Computer literacy, skills and knowledge among dentists and dentalcare professionals (DCPs) within primary care in Scotland
Bibliographic record
Abstract
OBJECTIVE: To gain a better understanding of the level of literacy in information technology (IT) across the dental team working within primary care in Scotland, thus allowing appropriate planning of education and training for effective use of IT. DESIGN: A postal questionnaire survey of all dentists and dental care professionals (DCPs) within primary care in Scotland; online reply was also an option. SETTING: General dental practice and the salaried dental service, May 2004. SUBJECTS AND METHODS: 2679 dentists and 2861 DCPs were surveyed. RESULTS: Forty-three percent of respondents considered their IT skills to be 'moderate', with a further one-third reporting 'nil' or 'low' skill level. Only a quarter of respondents had accessed a learning programme by computer. The majority of IT competence was self-acquired. CONCLUSIONS: 'Upskilling' the dental team in IT may be required in order to take advantage of e-learning opportunities available now and in the future.
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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 | 0.001 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".