Depression-linked beliefs in older adults with depression

"Accepting the Poem of Destiny": Identity Reconstruction in a Chinese Online Depression Community

As online health communities become important platforms for people with depression to express themselves, digital narratives provide a lens for understanding their identity work. Drawing on the communication theory of identity (CTI), this article explored the members' identity reconstruction by analyzing their narratives posted in a Chinese online depression community. The four levels of identities constructed by the members include "laggard" and "pioneer" at the personal layer, "idler" and "fighter" at the enacted level, "stress-maker" and "escaper" at the relational layer, and support providers and receivers at the communal layer. These identities at different levels usually interact in the narratives, showing that identity gaps exist among the members. The study shows that the members' autobiographical accounts of depression entail multiplicities and ambivalences, denying the dominant and stigmatizing representation of it by common sense and the media as a reductionist downward and one-way experience that is valueless and offers no possibility for personal growth. The findings regarding the communal level of identity show that narratives can help the narrators to create bonds of solidarity of an experience that is often marginalized.

A predictive model for depression in elderly people with arthritis based on the TRIPOD guidelines

OBJECTIVE

Through machine learning algorithms, a prediction model for depression in arthritis patients was established to provide a basis for related interventions.

METHODS

Data from 4240 patients with arthritis were collected from the National Health and Nutrition Examination Survey database and divided into a training set (70 %) and a test set (30 %). LASSO Regression was employed for feature variable selection, and predictive models were constructed using five machine learning algorithms: Random Forest (RF), Logistic Regression (LR), Extreme Gradient Boosting (XGBoost), Gaussian Naive Bayes (GNB), and Gradient Boosting Decision Tree (GBDT). Model performance was evaluated through various metrics, including the Area Under the Receiver Operating Characteristic Curve (AUC), accuracy, sensitivity, cutoff, recall, Kappa, Positive Predictive Value(PPV) and Negative Predictive Value(NPV). Additionally, Shapley Additive Explanations (SHAP) analysis was conducted for personalized risk assessment.

RESULT

The predictive performance of the random forest model was the highest,with an area under curve (AUC) of 0.811 (SD:0.000) for the training set and 0.780 (SD:0.001) for the test set. The model identified eight significant variables associated with the occurrence of arthritis depression, including health status, difficulty standing for extended periods, difficulty getting in and out of bed, difficulty sitting for prolonged durations, education, gender, difficulty managing finances, and race. DCA demonstrated that the nomogram was clinically beneficial.

CONCLUSION

The predictive model developed for identifying depression in patients with arthritis exhibits high predictive ability, and good clinical applicability. This model can aid healthcare providers in the early detection of depression, thereby enabling timely interventions that can enhance patient prognosis and promote healthy aging. Future research should incorporate real-time biomarker monitoring to refine dynamic risk assessment.

Factors influencing the level of insight and treatment attitude: a cross-sectional study of 141 elderly patients of major depression in Guangzhou, China

Objective

To explore the insight, treatment attitude, and related influencing factors of hospitalized elderly patients suffering from major depression.

Methods

A total of 141 hospitalized elderly patients with depression were selected as the research objects. Insight was evaluated by the total score of the Insight and Treatment Attitude questionnaire (ITAQ). The data collected included sociodemographic characteristics, psychiatric symptoms, delirium status, social functioning, social support, suicide risk, and cognitive function.

Results

The sample included 74.5% of female patients, and the mean age was 67.53 (sd=7.19) years. The influencing factors of inpatients with depression included alcohol consumption, length of hospitalization, admission types, and the main caregivers (P<0.05). The various factors were further analyzed by linear regression, revealing that the insight and treatment attitude of elderly depressed hospitalized patients were mainly related to the Mini-Mental State Examination (MMSE) (β= 0.225, 95% CI 0.055-0.395, P=0.01), dependent on a caregiver (β=-5.810, 95% CI -8.086~-3.535, P<0.001), the type of admission (involuntary admission) (β=-3.365, 95% CI -5.448~-1.283, P=0.002), Functional Activities Questionnaire (FAQ) (β=-0.156, 95% CI -0.303~-0.010, P=0.037), and length of stay (≤28 days) (β=2.272, 95% CI 0.055~-4.489, P=0.045).

Conclusion

The level of insight was affected by cognitive function, involuntary admission, dependent on a caregiver, social function and length of stay. Future studies should focus on cognitive function recovery, observation of admission mode, and self-care ability in elderly patients with depression.

Complaining, Regret, Superiority, and Discovery: Chinese Patients' Sense Making of Depression in an Online Forum

Drawing on observations of a Chinese online depression community, this article explored the members' sense making of depression by analyzing their narrative accounts of depression. Four types of sense making were predominant among the depression sufferers: complaining, regret, superiority, and discovery. The complaining narrative is the members' telling about the pain caused by family (parental control or neglect), school bullying, stress from study or work, and social norms. The regret narrative is the members' reflection on their habit of perfectionism and lack of self-disclosure. The superiority narrative is the members' attribution of depression to their intelligence and morality that surpass the average people. The discovery narrative is the members' novel understanding of the self, significant others, and key events. The findings suggest that the social and psychological explanation of the causes of depression, instead of the medical model, is popular among the Chinese patients. Their stories of depression are also stories of marginalization, visions for the future, and realizing the normalization of identity as depression patients. The findings have implications for public policy around support for mental health.

Guilt for perceiving oneself as a burden in healthy older adults. Associated factors

METHODS

Participants were 317 community-dwelling people over 60 years without cognitive or functional limitations. A path model that explores the role of self-perceived burden in the relationship between negative self-perception of aging, perceived control, depressive symptoms and guilt associated with self-perception as a burden was analyzed.

RESULTS

The model presented excellent fit to the data, explaining 41% of the depressive symptomatology and 45% of guilt for perceiving oneself as a burden. Negative self-perceptions of aging, lower sense of control, and a perception of being a burden were significantly associated with depressive symptoms and guilt for perceiving oneself as a burden.

DISCUSSION

This study documents potential correlates of psychological distress in older adults with no explicit physical or cognitive problems, suggesting paths through which feelings of guilt for perceiving oneself as a burden may be reported by this population.

Effects of social robots on depressive symptoms in older adults: a scoping review

Purpose

This review scopes evidence on the use of social robots for older adults with depressive symptoms, in the scenario of smart cities, analyzing the age-related depression specificities, investigated contexts and intervention protocols' features.

Design/methodology/approach

Studies retrieved from two major databases were selected against inclusion and exclusion criteria. Studies were included if used social robots, included older adults over 60, and reported depressive symptoms measurements, with any type of research design. Papers not published in English, published as an abstract or study protocol, or not peer-reviewed were excluded.

Findings

28 relevant studies were included, in which PARO was the most used robot. Most studies included very older adults with neurocognitive disorders living in long-term care facilities. The intervention protocols were heterogeneous regarding the duration, session duration and frequency. Only 35.6% of the studies had a control group. Finally, only 32.1% of the studies showed a significant improvement in depression symptoms.

Originality/value

Despite the potential for using social robots in mental health interventions, in the scenario of smart cities, this review showed that their usefulness and effects in improving depressive symptoms in older adults have low internal and external validity. Future studies should consider factors as planning the intervention based on well-established supported therapies, characteristics and needs of the subjects, and the context in which the subjects are inserted.

'I wanted to talk about it, but I couldn't', an H70 focus group study about experiencing depression in early late life

BACKGROUND

Knowledge about experiences of depression among younger-old adults from the general population is limited. The aim was to explore experiences of depression in early late life.

METHODS

Sixteen participants in the population-based Gothenburg H70 Birth Cohort Studies (12 women and 4 men) who had reported a history of depression between ages 60-70 took part in focus group discussions (n = 4). Data were analyzed using focus group methodology.

RESULTS

The analysis resulted in the overall theme 'I wanted to talk about it, but I couldn't'. The participants expressed unmet needs of communication about depression with family, friends, and healthcare staff. Participants wanted to know more about the causes and effects of depression, available treatment options and how to avoid recurrence. Lack of knowledge was a source of frustration; trust in health care providers was diminished. Being retired meant that opportunities for communication with co-workers were no longer available, and this made it harder to break negative thought and behavioral patterns. Being depressed meant losing one's normal self, and participants were grieving this. Thoughts of death and suicide were experienced in solitude; knowing that there was an escape could generate a feeling of comfort and control.

CONCLUSIONS

Younger-old adults have expressed a need to talk about their experiences of depression. They would like to know more about available treatments, potential side effects, and how to avoid recurrence. Care providers also need to be aware there is a need for an existential dialogue about death.