Different attitudes towards mental health revealed in a survey of nurses across five European countries; more positive attitudes found in Portugal, in women and in those in senior roles
Bibliographic record
Abstract
Commentary on: Chambers M, Guise V, Välimäki M, et al. Nurses' attitudes to mental illness: a comparison of a sample of nurses from five European countries. Int J Nurs Stud 2010;47:350–62.[OpenUrl][1][CrossRef][2][PubMed][3][Web of Science][4] Examining the attitudes of nurses is a well-trod route for nurse researchers: such papers are common in our journals, describing nurses' perspectives on topics from complementary medicine to assisted suicide. These studies may involve focus groups, interviews or non-validated question sets; alternatively they may be scale development studies or may use validated scales to examine attitudes in a particular area. The paper by Chambers and colleagues is an example of the latter: it uses the Community Attitudes to Mental Illness questionnaire (developed in Canada in the late 1970s in response to deinstitutionalisation) to identify the attitudes of nurses working in mental health inpatient and community settings in five European countries. Measuring attitudes … [1]: {openurl}?query=rft.jtitle%253DInternational%2Bjournal%2Bof%2Bnursing%2Bstudies%26rft.stitle%253DInt%2BJ%2BNurs%2BStud%26rft.aulast%253DChambers%26rft.auinit1%253DM.%26rft.volume%253D47%26rft.issue%253D3%26rft.spage%253D350%26rft.epage%253D362%26rft.atitle%253DNurses%2527%2Battitudes%2Bto%2Bmental%2Billness%253A%2Ba%2Bcomparison%2Bof%2Ba%2Bsample%2Bof%2Bnurses%2Bfrom%2Bfive%2BEuropean%2Bcountries.%26rft_id%253Dinfo%253Adoi%252F10.1016%252Fj.ijnurstu.2009.08.008%26rft_id%253Dinfo%253Apmid%252F19804882%26rft.genre%253Darticle%26rft_val_fmt%253Dinfo%253Aofi%252Ffmt%253Akev%253Amtx%253Ajournal%26ctx_ver%253DZ39.88-2004%26url_ver%253DZ39.88-2004%26url_ctx_fmt%253Dinfo%253Aofi%252Ffmt%253Akev%253Amtx%253Actx [2]: /lookup/external-ref?access_num=10.1016/j.ijnurstu.2009.08.008&link_type=DOI [3]: /lookup/external-ref?access_num=19804882&link_type=MED&atom=%2Febnurs%2F13%2F4%2F115.atom [4]: /lookup/external-ref?access_num=000275611400011&link_type=ISI
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 | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| 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 | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".