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The issue of self-neglect among older adults is receiving attention in modern societies where aging is accelerating. To help expand our understanding of this phenomenon, this study identified its different types using latent profile analysis and verified the main variables that distinguish these types from each other. The three profiles that were identified are high self-neglect (HSN: 28.8%), low self-neglect (LSN: 35.6%), and poor personal hygiene (PPH: 35.6%). Interestingly, PPH showed a high rate and was identified as a noticeable type of elder self-neglect. Gender, age group, SES, support size, and suicidal ideation were significant in classifying the types of self-neglect. Men were more likely to be within the HSN group, and late elderly were more likely to be within the PPH group. The higher SES and social support, the higher the probability of being within the LSN group. The higher the suicidal ideation, the higher the possibility of falling under the HSN group. To reduce self-neglect among older adults, this study suggests to older adults vulnerable to self-neglect, expansion of the social support available to them, and provision of mental health services to this population. [ABSTRACT FROM AUTHOR]

BackgroundAs China rapidly ages, it has now become a deeply aging society with the largest number of older individuals in the world. The issue is particularly severe in rural areas. With the aging population growing and the older population expanding, health problems are becoming more prevalent among older individuals, particularly frailty and cognitive impairments. This study aimed to identify the profiles of physical frailty, social frailty, and cognitive impairment among older adults and explore the influencing factors.MethodsIn this cross-sectional study, participants were recruited from six villages in four cities in Shandong Province, China from July to October 2023 through cluster random sampling. Latent profile analysis was used to determine the profiles of physical frailty, social frailty, and cognitive impairment. Chi-square tests and Mann–Whitney U tests were used for univariate analysis, while binary logistic regression was used to analyze the related factors.ResultsSeven hundred and sixty-nine older adult care in rural areas showed two profiles: the “high cognitive function and low frailty” group (73.7%, n = 567) and the “low cognitive function and high frailty” group (26.3%, n = 202). A binary logistic regression found that older people were more likely to be aged 80 or older (OR = 2.253, p = 0.029), have a low income level (OR = 1.051, p = 0.007), have one or two (OR = 2.287, p = 0.004), or more than three chronic diseases (OR = 3.092, p = 0.002), and report moderate (OR = 3.406, p = 0.024) or poor health status (OR = 9.085, p

Background Suicide is a serious social problem among older adults. However, little is known about how multidimensional factors affect suicide of older adults. Aims We classify the multidimensional suicidal risk types of older adults based on their characteristics and identify differences in suicidal ideation. Method Data were obtained via a nationwide online survey targeting 612 older adults over the age of 55 years. A latent profile analysis identified three profiles, one of which represented the optimal situation for these adults. Results We identified three distinct multidimensional suicidal risk types in older adults: high-risk predicament (24.5%), moderate-risk predicament (57.7%) and abundant internal/external resources (17.8%). In particular, depression, a major risk factor for suicide, was found together with self-neglect in each group. Multiple regression analysis showed that older adults in the moderate-risk predicament and high-risk predicament groups were more likely to have suicidal ideation than those in the abundant internal/external resources group. Conclusions Our findings suggest that co-occurrence of depression and self-neglect represents a suicide risk pattern in high-risk older individuals. Therefore, local communities need to urgently screen and provide interventions for such older adults and strengthen their capacity for multidimensional aspects of life to prevent suicide in the long term.

BackgroundNeglect is a common form of abuse, and long-term care facilities record higher incidences of this abuse. Given that older adult care workers are the main workforce in these facilities, their neglectful behavior requires public health attention. Internal individual characteristics can lead to older adult abuse, and managing workers who abuse older adults may require various methods. This study aimed to identify the profiles of neglect among older adult care workers in long-term care facilities and explore the influencing factors of neglect.MethodsIn this cross-sectional study, a convenience sample of older adult care workers from 15 long-term care facilities in Shandong Province (N = 421) completed a questionnaire on the characteristics associated with neglect. Latent profile analysis was used to identify distinct neglect profiles and promote the understanding of individual characteristics associated with varying levels of neglect. One-way analysis of variance and multivariate logistic regression analyses were used to examine the population characteristic differences.ResultsOlder adult care workers exhibited three neglect profiles, namely, the “low-risk group,” “medium-risk group,” and “high-risk group.” Males, participants with no employment qualification certificate, and those who did not attend regular training represented the majority of those in the “high-risk group.” Participants with a monthly income of more than ¥ 4,000 and nursing 1–2 older adults simultaneously represented the majority of those in the “low-risk group.”ConclusionLong-term care facility administrators should tailor interventions to individual care worker profiles to reduce neglect behaviors and improve care levels.

We aimed to examine the subtype classification characteristics of depressive symptoms in Shidu parents (SDPs, parents who have lost their only child) and their associations with resilience and coping styles. The sample comprised 182 SDPs (Mean age = 59.93 ± 7.41 years, 61.5% females). Latent profile analysis and logistic regression analysis were used to analyze the data. Three subgroups of depressive symptoms in SDPs were identified: the depression and pessimism group (38.4%), the low depression symptoms group (30.8%), and the well‐adapted group (30.8%). The low depression symptoms group had a lower education level and higher family monthly income than the depression and pessimism group. The low depression symptoms group and the well‐adapted group scored significantly higher in resilience, and lower in negative coping style than the depression and pessimism group. The results highlighted that target intervention is needed for SDPs with high education levels, low family monthly income, high negative coping style, and low resilience in the depression and pessimism group. [ABSTRACT FROM AUTHOR]

ObjectiveSocial participation has become a policy framework to address population aging. However, little is known about the social participation of older adults in western China, and extensive, multicenter, regional research is lacking. This research investigated the profiles of social participation of older adults in western China and explored the characteristics and factors influencing social participation.MethodThis cross-sectional study was conducted in 3 provinces (Chongqing, Sichuan, and Inner Mongolia) in western China from March 2021 to December 2021 and included 3,456 participants aged 60 years or older. Social participation was assessed using the Chinese version of the Impact on Participation and Autonomy Questionnaire (IPA). Latent profile analysis (LPA) was performed to extract latent classes of social participation among older adults in western China. The chi-square test and multinomial regression analyses were used to identify differences between these classes.ResultsThree social participation classes were identified by LPA: high social participation (25.2%), moderate social participation (55.1%), and low social participation (19.7%). Being older, having a primary school education level, having mobility or speaking impairment, using assistive devices, and having a chronic disease were highly associated with the low social participation class (P < 0.05). Furthermore, older adults with no dependence (OR = 0.018, 95% CI = 0.005–0.062) or mild dependence (OR = 0.039, 95% CI = 0.011–0.139) in activities of daily living (ADLs) were less likely to be in the low social participation class. Older adults who were cared for by non-spouse primary caregivers were more likely to be assigned to the moderate social participation group (OR = 2.097, 95% CI = 1.501–2.930) than to the high social participation group.ConclusionsMost older adults in western China have a moderate level of social participation. Advanced age, reduced ADL ability, reduced speech ability, reduced mobility, and non-spouse care are related to the level of social participation. Healthcare professionals should pay attention to the predictors for different classes, identifying high-risk groups as early as possible.

Background: As China rapidly ages, it has now become a deeply aging society with the largest number of older individuals in the world. The issue is particularly severe in rural areas. With the aging population growing and the older population expanding, health problems are becoming more prevalent among older individuals, particularly frailty and cognitive impairments. This study aimed to identify the profiles of physical frailty, social frailty, and cognitive impairment among older adults and explore the influencing factors., Methods: In this cross-sectional study, participants were recruited from six villages in four cities in Shandong Province, China from July to October 2023 through cluster random sampling. Latent profile analysis was used to determine the profiles of physical frailty, social frailty, and cognitive impairment. Chi-square tests and Mann-Whitney U tests were used for univariate analysis, while binary logistic regression was used to analyze the related factors., Results: Seven hundred and sixty-nine older adult care in rural areas showed two profiles: the "high cognitive function and low frailty" group (73.7%, n  = 567) and the "low cognitive function and high frailty" group (26.3%, n  = 202). A binary logistic regression found that older people were more likely to be aged 80 or older (OR = 2.253, p  = 0.029), have a low income level (OR = 1.051, p  = 0.007), have one or two (OR = 2.287, p  = 0.004), or more than three chronic diseases (OR = 3.092, p  = 0.002), and report moderate (OR = 3.406, p  = 0.024) or poor health status (OR = 9.085, p  < 0.001) in the "low cognitive function and high frailty" group. Meanwhile, older adults who have completed high school (OR = 0.428, p  = 0.005) or junior college and above (OR = 0.208, p  = 0.009), and engage in adequate physical activity (OR = 0.319, p  < 0.001) were more likely to be in the "high cognitive function and low frailty" group., Conclusion: In the future, medical professors should increasingly prioritize promptly identifying and intervening in cognitive decline and frailty status in older individuals without delay., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2024 Dong, Bu, Wang, Liu, Zhong and Liu.)

Background: Neglect is a common form of abuse, and long-term care facilities record higher incidences of this abuse. Given that older adult care workers are the main workforce in these facilities, their neglectful behavior requires public health attention. Internal individual characteristics can lead to older adult abuse, and managing workers who abuse older adults may require various methods. This study aimed to identify the profiles of neglect among older adult care workers in long-term care facilities and explore the influencing factors of neglect., Methods: In this cross-sectional study, a convenience sample of older adult care workers from 15 long-term care facilities in Shandong Province ( N = 421) completed a questionnaire on the characteristics associated with neglect. Latent profile analysis was used to identify distinct neglect profiles and promote the understanding of individual characteristics associated with varying levels of neglect. One-way analysis of variance and multivariate logistic regression analyses were used to examine the population characteristic differences., Results: Older adult care workers exhibited three neglect profiles, namely, the "low-risk group," "medium-risk group," and "high-risk group." Males, participants with no employment qualification certificate, and those who did not attend regular training represented the majority of those in the "high-risk group." Participants with a monthly income of more than ¥ 4,000 and nursing 1-2 older adults simultaneously represented the majority of those in the "low-risk group.", Conclusion: Long-term care facility administrators should tailor interventions to individual care worker profiles to reduce neglect behaviors and improve care levels., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2024 Yan, Wang, Ding, Sun, Gao and Liu.)

Purpose: Increasing physical activity level is a generally effective intervention goal for patients who suffer from chronic cancer-related fatigue (CCRF). However, patients are unlikely to benefit equally from these interventions, as their behavioral starting points might vary substantially. Therefore, we explored patterns of physical behavior of participants who suffer from CCRF.Methods: Baseline data of a randomized controlled trial were used for a latent profile analysis on nine accelerometer-derived physical behavior measures, describing levels and patterns of physical activity, moderate-to-vigorous intensity physical activity (MVPA), and sedentary behavior. The relation between participant characteristics and the latent profiles was analyzed.Results: Accelerometer data of 172 participants from the Netherlands was analyzed. Three latent profiles were distinguished that differed most on physical activity level and total time spent in MVPA. Eighty-eight percent of all participants were assigned to a profile with a probability higher than 8. Age and perceiving limitations by comorbid conditions and pain were significant covariates of profile membership.Conclusions: We distinguished three physical behavior profiles. The differences between the patterns indicate that the heterogeneity of this sample requires patients to have substantially different treatment goals. Further research should test the applicability of these profiles in clinical practice. [ABSTRACT FROM AUTHOR]

The issue of self-neglect among older adults is receiving attention in modern societies where aging is accelerating. To help expand our understanding of this phenomenon, this study identified its different types using latent profile analysis and verified the main variables that distinguish these types from each other. The three profiles that were identified are high self-neglect (HSN: 28.8%), low self-neglect (LSN: 35.6%), and poor personal hygiene (PPH: 35.6%). Interestingly, PPH showed a high rate and was identified as a noticeable type of elder self-neglect. Gender, age group, SES, support size, and suicidal ideation were significant in classifying the types of self-neglect. Men were more likely to be within the HSN group, and late elderly were more likely to be within the PPH group. The higher SES and social support, the higher the probability of being within the LSN group. The higher the suicidal ideation, the higher the possibility of falling under the HSN group. To reduce self-neglect among older adults, this study suggests to older adults vulnerable to self-neglect, expansion of the social support available to them, and provision of mental health services to this population.

Objective: Social participation has become a policy framework to address population aging. However, little is known about the social participation of older adults in western China, and extensive, multicenter, regional research is lacking. This research investigated the profiles of social participation of older adults in western China and explored the characteristics and factors influencing social participation., Method: This cross-sectional study was conducted in 3 provinces (Chongqing, Sichuan, and Inner Mongolia) in western China from March 2021 to December 2021 and included 3,456 participants aged 60 years or older. Social participation was assessed using the Chinese version of the Impact on Participation and Autonomy Questionnaire (IPA). Latent profile analysis (LPA) was performed to extract latent classes of social participation among older adults in western China. The chi-square test and multinomial regression analyses were used to identify differences between these classes., Results: Three social participation classes were identified by LPA: high social participation (25.2%), moderate social participation (55.1%), and low social participation (19.7%). Being older, having a primary school education level, having mobility or speaking impairment, using assistive devices, and having a chronic disease were highly associated with the low social participation class ( P < 0.05). Furthermore, older adults with no dependence (OR = 0.018, 95% CI = 0.005-0.062) or mild dependence (OR = 0.039, 95% CI = 0.011-0.139) in activities of daily living (ADLs) were less likely to be in the low social participation class. Older adults who were cared for by non-spouse primary caregivers were more likely to be assigned to the moderate social participation group (OR = 2.097, 95% CI = 1.501-2.930) than to the high social participation group., Conclusions: Most older adults in western China have a moderate level of social participation. Advanced age, reduced ADL ability, reduced speech ability, reduced mobility, and non-spouse care are related to the level of social participation. Healthcare professionals should pay attention to the predictors for different classes, identifying high-risk groups as early as possible., Competing Interests: Author FW is employed by Panzhihua Wuyue Technology Co., Ltd. The remaining authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2022 Luo, Yu, Wang, Zhu, Yang, Bai, Rao, Zhang, Wu, Wang, Zhao and Xiao.)