Evidence-based Development and Initial Validation of the Pain Assessment Checklist for Seniors With Limited Ability to Communicate-II (PACSLAC-II)
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
OBJECTIVES: Our goal was to develop and validate, based on theoretical and empirical knowledge, the Pain Assessment Checklist for Seniors with Limited Ability to Communicate (PACSLAC-II), a shorter tool that would improve on the PACSLAC, while addressing limitations of the original version. METHODS: The PACSLAC was revised based on the relevant clinical and theoretical literature. Psychometric properties and clinical utility of the resulting 31-item PACSLAC-II were examined. Specifically, the PACSLAC-II was used to assess pain based on video footage of long-term care (LTC) residents with dementia undergoing painful procedures as part of routine care. Its ability to discriminate pain from non-pain-related states was compared with that of preexisting pain assessment tools using archival data. A second phase involved the use of the PACSLAC and PACSLAC-II by LTC staff to solicit feedback from health care providers. Mixed-methods analysis of this feedback was conducted. RESULTS: The PACSLAC-II demonstrated satisfactory reliability, excellent validity, and ability to differentiate between pain and nonpain states. The PACSLAC-II also accounted for unique variance in differentiating between pain and nonpain states, even after controlling for the preexisting tools combined, including the PACSLAC. The PACSLAC-II was also preferred by many LTC nurses and care aides, because of its length and condensed nature, which was thought to facilitate documentation and greater efficiency in pain management. DISCUSSION: Findings indicate that the empirical and theoretically driven revisions to the PACSLAC led to improved ability to differentiate between pain and nonpain states, while retaining its clinical utility.
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 | 0.018 | 0.008 |
| 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