Beyond seeking: Information use among older adults with diabetes
Bibliographic record
Abstract
Abstract Health information empowers individuals to manage their health, but its impact is limited unless effectively used. Yet information use, that is, the specific actions individuals take after finding the information they need, remains under‐researched. This study focuses on information use in the context of health information and older adults with type 2 diabetes, asking what actions they take once they find information. Data collection involved semi‐structured interviews with 23 older adults with diabetes in Canada; data analysis used reflexive thematic analysis. The study identifies four themes: (1) active application of information in personal health management, (2) ongoing knowledge integration and development, (3) critical selection and evaluation of information, and (4) sharing information as a communal practice. These findings contribute empirical evidence to understanding information use as a distinct component of information behavior, revealing that it involves specific actions such as physical activities, decision‐making, knowledge integration, filtering, assessing, and sharing. These insights into information use are vital for improving the effectiveness of policies, health services, and information systems.
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 distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.005 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.019 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
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 teacher head, 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".