ReviewThe Journal of frailty & aging2024
Development of the Clinical pHysical rEsilience assEssment Scale (CHEES) in Chinese Older Adults.
Review in The Journal of frailty & aging, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
5 citing papers in PubMed.
- A nomogram model for identifying cognitive frailty in elderly patients with chronic diseases: a multicenter cross-sectional study.Frontiers in public health · 2026Observational
- Development and internal validation of a risk prediction model for oral frailty in hospitalized older adults with chronic diseases.Frontiers in public health · 2026Article
- Resilience and Intrinsic Capacity in Older Adults: A Review of Recent Literature.Journal of clinical medicine · 2025Review
- Translation, Cross-Cultural Adaptation, and Psychometric Validation of the Health Information Technology Usability Evaluation Scale in China: Instrument Validation Study.Journal of medical Internet research · 2025Article
- Association of motoric cognitive risk syndrome and incident mild cognitive impairment in community-dwelling older adults.Frontiers in neurologyArticle
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
9 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundPhysical resilience is an emerging concept that describes an individual's capacity to recover from stressors. However, few instruments are currently available for assessing physical resilience.
objectiveTo develop a scale to assess physical resilience in older adults.
designDevelopment of a clinical scale. SETTING AND
participantsA total of 172 hospitalized older adults were recruited. MEASUREMENTS: This study comprised two stages. First, a pool of physical resilience scale items was created through a literature review, and the Delphi method was used to establish an initial scale. Second, the initial physical resilience scale was tested on hospitalized older adults.
resultsFive primary and 19 secondary items were identified after reviewing the literature. After two rounds of expert consultations, three primary and 16 secondary items were determined. The overall Cronbach's alpha for the scale was 0.760. Except for items N2, N4, N5, N8, and N14, Pearson's correlation between the scores of the remaining items and the total score ranged from 0.407 to 0.672. Except for items N2, N4, and N5, the corrected item-total correlation results ranged from 0.301 to 0.580, indicating good consistency between each item and the overall scale. Factor analysis showed that except for N7, the factor loadings of the remaining items were between 0.584 and 0.844. After expert discussions, items N2, N4, N7, and N14 were included in the scale, and items N5 and N8 were removed.
conclusionA 14-item physical resilience scale, CHEES, was developed to assess physical resilience levels in older adults.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.