What is consumer health informatics? A systematic review of published definitions
Bibliographic record
Abstract
BACKGROUND: Consumer health informatics (CHI) is an emerging field that utilizes technology to provide health information to enhance health-care decision making by the public. There is, however, no widely accepted or uniform definition of CHI. A consensus definition would be important for pedagogical reasons, to build capacity and to reduce confusion about what the discipline consists of. AIM: We undertook a systematic review of published definitions of CHI and evaluated them using five quality assessment criteria and measures of similarity. METHODS: Five databases were searched (Embase, Web of Science, MEDLINE, CINAHL and Business Source Complete) resulting in 1101 citations. Twenty-three studies met the inclusion criteria. Definitions were appraised using five criteria (with each scoring out of one): use of published citation, multi-disciplinarity, journal impact, definition comprehensibility, text readability. RESULTS: Most definitions scored low on citation (Mean ± SD: 0.22 ± 0.42), multi-disciplinarity (0.15 ± 0.28) and readability (0.04 ± 0.21) and somewhat higher on IF (0.35 ± 0.45) and definition comprehensibility (idea density) (0.87 ± 0.34) criteria. Overall, the quality of the published definitions was low 1.63 ± 0.80 (out of five). CONCLUSIONS: The definitions of CHI were variable in terms of the quality assessment criteria. This suggests the need for continued discussion amongst consumer health informaticians to develop a clear consensus definition about CHI.
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 | 0.009 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.010 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| 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".