Pain Assessment for Nursing Home Residents
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
BACKGROUND: The burden of pain in nursing homes is substantial; however, pain assessment for both acute and chronic conditions remains inadequate, resulting in inappropriate or inadequate treatment. Complexities in assessing resident pain have been attributed to factors (barriers and facilitators) arising at the resident, healthcare provider, and healthcare system levels. OBJECTIVES: In this systematic review protocol, we identify our research approach that will be used to critically appraise and synthesize data in order to assess barriers and facilitators to pain assessment in nursing home residents aged ≥65 years. METHODS: This is a Cochrane style systematic review protocol adhering to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses-Protocols reporting standards. This review will include primary (original) qualitative literature concerning either barriers or facilitators to pain assessment in older adult nursing home residents. A thematic analysis approach will be employed in collating and summarizing included data and will be categorized into resident, healthcare provider, and system-level factors. Database searches will include Abstracts in Social Gerontology, CINAHL, Cochrane Central Register of Controlled Trials, Embase, MEDLINE, and Web of Science. DISCUSSION: The identification of barriers and facilitators to pain assessment in older adult nursing home residents may assist healthcare providers across all platforms and levels of education to improve pain assessment among nursing home residents. Improving the assessment of pain has the potential to improve quality of care and ultimately quality of life for older adult nursing home residents.
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.
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 | 0.005 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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 it