Cohort profile: the Scottish Research register SHARE. A register of people interested in research participation linked to NHS data sets
Bibliographic record
Abstract
PURPOSE: Recruitment to trials is often difficult. Many trials fail to meet recruitment targets resulting in underpowered studies which waste resources and the time of those who participated. While there is evidence that many people are willing to take part in research, particularly if it involves a condition from which they suffer, researchers are unable to easily contact such people often relying on busy clinicians to identify them. Many clinicians perceive themselves as too busy to take part in research activities. The Scottish Health Research Register SHARE adopts an approach which asks the public to consent to their data held in National Health Service databases to be used to determine their suitability for research projects. Additionally, participants can consent for spare blood, left after routine venepuncture to be automatically identified in the laboratory and stored for future research studies. PARTICIPANTS: Anyone over the age of 16 years in Scotland can participate. Participants are approached through a range of methods including directly at outpatient clinics and general practitioners practices, leaflets with hospital letters and personal email from employers. FINDINGS TO DATE: SHARE has recruited around 130 000 people. SHARE has demonstrated that it can quickly and efficiently recruit to studies, over 20 until now. In addition, it can be used to administer questionnaire studies by email and recruit to patient and public involvement groups. FUTURE PLANS: SHARE continues to steadily recruit with the ambition of eventually achieving 1 000 000 people in Scotland. We are steadily increasing the number of data sets we use for identifying participants. We are adding a mobile app which will facilitate dissemination about research and allow the collection of physiological and activity data if desired. We anticipate that SHARE will soon become the main source of health research recruitment in Scotland.
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 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 | 0.019 | 0.103 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.011 | 0.014 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.003 | 0.005 |
| Open science | 0.004 | 0.004 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.130 | 0.082 |
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".