Impact of Pain on Activities of Daily Living in Older Adults: A Cross-Sectional Analysis of Korean Longitudinal Study of Aging (KLoSA)
Bibliographic record
Abstract
Pain, particularly musculoskeletal (MSK) and multi-site pain, significantly impacts activities of daily living (ADL) in the elderly, leading to a decline in overall quality of life (QoL). This study, comprising 7490 participants, (mean age: 69 ± 10; females: 57%) from the sixth wave of the Korean Longitudinal Study of Aging (KLoSA), aimed to assess the association between self-reported pain and ADL impairment among the elderly population. Notably, 62% of participants reported experiencing pain, with back pain being the most prevalent (36%) and stomachache the least (0.39%). A majority (61%) of individuals reported MSK-related pain. Additionally, 20% reported pain at one site and 0.03% experienced pain at 12 sites. ADL impairment was observed in 376 (5.0%) participants. Compared to those without pain, participants reporting moderate and severe pain had higher odds of ADL impairment [2.31 (95% CI, 1.66-3.21) and 2.98 (95% CI, 1.95-4.53), respectively]. Pain experienced in the shoulder, arm, wrist, back, hip, leg, and ankle had a significant association with ADL impairment, with ORs ranging from 2.66 (95% CI, 1.80-3.93; hip pain) to 1.36 (95% CI 1.07-1.72; back pain). Furthermore, multi-site pain was associated with higher ADL impairment [1-6 sites: OR: 1.49 (95% CI, 1.11-2.01); 7-12 sites: OR: 7.16 (95% CI, 3.60-14.26)]. These findings underscore the importance of addressing MSK and multi-site pain through targeted interventions, potentially enhancing ADL and contributing to an improved QoL among the elderly population.
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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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 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".