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Record W2494556365 · doi:10.2196/publichealth.5184

A Comparison of Web and Telephone Responses From a National HIV and AIDS Survey

2016· article· en· W2494556365 on OpenAlexafffundvenueabout
Marcella K. Jones, Liviana Calzavara, Dan Allman, Catherine Worthington, Mark Tyndall, James Iveniuk

Bibliographic record

VenueJMIR Public Health and Surveillance · 2016
Typearticle
Languageen
FieldSocial Sciences
TopicSurvey Methodology and Nonresponse
Canadian institutionsBC Centre for Disease ControlPublic Health OntarioUniversity of British ColumbiaUniversity of VictoriaCentre for Social InnovationUniversity of Toronto
FundersCanadian Institutes of Health ResearchCanadian Foundation for AIDS Research
KeywordsSocial desirability biasTelephone interviewPublic healthRandom digit dialingThe InternetPsychologyNon-response biasBivariate analysisMultivariate analysisMedicineSelection biasSocial psychologyFamily medicineEnvironmental healthSocial desirabilityPopulationStatisticsComputer science

Abstract

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BACKGROUND: Response differences to survey questions are known to exist for different modes of questionnaire completion. Previous research has shown that response differences by mode are larger for sensitive and complicated questions. However, it is unknown what effect completion mode may have on HIV and AIDS survey research, which addresses particularly sensitive and stigmatized health issues. OBJECTIVES: We seek to compare responses between self-selected Web and telephone respondents in terms of social desirability and item nonresponse in a national HIV and AIDS survey. METHODS: A survey of 2085 people in Canada aged 18 years and older was conducted to explore public knowledge, attitudes, and behaviors around HIV and AIDS in May 2011. Participants were recruited using random-digit dialing and could select to be interviewed on the telephone or self-complete through the Internet. For this paper, 15 questions considered to be either sensitive, stigma-related, or less-sensitive in nature were assessed to estimate associations between responses and mode of completion. Multivariate regression analyses were conducted for questions with significant (P≤.05) bivariate differences in responses to adjust for sociodemographic factors. As survey mode was not randomly assigned, we created a propensity score variable and included it in our multivariate models to control for mode selection bias. RESULTS: A total of 81% of participants completed the questionnaire through the Internet, and 19% completed by telephone. Telephone respondents were older, reported less education, had lower incomes, and were more likely from the province of Quebec. Overall, 2 of 13 questions assessed for social desirability and 3 of 15 questions assessed for item nonresponse were significantly associated with choice of mode in the multivariate analysis. For social desirability, Web respondents were more likely than telephone respondents to report more than 1 sexual partner in the past year (fully adjusted odds ratio (OR)=3.65, 95% CI 1.80-7.42) and more likely to have donated to charity in the past year (OR=1.63, 95% CI 1.15-2.29). For item nonresponse, Web respondents were more likely than telephone respondents to have a missing or "don't know" response when asked about: the disease they were most concerned about (OR=3.02, 95% CI 1.67-5.47); if they had ever been tested for HIV (OR=8.04, 95% CI 2.46-26.31); and when rating their level of comfort with shopping at grocery store if the owner was known to have HIV or AIDS (OR=3.11, 95% CI 1.47-6.63). CONCLUSION: Sociodemographic differences existed between Web and telephone respondents, but for 23 of 28 questions considered in our analysis, there were no significant differences in responses by mode. For surveys with very sensitive health content, such as HIV and AIDS, Web administration may be subject to less social desirability bias but may also have greater item nonresponse for certain questions.

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)0.010
metaresearch head score (Gemma)0.049
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesnone
DomainCandidate signal: Methods · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.990
Threshold uncertainty score0.054

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0100.049
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0020.002
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0030.001

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.

Opus teacher head0.286
GPT teacher head0.488
Teacher spread0.202 · 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.

Study designObservational
DomainMethods
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".

Quick stats

Citations33
Published2016
Admission routes4
Has abstractyes

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