ArticleFrontiers in public health2026
Self-awareness of falls and its influencing factors in older patients with cardiometabolic multimorbidity: a latent profile analysis.
Article in Frontiers in public health, 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
7 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Background: Self-awareness of falls is a comprehensive psychological trait encompassing an individual's subjective assessment of their own falls risk, risk identification, and prospective preventive behavioral tendencies. It serves as a key cognitive-behavioral mediating factor influencing the occurrence of falls. Older patients with cardiometabolic multimorbidity face multiple fall-related risks due to advanced age, multimorbidity, and polypharmacy. However, research on self-awareness of falls in this population remains in its early stages, and most existing studies have adopted a variable-centered approach, which fails to capture the potential individual heterogeneity. Methods: Using convenience sampling, a total of 363 older patients with cardiometabolic multimorbidity were recruited from six communities in Anhui Province, China, between September and December 2025. Demographic and disease-related information were collected using a general information questionnaire. Assessments were conducted using the following instruments: the Self-awareness of Falls Scale, the STEADI Stay Independent Brochure Questionnaire, the Barthel Index, the Self-Rating Anxiety Scale (SAS), the Multidimensional Scale of Perceived Social Support, and the Pittsburgh Sleep Quality Index. Latent profile analysis was performed using Mplus 8.7 to identify distinct profiles of self-awareness of falls. Univariate analysis and multivariate logistic regression were conducted using SPSS 27.0 to explore factors associated with latent profile membership. Results: A total of 343 valid questionnaires were collected in this study, yielding an effective response rate of 94.5%. Based on the characteristics of self-awareness of falls in older patients with cardiometabolic multimorbidity, latent profile analysis identified four distinct latent profiles: Low Falls Alertness Profile (Profile 1, Conclusion: The level of self-awareness of falls among older patients with cardiometabolic multimorbidity remains at a moderate level. Latent profile analysis identified four distinct subtypes of self-awareness of falls in this population, exhibiting significant heterogeneity. Based on the characteristics of each profile and the differences in influencing factors, clinical nursing practice should move beyond traditional uniform interventions and implement profile-specific assessment and targeted interventions according to different falls alertness subtypes, thereby enhancing the effectiveness of falls prevention.
Indexed as
Identifiers
What Socratic 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 Socratic graph.