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Record W3105244491 · doi:10.2196/22440

Outcomes of Equity-Oriented, Web-Based Parenting Information in Mothers of Low Socioeconomic Status Compared to Other Mothers: Participatory Mixed Methods Study

2020· article· en· W3105244491 on OpenAlexafffund
Pierre Pluye, Reem El Sherif, Araceli Gonzalez‐Reyes, Emmanuelle Turcotte, Tibor Schuster, Gillian Bartlett, Roland Grad, Vera Granikov, Melanie Barwick, Geneviève Doray, François Lagarde, Christine Loignon

Bibliographic record

VenueJournal of Medical Internet Research · 2020
Typearticle
Languageen
FieldHealth Professions
TopicHealth Literacy and Information Accessibility
Canadian institutionsUniversité de SherbrookeLucie and André Chagnon FoundationMcGill UniversityInstitute for Clinical Evaluative SciencesUniversity of TorontoSickKids FoundationHospital for Sick Children
FundersCanadian Institutes of Health Research
KeywordsSocioeconomic statusCitizen journalismPsychologyEquity (law)Low incomeDevelopmental psychologyEnvironmental healthSociologyMedicineSocioeconomicsComputer sciencePolitical scienceWorld Wide Web

Abstract

fetched live from OpenAlex

BACKGROUND: Typically, web-based consumer health information is considered more beneficial for people with high levels of education and income. No evidence shows that equity-oriented information offers equal benefits to all. This is important for parents of low socioeconomic status (SES; low levels of education and income and usually a low level of literacy). OBJECTIVE: This study is based on a conceptual framework of information outcomes. In light of this, it aims to compare the perception of the outcomes of web-based parenting information in low-SES mothers with that of other mothers and explore the perspective of low-SES mothers on contextual factors and information needs and behavior associated with these outcomes. METHODS: A participatory mixed methods research was conducted in partnership with academic researchers and Naître et grandir (N&G) editors. N&G is a magazine, website, and newsletter that offers trustworthy parenting information on child development, education, health, and well-being in a format that is easy to read, listen, or watch. Quantitative component (QUAN) included a 3-year longitudinal observational web survey; participants were mothers of 0- to 8-year-old children. For each N&G newsletter, the participants' perception regarding the outcomes of specific N&G webpages was gathered using a content-validated Information Assessment Method (IAM) questionnaire. Differences between participants of low SES versus others were estimated. Qualitative component (QUAL) was interpretive; participants were low-SES mothers. The thematic analysis of interview transcripts identified participants' characteristics and different sources of information depending on information needs. Findings from the two components were integrated (QUAN+QUAL integration) through the conceptual framework and assimilated into the description of an ideal-typical mother of low SES (Kate). A narrative describes Kate's perception of the outcomes of web-based parenting information and her perspective on contextual factors, information needs, and behavior associated with these outcomes. RESULTS: QUAN-a total of 1889 participants completed 2447 IAM responses (50 from mothers of low SES and 2397 from other mothers). N&G information was more likely to help low-SES participants to better understand something, decrease worries, and increase self-confidence in decision making. QUAL-the 40 participants (21 N&G users and 19 nonusers) used 4 information sources in an iterative manner: websites, forums, relatives, and professionals. The integration of QUAN and QUAL findings provides a short narrative, Kate, which summarizes the main findings. CONCLUSIONS: This is the first study comparing perceptions of information outcomes in low-SES mothers with those of other mothers. Findings suggest that equity-oriented, web-based parenting information can offer equal benefits to all, including low-SES mothers. The short narrative, Kate, can be quickly read by decision policy makers, for example, web editors, and might encourage them to reach the underserved and provide and assess trustworthy web-based consumer health information in a format that is easy to read, listen, or watch.

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 imitation

Not 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.

metaresearch head score (Codex)0.011
metaresearch head score (Gemma)0.012
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.011
Threshold uncertainty score0.056

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0110.012
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0020.001
Scholarly communication0.0010.001
Open science0.0010.002
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.000

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.

Opus teacher head0.267
GPT teacher head0.613
Teacher spread0.346 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

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Citations17
Published2020
Admission routes2
Has abstractyes

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