Social and general cognition are uniquely associated with social connectedness in later life.

The mechanisms by which older adults maintain large, complex social networks are not well understood. Prior work has primarily focused on general cognitive ability (e.g., executive function, episodic memory), largely overlooking social cognition-the ability to process, store, and remember social information. Because social cognition plays a key role in navigating social interactions and is distinct from general cognition, we examined whether general and social cognition uniquely predicted the nature of older adults' personal social networks. Our study leveraged comprehensive measures of general cognition (executive function, episodic memory), social cognition (face memory and dynamic measures of cognitive and affective theory of mind), and a rigorous measure of personal social networks from 143 community-dwelling older adults. We found that, when modeled together and controlling for sociodemographic variables, only executive function and dynamic cognitive theory of mind positively predicted having social networks with relatively unfamiliar, loosely connected others, accounting for 17% of the unique variance in older adults' social connectedness. Interestingly, having a social network comprised primarily of close, tightly knit relationships was negatively associated with affective theory of mind performance. Findings are discussed in the context of the social-cognitive resource framework-which suggests that social cognition may be more engaged in relatively unfamiliar, versus close, interactions. Specifically, our results show that social-cognitive processes may be relatively automatic for individuals whose primary social relationships are very close but may be more strongly engaged for individuals whose interactions include at least some relatively less close relationships. (PsycInfo Database Record (c) 2024 APA, all rights reserved).

Mixed Methods for Research on Support Networks of People Experiencing Chronic Illness and Social Marginalization.

Substantial research has focused on how social networks help individuals navigate the illness experience. Sociologists have begun to theorize beyond the binary of strong and weak social network ties (e.g., compartmental, elastic, and disposable ties), citing the social, economic, and health conditions that shape their formation. However, limited research has employed mixed social network methods, which we argue is especially critical for examining the "non-traditional" social support networks of marginalized individuals. We employ quantitative social network methods (i.e., the egocentric network approach) in addition to in-depth interviews and observations, with a novel tool for capturing network data about social groups, to surface these kinds of supportive relationships. Using the case of "nameless ties"-non-kin, non-provider ties who were unidentifiable by given name or were grouped by context or activity rather than individually distinguished-we show how mixed social network methods can illuminate supporters who are commonly overlooked when only using traditional social network analysis. We conclude with a proposal for mixed methods and group alter approaches to successfully observe liminal support ties that is ideal for research about individuals experiencing chronic disability, poverty, housing insecurity, and other forms of social marginalization.

Detecting Variation in Clinical Practice Patterns for Geriatric Trauma Care Using Social Network Analysis.

OBJECTIVE: To characterize hospital-level professional networks of physicians caring for older trauma patients as a function of trauma patient age distribution. BACKGROUND: The causal factors associated with between-hospital variation in geriatric trauma outcomes are poorly understood. Variation in physician practice patterns reflected by differences in professional networks might contribute to hospital-level differences in outcomes for older trauma patients. METHODS: This is a population-based, cross-sectional study of injured older adults (age 65 or above) and their physicians from January 1, 2014, to December 31, 2015, using Health Care Cost and Utilization Project inpatient data and Medicare claims from 158 hospitals in Florida. We used social network analyses to characterize the hospitals in terms of network density, cohesion, small-worldness, and heterogeneity, then used bivariate statistics to assess the relationship between network characteristics and hospital-level proportion of trauma patients who were aged 65 or above. RESULTS: We identified 107,713 older trauma patients and 169,282 patient-physician dyads. The hospital-level proportion of trauma patients who were aged 65 or above ranged from 21.5% to 89.1%. Network density, cohesion, and small-worldness in physician networks were positively correlated with hospital geriatric trauma proportions ( R =0.29, P <0.001; R =0.16, P =0.048; and R =0.19, P <0.001, respectively). Network heterogeneity was negatively correlated with geriatric trauma proportion ( R =0.40, P <0.001). CONCLUSIONS: Characteristics of professional networks among physicians caring for injured older adults are associated with the hospital-level proportion of trauma patients who are older, indicating differences in practice patterns at hospitals with older trauma populations. Associations between interspecialty collaboration and patient outcomes should be explored as an opportunity to improve the treatment of injured older adults.

Social Networks, the COVID-19 Pandemic, and Emerging Adults' Mental Health: Resiliency Through Social Bonding and Cohesion.

Objectives. To assess how personal social network characteristics moderated mental health declines during the COVID-19 pandemic in emerging adults compared with other age groups. Methods. The Person to Person Health Interview Study, a representative, probability-based cohort study (n = 2485) in Indiana, collected data through face-to-face (baseline) and phone (follow-up) interviews before and during the pandemic. We used survey-weighted growth curve models to examine network effects on computer-adaptive testing measures of depression and anxiety severity. Results. Respondents reported significantly increased depression and anxiety in 2021, which returned almost to baseline levels for most age groups by 2022 (P < .001). Stronger ties to others and more interconnected ties were significantly associated with lower depression (B = -0.112 [P < .05]; B = -0.086 [P < .001]) and anxiety (B = -0.101 [P < .05]; B = -0.063 [P < .01]) severity across the pandemic. Interaction models revealed disproportionate protective effects of network characteristics on depression (B = -0.456 [P < .001]; B = -0.268 [P < .001]) and anxiety (B = -0.388 [P < .001]; B = -0.284 [P < .001]) for emerging adults. Conclusions. Cohesive and affectively strong personal networks promote resiliency to common mental health challenges during periods of crisis, particularly for emerging adults whose social roles and relationships were disrupted during a critical period of development. (Am J Public Health. 2024;114(S3):S258-S267. https://doi.org/10.2105/AJPH.2023.307426).

Associations Between Social Network Characteristics and Brain Structure Among Older Adults.

INTRODUCTION: Social connectedness is associated with slower cognitive decline among older adults. Recent research suggests that distinct aspects of social networks may have differential effects on cognitive resilience, but few studies analyze brain structure. METHODS: This study includes 117 cognitively impaired and 59 unimpaired older adults. The effects of social network characteristics (bridging/bonding) on brain regions of interests were analyzed using linear regressions and voxel-wise multiple linear regressions of gray matter density. RESULTS: Increased social bridging was associated with greater bilateral amygdala volume and insular thickness, and left frontal lobe thickness, putamen, and thalamic volumes. Increased social bonding was associated with greater bilateral medial orbitofrontal and caudal anterior cingulate thickness, as well as right frontal lobe thickness, putamen, and amygdala volumes. DISCUSSION: The associations between social connectedness and brain structure vary depending on the types of social enrichment accessible through social networks, suggesting that psychosocial interventions could mitigate neurodegeneration. HIGHLIGHTS: Distinct forms of social capital are uniquely linked to gray matter density (GMD). Bridging is associated with preserved GMD in limbic system structures. Bonding is associated with preserved GMD in frontal lobe regions. Bridging is associated with increased brain reserve in sensory processing regions. Bonding is associated with increased brain reserve in regions of stress modulation.

Pandemic Precarity: COVID-19's Impact on Mexican and Central American Immigrant Families.

Objective: The study examines the association of gender, parenthood, and marriage with reports of perceived pandemic precarity among Mexican and Central American immigrants during the COVID-19 pandemic (Fall 2020) to understand predictors of vulnerability in periods of crisis. Background: Latinos/as, immigrants, parents, and women have faced significant challenges during the COVID-19 pandemic. Family structure, along with social expectations for gender (i.e., self-sacrificing femininity for women and hegemonic masculinity for men), parenthood, and marriage may explain perceptions of pandemic precarity - defined as the material deprivation and economic anxiety resulting from the COVID-19 pandemic. Method: This study used data from the Hispanic COVID-19 Rapid Response Study (n=400), a follow-up of the VidaSana Study of Mexican and Central American immigrants, to examine how family structure is associated with pandemic precarity (i.e., food, housing, and economic insecurity). Using linear regression models, average marginal effects (AMEs), and tests for group differences we investigate the independent and interactive effects of gender, parenthood, and marriage on pandemic precarity. Results: Men and parents reported the highest pandemic precarity. Fathers reported higher pandemic precarity than mothers. For men, marriage is associated with greater precarity, and for women, marriage is associated with less precarity, yet marriage increased precarity for those without children. Conclusion: We discuss the importance and implications of examining gender along with family structure to understand how immigrant families were faring in response to the pandemic.

Stigma Toward Substance Dependence: Causes, Consequences, and Potential Interventions.

Substance dependence is a prevalent and urgent public health problem. In 2021, 60 million Americans reported abusing alcohol within the month prior to being surveyed, and nearly 20 million Americans reported using illegal drugs (e.g., heroin) or prescription drugs (e.g., opioids) for nonmedical reasons in the year before. Drug-involved overdose rates have been steadily increasing over the past 20 years. This increase has been primarily driven by opioid and stimulant use. Despite its prevalence, drug dependence is one of the most stigmatized health conditions. Stigma has myriad negative consequences for its targets, including limiting their access to employment and housing, disrupting interpersonal relationships, harming physical and mental health, and reducing help-seeking. However, because research on stigma toward people with substance use disorders (SUDs) is relatively sparse compared with research on stigma toward other mental illnesses, the field lacks a comprehensive understanding of the causes and consequences of SUD stigma. Moreover, it remains unclear how, if at all, these factors differ from other types of mental illness stigma. The goal of this review is to take stock of the literature on SUD stigma, providing a clear set of foundational principles and a blueprint for future research and translational activity.

Comparing professional communities: Opioid prescriber networks and Public Health Preparedness Districts.

Problem opioid use and opioid-related drug overdoses remain a major public health concern despite attempts to reduce and monitor opioid prescriptions and increase access to office-based opioid treatment. Current provider-focused interventions are implemented at the federal, state, regional, and local levels but have not slowed the epidemic. Certain targeted interventions aimed at opioid prescribers rely on populations defined along geographic, political, or administrative boundaries; however, those boundaries may not align well with actual provider-patient communities or with the geographic distribution of high-risk opioid use. Instead of relying exclusively on commonly used geographic and administrative boundaries, we suggest augmenting existing strategies with a social network-based approach to identify communities (or clusters) of providers that prescribe to the same set of patients as another mechanism for targeting certain interventions. To test this approach, we analyze 1 year of prescription data from a commercially insured population in the state of Indiana. The composition of inferred clusters is compared to Indiana's Public Health Preparedness Districts (PHPDs). We find that in some cases the correspondence between provider networks and PHPDs is very high, while in other cases the overlap is low. This has implications for whether an intervention is reaching its intended provider targets efficiently and effectively. Assessing the best intervention targeting strategy for a particular outcome could facilitate more effective interventions to tackle the ongoing opioid use epidemic.

Trends in Abortion- and Contraception-Related Internet Searches After the US Supreme Court Overturned Constitutional Abortion Rights: How Much Do State Laws Matter?

Importance: The US Supreme Court ruling in Dobbs v Jackson Women's Health Organization on June 24, 2022, revealed immediate and distinct differences between states regarding abortion legality. Whether the ruling was associated with population-level changes in seeking information on reproductive health care-related information is unknown. Objective: To determine whether the US Supreme Court ruling on Dobbs v Jackson Women's Health Organization was associated with increased information seeking for reproductive health care access in the states with immediately effective (trigger and pre-Roe) abortion laws vs other states. Design, Setting, and Participants: This was a retrospective cross-sectional study of nationwide real-time internet search data by state-week from January 1, 2021, through July 16, 2022. Difference-in-difference event study estimates were used to evaluate abortion- and contraception-related internet searches after the Supreme Court draft majority decision was leaked on May 2, 2022, and the final ruling was issued on June 24, 2022, in states immediately affected vs other states. Data analyses were performed from July 18 to January 14, 2022. Exposures: The Supreme Court's draft majority decision leaked on May 2, 2022, and the final ruling on Dobbs v Jackson Women's Health Organization on June 24, 2022. Preexisting state trigger laws and pre-Roe bans that became effective immediately when Roe was overturned by the decision on Dobbs. Main Outcomes and Measures: Number of searches per 10 million Google queries in a state-week for terms related to abortion or contraception. Results: Searches for abortion-related terms increased from 16 302 to 75 746 per 10 million searches per state-week during the weeks before vs after the May 2, 2022, leak of the draft majority decision in states with trigger laws or abortion bans. This was a 42% (95% CI, 24%-59%) higher increase than in states with laws that protect abortion access. Searches for contraception also increased from 56 055 to 82 133 searches per state-week after the ruling in the states with abortion bans, 25% (95% CI, 13%-36%) higher than the increase in states protecting abortion access. Conclusions and Relevance: The findings of this retrospective cross-sectional study suggest that changes in internet searching for terms related to reproductive health care can capture immediate population-level changes in information-seeking behavior regarding reproductive health care access. These data are critical for shaping health policy discussions.

Social enrichment on the job: Complex work with people improves episodic memory, promotes brain reserve, and reduces the risk of dementia.

Individuals with more complex jobs experience better cognitive function in old age and a lower risk of dementia, yet complexity has multiple dimensions. Drawing on the Social Networks in Alzheimer Disease study, we examine the association between occupational complexity and cognition in a sample of older adults (N = 355). A standard deviation (SD) increase in complex work with people is associated with a 9% to 12% reduction in the probability of mild cognitive impairment or dementia, a 0.14-0.19 SD increase in episodic memory, and a 0.18-0.25 SD increase in brain reserve, defined as the gap (residual) between global cognitive function and magnetic resonance imaging (MRI) indicators of brain atrophy. In contrast, complexity with data or things is rarely associated with cognitive outcomes. We discuss the clinical and methodological implications of these findings, including the need to complement data-centered activities (e.g., Sudoku puzzles) with person-centered interventions that increase social complexity.

Social ecological factors and medication treatment for opioid use disorder among justice-involved rural and urban persons: the Geographic variation in Addiction Treatment Experiences (GATE) longitudinal cohort study protocol.

INTRODUCTION: Three medications are Food and Drug Administration approved for the treatment of opioid use disorder (OUD); however, these medications are underused within prisons, which elevates the risk of relapse and overdose when persons with opioid use disorder (POUD) are released. Research is scant regarding the multilevel factors associated with POUDs' willingness to initiate medication treatment for opioid use disorder (MOUD) while in prison and their continued engagement in treatment after release. Furthermore, rural and urban populations have not been compared. The Geographic variation in Addiction Treatment Experiences (GATE) study seeks to identify multilevel factors (ie, individual, personal network, and structural factors) influencing prison-based extended-release injectable naltrexone (XR-NTX) and buprenorphine initiation and will examine predictors of postrelease MOUD use and adverse outcomes (ie, relapse, overdose, recidivism) among both rural and urban POUDs. METHODS AND ANALYSIS: This mixed methods study employs a social ecological framework. A prospective observational longitudinal cohort study is being conducted with 450 POUDs using survey and social network data collected in prison, immediately postrelease, 6 months postrelease and 12 months postrelease to identify multilevel rural-urban variation in key outcomes. In-depth qualitative interviews are being conducted with POUDs, prison-based treatment staff and social service clinicians. To maximise rigour and reproducibility, we employ a concurrent triangulation strategy, whereby qualitative and quantitative data contribute equally to the analysis and are used for cross-validation when examining scientific aims. ETHICS AND DISSEMINATION: The GATE study was reviewed and approved by the University of Kentucky's Institutional Review Board prior to implementation. Findings will be disseminated through presentations at scientific and professional association conferences, peer-reviewed journal publications and a summary aggregate report submitted to the Kentucky Department of Corrections.

Random sampling of alters from networks: A promising direction in egocentric network research.

The social network perspective has great potential for advancing knowledge of social mechanisms in many fields. However, collecting egocentric (i.e., personal) network data is costly and places a heavy burden on respondents. This is especially true of the task used to elicit information on ties between network members (i.e., alter-alter ties or density matrix), which grows exponentially in length as network size increases. While most existing national surveys circumvent this problem by capping the number of network members that can be named, this strategy has major limitations. Here, we apply random sampling of network members to reduce cost, respondent burden, and error in network studies. We examine the effectiveness and reliability of random sampling in simulated and real-world egocentric network data. We find that in estimating sample/population means of network measures, randomly selecting a small number of network members produces only minor errors, regardless of true network size. For studies that use network measures in regressions, randomly selecting the mean number of network members (e.g., randomly selecting 10 alters when mean network size is 10) is enough to recover estimates of network measures that correlate close to 1 with those of the full sample. We conclude with recommendations for best practices that will make this versatile but resource intensive methodology accessible to a wider group of researchers without sacrificing data quality.

Intergroup relationships with people who use drugs: A personal network approach.

Positive and meaningful intergroup contact between people who use drugs and those with the potential to provide positive social interactions has been identified as an important pathway to address the burden of drug use by reducing stigmatizing views and behaviors. Traditional approaches to intergroup contact typically rely on laboratory experiments or survey vignettes to examine the consequences of variation in contact conditions and relationships. Although seldom measured, contact occurs naturally through individuals' personal social networks. Here, we apply this latter approach to examine how the characteristics of drug use and social roles are associated with positive and meaningful intergroup contact in daily life. We leverage unique data from a state representative sample of Indiana residents aged 18 or older (n = 926) that completed a personal network interview and separately reported people they know who have a drug use problem. We first identified the respondents who nominated a person who uses drugs as a member of their core personal network and then evaluated the relationship, disease, and individual characteristics that were associated with that person's inclusion in the personal network. We find that primary relationships (e.g., having a spouse or child who uses drugs) are associated with meaningful contact with people who use drugs but that intense manifestations of disease characteristics (severe or problematic, danger to self) can limit the likelihood of contact. These findings demonstrate how the nature of intergroup contact can shape the types of relationships that have been shown to help reduce stigmatizing attitudes and the behavioral barriers to recovery, such as social isolation. Thus, core networks present a valuable approach to defining the factors that likely contribute to effective intergroup contact.

Comparing measures of centrality in bipartite patient-prescriber networks: A study of drug seeking for opioid analgesics.

Visiting multiple prescribers is a common method for obtaining prescription opioids for nonmedical use and has played an important role in fueling the United States opioid epidemic, leading to increased drug use disorder and overdose. Recent studies show that centrality of the bipartite network formed by prescription ties between patients and prescribers of opioids is a promising indicator for drug seeking. However, node prominence in bipartite networks is typically estimated with methods that do not fully account for the two-mode topology of the underlying network. Although several algorithms have been proposed recently to address this challenge, it is unclear how these algorithms perform on real-world networks. Here, we compare their performance in the context of identifying opioid drug seeking behaviors by applying them to massive bipartite networks of patients and providers extracted from insurance claims data. We find that two variants of bipartite centrality are significantly better predictors of subsequent opioid overdose than traditional centrality estimates. Moreover, we show that incorporating non-network attributes such as the potency of the opioid prescriptions into the measures can further improve their performance. These findings can be reproduced on different datasets. Our results demonstrate the potential of bipartiteness-aware indices for identifying patterns of high-risk behavior.

Addiction onset and offset characteristics and public stigma toward people with common substance dependencies: A large national survey experiment.

Drug-related overdose deaths topped 100,000 between 2020 and 2021. Opioids and stimulants are implicated as the primary drivers of this public health crisis. Stigma remains one of the primary barriers to treatment and recovery from substance use disorders. However, little is known about how stigma varies across different substance types, whether individuals are actively using or in recovery, and medical versus recreational onset. We examined these questions using data from the 2021 Shatterproof Addiction Stigma Index, the only nationally representative data available on this topic. Respondents (N = 7051) completed a vignette-based survey experiment to assess public stigma (social distance, prejudice, competence, and causal attributions) toward people with alcohol, opioid (following a prescription pain or recreational use onset), heroin, or methamphetamine dependencies. Vignette characters were described as active users or in recovery. Adjusting for covariates (e.g., race, age, gender), prejudice and desire for social distance were highest toward heroin and methamphetamine, and lowest toward alcohol dependence. The perceived onset of the dependency affected stigma. Specifically, prescription opioids with a recreational onset were more stigmatized than those with a medical onset. Moreover, individuals depicted as being in recovery were less stigmatized than those depicted as active users. Recovery status had the largest impact on prejudice and social distance toward methamphetamine, relative to other conditions. The nature and magnitude of substance dependency stigma differs across substance types and onset and offset conditions. Reducing stigma will require tailored strategies that consider the multidimensional nature of stigma toward people with addiction.

What kinds of social networks protect older adults' health during a pandemic? The tradeoff between preventing infection and promoting mental health.

When the coronavirus emerged in early 2020, older adults were at heightened risk of contracting the virus, and of suffering mental health consequences from the pandemic and from the precautions designed to mitigate it. In this paper, we examine how social networks prior to the pandemic helped to shape health beliefs, behaviors, and outcomes among older adults during its onset, focusing on (1) perceived risk of COVID-19, (2) preventative health behaviors, and (3) mental health, including loneliness, perceived stress, depression, and anxiety. Drawing on the longitudinal Social Networks in Alzheimer Disease study, we find that networks high in bridging social capital predict greater perceived risk and more precautions taken, but worse mental health. In contrast, networks high in bonding social capital predict less perceived risk and fewer precautions taken, but better mental health. We discuss this apparent tradeoff between physical and mental health.

Functional Status, Mood State, and Physical Activity Among Women With Post-Acute COVID-19 Syndrome.

Objectives: While organ-specific pathophysiology has been well-described in SARS-CoV-2 infection, less is known about the attendant effects on functional status, mood state and leisure-time physical activity (PA) in post-acute COVID-19 syndrome (PASC). Methods: A case-control design was employed to recruit 32 women (n = 17 SARS-CoV-2; n = 15 controls) matched on age (54 ± 12 years) and body mass index (27 ± 6 kg/m2) that did not differ by smoking status or history of cardiopulmonary disease. Participants completed a series of assessments including Profile of Mood States (POMS), Modified Pulmonary Functional Status and Dyspnea Questionnaire (PFSDQ-M), and Godin-Shephard Leisure-Time PA. Results: Significant between-group differences were detected for the POMS total mood disturbance with sub-scale analyses revealing elevated tension, confusion, and lower vigor among SARS-CoV-2 participants (all p-values < 0.05). The number of SARS-CoV-2 symptoms (e.g., loss of taste/smell, muscle aches etc.) were associated (r = 0.620, p = 0.008) with confusion. SARS-CoV-2 participants exhibited poorer functional status (p = 0.008) and reduced leisure-time PA (p = 0.004) compared to controls. Conclusion: The sequela of persistent SARS-CoV-2 symptoms elicit clear disturbances in functional status, mood state, and leisure-time PA among women with PASC. Ongoing symptom presentation affects recovery time-course and PA participation.

Online misinformation is linked to early COVID-19 vaccination hesitancy and refusal.

Widespread uptake of vaccines is necessary to achieve herd immunity. However, uptake rates have varied across U.S. states during the first six months of the COVID-19 vaccination program. Misbeliefs may play an important role in vaccine hesitancy, and there is a need to understand relationships between misinformation, beliefs, behaviors, and health outcomes. Here we investigate the extent to which COVID-19 vaccination rates and vaccine hesitancy are associated with levels of online misinformation about vaccines. We also look for evidence of directionality from online misinformation to vaccine hesitancy. We find a negative relationship between misinformation and vaccination uptake rates. Online misinformation is also correlated with vaccine hesitancy rates taken from survey data. Associations between vaccine outcomes and misinformation remain significant when accounting for political as well as demographic and socioeconomic factors. While vaccine hesitancy is strongly associated with Republican vote share, we observe that the effect of online misinformation on hesitancy is strongest across Democratic rather than Republican counties. Granger causality analysis shows evidence for a directional relationship from online misinformation to vaccine hesitancy. Our results support a need for interventions that address misbeliefs, allowing individuals to make better-informed health decisions.

Cognitively stimulating environments and cognitive reserve: the case of personal social networks.

Cognitively stimulating environments are thought to be protective of cognitive decline and onset of Alzheimer's disease and related dementias (ADRD) through the development of cognitive reserve (CR). CR refers to cognitive adaptability that buffers the impact of brain pathology on cognitive function. Despite the critical need to identify cognitively stimulating environments to build CR, there is no consensus regarding which environmental determinants are most effective. Rather, most studies use education as proxies for CR and little is known about the association between older adults' personal social networks and CR. Using neuroimaging data from 135 older adults participating in the Social Networks in Alzheimer Disease (SNAD) study, this article adopted a residual method for measuring CR and found that large network size, high network diversity, and loosely connected networks were positively associated with greater CR. These results suggest that expansive social networks in later life may constitute cognitively stimulating environments which can be leveraged to build CR and reduce the burden of ADRD.

Do subjective or objective cognitive measures better predict social network type among older adults?

A large literature highlights the link between cognitive function and social networks in later life. Yet there remains uncertainty about the factors driving this relationship. In the present study, we use measures of subjective cognitive decline and clinical cognitive assessments on a sample of older adults to investigate whether the relationship between cognitive function and social networks is driven by psychosocial factors. We found a consistent link between clinical cognitive assessments and social network type, but no association between subjective concerns of cognitive decline and networks. Participants who exhibited signs of clinical cognitive impairment were more likely to have restricted networks (i.e., smaller networks consisting of fewer contacts, more interconnectivity, and less social diversity) compared to their cognitively normal counterparts, regardless of subjective measures of cognitive decline - both from the participant's perspective and study partner's perspective. These findings suggest that neither cognitively impaired older adults nor their network members appear to consciously dissolve social ties on the basis of perceived cognitive decline. However, it remains unclear whether the association between clinical cognitive impairment and social network type indicates the protective nature of social networks against cognitive decline or a subconscious process leading to social contraction.