Disability and severe depression among Peruvian older adults: analysis of the Peru Demographic and Family Health Survey, ENDES 2017

Chronic health conditions and disability are prevalent among community users of a digital mental health service: a scoping survey

Objectives: Digital interventions can offer accessible and scalable treatment for chronic conditions, though often focus separately on physical or mental health. People accessing digital health services may live with multiple conditions or experience overlapping symptoms. This study aimed to describe the breadth and characteristics of chronic health conditions and self-reported disability among routine users of a digital mental health service, and to examine related motivations to engage with digital mental health interventions.

Methods: A cross-sectional survey of adults registered with a digital mental health service in the Australian community (THIS WAY UP) was conducted. Participant demography, chronic health conditions, self-reported disability and motivations for accessing digital treatment were collected and analyzed descriptively.

Results: 366 participants responded (77% female, mean age 50 ± 15 years). 71.6% of participants (242/338) reported ≥1 chronic health condition and one-third reported multimorbidity (112/338, 33.1%). Chronic pain, musculoskeletal and connective tissue disorders were most common. 26.9% of respondents (90/334) reported a disability, most commonly physical disabilities. 95% of those with chronic conditions reported negative mental health effects and 46% reported heightened interest in digital mental health treatments because of their condition. Primary motivations for digital service use were receiving a recommendation from a health professional and service accessibility.

Discussion: People who access digital mental health services in routine care report high rates of heterogenous chronic illness and related disability. There is interest in accessible digital treatments to support mental health at scale among people who live with varied chronic conditions and disabilities.

Depression in persons with disabilities: a scoping review

Individuals with disabilities are more vulnerable to depression development than the general population. This study sought to map the evidence on current knowledge of depression, intervention strategies, and assessment tools among people with disabilities. This review was conducted following Arksey and O'Malley's scoping review methodology framework. An electronic search was performed on four English databases: PubMed, Cochrane Library, PsycINFO, and Web of Science. The original search returned 1802 results, with 1,116 from Web of Science, 626 from PubMed, 25 from Cochrane, and 35 from PsycINFO. After removing duplicates, 786 articles were chosen for the title and abstract screening processes. Finally, 112 full-text publications were deemed eligible, with 41 papers being included in this scoping review for analysis. A large proportion (32; 78.04%) of the studies chosen were cross-sectional, 14 (34.14%) of them reported general disability, 12 (29.26%) used a patient health questionnaire (PHQ-9) to measure depression, and 14 (34.14%) had interventions, including cognitive behavioral therapy, psychological counseling, social support, and physical activity. All interventions successfully reduced the severity of the depression. Cognitive behavioral therapies and psychological counseling were widely used interventions that had a significant impact on reducing depression. More randomized controlled trials are required, and they should focus on individuals with specific disabilities to provide disability-specific care that can improve the quality of life for disabled individuals.

A predictive model for depression in Chinese middle-aged and elderly people with physical disabilities

BACKGROUND

Middle-aged and older adults with physical disabilities exhibit more common and severe depressive symptoms than those without physical disabilities. Such symptoms can greatly affect the physical and mental health and life expectancy of middle-aged and older persons with disabilities.

METHOD

This study selected 2015 and 2018 data from the China Longitudinal Study of Health and Retirement. After analyzing the effect of age on depression, we used whether middle-aged and older adults with physical disabilities were depressed as the dependent variable and included a total of 24 predictor variables, including demographic factors, health behaviors, physical functioning and socialization, as independent variables. The data were randomly divided into training and validation sets on a 7:3 basis. LASSO regression analysis combined with binary logistic regression analysis was performed in the training set to screen the predictor variables of the model. Construct models in the training set and perform model evaluation, model visualization and internal validation. Perform external validation of the model in the validation set.

RESULT

A total of 1052 middle-aged and elderly persons with physical disabilities were included in this study, and the prevalence of depression in the elderly group > middle-aged group. Restricted triple spline indicated that age had different effects on depression in the middle-aged and elderly groups. LASSO regression analysis combined with binary logistic regression screened out Gender, Location of Residential Address, Shortsightedness, Hearing, Any possible helper in the future, Alcoholic in the Past Year, Difficulty with Using the Toilet, Difficulty with Preparing Hot Meals, and Unable to work due to disability constructed the Chinese Depression Prediction Model for Middle-aged and Older People with Physical Disabilities. The nomogram shows that living in a rural area, lack of assistance, difficulties with activities of daily living, alcohol abuse, visual and hearing impairments, unemployment and being female are risk factors for depression in middle-aged and older persons with physical disabilities. The area under the ROC curve for the model, internal validation and external validation were all greater than 0.70, the mean absolute error was less than 0.02, and the recall and precision were both greater than 0.65, indicating that the model performs well in terms of discriminability, accuracy and generalisation. The DCA curve and net gain curve of the model indicate that the model has high gain in predicting depression.

CONCLUSION

In this study, we showed that being female, living in rural areas, having poor vision and/or hearing, lack of assistance from others, drinking alcohol, having difficulty using the restroom and preparing food, and being unable to work due to a disability were risk factors for depression among middle-aged and older adults with physical disabilities. We developed a depression prediction model to assess the likelihood of depression in Chinese middle-aged and older adults with physical disabilities based on the above risk factors, so that early identification, intervention, and treatment can be provided to middle-aged and older adults with physical disabilities who are at high risk of developing depression.

A model for predicting physical function upon discharge of hospitalized older adults in Taiwan-a machine learning approach based on both electronic health records and comprehensive geriatric assessment

Background

Predicting physical function upon discharge among hospitalized older adults is important. This study has aimed to develop a prediction model of physical function upon discharge through use of a machine learning algorithm using electronic health records (EHRs) and comprehensive geriatrics assessments (CGAs) among hospitalized older adults in Taiwan.

Methods

Data was retrieved from the clinical database of a tertiary medical center in central Taiwan. Older adults admitted to the acute geriatric unit during the period from January 2012 to December 2018 were included for analysis, while those with missing data were excluded. From data of the EHRs and CGAs, a total of 52 clinical features were input for model building. We used 3 different machine learning algorithms, XGBoost, random forest and logistic regression.

Results

In total, 1,755 older adults were included in final analysis, with a mean age of 80.68 years. For linear models on physical function upon discharge, the accuracy of prediction was 87% for XGBoost, 85% for random forest, and 32% for logistic regression. For classification models on physical function upon discharge, the accuracy for random forest, logistic regression and XGBoost were 94, 92 and 92%, respectively. The auROC reached 98% for XGBoost and random forest, while logistic regression had an auROC of 97%. The top 3 features of importance were activity of daily living (ADL) at baseline, ADL during admission, and mini nutritional status (MNA) during admission.

Conclusion

The results showed that physical function upon discharge among hospitalized older adults can be predicted accurately during admission through use of a machine learning model with data taken from EHRs and CGAs.

Profiles of depressive symptoms in Peru: An 8-year analysis in population-based surveys

Background Profiles of depressive symptoms have been described due to heterogeneity in symptomatology and presentation. In our study, we estimate depressive symptom profiles and relate these symptom profiles to risk factors in the Peruvian population. Methods We carried out an observational study based on the Peruvian Demographic and Health Survey (2014-2022). Men and women aged 15 years and older living in urban and rural areas in all regions of Peru were included. The Patient Health Questionnaire-9 was used to define depressive symptom profiles. We estimated latent class models to define the profiles and performed a Poisson regression analysis to determine the associated factors. Results A total of 259,655 participants were included. The three-class model was found to be the most appropriate, and the classes were defined according to the severity of depressive symptoms (moderate-severe symptoms, mild symptoms, and without depressive symptoms). Also, it was found that the three classes identified have not changed during the years of evaluations, presenting very similar prevalence over the years. In addition, women are more likely than men to belong to a class with more severe depressive symptoms; and the older the age, the higher the probability of belonging to a class with greater severity of depressive symptoms. Conclusions Our study found that at the population level in Peru, depressive symptoms are grouped into three classes according to the intensity of the symptomatology present (no symptoms, mild symptoms and moderate-severe symptoms).

Predictors of depression among the elderly persons with disabilities in Indonesia

BACKGROUND

Depression is a major mental problem in the elderly, particularly those with disability. This study's aim was to identify variables that predict depression in the elderly with disabilities.

MATERIALS AND METHODS

This cross-sectional study was conducted in Gunungkidul Regency and Yogyakarta City from April to June 2021. The study participants were community-dwelling elderly aged 60 years and above with disabilities, who could communicate verbally without any apparent cognitive impairment. Data was collected by interviewing participants using structured questionnaire on following sections: Demographic characteristics, Mini-Mental State Examination (MMSE), Washington Group Short Set (WG-SS), Barthel Index of activities of daily living (ADL), Lawton Instrumental ADL (IADL) Scale, and Geriatric Depression Scale-30 (GDS-30). Multivariate linear regression analysis applied to identify variables significantly correlated with depression. Multinomial logistic regression analysis performed to obtain the odds ratio (OR).

RESULTS

Study included 115 elderly persons with disabilities. Most of them had mobility impairment. Higher independence in ADL and being married were related with lower risk of depression, whereas increased age at disability increased the risk of depression (P = 0.001). The elderly who had greater independence with daily activities were less likely to have depression (OR = 0.639 for mild depression and OR = 0.589 for severe depression). Those who were not married were more likely to have mild depression (OR = 3.203) and severe depression (OR = 29.119). compared to the married elderly. Age at acquiring disability was associated with higher risk for mild depression (OR = 1.025) and severe depression (OR = 1.053). Higher independence in ADL and being married were related with lower risk of depression, whereas increased age at disability increased the risk of depression (P = 0.001).

CONCLUSION

Independence in the ADL, being married, and being disabled as a young adult are negative predictors of depression in the elderly with disability.

Depression Screening in a population-based study: Brazilian National Health Survey 2019

This study evaluated the prevalence of positive screening for depression in Brazil and its associated factors. We used data from National Health Survey 2019 (Pesquisa Nacional de Saúde - PNS), a population-based survey with 88,531 adults. The Patient Health Questionnaire (PHQ-9) was used with two scoring methods, the algorithm and the cutoff point≥10. The variables included sociodemographic characteristics. The prevalence ratios and 95% confidence intervals (95%CI) were estimated using Poisson regression. The positive screening for depression was 10.8% (95%CI: 10.4-11.0), at the cutoff point ≥10 and 5.7% (95%CI: 5.4-6.0) for algorithm. Significant differences were found in prevalence in some Brazilian states. Multivariable analyses showed that being female, black, under 70 years of age, having little education, being single, and living in an urban area were independently associated with a depressive symptoms. The highest association was found in the states of Sergipe, Goiás, Piauí, Espírito Santo, São Paulo, Alagoas and lowest in Pará, Mato Grosso and Maranhão. The prevalence of positive screening for depression in Brazil has increased in recent years. More investment in mental health resources is necessary and surveys such as the PNS should be continued.

Depression Is Associated with Chronic Pain in Disabled Older Adults

BACKGROUND

The association between depression and chronic pain has been clearly demonstrated in healthy older adults, but not in older adults with disabilities. This study thus aimed to clarify the association between depression and chronic pain in older adults with disabilities.

METHODS

In total, 92 older adults aged 65 years or older subscribed to Japanese long-term care insurance services were included in this study. Depression was assessed using the Geriatric Depression Scale-Short Version-Japanese (GDS-S-J) and was diagnosed among respondents who scored 6 or more points. Chronic pain was assessed using a questionnaire and defined as a "pain that persists in the present and has lasted for more than three months."

RESULTS

Chronic pain was associated with depression in older adults with disabilities (odds ratio: 3,355, 95% confidence interval: 1,232-9,135, p = 0,018). There was a strong association between severe chronic pain and depression (odds ratio: 3,699, 95% confidence interval: 1,345-10,173, p = 0,011).

CONCLUSION

Our findings suggest that it is necessary to focus on intensity of chronic pain to improve depression in older adults with disabilities who are more difficult to treat than healthy older adults.

Disability and psychological distress in nine countries of the former Soviet Union

BACKGROUND

People with disabilities (PWD) are at increased risk of poor mental health. However, this association and the pathways involved remain under-researched in many parts of the world. This study examined the association between disability and psychological distress in nine countries of the former Soviet Union (FSU).

METHODS

Data were analysed from 18,000 adults aged ≥18 years collected during the Health in Times of Transition (HITT) survey undertaken in Armenia, Azerbaijan, Belarus, Georgia, Kazakhstan, Kyrgyzstan, Moldova, Russia, and Ukraine in 2010 and 2011. Information was obtained on disability status, the severity of the disability and psychological distress. Logistic regression analysis was used to estimate associations.

RESULTS

In a fully adjusted combined country analysis, disability was associated with over two times higher odds for psychological distress (odds ratio [OR]: 2.19, 95% confidence interval [CI]: 1.86-2.58). The strength of the association varied across the individual countries. Among PWD more severe disability was associated with significantly higher odds for psychological distress (OR: 2.12, 95%CI: 1.26-3.55).

LIMITATIONS

The data were cross-sectional and disability status was self-reported, possibly resulting in underreporting.

CONCLUSIONS

Disability is associated with worse psychological health in FSU countries, especially among those with more severe disabilities. As poor mental health may also increase the risk of negative outcomes in PWD, this finding highlights the importance of the early detection and treatment of mental disorders in PWD in these countries.