The research activities of Ontario’s large community acute care hospitals: a scoping review
Bibliographic record
Abstract
BACKGROUND: Ontario's large community hospitals (LCHs) provide care to 65% of the province's hospitalized patients, yet we know very little about their research activities. By searching for research publications from 2013 to 2015, we will describe the extent, type and collaborative nature of Ontario's LCHs' research activities. METHODS: We conducted a scoping review by searching PubMed, Embase and the Cumulative Index to Nursing and Allied Health Literature databases from January 1, 2013 until December 31, 2015 for all publication types whose author(s) was affiliated with any of the 44 LCHs. Articles were screened and abstracted by three reviewers, independently. The data were charted and results described using summary statistics, scatter plots, and bar charts. RESULTS: We included 798 publications from 39 LCHs and 454 authors. The median number of publications was 7 (Interquartile range (IQR) 23). Observational study design was most commonly reported in over 50% of publications. Program evaluation was the focus in 40% of publications. Primary LCH authorship was observed for 535 publications. Over 25% and 65% of the publications were attributable to 24 authors and 9 LCHs, respectively. There was minimal collaboration both within (21.2%) and between (7.8%) LCHs. LCH size and geographic proximity to academic hospitals had minimal impact on research activity. CONCLUSIONS: Ontario's LCHs publish infrequently, collaborate infrequently, and their role in translational research activity is not well defined. A future survey questionnaire to LCH researchers identified through this review is planned to both validate and elicit their interpretations of our study findings and opinions about LCH involvement in research.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.044 | 0.121 |
| Meta-epidemiology (narrow) | 0.001 | 0.002 |
| Meta-epidemiology (broad) | 0.003 | 0.003 |
| Bibliometrics | 0.030 | 0.048 |
| Science and technology studies | 0.005 | 0.004 |
| Scholarly communication | 0.010 | 0.005 |
| Open science | 0.003 | 0.003 |
| Research integrity | 0.003 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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 source (direct Gemma or distilled Codex), 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".