Association Between Subjective Cognitive Decline and Social and Emotional Support in US Adults

Speech Emotion Recognition in People at High Risk of Dementia

Background and Purpose

The emotions of people at various stages of dementia need to be effectively utilized for prevention, early intervention, and care planning. With technology available for understanding and addressing the emotional needs of people, this study aims to develop speech emotion recognition (SER) technology to classify emotions for people at high risk of dementia.

Methods

Speech samples from people at high risk of dementia were categorized into distinct emotions via human auditory assessment, the outcomes of which were annotated for guided deep-learning method. The architecture incorporated convolutional neural network, long short-term memory, attention layers, and Wav2Vec2, a novel feature extractor to develop automated speech-emotion recognition.

Results

Twenty-seven kinds of Emotions were found in the speech of the participants. These emotions were grouped into 6 detailed emotions: happiness, interest, sadness, frustration, anger, and neutrality, and further into 3 basic emotions: positive, negative, and neutral. To improve algorithmic performance, multiple learning approaches were applied using different data sources-voice and text-and varying the number of emotions. Ultimately, a 2-stage algorithm-initial text-based classification followed by voice-based analysis-achieved the highest accuracy, reaching 70%.

Conclusions

The diverse emotions identified in this study were attributed to the characteristics of the participants and the method of data collection. The speech of people at high risk of dementia to companion robots also explains the relatively low performance of the SER algorithm. Accordingly, this study suggests the systematic and comprehensive construction of a dataset from people with dementia.

Decrements in Both Physical and Cognitive Function Are Associated With a Higher Symptom Burden in Oncology Patients

OBJECTIVES

Physical and cognitive function are two of the most important patient-reported outcomes. In oncology patients receiving chemotherapy (N = 1331), purposes were to identify subgroups of patients with distinct joint physical and cognitive function profiles and evaluate for differences in demographic and clinical characteristics, severity of common symptoms, and quality of life outcomes.

DATA SOURCES

Measures of physical and cognitive functions were obtained six times over two cycles of chemotherapy. All of the other measures were done prior to the second or third cycle of chemotherapy. Latent profile analysis was done to identify the distinct joint physical and cognitive function profiles. Differences among the profiles were evaluated using parametric and nonparametric tests.

CONCLUSION

Five distinct profiles were identified (ie, Very Low Physical and Low Cognitive Function [18.4%; Both Low], Low Physical and High Cognitive Function [19.8%], Moderate Physical and Low Cognitive Function [26.7%], Changing Physical and Cognitive Function [5.4%], and Normal Physical and Cognitive Function [29.7%]). Patients in the Both Low class had the highest symptom burden and the poorest quality of life. Over 70% of the sample had moderate to severe decrements in one or both of these extremely important patient outcomes.

IMPLICATIONS FOR NURSING PRACTICE

Clinicians need to assess for both physical and cognitive function using simple subjective and objective measures.

The Built Environment and Social and Emotional Support among Rural Older Adults: The Case for Social Infrastructure and Attention to Ethnoracial Differences

Social and emotional support (SaES) is essential for older adult mental health and is shaped by individual-level factors and the built environment. However, much of the focus on the built environment, and specifically social infrastructure - the physical places that facilitate social interaction and social tie formation - relies heavily on urban settings or samples with limited diversity. Consequently, there is little understanding if social infrastructure matters for the SaES of older adults in rural America, and across race and ethnicity. Therefore, we use social cohesion as a conceptual lens and the community gerontology framework to determine if availability of social infrastructure is associated with SaES among older adults in rural America and if this relationship varies across race and ethnicity. Using data from 110,850 rural older adults from the Behavioral Risk Factors Surveillance System and data from the National Neighborhood Data Archive, we show that among rural ethnoracial minority older adults, higher densities of social infrastructure are associated with higher SaES. This is not true for rural non-Hispanic White older adults. Results highlight the importance of accounting for both social infrastructure as part of the built environment and heterogeneity across race and ethnicity in studies that examine older adult mental and emotional health.

Symptom profiles and their influencing factors among people with subjective cognitive decline: a secondary analysis of cross-sectional data from the 2019 Korea Community Health Survey using latent class analysis

OBJECTIVE

Subjective cognitive decline, self-perceived cognitive deterioration without objective impairment, is becoming a vital health indicator, especially due to its intermediate stage between normal function and mild cognitive impairment. Cognitive decline often coexists with various symptoms that may interact with each other, serve as prognostic indicators and influence the progression of cognitive decline. This study aims to identify symptom clusters among individuals with subjective cognitive decline, using latent class analysis, and to identify factors affecting these symptom clusters, offering insights into understanding and potentially preventing cognitive decline progression.

DESIGN AND SETTING

A secondary data analysis of the nationally representative cross-sectional data obtained from the 2019 Korea Community Health Survey.

OUTCOMES

We performed latent class analysis using six symptoms (pain, sleep deprivation, depression, fatigue, restlessness and apathy) to determine the distinct symptom clusters. After selecting the best latent class model, we identified factors influencing those symptom clusters using multinomial logistic regression analyses.

RESULTS

We found that a three-latent-class model best fitted the data: a low symptom-burden group (39.9%), a moderate symptom-burden group (44.8%) and a high symptom-burden group (15.3%). Male gender, higher age, higher perceived health status and lower perceived stress status, were strongly associated with lesser odds of being in the moderate (OR: 0.37 (95% CI: 0.33 to 0.41)) to OR: 2.20 (95% CI: 2.03 to 2.39)) and high symptom-burden groups (OR: 0.18 (95% CI: 0.15 to 0.21)) to OR: 8.53 (95% CI: 7.68 to 9.49)) as compared with being in the low symptom-burden group.

CONCLUSION

Findings may contribute to improving clinical practitioners' understanding of the unique symptom patterns experienced by people with subjective cognitive decline and their influencing factors. Furthermore, we recommend that formal caregivers screen and manage prevalent symptoms considering the factors affecting the symptoms of people with subjective cognitive decline in clinical practice.

Functional social support and cognitive function in middle- and older-aged adults: a systematic review of cross-sectional and cohort studies

BACKGROUND

Intact cognitive function is crucial for healthy aging. Functional social support is thought to protect against cognitive decline. We conducted a systematic review to investigate the association between functional social support and cognitive function in middle- and older-aged adults.

METHODS

Articles were obtained from PubMed, PsycINFO, Sociological Abstracts, CINAHL, and Scopus. Eligible articles considered any form of functional social support and cognitive outcome. We narratively synthesized extracted data by following the Synthesis Without Meta-Analysis (SWiM) guidelines and assessed risk of bias using the Newcastle-Ottawa Scale (NOS).

RESULTS

Eighty-five articles with mostly low risk-of-bias were included in the review. In general, functional social support-particularly overall and emotional support-was associated with higher cognitive function in middle- and older-aged adults. However, these associations were not all statistically significant. Substantial heterogeneity existed in the types of exposures and outcomes evaluated in the articles, as well as in the specific tools used to measure exposures and outcomes.

CONCLUSIONS

Our review highlights the role of functional social support in the preservation of healthy cognition in aging populations. This finding underscores the importance of maintaining substantive social connections in middle and later life.

SYSTEMATIC REVIEW REGISTRATION

Rutter EC, Tyas SL, Maxwell CJ, Law J, O'Connell ME, Konnert CA, Oremus M. Association between functional social support and cognitive function in middle-aged and older adults: a protocol for a systematic review. BMJ Open;10(4):e037301. https://doi.org/10.1136/bmjopen-2020-037301.

Relationship among number of close friends, subclinical geriatric depression, and subjective cognitive decline based on regional homogeneity of functional magnetic resonance imaging data

The relationship between geriatric depression and dementia has been widely debated, and the neurological mechanisms underlying subjective cognitive decline (SCD) associated with social relationships remain elusive. Subclinical geriatric depression (SGD) is common in patients with SCD, and close friends (CFs) have a great influence on a person's social life. Studies have proven that communication or leisure activities with CFs can improve the cognitive performance of elderly. However, it remains unclear whether the engagement of specific brain regions mediates having CFs, SGD, and SCD. In this study, we aimed to assess the association between social relationships (that is, CFs), SGD, and SCD from the perspective of brain function. We examined the data of 66 patients with SCD and 63 normal controls (NC). Compared with NC, SGD was significantly inversely correlated with the number of CFs in the SCD group. We calculated regional homogeneity (ReHo) of functional magnetic resonance imaging (MRI) data of each subject. At a corrected threshold, the right occipital gyrus (SOG.R) and right fusiform gyrus (FFG.R) exhibited positive correlation with SGD in patients with SCD. Mediation analyses to query the inter-relationships between the neural markers and clinical variables exhibited a best fit of the model with CFs → FFG.R → SGD → SOG.R → SCD. These findings suggested a pathway whereby social relationships alter the function of specific brain regions, and SGD may be an early symptom of SCD. We observed that the FFG.R mediate social relationships and SGD, and the abnormality of the SOG.R may be a key factor in the SCD caused by depression. Moreover, a greater number of CFs may reduce the risk of developing SGD.

The Moderating Role of Social Support in the Relationship between Poor Mental Health and Excessive Alcohol Consumption: A Gender-Specific Analysis

Background: Social support can potentially attenuate the positive relationship between poor mental health and excessive drinking. The present study tried to understand: (1) whether there is a gender-specific relationship between poor mental health and excessive drinking; and (2) if and how social support moderates the relationship between poor mental health and excessive drinking. Methods: We analyzed the data from 2016 Behavioral Risk Factor Surveillance System (BRFSS; N = 33,705). Weighted data were stratified by gender and controlled for demographic variables. We assessed poor mental health and social support as correlates of heavy and binge drinking, followed by analyzing the moderation effect of social support X poor mental health interaction terms. Results: Poor mental health is linked with excessive drinking across genders. The interaction analysis shows that social support moderates the effect of ever having a poor mental health day in men's heavy drinking, but the interaction term is not significant in all other excessive drinking models, suggesting that social support may not buffer the negative impact of poor mental health on problem drinking, particularly among women. Conclusion: Individuals with greater mental health challenges are more likely to drink hazardously, regardless of gender. Those who have low level of social support and poor mental health, particularly men, are at risk for heavy drinking. Given the majority of the interaction results is not significant, the study provides limited support for the buffering role of social support between poor mental health and problem drinking.

Social Support and Cognitive Impairment: Results from a Portuguese 4-Year Prospective Study

(1) Background: In an ageing society, social relationships may benefit cognitive performance with an impact on the health of older people. This study aims to estimate the effect of different social support sources on the risk of cognitive impairment in a sample of older Portuguese people. (2) Methods: From the Portuguese EpiPorto cohort study, we followed a sample of participants with 60 to 85 years (N = 656) between 2009 and 2015 (4.63 mean years of follow-up). The participants’ perception of social support from family, friends and significant others was evaluated. Cox’s regression models were used to investigate the association between this and sociodemographic variables. (3) Results: It was found that social support from friends reduces the risk of cognitive impairment. Men, participants aged 60 to 64 and those not married have a lower risk of cognitive impairment after adjusting for other variables. Participants between 80 and 85 years old (p = 0.021), those with less than four years of education (p < 0.001), and those with cognitive impairment (p = 0.007) have perception of less social support from friends. (4) Conclusions: A social support network from friends reduces the risk of cognitive impairment for older people.