 1 was completed in 2018. Phases 2 to 4 will be conducted until 2020. Findings from this study will also be used to develop a free toolkit, useful to all Web editors, with recommendations for improving health information for low-SES persons and interactions with them using IAM. CONCLUSIONS: The results of this study will provide a deep understanding of how low-SES parents use online child information and interact with Web editors. Following the implementation of IAM+N&G+, results will also elucidate subsequent health outcomes for low-SES parents and children after interaction with Web editors has been optimized. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): PRR1-10.2196/9996.
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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 | 0.054 | 0.039 |
| Meta-epidemiology (narrow) | 0.003 | 0.003 |
| Meta-epidemiology (broad) | 0.004 | 0.005 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.005 | 0.002 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.004 | 0.003 |
| Research integrity | 0.004 | 0.006 |
| Insufficient payload (model declined to judge) | 0.037 | 0.008 |
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".