The impact of loneliness and social isolation on health state utility values: a systematic literature review

A Systematic Review of Artificial Intelligence Used to Predict Loneliness, Social Isolation, and Drug Use During the COVID-19 Pandemic

This systematic literature review evaluates the role of machine learning, artificial intelligence (AI), and social determinants of health (SDOH) in identifying loneliness during the COVID-19 pandemic. By examining various studies and articles through a comprehensive search of databases EBSCOhost, Medline Complete, Academic Search Complete, Directory of Open Access Journals, and Complementary Index, the research team sought to discern consistent themes and patterns. We identified four constructs central to understanding the impact of the pandemic on societal well-being: (1) the prediction of compliance with COVID-19 measures, (2) the prediction of loneliness and its effects, (3) the prediction of well-being and social inclusion, and (4) the prediction of drug use. Within these constructs, prevalent themes related to opioid overdose, stress levels, mental health, well-being, and cognitive decline emerged. The adherence to the PRISMA 2020 checklist has resulted in a PRISMA flow diagram that categorizes the selected literature. The findings of this review, including the proportion of studies predicting various attributes related to loneliness, demonstrate the critical intersections between machine learning, AI, SDOH, and the psychosocial phenomenon of loneliness amidst a global health crisis. The review results provide a summary of the occurrences and predictive percentages of each construct as determined by the literature, contributing to a nuanced understanding of the pandemic's multifaceted impact on loneliness, social isolation, and drug use. Using AI to predict these constructs has remarkable capabilities in identifying individuals at risk and facilitating timely interventions to mitigate adverse outcomes and promote mental health resilience in the face of challenges such as the COVID-19 pandemic. Moving forward, future research is warranted to refine AI algorithms, validate predictive models and utilize AI-based interventions in healthcare and mental health services while ensuring data security, and individuals' privacy.

The impact of loneliness on mental and physical health outcomes: An umbrella review

Loneliness and related constructs associated with isolation are public health problems with increasing prevalence. The aim of this umbrella was to collate and grade evidence analyzing actual and subjective loneliness as a health risk factor. Following prospective registration, a systematic search was conducted in Pubmed, Embase, Scopus, Web of Sciences, psycoINFO and Cochrane Library until August 2023. Systematic reviews assessing the association between actual and subjective loneliness with adverse health outcomes were selected. Risk of bias was evaluated using AMSTAR-2 tool. Data were tabulated and synthesis was narrative. A total of 13 systematic reviews was selected (four included meta-analysis). The methodological quality was critically low in 10 reviews (76.92%) and low in 3 (23.08%). Results showed that loneliness was related to poor well-being and increase the risk of negative mental and physical health. The available data suggested but did not allow the confirmation of a causal association. Most constructs of loneliness seem to be related to mental and physical health conditions. A preventive strategy ought to be recommended, especially for vulnerable populations.

The association between loneliness with health service use and quality of life among informal carers in Australia

OBJECTIVE

The demanding nature of caregiving and limited social support can lead to informal carers experiencing loneliness, which can impact their well-being and overall health service use (HSU). The study aims to examine the association between loneliness with HSU and Health state utility values among informal carers in Australia.

METHODS

Data were derived from three waves (2009, 2013, and 2017) of the nationally representative longitudinal Household Income and Labour Dynamics of Australia (HILDA) survey, focusing on adult informal carers. Outcome measures included visits to the General Practitioner, the number of hospital admissions, and the SF-6D score. Generalized Estimating Equations (GEE) analysis was conducted to explore the associations between loneliness and HSU, as well as loneliness and utility values (based on SF-6D) while adjusting for age, sex, education, marital status, income, and physical/mental health conditions.

RESULTS

After controlling for covariates, lonely carers reported lower utility values (IRR = 0.91, 95%CI [0.89, 0.93], p < 0.001) compared to non-lonely carers. Lonely carers reported a higher number of GP visits (IRR = 1.18, 95% CI [1.04, 1.36], p < 0.05) as well as a higher likelihood of visiting specialists (AOR = 1.31, p = 0.046) and hospital doctors (AOR = 1.42, p = 0.013) compared to the non-lonely carers.

CONCLUSIONS

The findings of this study highlight the relationship between loneliness on both healthcare utilization and carers' overall well-being. Addressing loneliness through targeted interventions and social support systems can help improve health outcomes and potentially reduce the overall healthcare costs among informal carers in Australia.

Exploring the Comparability Between EQ-5D and the EQ Health and Wellbeing in the General Australian Population

OBJECTIVES

The EQ Health and Wellbeing (EQ-HWB) is a novel measure that conceptually overlaps with the 5-level EQ-5D (EQ-5D-5L) while capturing broader dimensions of health and well-being. This study aimed to explore the extent to which the EQ-HWB and EQ-5D-5L capture overlapping or complementary constructs and to explore the discriminative ability of the EQ-HWB Short version (EQ-HWB-S) as a multiattribute utility instrument in the Australian setting.

METHODS

A secondary analysis of data from a nationally representative cross-sectional survey of 2002 Australian adults was performed. The survey included socioeconomic questions and health characteristics and the EQ-HWB and EQ-5D-5L instruments. Convergent and known-group validity were evaluated through Spearman rank correlation and multivariable regression analyses, respectively. An exploratory factor analysis was also performed to explore the underlying constructs of the 2 measures.

RESULTS

Correlation coefficients varied from moderate to strong (rs ≥ 0.40) between the EQ-5D-5L and the corresponding EQ-HWB dimensions (all P < .001). Based on the exploratory factor analysis, both instruments measure similar underlying constructs, with the EQ-HWB capturing broader aspects of well-being. The known-group analysis demonstrated the relative discriminative ability of the EQ-HWB-S in capturing broader aspects of health and well-being.

CONCLUSIONS

The EQ-HWB was at least moderately correlated with the EQ-5D-5L in overlapping domains/dimensions and demonstrated greater sensitivity in participants with mental health problems versus the EQ-5D-5L. Our findings support future research exploring the value of the EQ-HWB-S as a multiattribute utility instrument for the general Australian population.

Factors Related to the Need for Informal Care Among Community-Dwelling Older Adults in Chile

PURPOSE

To identify factors contributing to the need for informal care among community-dwelling older adults with functional impairment in Chile.

METHOD

A secondary data analysis was conducted using cross-sectional data from 540 Chilean older adults aged ≥60 years (mean age = 72.2 years, SD = 6.22 years).

RESULTS

Informal care need was reported by 24.3% (n = 131) of participants. Among the variables that most influenced the need for informal care among older adults were hospitalization in the past 1 year, functionality, comorbidities, and multidimensional frailty (all p < 0.05).

CONCLUSION

This study identified factors that clinicians and nurses should be aware of when caring for this population to prevent or manage the need for informal care. [Journal of Gerontological Nursing, 50(2), 43-52.].

Extending the EQ-5D: the case for a complementary set of 4 psycho-social dimensions

OBJECTIVES

The EQ-5D is the most widely applied preference-based health-related quality of life measure. However, concerns have been raised that the existing dimensional structure lacks sufficient components of mental and social aspects of health. This study empirically explored the performance of a coherent set of four psycho-social bolt-ons: Vitality; Sleep; Personal relationships; and Social isolation.

METHODS

Cross-sectional surveys were conducted with online panel members from five countries (Australia, Canada, Norway, UK, US) (total N = 4786). Four bolt-ons were described using terms aligned with EQ nomenclature. Latent structures among all nine dimensions are studied using an exploratory factor analysis (EFA). The Shorrocks-Shapely decomposition analyses are conducted to illustrate the relative importance of the nine dimensions in explaining two outcome measures for health (EQ-VAS, satisfaction with health) and two for subjective well-being (the hedonic approach of global life satisfaction and an eudemonic item on meaningfulness). Sub-group analyses are performed on older adults (65 +) and socially disadvantaged groups.

RESULTS

Strength of correlations among four bolt-ons ranges from 0.34 to 0.49. As for their correlations with the EQ-5D dimensions, they are generally much less correlated with four physical health dimensions than with mental health dimensions (ranged from 0.21 to 0.50). The EFA identifies two latent factors. When explaining health, Vitality is the most important. When explaining subjective well-being, Social isolation is second most important, after Anxiety/depression.

CONCLUSION

We provide evidence that further complementing the current EQ-5D-5L health state classification system with a coherent set of four bolt-on dimensions that will fill its psycho-social gap.

The effects of social isolation stress and discrimination on mental health

Social isolation and discrimination are growing public health concerns associated with poor physical and mental health. They are risk factors for increased morbidity and mortality and reduced quality of life. Despite their detrimental effects on health, there is a lack of knowledge regarding translation across the domains of experimental research, clinical studies, and real-life applications. Here, we review and synthesize evidence from basic research in animals and humans to clinical translation and interventions. Animal models indicate that social separation stress, particularly in early life, activates the hypothalamic-pituitary-adrenal axis and interacts with monoaminergic, glutamatergic, and GABAergic neurotransmitter systems, inducing long-lasting reductions in serotonin turnover and alterations in dopamine receptor sensitivity. These findings are of particular importance for human social isolation stress, as effects of social isolation stress on the same neurotransmitter systems have been implicated in addictive, psychotic, and affective disorders. Children may be particularly vulnerable due to lasting effects of social isolation and discrimination stress on the developing brain. The effects of social isolation and loneliness are pronounced in the context of social exclusion due to discrimination and racism, during widespread infectious disease related containment strategies such as quarantine, and in older persons due to sociodemographic changes. This highlights the importance of new strategies for social inclusion and outreach, including gender, culture, and socially sensitive telemedicine and digital interventions for mental health care.