Geographic patterns of implicit age bias and associations with state‐level health outcomes across the United States

Internalized stigma: Social support, coping, psychological distress, and mental well-being among older adults in Ghana

BACKGROUND

Older adults have been found to internalize stigma from society and this has been linked to several variables including social support, coping, psychological distress, and mental well-being. However, there is a dearth of research on how these variables interact with each other to impact the life of older adults.

AIMS

This study employed path analysis to explore social support and coping as boundary conditions and underlying mechanisms in the link between internalized stigma, psychological distress, and mental well-being, among older adults in Ghana.

METHOD

Using a cross-sectional design, the study recruited 167 older adults who responded to standardized questionnaires including The Internalized Stigma of Mental Illness scale, Multidimensional Perceived Social Support Scale, The Brief Coping Inventory, Kessler Distress Scale, and the Warwick-Edinburgh Mental Well-being Scale, to determine levels of internalized stigma, social support, coping strategies, psychological distress, and mental well-being, respectively.

RESULTS

The findings revealed that at low levels of social support, there is a significant and positive correlation between internalized stigma and mental well-being (β = -.36, SE = 0.17, p < .001). Path analysis showed that the relationship between internalized stigma and mental well-being was fully mediated by problem-focused coping (β = .11, p = . 001, 95% CI [0.04, 0.21]), but not psychological distress. Problem-focused coping was also found to have a significant positive correlation with mental well-being but no significant correlation with psychological distress. Conversely, avoidant-focused coping was found to have a significant positive correlation with psychological distress and a significant negative correlation with mental well-being.

CONCLUSIONS

This study revealed the importance of social support and coping to attaining mental well-being among older adults. This study provides insights into the development of tailored interventions aimed at improving social support and problem-focused coping among older Ghanaian adults facing internalized stigma, and it also establishes a base for future research.

How do explicit, implicit, and sociodemographic measures relate to concurrent suicidal ideation? A comparative machine learning approach

INTRODUCTION

Suicide is a leading cause of death, and decades of research have identified a range of risk factors, including demographics, past self-injury and suicide attempts, and explicit suicide cognitions. More recently, implicit self-harm and suicide cognitions have been proposed as risk factors for the prospective prediction of suicidal behavior. However, most studies have examined these implicit and explicit risk factors in isolation, and little is known about their combined effects and interactions in the prediction of concurrent suicidal ideation.

METHODS

In an online community sample of 6855 participants, we used different machine learning techniques to evaluate the utility of measuring implicit self-harm and suicide cognitions to predict concurrent desire to self-harm or die.

RESULTS

Desire to self-harm was best predicted using gradient boosting, achieving 83% accuracy. However, the most important predictors were mood, explicit associations, and past suicidal thoughts and behaviors; implicit measures provided little to no gain in predictive accuracy.

CONCLUSION

Considering our focus on the concurrent prediction of explicit suicidal ideation, we discuss the need for future studies to assess the utility of implicit suicide cognitions in the prospective prediction of suicidal behavior using machine learning approaches.

Demographic patterns in Lyme borreliosis seasonality over 25 years

Lyme borreliosis, the most common vector-borne disease in Europe and North America, is attracting growing concern due to its expanding geographic range. The growth in incidence and geographic spread is largely attributed to climate and land-use changes that support the tick vector and thereby increase disease risk. Despite a wide range of symptoms displayed by Lyme borreliosis patients, the demographic patterns in clinical manifestations and seasonal case timing have not been thoroughly investigated and may result from differences in exposure, immunity and pathogenesis. We analysed 25 years of surveillance data from Norway, supplemented by population demography data, using a Bayesian modelling framework. The analyses aimed to detect differences in case seasonality and clinical manifestations of Lyme borreliosis across age and sex differentiated patient groups. The results showed a bimodal pattern of incidence over age, where children (0-9 years) had the highest incidence, young adults (20-29 years) had low incidence and older adults had a second incidence peak in the ages 70-79 years. Youth (0-19 years) presented with a higher proportion of neuroborreliosis cases and a lower proportion of arthritic manifestations compared to adults (20+ years). Adult males had a higher overall incidence than adult females and a higher proportion of arthritis cases. The seasonal timing of Lyme borreliosis consistently occurred around 4.4 weeks earlier in youth compared to adults, regardless of clinical manifestation. All demographic groups exhibited a shift towards an earlier seasonal timing over the 25-year study period, which appeared unrelated to changes in population demographics. However, the disproportionate incidence of Lyme borreliosis in seniors requires increased public awareness and knowledge about this high-risk group as the population continues to age concurrently with disease emergence. Our findings highlight the importance of considering patient demographics when analysing the emergence and seasonal patterns of vector-borne diseases using long-term surveillance data.

Masquerading their way to authenticity: Does age stigma concealment benefit older women?

As women age they can be subject to both sexism and ageism, and consequently be stereotyped as low in competence and irrelevant despite having a relatively young subjective age. Drawing on theories of stigma, we conducted a survey study of older women (N = 184) with a strong interest in fashion and their visual image. We used template thematic analysis to understand their experiences in relation to their age-changed appearance. Two major themes were identified: unfavourable experiences of ageism and efforts to evade these experiences through attention to appearance. Our participants employed masquerade to conceal or reduce the visible evidence of their age-both to avoid ageism and to align their outward appearance more closely with their inner, felt, authentic selves. We interrogate the benefits and penalties of concealment for a group whose stigmatised condition is dynamic, changing as their appearance grows increasingly dissimilar to societally favoured youthfulness. Masquerade may for this group of women produce more positive than negative outcomes, via effects on felt authenticity.

Suicidality and mood: the impact of trends, seasons, day of the week, and time of day on explicit and implicit cognitions among an online community sample

Decades of research have established seasonality effects on completed and attempted suicides, with rates increasing in spring. Little advancements have been made to explain this phenomenon, with most studies focusing almost exclusively on the number of suicide attempts and deaths. Using more than six years of data collected among a US, UK, and Canadian online community sample (N > 10,000), we used newly developed Prophet forecasting and autoregressive-integrated moving average time-series models to examine the temporal dynamics of explicit and implicit self-harm cognitions. We created three groups (past suicide attempters; suicide ideation and/or non-suicidal self-injury; no previous self-harm, suicidal thoughts, or behaviors). We found a general increase of negative self-harm cognitions across the six years and seasonality effects for mood and desire to die, particularly among those who previously made a suicide attempt. Negative explicit self-harm cognitions peaked in winter (December), with implicit self-harm showing a lagged peak of two months (February). Moreover, daily negative self-harm cognitions consistently peaked around 4-5 am, with implicit cognitions again showing a lagged effect (1-hour). Limitations include the volunteer sample not being representative and the cross-sectional nature of the data being unable to separate between-subject and within-subject structural trends in the time series. Our findings show that negative explicit and implicit cognitions precede the rise in suicidal behaviors in spring. We proposed a conceptual model of seasonal suicide risk that may offer fertile ground for theoretical advancements, including implications for clinical risk assessment and public policies regarding the availability of health services.

The cognitive tenacity of self-directed ageism

Ageism refers to prejudice or discrimination based on a person's age. When ageism is directed at older people, it is unique in two ways: it is socially condoned in a manner that other types of prejudice are not, and the animus is eventually self-directed. Of central interest here is why ageism becomes self-directed in late adulthood, despite its potentially harmful personal costs. We present a cognitive model in which negative ageist beliefs become increasingly accessible and difficult to eliminate owing to broader developmental shifts in mentation. Given that these effects are contingent on our social environment, systemic changes in societal conceptions of age and aging are needed if we are to reduce vulnerability to self-directed ageism.

Reprint of: Community-level age bias and older adult mortality

RATIONALE

As the older adult population increases, understanding the health effects of bias against older adults is increasingly important. Whether structural forms of age bias predict worse health has received limited attention.

OBJECTIVE

We hypothesized that communities with greater age bias would have higher mortality among residents aged 65 and older. We expected the association to be unique to age bias, rather than general bias (i.e., sexual minority and racial bias), and that the age bias-mortality association would be strongest in predominantly White and younger communities.

METHODS

Explicit and implicit attitudes toward older adults (N = 1,001,735), sexual minorities (N = 791,966), and Black Americans (N = 2,255,808) were drawn from Project Implicit. Post-stratification relative to U.S. Census demographics was executed to improve the representativeness of county-level explicit and implicit bias estimates. County older adult mortality, estimated cross-sectionally with and longitudinally relative to bias scores, served as outcomes. Models controlled for relevant county-level covariates (e.g., median age) and included all U.S. counties (N = 3142).

RESULTS

Contrary to hypotheses but consistent with prior work, explicit age bias was cross-sectionally and longitudinally associated with lower mortality, over and above covariates and generalized community bias. The explicit age bias-lower mortality association only emerged in younger counties but did not depend on county ethnic composition. Implicit age bias was unassociated with outcomes. Post-hoc analyses supported that ageist communities may be associated with better health across the lifespan. Explicit age bias predicted lower mortality in young and middle adulthood; better mental health in middle adulthood, but not exercise or self-rated health, mediated the explicit age bias-older adult mortality association.

CONCLUSIONS

Results highlight the uniqueness of older age relative to other stigmatized identities. Further examination of the association of community-level age bias with better health may improve longevity for all communities.

Ageism and late-life mortality: How community matters

AGEISM: the deeply entrenched biases that people hold about old age-is a persistent social problem that intensified during the COVID-19 pandemic. The harmful physical, emotional, and cognitive health consequences of individual-level age bias are well-documented, with most studies operationalizing ageism as an older adult's personal encounters with age discrimination, self-perceptions of their own aging, and internalized negative beliefs about old age. However, the impacts of community-level age bias on older adults' well-being have received less attention. This commentary reviews recent evidence (Kellogg et al.,) showing that county-level explicit age bias is associated with lower mortality rates among older adults, with effects limited to older adults residing in counties with relatively younger populations. Effects were not detected in counties with relatively older populations, or for implicit age bias. These counterintuitive findings require further exploration, including the use of more fine-grained measures of community-level ageism, attention to the role of gentrification in communities, and the development of new measures of structural ageism, drawing on approaches used to study the impacts of structural racism. Data science approaches, including the use of social media data in tandem with mortality data, may reveal how age bias affects older adults. Communities are especially important to older adults, who spend much of their time in areas immediately proximate to their homes. As more individuals age in place, and as federal funding for home-based and community services (HCBS) increases, researchers should identify which community-level characteristics, including age bias, undermine or enhance late-life well-being.

Community-level age bias and older adult mortality

RATIONALE

As the older adult population increases, understanding the health effects of bias against older adults is increasingly important. Whether structural forms of age bias predict worse health has received limited attention.

OBJECTIVE

We hypothesized that communities with greater age bias would have higher mortality among residents aged 65 and older. We expected the association to be unique to age bias, rather than general bias (i.e., sexual minority and racial bias), and that the age bias-mortality association would be strongest in predominantly White and younger communities.

METHODS

Explicit and implicit attitudes toward older adults (N = 1,001,735), sexual minorities (N = 791,966), and Black Americans (N = 2,255,808) were drawn from Project Implicit. Post-stratification relative to U.S. Census demographics was executed to improve the representativeness of county-level explicit and implicit bias estimates. County older adult mortality, estimated cross-sectionally with and longitudinally relative to bias scores, served as outcomes. Models controlled for relevant county-level covariates (e.g., median age) and included all U.S. counties (N = 3142).

RESULTS

Contrary to hypotheses but consistent with prior work, explicit age bias was cross-sectionally and longitudinally associated with lower mortality, over and above covariates and generalized community bias. The explicit age bias-lower mortality association only emerged in younger counties but did not depend on county ethnic composition. Implicit age bias was unassociated with outcomes. Post-hoc analyses supported that ageist communities may be associated with better health across the lifespan. Explicit age bias predicted lower mortality in young and middle adulthood; better mental health in middle adulthood, but not exercise or self-rated health, mediated the explicit age bias-older adult mortality association.

CONCLUSIONS

Results highlight the uniqueness of older age relative to other stigmatized identities. Further examination of the association of community-level age bias with better health may improve longevity for all communities.

The Role of Country-Level Availability and Generosity of Healthcare Services, and Old-Age Ageism for Missed Healthcare during the COVID-19 Pandemic Control Measures in Europe

Objectives: The effects of the COVID-19 outbreak on non-COVID-19-related healthcare need further investigation. Methods: Using the Survey of Health, Ageing and Retirement in Europe's COVID-19 module (2020) (N = 57,025), country-level data from the European Social Survey (2008) and OECD (2020), and logistic regressions, this study examines predictors of older Europeans' forgone, postponed, and denied healthcare during the pandemic. Results: Country-level availability of physicians, healthcare systems' generosity, and beliefs that older persons burden healthcare systems all increased forgone healthcare. Healthcare system generosity increased postponed and denied healthcare. Greater medical resources decreased denied healthcare. Furthermore, missed healthcare varied by individual-level gender (higher rates among women), age, education, and health. Discussion: This study reveals predictors of missed healthcare during the pandemic. To decrease unintended health consequences of a pandemic, both individual-level determinants, such as gender and health, and contextual-level determinants, such as healthcare systems' characteristics, should be considered in research and practice.

The Significance of Race/Ethnicity and Income in Predicting Preoperative Patient-Reported Outcome Measures in Primary Total Joint Arthroplasty

BACKGROUND

Utilization of total joint arthroplasty (TJA) by minorities is disproportionately low compared to Whites. Contributing factors include poorer outcomes, lower expectations, and decreased access to care. This study aimed to evaluate if race and income were predictive of preoperative patient-reported outcome measures (PROMs) and the likelihood of achieving the minimal clinically important difference (MCID) following TJA.

METHODS

We retrospectively reviewed 1,371 patients who underwent primary TJA between January 2018 and March 2021 in a single healthcare system. Preoperative and postoperative PROM scores were collected for Patient-Reported Outcomes Measurement Information System (PROMIS) Mental Health, PROMIS Physical Function (PF10a), and either Knee injury and Osteoarthritis Outcome Score (KOOS) or Hip disability and Osteoarthritis Outcome Score (HOOS). Demographic and comorbidity data were included as explanatory variables. Multivariable regression was used to analyze the association between predictive variables and PROM scores.

RESULTS

Mean preoperative PROM scores were lower for non-Whites compared to Whites. Increased median household income was associated with higher preoperative PROM scores. Non-White race was associated with lower PROMIS Mental Health and KOOS, but not PF10a or HOOS scores. Only non-White race was associated with a decreased likelihood of achieving MCID for PF10a. Neither race nor income was predictive of achieving MCID for KOOS and HOOS.

CONCLUSION

Non-White race/ethnicity and lower income were associated with lower preoperative PROMs prior to primary TJA. Continued research is necessary to identify the causes of this discrepancy and correct this disparity.

Nephrologist referrals of elderly CKD patients in Singapore: A cross-sectional study

Background

Chronic kidney disease (CKD) is common in the elderly population. By 2035, approximately one-quarter of Singapore residents are expected to have CKD. Many of these patients are not referred to nephrologists.

Aim

We aimed to compare the characteristics of elderly (≥ 65 years old) patients with stage 3B CKD and above in the referral and non-referral groups.

Design and settings

A cross-sectional study in the primary care organisation National University Polyclinics (NUP), Singapore.

Method

Retrospective data were extracted from the electronic health records of CKD patients (≥ 65 years old) with stage 3B CKD and above.

Results

From 1 January to 31 December 2018, a total of 1,536 patients aged 65 years or older were diagnosed with stage 3B CKD or above (non-referral group =1,179 vs. referral group =357). The mean patient age in the non-referral group (78.3 years) was older than that in the referral group (75.9 years) (P<0.001). Indian elderly patients were referred more compared to their Chinese counterparts (P=0.008). The non-referral group was prescribed significantly less fibrate, statins, insulin, sulfonylureas, dipeptidyl peptidase-4 inhibitors, and antiplatelet than the referral group (P<0.05), but only the difference in fibrates remained significant on subsequent multivariate analysis.

Conclusions

This study demonstrates that there is a considerable number of elderly CKD patients exclusively managed in the primary care setting (n = 1,179) and that referrals primarily depend on demographic factors, namely age and ethnicity, rather than medical determinants of CKD severity or case complexity.

Regional Implicit Bias Does Not Account for Racial Disparity in Total Joint Arthroplasty Utilization

BACKGROUND

Racial disparities surrounding the utilization of total hip and total knee arthroplasty (THA, TKA) are well documented. The Implicit Association Test (IAT) is a validated tool used to measure implicit and explicit bias. The purpose of this study is to evaluate if variations in IAT scores by geographical region in the United States (US) correspond with regional variations in THA and TKA utilization by blacks compared to whites.

METHODS

Data from the US Census and National Inpatient Sample from 2012 to 2014 were used to calculate THA and TKA utilization rates among Medicare-aged blacks and whites. Data were aggregated by US Census Bureau Division. Regional implicit bias was assessed by calculating a weighted average of IAT scores for each division.

RESULTS

Across all geographic regions and years, the surveyed population demonstrated an implicit bias favoring whites over blacks. The population adjusted ratio of white-to-black utilization of THA and TKA by geographic division varied between 0.86-1.85 and 0.87-2.01, respectively. The difference in utilization between geographic divisions reached statistical significance (P < .001). No correlation was found between the IAT scores and race-specific utilization ratios among geographic divisions.

CONCLUSION

Implicit bias as measured by regional IAT did not reflect THA and TKA utilization disparities. The racial disparity in utilization of THA and TKA significantly varied between divisions. The observed disparity was greater in divisions with a relatively higher proportion of blacks. To the authors' knowledge, this is the first study to evaluate the impact of implicit bias on utilization of THA and TKA.

Who is more likely to ignore experts' advice related to COVID-19?

Failing to adhere to COVID-19 experts' advice could have devastating consequences for individuals and communities. Here we determine which demographic factors can impact trust in COVID-19 experts. Participants consisted of more than 1875 online volunteers, primarily from the U.S. Survey data were collected before and after the first peak of the COVID-19 outbreak in the U.S. (28th of March-15th of May 2020). We consistently find that participants with a lower perceived socio-economic status, social conservatives, individualists, and participants who are less worried about COVID-19 are significantly more likely to support individuals who ignore the goverment's, scientists', medical professionals' COVID-19 advice. Regarding race, Black participants consistently (and Hispanics to a lesser degree) were more likely to support individuals who ignore the three expert groups relative to Whites. All these findings generalized to weaker trust towards public policy decision experts. Asian and other racial groups' trust was consistently lower than Whites, but primarily numerically, not statistically. Age and gender showed weak or inconsistent results respectively. We provide an enhanced understanding of the demographic factors that can result in individuals/groups ignoring COVID-19 experts. Lack of compliance could increase the transmission risks of the virus. Therefore, non-partisan campaigns that target individuals/groups who distrust COVID-19 experts will likely reduce COVID-19 related deaths. Increasing expert representatives' racial diversity may also increase trust among racial minorities.