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Record W4409373974 · doi:10.1016/j.imu.2025.101640

Characterizing users and intention to use online health information resources: A comprehensive study

2025· article· en· W4409373974 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.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueInformatics in Medicine Unlocked · 2025
Typearticle
Languageen
FieldDecision Sciences
TopicTechnology Adoption and User Behaviour
Canadian institutionsUniversité du Québec à Trois-RivièresUniversité de MontréalUniversité de Sherbrooke
FundersSocial Sciences and Humanities Research Council of CanadaMitacs
KeywordsKnowledge managementHealth informationPsychologyComputer scienceData scienceInternet privacyHealth carePolitical science

Abstract

fetched live from OpenAlex

There are a large number of online health information resources (OHIR) and they have the potential to meet a need for health information. However, little is known about users’ characteristics, motivations and intentions to use OHIR, especially among older people. This study, based on the Technology Acceptance Model III (TAM III), aims to address these gaps using an electronic questionnaire and focus groups. 164 participants, 53.7% female, affected by chronic diseases, mean age 64.27 ± 11.68, completed the questionnaire. Results are presented for all participants and by age group, i.e., under 64, 65–74 and 75+. Older participants (75+) reported, performing significantly fewer digital tasks (p < 0.05) and self-assessing, on a scale of 0 to 10, to have lower digital skills, 4.0 ± 2.8, than the 65–74, 5.3 ± 2.7, and the 64 and under group, 7.0 ± 3.0 (p < 0.05). The 75+ group showed higher extrinsic motivation score to use OHIR, 3.10 ± 1.24, than the younger group, 2.38 ± 1.48 (p < 0.05). The intention to use OHIR (scores from 1 to 7) was higher in the 75+ group 6.19 ± 1.15, compared to the 65–74 group (5.38 ± 1.59) and the 64 and under (5.17 ± 1.64) (p < 0.05). Variables, perceived usefulness, OR (95% CI) 6.04 (4.13; 9.09) and perceived ease of use, OR (95% CI) 2.39 (1.77; 3.26), (p < 0.01) showed a significant interaction with intention to use OHIR p < 0.01. In the focus groups (n = 2), participants (n = 5 in each, aged 41 to 76), mentioned that consulting an OHIR is associated with the presence of a specific health condition and emphasized the need for accessible, reliable information that meets their specific needs. While age is associated with differences in digital skills, it does not constitute a barrier to using OHIR. Perceived usefulness in relation to personal health concerns and perceived ease of use—interface simplicity—are determinants of intention to use OHIR. We hypothesize that older individuals with chronic diseases, followed by a care team for a long time, may have additional (extrinsic) motivation to use OHIR. This study highlights the need to characterize the target population and adapt OHIR.

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)0.002
metaresearch head score (Gemma)0.003
Version: codex-gemma-dda1882f352aValidation 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 score0.146
Threshold uncertainty score0.528

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.002
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.134
GPT teacher head0.428
Teacher spread0.294 · 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