ArticleBMC geriatrics2026
Aging self-stereotypes and associated factors among elderly patients with multimorbidity undergoing elective surgery: a cross-sectional study.
Article in BMC geriatrics, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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
0 citing papers in PubMed.
No citing paper in PubMed yet.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
6 authors.
Funding
Abstract
backgroundThe aging self-stereotypes are increasingly recognized as a significant psychosocial issue affecting older adults with multimorbidity, particularly those undergoing elective surgery. The aging self-stereotypes can exacerbate postoperative recovery and reduce quality of life. However, factors influencing aging self-stereotypes in this vulnerable population remain underexplored. This study aimed to investigate the level of aging self-stereotypes among elderly patients with multimorbidity undergoing elective surgery and to analyze relevant influencing factors with the goal of laying a foundation for the development of targeted intervention strategies. The findings will help medical staff identify high-risk patients and inform the development of targeted perioperative interventions to improve recovery outcomes and quality of life.
methodsThis study, which featured a cross-sectional survey design, focused on a total of 188 elderly patients with multimorbidity who underwent elective surgeries at a tertiary A-grade hospital in Chongqing and were recruited through convenience sampling between July 2025 and December 2025. General information questionnaires, the Barthel index, the Cumulative Illness Rating Scale, the Aging Self-Stereotypes Scale, the Fried Frailty Phenotype, and the Control Preference Scale were used in this research. Multiple linear regression was used to identify associated factors. Statistical significance was set at P < 0.05.
resultsThe aging self-stereotypes scores obtained by elderly patients with multimorbidity who underwent elective surgery were 27.697 ± 1.953 points. The results of multiple linear regression analysis identified first-time surgery ( β = 0.143, CI (-0.008, 1.072), P = 0.034), Cumulative Illness Rating Scale score ( β = 0.177, CI (0.230,1.741), P = 0.011), and active decision-making (β = -0.161, CI (-1.900, -0.134), P = 0.024) as influencing factors pertaining to aging self-stereotypes among elderly patients with multimorbidity who underwent elective surgeries, which altogether explained 50.1% of the total variance.
conclusionsElderly patients with multimorbidity who underwent elective surgeries have high aging self‑stereotype scores, which are independently associated with first‑time surgery, multimorbidity burden, and decision‑making preference. A management model that combines multidisciplinary collaboration with family support should be established to reduce negative stereotypes and improve quality of life among these patients.
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.