Predictive models for delay in medical decision-making among older patients with acute ischemic stroke: a comparative study using logistic regression analysis and lightGBM algorithm.

OBJECTIVE: To explore the factors affecting delayed medical decision-making in older patients with acute ischemic stroke (AIS) using logistic regression analysis and the Light Gradient Boosting Machine (LightGBM) algorithm, and compare the two predictive models. METHODS: A cross-sectional study was conducted among 309 older patients aged ≥ 60 who underwent AIS. Demographic characteristics, stroke onset characteristics, previous stroke knowledge level, health literacy, and social network were recorded. These data were separately inputted into logistic regression analysis and the LightGBM algorithm to build the predictive models for delay in medical decision-making among older patients with AIS. Five parameters of Accuracy, Recall, F1 Score, AUC and Precision were compared between the two models. RESULTS: The medical decision-making delay rate in older patients with AIS was 74.76%. The factors affecting medical decision-making delay, identified through logistic regression and LightGBM algorithm, were as follows: stroke severity, stroke recognition, previous stroke knowledge, health literacy, social network (common factors), mode of onset (logistic regression model only), and reaction from others (LightGBM algorithm only). The LightGBM model demonstrated the more superior performance, achieving the higher AUC of 0.909. CONCLUSIONS: This study used advanced LightGBM algorithm to enable early identification of delay in medical decision-making groups in the older patients with AIS. The identified influencing factors can provide critical insights for the development of early prevention and intervention strategies to reduce delay in medical decisions-making among older patients with AIS and promote patients' health. The LightGBM algorithm is the optimal model for predicting the delay in medical decision-making among older patients with AIS.

Depression Mediates the Association Between Burden and Quality of Life in Informal Caregivers of Stroke Survivors: Meta-analytic Structural Equation Modeling.

OBJECTIVE: This study aims to use Meta-analytical structural equation modeling (MASEM) to clarify the relationship between burden, depression, and quality of life in informal caregivers of stroke survivors. DATA SOURCES: The databases of PubMed, Cochrane Library, Embase, China Knowledge Resource Integrated Database, Wan Fang Database, and Chinese Biomedical Database were comprehensively searched before January 16, 2023. STUDY SELECTION: Two researchers performed an independent initial search by using a unified search strategy. Observational studies investigating the relation between burden, depression, and quality of life in informal caregivers of stroke survivors were included. The studies that met the inclusion criteria were appraised by "Quality Assessment and Validity Tool for Correlational Studies". DATA EXTRACTION: PRISMA guidelines were used for this study. Data extraction was performed independently by 2 researchers. The following data were extracted: study author, year of publication, country, language, sample size, age, sex (%women), the caregivers' relation with stroke survivor, measures, type of outcome reported in the study, study design, and main conclusion. DATA SYNTHESIS: The analysis included 18 articles that reported 23 effect sizes (N=3284). The MASEM findings showed that caregiver burden was positively associated with caregiver depression (ß=0.474, 95% CI [0.398, 0.550]), caregiver depression was negatively associated with caregiver quality of life (ß=-0.316, 95% CI [-0.545, -0.087]). Furthermore, the association between caregiver burden and quality of life was completely mediated by caregiver depression (ß=-0.150, 95% CI [-0.271, -0.041]). CONCLUSIONS: Using the MASEM approach, we observed that caregiver depression completely mediated the relation between burden and quality of life in informal caregivers of stroke survivors. Although the results did not allow for causal inference, this result suggested that for burdened stroke survivors' informal caregivers efforts should be made to their mental health to eliminate the internal barriers, then eventually improve their quality of life.

Latent class analysis of symptoms of depression and anxiety among older women.

OBJECTIVES: This cross-sectional study aims to consider the potential classification of depression and anxiety symptoms among older women, and identify the influencing factors of this classification. METHODS: This study examines Chinese women aged 65 years and older. Latent class analysis was used to explore the mental health subgroups of older women, and multivariate logistic regression was employed to examine the influencing factors based on the health ecological model among these subgroups. RESULTS: The results helped classify this population under three subgroups: the coexistence of depression and anxiety group, dominated depression group, and the low symptoms group. Moreover, class differences in terms of age, residence, education, income, assessment of current life and health status, sleep duration, and health behaviors, such as alcohol use and exercise were noted. CONCLUSIONS: These findings explain the heterogeneity among older women, and help illuminate their unique aspects of mental health. Accordingly, they are significant for scholars and policymakers to understand depression and anxiety among older women.

Latent profile analysis of the symptoms of depression and activities of daily living impairment among older adults.

BACKGROUND: With the aging population, depressive symptoms and impaired Activities of Daily Living have increased medical costs and mortality, generating severe public health issues. This study reconsiders the potential classification of depressive symptoms and ADL impairment in older adults and identifies various factors that may affect classifications. METHODS: This study focused on 6270 Chinese adults aged 65 years or older. We used latent profile analysis to explore depressive symptoms and ADL impairment (basic ADLs and instrumental ADLs) in various subgroups of older adults. We used Chi-square analysis and multivariate logistic regression to examine the determinants of depressive symptoms and ADL impairment among subgroups. RESULTS: The study's results classified older adults into three subgroups: those with high level depressive symptoms and BADLs and IADLs impairment, those with moderate level depressive symptoms and IADLs impairment, and those with no to low level depressive symptoms and without BADLs and IADLs impairment. Illiterate, having fallen in the past year, as well as having hearing difficulties all predicted high level depressive symptoms and severe BADLs and IADLs impairment. In contrast, regular exercise, contact with friends, playing cards/mahjong, participating in organized social activities, and visiting siblings predicted moderate level depressive symptoms and IADLs impairment. CONCLUSION: This paper discusses what is known about the various subgroups as well as the treatment of depressive symptoms and ADL impairment in older populations. It also gives policy and practice recommendations for the future that may help rehabilitate and maintain the mental health and ADLs independence of older adults. (PsycInfo Database Record (c) 2024 APA, all rights reserved).

Effect of stressors on family adaptation in stroke patients: A parallel multivariable mediation model.

AIMS: The mechanisms underlying how stressors affect family adaptation are unclear. This study determined the relationship between stressors and family adaptation among stroke patients, particularly the parallel mediating role of family function and family resilience. METHODS AND RESULTS: The study was conducted in the neurology ward of a tertiary hospital in China. A total of 335 stroke inpatients were interviewed face-to-face from August 2020 to March 2021. A questionnaire was administered that included demographic characteristics, the Family Inventory of Life Events and Changes, Family Apgar Index Scale, Family Hardiness Index Scale, and Family Adaptation Scale. The demographic data and correlations among the research variables were analyzed. A bootstrap method using the SPSS PROCESS macro was employed to test a mediation model. Family adaptation was negatively related to stressors (r = -0.291, p < 0.01) and positively related to family function (r = 0.531, p < 0.01) and family resilience (r = 0.393, p < 0.01). Furthermore, family function and family resilience played parallel mediating roles between stressors and family adaptation. CONCLUSIONS: This study elaborated how stressors interacted with family adaptation through the mediation of family function and family resilience. The findings suggest that enhancement of family function and family resilience may help to improve family adaptation among stroke patients.

Determinants Influencing Health-Promoting Behaviors in Individuals at High Risk of Stroke: A Cross-Sectional Study.

BACKGROUND: Health-promoting behaviors and positive lifestyle changes are crucial for effective stroke prevention. However, individuals at high risk of stroke exhibit poor health behavior due to a deficiency of individual motivation. Moreover, there are only a few studies on health-promoting behaviors that have applied behavior change theories in individuals at high risk of stroke. OBJECTIVE: This study aimed to use the theory of the planned behavior (TPB) model to investigate determinants of health-promoting behaviors for stroke prevention and control. METHOD: In this cross-sectional study, 263 participants were recruited from five community health centers in Qingdao. Confirmatory factor analysis was performed to assess the reliability and validity of the constructs, and structural equation modeling was used to analyze the proposed relationships between the TPB-related variables. RESULTS: The attitudes, subjective norms, and perceptions of behavioral control positively influenced behavioral intention. The behavioral intention had a positive effect on health-promoting behaviors. Attitudes, subjective norms, and perceived behavioral control were influenced primarily by the mediating variable behavioral intention to affect health-promoting behaviors. Stroke knowledge was an influential facilitator of behavioral attitudes, subjective norms, and perceived behavior control. CONCLUSION: The TPB-based model is suitable for explaining health-promoting behaviors in individuals at risk of stroke and for guiding the development of effective health management programs. A comprehensive person-centered motivation behavior strategy that is based on health education and complemented by social support and health resource optimization is critical in promoting health behavior motivation and health promotion behaviors in stroke high-risk groups.

Mediating effect of post-stroke depression between activities of daily living and health-related quality of life: meta-analytic structural equation modeling.

BACKGROUND: Stroke survivors face various problems that affect their health-related quality of life (HRQoL). Reduced activities of daily living (ADL) may contribute to post-stroke depression (PSD) and low HRQoL, and depression might be associated with low HRQoL. However, these relationships are not well known. This study aimed to analyze correlations among ADL, PSD, and HRQoL in stroke survivors and further explore the mediating role of PSD between ADL and HRQoL. METHODS: This study utilized meta-analytic structural equation modeling (MASEM) on systematically searched articles from six electronic databases, namely PubMed, Embase, the Cochrane Library, China National Knowledge Infrastructure (China), Wanfang database (China), and SinoMed (China), from inception up to July 31, 2021. Two researchers independently assessed study eligibility, and data from the eligible studies were encoded and assessed for quality. MASEM was utilized to examine correlations among ADL, PSD, and HRQoL, with an estimation of a pooled correlation matrix under a random-effects model. The matrix was directly fitted to a structural equation model using webMASEM. RESULTS: In total, 8580 articles were screened, and data from 27 studies involving 33 effect sizes were used in the MASEM analysis. Correlations among the three variables were significant (both P < 0.01). Furthermore, PSD partially mediated the correlation between ADL and HRQoL (ß = 0.24, 95% confidence interval 0.15-0.30). CONCLUSIONS: The findings suggest that both decreased ADL and PSD may reduce HRQoL, while a decrease in ADL tends to cause depression after stroke. Therefore, ADL and PSD reductions should be improved to achieve better HRQoL of stroke survivors. Future studies should continue to discuss other factors affecting HRQoL to achieve optimal recovery in stroke survivors.

Corrigendum: Longitudinal Association Between Depressive Symptoms and Cognitive Function Among Older Adults: A Parallel Latent Growth Curve Modeling Approach.

[This corrects the article DOI: 10.3389/ijph.2022.1605124.].

Has the COVID-19 pandemic affected nursing students' career self-efficacy and professional calling? The mediating impact of professional identity.

BACKGROUND: Professional calling (PC) is crucial for ascertaining their professional goals and fulfilling career choices in nursing students. Thus, understanding its antecedents and helping schools improve PC among nursing students is critical. This study aims to explore whether professional identity (PI), as a crucial antecedent of PC, acts as an intermediary between career self-efficacy (CSE) and professional calling during the COVID-19 pandemic. METHODS: A sample of 565 nursing students were selected by a web-based survey through convenience sampling. The study was conducted from October to November 2020. Measures of CSE, PI, and PC were assessed during the COVID-19 pandemic. We analyzed demographic data and the correlation of the research variables. The significance of the mediation effect was assessed using a bootstrap method with SPSS. RESULTS: CSE during the COVID-19 pandemic outbreak (r = 0. 359, p < 0. 01) and PI (r = 0. 670, p < 0. 01) were both relevant to PC among nursing students. In addition, CSE had a positive indirect effect on PC through PI (ß = 0. 288, p < 0. 05). CONCLUSIONS: Higher scores in CSE and a better PI were associated with PC in nursing students. Furthermore, a better CSE had an indirect effect on the PC of students through PI. The favorable evidence in our study confirms that nursing educators can adopt PI interventions to improve the sense of PC among nursing students.

The mediating effect of post-stroke depression between social support and quality of life among stroke survivors: A meta-analytic structural equation modeling.

OBJECTIVES: The aim was to confirm the relationship between social support (SS), post-stroke depression (PSD), and quality of life (QOL) and determine the mediating effect of PSD in stroke survivors. Additionally, we tested the impact of economic development level (in developed or developing countries) on the relationship between SS, PSD, and QOL. METHODS: This study utilized meta-analytic structural equation modeling on systematically searched articles from PubMed, MEDLINE, Cochrane Library, Scopus, PsycINFO, Web of Science, China National Knowledge Infrastructure, and WanFang data published from inception to February 2022. Collect the sample size (n) of each study and the associations of observed variables, and conduct meta-analysis path analysis using AMOS 23.0 to assess the relationships. Concurrently, the effects of the national economic development level were extracted for moderator analysis. RESULTS: A total of 28 studies (N = 3967) were included for analysis. SS and PSD were significant predictors of QOL (both p < 0.01). PSD mediated the relationship between SS and QOL (ß = 0.31; 95% confidence interval 0.273-0.345; p < 0.01). Furthermore, in developed countries, SS was not statistically correlated with PSD (p = 0.811) compared to developing countries. CONCLUSIONS: Improving SS may help improve the QOL of stroke patients. PSD should be addressed using a comprehensive approach that includes interventions to enhance the QOL. Additionally, people have different psychological reactions to SS at different stages of economic development; thus, further research is needed to develop different measurement standards for patients according to the country's level of economic development.

Longitudinal Association Between Depressive Symptoms and Cognitive Function Among Older Adults: A Latent Growth Curve Modeling Approach.

Objectives: Although the evidence from numerous longitudinal studies has indicated a remarkable change in cognitive function (CF) and depressive symptoms (DS) over time, the parallel latent growth curve model (LGCM) has seldom been used to simultaneously investigate the relationship between their change trajectories. This study aimed to examine whether a change in DS was associated with CF over time using an LGCM. Methods: Data were collected from the Chinese Longitudinal Healthy Longevity Survey's 2011, 2014, and 2018 waves. A parallel LGCM examined the association between CF and DS. Results: The multivariate conditioned model's goodness of fit supported the validity of the longitudinal model (Tucker-Lewis index [TLI] = 0.90, comparative fit index [CFI] = 0.96, root mean square error of approximation [RMSEA] = 0.04). The results showed that the CF intercept was positively to the DS slope (ß = 0.42, p = 0.004). The CF and DS slopes were significantly linked (ß = -0.65, p = 0.002). Conclusion: The findings expand the knowledge about CF's effect on DS in older adults.

Joint developmental trajectories and temporal precedence of physical function decline and cognitive deterioration: A longitudinal population-based study.

Objectives: Previous studies primarily explored the unidirectional impact of cognition on physical function. However, the interplay between physical function and cognition and the temporal precedence in their predictive relationships have not been elucidated. We explored the bidirectional mechanism between physical function and cognition in a longitudinal dataset. Materials and methods: A total of 1,365 participants in the Chinese Longitudinal Healthy Longevity Survey assessed physical function and cognition in 2011 (T1), 2014 (T2), and 2018 (T3) by the Katz scale and the Chinese version of the Mini-Mental State Examination scale, respectively. Changes in the trajectories of physical function and cognition were examined using the latent growth model. The correlational and reciprocal relationships between physical function and cognition were examined using the parallel process latent growth model and autoregressive cross-lagged (ARCL) models. Results: Cognition and physical function decreased by an average of 0.096 and 0.017 points per year, respectively. Higher physical function was associated with better cognition at baseline (r = 0.237, p < 0.05), and longitudinal changes in physical function and cognition were positively correlated (r = 0.756, p < 0.05). ARCL analysis indicated that physical function at T1 positively predicted T2 cognitive function. However, this predictive relationship reversed between T2 and T3, whereby cognitive function at T2 predicted physical function at T3. Conclusion: Both physical function and cognition declined over time. Early identification and intervention in physical dysfunction among older adults could be critical to prevent further cognitive impairment and maintain functional independence. Hence, regular functional assessment and individualized care plans are required to achieve healthy aging.

Factors influencing alertness to premonitory symptoms in stroke patients with pre-hospital delay.

OBJECTIVE: The purpose was to explore the alertness of premonitory symptoms in stroke patients with prehospital delay, and to analyze the influencing factors. DESIGN AND SAMPLE: A cross-sectional study using the convenience sampling method was conducted in the neurology department of a general hospital between November 2018 and July 2019. A total of 352 stroke patients were participated in the survey. MEASURES: A hierarchical multiple regression was performed to analyze the factors related to the alertness of premonitory symptoms (0-9 scores) in stroke patients with prehospital delay. RESULTS: The alertness score was 6.53 ± 2.377. The lowest score of 0.55 ± 0.498 was for "Continuous yawning occurs continuously despite no tiredness or lack of sleep is okay, and need not be treated." The hierarchical regression results revealed that symptom onset, symptom change before admission, knowledge, social support were the influencing factors delaying the alertness of premonitory symptoms. Knowledge and support from friends could improve the alertness, while support from family and other support had a notable negative impact. CONCLUSIONS: Stroke patients need to be more alert toward premonitory symptoms. This alertness is related to stroke knowledge and social support. Nurses should formulate interventions and advise stroke patients to improve their stroke knowledge and expand their social network.