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Record W2912061461 · doi:10.2196/11865

Socioeconomic Status and Racial or Ethnic Differences in Participation: Web-Based Survey

2019· article· en· W2912061461 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

venuePublished in a venue whose home country is Canada.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueJMIR Research Protocols · 2019
Typearticle
Languageen
FieldSocial Sciences
TopicSurvey Methodology and Nonresponse
Canadian institutionsnot available
Fundersnot available
KeywordsSocioeconomic statusEthnic groupOddsMedicineDemographyPsychologyFamily medicineGerontologyPopulationLogistic regressionEnvironmental healthSociology

Abstract

fetched live from OpenAlex

BACKGROUND: Web-based survey data collection has been widely used because of its advantages, although attaining and retaining participants can be challenging. There are several factors associated with successful Web-based survey participation; yet little is known regarding racial or ethnic and socioeconomic differences in the progress of a Web-based survey. OBJECTIVE: This study aimed to examine racial or ethnic and socioeconomic status (SES) differences in participation in a Web-based survey. METHODS: We conducted a secondary data analysis of a study dataset containing information on parents of preschool children. We used 2 phases of Web-based surveys: (1) screening questions including race or ethnicity information and (2) full survey with a consent form. Once potential participants submitted the screening questions, including their racial or ethnic information, the team sent the full survey link to potential participants who met study eligibility criteria. We calculated the proportion of racial or ethnic groups in each of the following areas: consent, partial survey completion, and total survey completion. RESULTS: A total of 487 participants (236 non-Hispanic white, 44 Hispanic, 137 black, and 70 Asian) completed initial screening questions, and a total of 458 participants met study eligibility criteria. Compared with black participants, non-Hispanic white and Asian participants were more likely to consent to participate in the study (odds ratio [OR] 1.73, 95% CI 1.08-2.78, P=.02; OR 2.07, 95% CI 1.04-4.13, P=.04, respectively). There was no racial or ethnic difference with respect to the completion of demographic questions or completion of a partial survey. Finally, compared with black participants, non-Hispanic white participants were more likely to complete the entire survey (OR 3.36, 95% CI 1.51-7.06, P<.001). With respect to SES, less educated non-Hispanic white participants were less likely to complete the survey compared with their counterparts with more education (OR 0.15, 95% CI 0.50-1.48, P<.001). CONCLUSIONS: We found a significant difference among racial or ethnic groups as well as different education levels in Web-based survey participation. Survey researchers need to consider the SES and racial or ethnic differences in Web-based survey participation and develop strategies to address this bias in participation and completion in their research.

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.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.067
metaresearch head score (Gemma)0.010
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Insufficient payload (model declined to judge)
Consensus categoriesMetaresearch
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.259
Threshold uncertainty score0.998

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0670.010
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0030.000

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 head0.757
GPT teacher head0.671
Teacher spread0.086 · 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