Stability and transition of depression subtypes in late life

The longitudinal patterns of depression subtypes and stressors in depression severity in the Canadian longitudinal study on aging (CLSA)

AIM

The current study aims to characterize the longitudinal patterns of depression subtypes and investigate the associations among the stability of depression subtypes, COVID-19-related stressors, and depression severity.

METHODS

The study utilized data from the Canadian Longitudinal Study on Aging, which is a national, long-term study of Canadian adults aged 45 and older (n = 12,957). Latent profile analysis was used to identify latent depression subtypes. Latent transition analysis was then applied to assess the stability of these subtypes over time. Hierarchical multivariate linear regression was used to explore the relationships among these identified depression subtypes, COVID-19-related stressors, and depression severity among males and females, respectively.

RESULTS

Distinct depression subtypes were identified. Except for atypical depression, other depression subtypes showed greater stability over time. We also found that melancholic depression (B = 9.432) and typical depression (B = 6.677) were strongly associated with depression severity during the pandemic. Health-related stressors (B = 0.840), conflict (B = 3.639), difficulties accessing resources (B = 0.927), separation from family (B = 0.840), and caregiving experience (B = 0.764), were significantly associated with increased depression severity. Sex-specific analyses also revealed differences in the associations between stressors and depression severity between males and females.

CONCLUSIONS

This study contributes valuable insights into the latent clustering of depression subtypes and their stability. Stressors were associated with increased depression severity, with distinct associations observed among males and females. These findings have implications for targeted early interventions and integrated clinical management strategies by providing the evidence base for tailored mental health care during and after the pandemic.

E-health literacy in stroke patients: Latent profile analysis and influencing factors

AIMS

This study sought to explore latent categories of electronic health (e-health) literacy among stroke patients and analyse its influencing factors.

DESIGN

A cross-sectional, descriptive exploratory design with the STROBE reporting checklist was applied.

METHODS

Between July and October 2020, 558 stroke participants from three tertiary care hospitals in Henan Province, China, were recruited using a convenience sampling method. A general information questionnaire and the Electronic Health Literacy Scale were used to collect their socio-demographic information and e-health literacy. Latent profile analysis was used to analyse latent categories of e-health literacy in stroke patients. Multiple logistic regression was used to analyse factors influencing latent categories of e-health literacy in stroke patients.

RESULTS

Three latent categories of e-health literacy existed, including the low e-health literacy group, the low application-high decision-making group and the high literacy-low decision-making group. Multiple logistic regression showed that education level, presence of comorbidities, willingness to interact with people with mental illness, health information sources, frequency of Internet access, frequency of health information inquiry and willingness to receive remote care were predictors of the participants' latent categories of e-health literacy.

CONCLUSION

Three latent categories of e-health literacy in stroke patients exist, and each latent category's characteristics should be considered while developing health education programmes. It is imperative that healthcare providers understand the requirement of creating tailored and efficient health education programmes for various categories of stroke patients to enhance their e-health literacy.

IMPACT

It is imperative to improve Chinese stroke patients' overall e-health literacy. We categorized stroke patients' e-health literacy using advanced LPA. These findings hold implications for healthcare approaches, contributing to the enhancement of stroke patients' e-health literacy, enabling them to apply the acquired e-health information to manage and solve their own health issues.

PATIENT OR PUBLIC CONTRIBUTION

No patient or public contribution.

Depression in Older Adults: Do Current DSM Diagnostic Criteria Really Fit?

OBJECTIVES

The great heterogeneity in symptoms and clinical signs of depression in older adults makes the current diagnostic criteria difficult to apply. This scoping review aims to provide an update on the relevance of each of the diagnostic criteria as defined in the DSM-5.

METHODS

In order to limit the risk of bias inherent in the study selection process, a priori inclusion and exclusion criteria were defined. Articles meeting these criteria were identified using a combination of search terms entered into PubMed, PsycINFO, PsycARTICLES and SocINDEX.

RESULTS

Of the 894 articles identified, 33 articles were selected. This review highlights a different presentation of depression in older adults. Beyond the first two DSM core criteria, some symptoms are more common in older adults: appetite change, sleep disturbance, psychomotor slowing, difficulty concentrating, indecisiveness, and fatigue.

CONCLUSIONS

This review provides an updated description of the clinical expression of depressive symptoms in the older population while highlighting current pending issues.

CLINICAL IMPLICATIONS

Somatic symptoms should be systematically considered in order to improve the diagnosis of depression in older adults, even if, in some cases, they may reflect symptoms of age-related illnesses.

Depression Subtypes in Systolic Heart Failure: A Secondary Analysis From a Randomized Controlled Trial

BACKGROUND

Heart failure (HF) is associated with an elevated risk of morbidity, mortality, hospitalization, and impaired quality of life. One potential contributor to these poor outcomes is depression. Yet the effectiveness of treatments for depression in patients with HF is mixed, perhaps due to the heterogeneity of depression.

METHODS

This secondary analysis applied latent class analysis (LCA) to data from a clinical trial to classify patients with systolic HF and comorbid depression into LCA subtypes based on depression symptom severity, and then examined whether these subtypes predicted treatment response and mental and physical health outcomes at 12 months follow-up.

RESULTS

In LCA of 629 participants (mean age 63.6 ± 12.9; 43% females), we identified 4 depression subtypes: mild (prevalence 53%), moderate (30%), moderately severe (12%), and severe (5%). The mild subtype was characterized primarily by somatic symptoms of depression (e.g., energy loss, sleep disturbance, poor appetite), while the remaining LCA subtypes additionally included nonsomatic symptoms of depression (e.g., depressed mood, anhedonia, worthlessness). At 12 months, LCA subtypes with more severe depressive symptoms reported significantly greater improvements in mental quality of life and depressive symptoms compared to the LCA mild subtype, but the incidence of cardiovascular- and noncardiovascular-related readmissions, and mortality was similar among all subtypes.

CONCLUSIONS

In patients with depression and systolic heart failure those with the LCA mild depression subtype may not meet full criteria for major depressive disorder, given the overlap between HF and somatic symptoms of depression. We recommend requiring depressed mood or anhedonia as a necessary symptom for major depressive disorder in patients with HF.

Meaning in life among nursing students: a latent profile analysis

BACKGROUND

Meaning in life, defined by an individual's understanding and appreciation of life, is a vital aspect of a positive psychological state, that has a significant influence on physical and mental health. Therefore, improving the sense of meaning in life among nursing students has emerged as a crucial concern in nursing education. This study aimed to clarify the profiles and influencing factors of meaning in life among nursing students.

METHODS

A descriptive cross-sectional online survey was conducted among nursing students in China from November 16, 2022, to January 17, 2023. The demographic information questionnaire and the meaning in life questionnaire (MLQ) were used to collect data. Latent profile analysis (LPA) was used to identify groups exhibiting distinct levels of meaning in life. Additionally, univariate analysis and multinominal logistic regression analysis were used to investigate the factors influencing each group. The reporting of this study adhered to the Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) checklist.

RESULTS

A total of 10,583 valid responses were received, and the analysis revealed four distinct profiles. The profiles identified were the medium meaning group (C1, 41.4%), medium fluctuation meaning-no motivation group (C2, 8.7%), lower meaning group (C3, 9.7%), and higher meaning group (C4, 40.2%). The univariate analysis revealed that age, gender, ethnicity, marital status, educational level, grade, university classification, student leadership experience, and political affiliation were factors that influenced the four latent profiles (P < 0.05). The multinomial logistic regression analysis showed that age, gender, ethnicity, education level, and student leadership experience were significant predictors of the various profiles (P < 0.05).

CONCLUSION

There is heterogeneous in meaning in life among nursing students in China. Nursing educators need to provide tailored guidance based on the latent classification characteristics of meaning in life among nursing students, aiming at improving their meaning in life and promoting the development of the nursing workforce.

Stability of the Subtypes of Major Depressive Disorder in Older Adults and the Influence of Mild Cognitive Impairment on the Stability

OBJECTIVES

To assess 1) the longitudinal stability of the atypical, melancholic, combined atypical-melancholic and the unspecified subtypes of major depressive disorder (MDD) according to the diagnostic and statistical manual of mental disorders (DSM -IV) specifiers in older adults, and 2) the effect of mild cognitive impairment (MCI) on the stability of these subtypes.

DESIGN

Prospective cohort study with a 5.1 year-follow-up.

SETTING

Population-based cohort from Lausanne, Switzerland.

PARTICIPANTS

A total of 1,888 participants (mean age: 61.7 years, women: 69.2%) with at least two psychiatric evaluations, one after the age of 65 years.

MEASUREMENTS

Semistructured diagnostic interview to assess lifetime and 12-month DSM-IV Axis-1 disorders at each investigation and neuro-cognitive tests to identify MCI in participants aged 65 years and over. Associations between lifetime MDD status before and 12-month depression status after the follow-up were assessed using multinomial logistic regression. The effect of MCI on these associations was assessed by testing interactions between MDD subtypes and MCI status.

RESULTS

1) Associations between depression status before and after the follow-up were observed for atypical (adjusted OR [95% CI] = 7.99 [3.13; 20.44]), combined (5.73 [1.50; 21.90]) and unspecified (2.14 [1.15; 3.98]), but not melancholic MDD (3.36 [0.89; 12.69]). However, there was a certain degree of overlap across the subtypes, particularly between melancholic MDD and the other subtypes. 2) No significant interactions were found between MCI and lifetime MDD subtypes regarding depression status after follow-up.

CONCLUSION

The strong stability of the atypical subtype in particular highlights the need for identifying this subtype in clinical and research settings, given its well-documented links to inflammatory and metabolic markers.

The Course of Depressive Symptoms Over 36 Months in 696 Newly Admitted Nursing Home Residents

OBJECTIVES

To investigate the course of depressive symptoms in newly admitted nursing home (NH) residents and how resident characteristics were associated with the symptoms. To identify groups of residents following the same symptom trajectory.

DESIGN

An observational, multicenter, longitudinal study over 36 months with 7 biannual assessments.

SETTING AND PARTICIPANTS

Representing 47 Norwegian NHs, 696 residents were included at admission to a NH.

METHODS

Depressive symptoms were assessed with the Cornell Scale for Depression in Dementia (CSDD). We selected severity of dementia, functional impairment, physical health, pain, use of antidepressants, age, and sex as covariates. Time trend in CSDD score was assessed by a linear mixed model adjusting for covariates. Next, a growth mixture model was estimated to investigate whether there were groups of residents following distinct trajectories in CSDD scores. We estimated a nominal regression model to assess whether the covariates at admission were associated to group membership.

RESULTS

There was a nonlinear trend in CSDD score. More severe dementia, a lower level of functioning, poorer physical health, more pain, use of antidepressants, and younger age at admission were associated with higher CSDD scores. Growth mixture model identified 4 groups: (1) persistent mild symptoms (32.6%), (2) persistent moderate symptoms (50.8%), (3) increasing symptoms (5.1%), and (4) severe but decreasing symptoms (11.6%). A lower level of functioning, poorer physical health, more pain, use of antidepressants, and younger age at admission were associated with higher odds for belonging to the severe but decreasing symptoms group compared with the persistent mild symptoms group.

CONCLUSIONS AND IMPLICATIONS

Most NH residents were in trajectory groups with persistent mild or moderate depressive symptoms. Residents with more severe dementia, lower levels of functioning, poor physical health, severe pain, younger age at admittance, and who are using antidepressants should be monitored closely and systematically with respect to depression. Taking actions toward a more personalized treatment for depression in NHs is a priority and should be investigated in future studies.

Heterogenous Subtypes of Late-Life Depression and Their Cognitive Patterns: A Latent Class Analysis

Background

Late-life depression (LLD), characterized by cognitive deficits, is considered heterogeneous across individuals. Previous studies have identified subtypes with diverse symptom profiles, but their cognitive patterns are unknown. This study aimed to investigate the subtypes of LLD and the cognitive profile of each group.

Methods

In total, 109 depressed older adults were enrolled. We performed latent class analysis using Geriatric Depression Scale items as indicators to generate latent classes. We compared the sociodemographic and clinical characteristics with cognitive functions between groups and conducted regression analysis to investigate the association between class membership and variables with significant differences.

Results

Two classes were identified: the "pessimistic" group was characterized by pessimistic thoughts and the "worried" group with a relatively high prevalence of worry symptoms. The two groups did not differ in sociodemographic characteristics. The "pessimistic" group showed a higher rate of past history of depression and lower age of onset. The "worried" group had more physical comorbidities and a higher rate of past history of anxiety. The "pessimistic" group was more impaired in general cognitive function, executive function, information processing speed, and attention. Lower general and executive functions were associated with the membership in the "pessimistic" group.

Conclusions

Subjects with pessimistic symptoms and subjects with a propensity to worry may form two distinct subtypes of late-life depression with different cognitive profiles. Further, the cognitive evaluation of subjects with pessimistic symptoms is of utmost importance.

Changes in depressive symptoms and cognitive impairment in older long-stay nursing home residents in the USA: a latent transition analysis

OBJECTIVES

To longitudinally examine the latent statuses of depressive symptoms and their association with cognitive impairment in older U.S. nursing home (NH) residents.

METHOD

Using Minimum Data Set 3.0, newly-admitted, long-stay, older NH residents with depression in 2014 were identified (n = 88,532). Depressive symptoms (Patient Health Questionnaire-9) and cognitive impairment (Brief Interview of Mental Status) were measured at admission and 90 days. Latent transition analysis was used to examine the prevalence of and the transition between latent statuses of depressive symptoms from admission to 90 days, and the association of cognitive impairment with the statuses at admission.

RESULTS

Four latent statuses of depressive symptoms were identified: 'Multiple Symptoms' (prevalence at admission: 17.3%; 90 days: 13.6%), 'Depressed mood' (20.0%; 19.5%), 'Fatigue' (27.4%; 25.7%), and 'Minimal Symptoms' (35.3%; 41.2%). Most residents remained in the same status from admission to 90 days. Compared to residents who were cognitively intact, those with moderate impairment were more likely to be in 'Multiple Symptoms' and 'Fatigue' statuses; those with severe impairment had lower odds of belonging to 'Multiple Symptoms', 'Depressed Mood', and 'Fatigue' statuses.

CONCLUSION

By addressing the longitudinal changes in the heterogeneous depressive symptoms and the role of cognitive impairment, findings have implications for depression management in older NH residents.