Prevalence of financial hardship and health-related social needs among patients with missed radiology appointments.

PURPOSE: We aimed to evaluate the prevalence of financial hardship and Health-Related Social Needs (HRSN) among patients who missed their radiology appointment. METHODS: English-speaking adult patients, with a missed outpatient imaging appointment at any of a tertiary care imaging centers between 11/2022 and 05/2023 were eligible. We measured self-reported general financial worry using Comprehensive Score for Financial Toxicity (COST), imaging hardship (worry that the current imaging is a financial hardship to patient and their family), material hardship (e.g., medical debt), cost-related care nonadherence, and HRSNs including housing instability, food insecurity, transportation problems, and utility help needs. RESULTS: 282 patients were included (mean age 54.7 ± 15.0 years; 70.7 % female). Majority were non-Hispanic White (52.4 %), followed by Asian (23.0 %) and Hispanic (16.0 %) racial/ethnic background. Most missed appointments were patient-initiated (74.8 %); 13.5 % due to cost or insurance coverage and 6.4 % due to transportation and parking. Mean COST score was 26.8 with 44.4 % and 28.8 % reporting their illness and imaging as a source of financial hardship. 18.3 % and 35.2 % endorsed cost-related care nonadherence and material hardship. 32.7 % had at least one HRSNs with food insecurity the most common (25.4 %). Only 12.5 % were previously screened for financial hardship or HRSNs. Having comorbidity and living in more disadvantaged neighborhoods was associated with higher report of financial hardship and HRSNs. CONCLUSION: Financial hardship and HRSNs are common among those who miss radiology appointments. There needs to be more rigorous screening for financial hardship and HRSNs at every health encounter and interventions should be implemented to address these.

The association between social risks and days at home for older veterans.

BACKGROUND: Many health systems are trying to support the ability of older adults to remain in their homes for as long as possible. Little is known about the relationship between patient-reported social risks and length of time spent at home. We assessed how social risks were associated with days at home for a cohort of older Veterans at high risk for hospitalization and mortality. METHODS: A prospective cross-sectional study using a 2018 survey of 3479 high-risk Veterans aged ≥65 linked to Veterans Health Administration data. Social risks included measures of social resources (i.e., no partner present, low social support), material resources (i.e., not employed, financial strain, medication insecurity, food insecurity, and transportation barriers), and personal resources (i.e., low medical literacy and less than high school education). We estimated how social risks were associated with days at home, defined as the number of days spent outside inpatient, long-term care, observation, or emergency department settings over a 12-month period, using a negative binomial regression model. RESULTS: Not having a partner, not being employed, experiencing transportation barriers, and low medical literacy were respectively associated with 2.57, 3.18, 3.39, and 6.14 fewer days at home (i.e., 27% more facility days, 95% confidence interval [CI] 8%-50%; 42% more facility days, 95% CI 7%-89%; 34% more facility days, 95% CI 7%-68%; and 63% more facility days, 95% CI 27%-109%). Experiencing food insecurity was associated with 2.62 more days at home (i.e., 24% fewer facility days, 95% CI 3%-59%). CONCLUSIONS: Findings suggest that screening older Veterans at high risk of community exit for social risks (i.e., social support, material resources, and medical literacy) may help identify patients likely to benefit from home- and community-based health and social services that facilitate remaining in home settings. Future research should focus on understanding the mechanisms by which these associations occur.

Screening tools for employment in clinical healthcare delivery systems: a content analysis.

BACKGROUND: The relationship between work and health is complex and bidirectional, where work can have both health-harming and health-enhancing effects. Though employment is recognized as a social determinant of health, and clinical healthcare delivery systems are increasingly using screening tools to ask patients about social needs, little research has explored the extent to which employment-related social risk is captured in these screening tools. This study aimed to identify and characterize employment- and work-related questions in social risk screening tools that have been implemented in clinical healthcare delivery systems. METHODS: We conducted a qualitative content analysis of employment-related items in screening tools that have been implemented in clinical healthcare service delivery systems. Three content areas guided data extraction and analysis: Setting, Domain, and Level of Contextualization. RESULTS: Screening tools that asked employment-related questions were implemented in settings that were diverse in the populations served and the scope of care provided. The intent of employment-related items focused on four domains: Social Risk Factor, Social Need, Employment Exposure, and Legal Need. Most questions were found to have a low Level of Contextualization and were largely focused on identifying an individual's employment status. CONCLUSIONS: Several existing screening tools include measures of employment-related social risk, but these items do not have a clear purpose and range widely depending on the setting in which they are implemented. In order to maximize the utility of these tools, clinical healthcare delivery systems should carefully consider what domain(s) they aim to capture and how they anticipate using the screening tools to address social determinants of health.

Codesigning Online Continuing Medical Education on Social Health Integration and Social Risk-Informed Care for Primary Care Providers.

INTRODUCTION: Adapting clinical care decisions for patient-reported social risks is essential to social health integration and patient-centered care. Most research in this area focuses on awareness and assistance (social-needs-targeted care), such as screening and referral to food, financial, and other resources. Limited evidence for adjustment strategies (social risk-informed care) or adapting care for social risks made it difficult for Kaiser Permanente to implement new initiatives. This article describes a codesign process to build a novel, adjustment-focused continuing medical education course. METHODS: The authors codeveloped the online continuing medical education course with patients and clinicians using user-centered design. Transcripts from codesign activities were coded and analyzed by thematic analysis to identify major themes, including perceptions of social risk-informed care and barriers to care adjustment. RESULTS: Practical hurdles for implementing social risk-informed care emerged, including clinicians' concerns about the ethics of adjustment as substandard care, particularly without robust assistance activities. However, patients expressed a desire for their care to be adapted to their social circumstances, to allow for more realistic care plans. DISCUSSION: Implementation barriers identified from the codesign were addressed through an interactive, case-study approach. Existing evidence on contextualized care and shared decision making informed a general framework for primary care providers to engage in awareness and adjustment activities, paired with 3 interactive case studies based on real-world, clinician-supplied scenarios. CONCLUSION: The authors recommend that multiple stakeholder perspectives be incorporated during the development of social health integration initiatives, particularly adjustment. Education complemented by active, nuanced, flexible implementation strategies may be necessary for the successful uptake of care-delivery-based social health integration activities.

Understanding Health-Related Social Risks.

Because of the established contribution of social factors to health outcomes, approaches that address upstream determinants of health have increasingly been recognized as cost-effective means to improve population health. Understanding and usage of precise terminology is important to facilitate collaboration across disciplines. Social determinants of health affect everyone, not just the socially and economically disadvantaged, whereas health-related social risks (HRSR) are specific adverse conditions at the individual or family level that are associated with poor health and related to the immediate challenges individuals face. Health-related social needs account for patient preference in addressing identified social risks. The use of validated screening tools is important to capture risk factors in a standardized fashion to support research and quality improvement. There is a paucity of studies that address HRSR in the context of radiology. This review provides an understanding of HRSR and outlines various ways in which radiologists can work to mitigate them.

In-person versus electronic screening for social risks among carers of pediatric inpatients: A mixed methods randomized trial.

We aimed to compare disclosure of social risks according to self-report on an iPad versus face-to-face questions from a health professional and to explore carers' experiences of screening. This two-arm, parallel group, randomized trial was conducted from January 19, 2021, to December 17, 2021, in a public hospital pediatric ward serving a disadvantaged area of an Australian capital city. Carers of children aged ≤ 5 years admitted to the Children's Ward were eligible. The primary outcome was disclosure of social risks. The screener included nine items on food security, household utilities, transport, employment, personal and neighborhood safety, social support, housing and homelessness. Disclosure of social risks was similar between the self-completion (n = 193) and assisted-completion (n = 193) groups for all 9 items, ranging 4.1% higher for worrying about money for food (95% CI - 11.4, 3.1%) among the assisted-completion group, to 5.7% (-1.6, 13.0%) higher for unemployment among the self-completion group. In qualitative interviews, participants were positive about screening for social risks in the hospital ward setting and the majority indicated a preference for self-completion.  Conclusion: Differences in the disclosure of social risks according to self- versus assisted-completion were small, suggesting that either method could be used. Most carers expressed a preference for self- completion, which is therefore recommended as the ideal mode for such data collection for Australian pediatric inpatient settings.  Trial registration: Australia New Zealand Clinical Trial Registry ( www.anzctry.org.au ; #ACTRN12620001326987; date of registration 8 December 2020). What is Known: • Most evidence on screening of social risks in pediatric inpatient settings is from the USA. • Little is known about disclosure of social risks in countries with universal health care and social welfare. What is New: • Disclosure of social risks was similar for electronic compared with face-to-face screening. • Carers preferred electronic completion over face-to-face completion.

Development of a Social Risk Score in the Electronic Health Record to Identify Social Needs Among Underserved Populations: Retrospective Study.

BACKGROUND: Patients with unmet social needs and social determinants of health (SDOH) challenges continue to face a disproportionate risk of increased prevalence of disease, health care use, higher health care costs, and worse outcomes. Some existing predictive models have used the available data on social needs and SDOH challenges to predict health-related social needs or the need for various social service referrals. Despite these one-off efforts, the work to date suggests that many technical and organizational challenges must be surmounted before SDOH-integrated solutions can be implemented on an ongoing, wide-scale basis within most US-based health care organizations. OBJECTIVE: We aimed to retrieve available information in the electronic health record (EHR) relevant to the identification of persons with social needs and to develop a social risk score for use within clinical practice to better identify patients at risk of having future social needs. METHODS: We conducted a retrospective study using EHR data (2016-2021) and data from the US Census American Community Survey. We developed a prospective model using current year-1 risk factors to predict future year-2 outcomes within four 2-year cohorts. Predictors of interest included demographics, previous health care use, comorbidity, previously identified social needs, and neighborhood characteristics as reflected by the area deprivation index. The outcome variable was a binary indicator reflecting the likelihood of the presence of a patient with social needs. We applied a generalized estimating equation approach, adjusting for patient-level risk factors, the possible effect of geographically clustered data, and the effect of multiple visits for each patient. RESULTS: The study population of 1,852,228 patients included middle-aged (mean age range 53.76-55.95 years), White (range 324,279/510,770, 63.49% to 290,688/488,666, 64.79%), and female (range 314,741/510,770, 61.62% to 278,488/448,666, 62.07%) patients from neighborhoods with high socioeconomic status (mean area deprivation index percentile range 28.76-30.31). Between 8.28% (37,137/448,666) and 11.55% (52,037/450,426) of patients across the study cohorts had at least 1 social need documented in their EHR, with safety issues and economic challenges (ie, financial resource strain, employment, and food insecurity) being the most common documented social needs (87,152/1,852,228, 4.71% and 58,242/1,852,228, 3.14% of overall patients, respectively). The model had an area under the curve of 0.702 (95% CI 0.699-0.705) in predicting prospective social needs in the overall study population. Previous social needs (odds ratio 3.285, 95% CI 3.237-3.335) and emergency department visits (odds ratio 1.659, 95% CI 1.634-1.684) were the strongest predictors of future social needs. CONCLUSIONS: Our model provides an opportunity to make use of available EHR data to help identify patients with high social needs. Our proposed social risk score could help identify the subset of patients who would most benefit from further social needs screening and data collection to avoid potentially more burdensome primary data collection on all patients in a target population of interest.

Addressing adverse social determinants of health in pediatric primary care: Study protocol for a hybrid type 2 effectiveness-implementation randomized controlled trial in two national pediatric practice-based research networks.

BACKGROUND: Growing evidence linking social determinants of health (SDOH) to child health outcomes has prompted widespread recommendations for pediatricians to screen and refer for adverse SDOH at primary care visits. Yet there is little evidence to date demonstrating the effectiveness of practice-based SDOH screening and referral interventions on increasing family engagement with resources. This hybrid type 2 effectiveness-implementation trial aims to demonstrate the non-inferiority of a low-touch implementation strategy in order to facilitate dissemination of an existing SDOH screening and referral system (WE CARE) and demonstrate its effectiveness and sustainability in various pediatric practices. METHODS: We recruited eighteen pediatric practices in fourteen US states through two pediatric practice-based research networks. For this stepped wedge cluster RCT, practices serve as their own controls during the Usual Care phase and implement WE CARE during the intervention phase via one of two randomized implementation strategies: self-directed, pre-recorded webinar vs. study team-facilitated, live webinar. We collect data at practice, clinician/staff, and parent levels to assess outcomes grounded in the Proctor Conceptual Model of Implementation Research. We use generalized mixed effects models and differences in proportions to compare rates of resource referrals by implementation strategy, and intention-to-treat analysis to compare odds of engagement with new resources among families enrolled in the Usual Care vs. WE CARE phases. DISCUSSION: Findings from this trial may inform decisions about broader dissemination of SDOH screening systems into a diverse spectrum of pediatric practices across the US and potentially minimize the impact of adverse SDOH on children and families.

Age at diagnosis and social risks among Black cancer survivors: Results from the Detroit Research on Cancer Survivors cohort.

BACKGROUND: Social risks are common among cancer survivors who have the fewest financial resources; however, little is known about how prevalence differs by age at diagnosis, despite younger survivors' relatively low incomes and wealth. METHODS: The authors used data from 3703 participants in the Detroit Research on Cancer Survivors (ROCS) cohort of Black cancer survivors. Participants self-reported several forms of social risks, including food insecurity, housing instability, utility shut-offs, not getting care because of cost or lack of transportation, and feeling unsafe in their home neighborhood. Modified Poisson models were used to estimate prevalence ratios and 95% confidence intervals (CIs) of social risks by age at diagnosis, controlling for demographic, socioeconomic, and cancer-related factors. RESULTS: Overall, 35% of participants reported at least one social risk, and 17% reported two or more risks. Social risk prevalence was highest among young adults aged 20-39 years (47%) followed by those aged 40-54 years (43%), 55-64 years (38%), and 65 years and older (24%; p for trend < .001). Compared with survivors who were aged 65 years and older at diagnosis, adjusted prevalence ratios for any social risk were 1.75 (95% CI, 1.42-2.16) for survivors aged 20-39 years, 1.76 (95% CI, 1.52-2.03) for survivors aged 40-54 years, and 1.41 (95% CI, 1.23-1.60) for survivors aged 55-64 years at diagnosis. Similar associations were observed for individual social risks and experiencing two or more risks. CONCLUSIONS: In this population of Black cancer survivors, social risks were inversely associated with age at diagnosis. Diagnosis in young adulthood and middle age should be considered a risk factor for social risks and should be prioritized in work to reduce the financial effects of cancer on financially vulnerable cancer survivors.

Positive and Negative Social Consequences of Participating in a Sexual-Network Study.

Assessment of risks and benefits of study participation is standard practice preceding the initiation of human subjects research. Although tracking adverse events during research participation is routine, collecting information from participants about what they perceive as benefits is less common. We longitudinally tracked social risks and benefits of participation among a cohort of 241 men who have sex with men participating in a sexual health study to improve participants' experiences and enhance understanding of participant motivations to enroll and attend follow-up. Of the participants who returned for at least one follow-up visit (n = 217, 90%), most (n = 185, 85%) reported positive consequences resulting from participation. Reporting of negative social consequences was rare, and all concerned a stigmatized reaction from someone learning about the participant's involvement in a sexual health study. Better identification of both positive and negative consequences resulting from research participation may improve how researchers design, recruit, and conduct research.

Racial and ethnic disparities in self-reported general and mental health status among colorectal cancer survivors: impact of sociodemographic factors and implications for mortality-a SEER-CAHPS study.

PURPOSE: Patient-reported outcomes are recognized as strong predictors of cancer prognosis. This study examines racial and ethnic differences in self-reported general health status (GHS) and mental health status (MHS) among patients with colorectal cancer (CRC). METHODS: A retrospective analysis of Medicare beneficiaries between 1998 and 2011 with non-distant CRC who underwent curative resection and completed a Consumer Assessment of Healthcare Providers and Systems (CAHPS) survey within 6-36 months of CRC diagnosis. Analysis included a stepwise logistic regression to examine the relationship between race and ethnicity and fair or poor health status, and a proportional hazards model to determine the mortality risk associated with fair or poor health status. RESULTS: Of 1867 patients, Non-Hispanic Black (OR 1.56, 95% CI 1.06-2.28) and Hispanic (OR 1.48, 95% CI 1.04-2.11) patients had higher unadjusted odds for fair or poor GHS compared to Non-Hispanic White patients, also Hispanic patients had higher unadjusted odds for fair or poor MHS (OR 1.92, 95% CI 1.23-3.01). These relationships persisted after adjusting for clinical factors but were attenuated after subsequently adjusting for sociodemographic factors. Compared to those reporting good to excellent health status, patients reporting fair or poor GHS or MHS had an increased mortality risk (OR 1.52, 95% CI 1.31-1.76 and OR 1.63, 95% CI 1.34-1.99, respectively). CONCLUSION: Racial and ethnic differences in GHS and MHS reported after CRC diagnosis are mainly driven by sociodemographic factors and reflect a higher risk of mortality. Identifying unmet biopsychosocial needs is necessary to promote equitable care.

Vulnerability or resilience? Examining trust asymmetry from the perspective of risk sources under descriptive versus experiential decision.

Introduction: The investigation of trust vulnerability is important to the understanding of the potential mechanisms of trust formation and erosion. However, more effective exploration of trust vulnerability has been hindered due to the lack of consideration of risk sources and types of information. Methods: This study extended the investigation of asymmetry to both social and natural risk under experiential and descriptive decisions. Using the trust game as the decision-making paradigm and money as the subject matter, the research employed experimental methods to examine how people perceive and make decisions after being positively and negatively affected by natural and social risks. A total of 286 college students were participated in our study. Study 1 (n = 138) and Study 2 (n = 148) explored asymmetry in experiential and descriptive decision separately. Results: The findings indicated that when considering experiential information, negative information had a greater effect in reducing trust compared to the enhancing effect of positive information (t = -1.95, p = 0.050). Moreover, the study revealed that negative information had a stronger negative impact in the context of social risks rather than natural risks (t = -3.26, p = 0.002), suggesting that trust is vulnerable both internally and externally. Conversely, when considering descriptive information, the effect of both positive and negative information on trust was symmetrical, and the impact of negative information was less significant compared to that of natural risks, indicating that trust has a certain level of resilience (t = 2.25, p = 0.028). Discussion: The study emphasizes the importance of refining risk sources and information characteristics in complex scenarios in order to improve understanding of trust enhancement and repair.

Addressing Social Determinants of Health in Practice.

This review summarizes the current pediatric literature related to social determinants of health, including strengths and weaknesses of screening practices and intervention strategies, common concerns and potential unintended consequences, opportunities for further research, and provides evidence-informed practical strategies for clinicians.

Social Risk and Smoking Among Women Smokers Early in the COVID-19 Pandemic: The Role of Mental Health.

Background: We examined patterns of smoking in relation to health-related socioeconomic vulnerability (HRSV) among U.S. women early in the pandemic and whether mental health symptoms mediated these relationships. Materials and Methods: Data were obtained from the April 2020 National U.S. Women's Health COVID-19 Study (N = 3200). Among current smokers, adjusted odds of increased smoking since the start of the pandemic (vs. same or less) by incident and worsening HRSVs were modeled. Structural equation modeling was used to assess anxiety, depression, and traumatic stress symptoms as mediators of the relationship between six HRSVs (food insecurity; housing, utilities, and transportation difficulties; interpersonal violence; financial strain) and increased smoking early in the pandemic. Results: Nearly half (48%) of current smokers reported increased smoking since the pandemic started. Odds of increased smoking were higher among women with incident financial strain (aOR = 2.0, 95% CI 1.2-3.3), incident food insecurity (aOR = 2.9, 95% CI 1.7-5.1), any worsening HRSV (aOR = 2.2, 95% CI 1.5-3.0), and worsening food insecurity (aOR = 1.9, 95% CI 1.3-3.0). Anxiety symptoms were a significant, partial mediator of the relationship between increased smoking and any worsening HRSVs (proportion mediated = 0.17, p = 0.001) and worsening food insecurity (0.19, p = 0.023), specifically. Depression symptoms were a significant, partial mediator of the relationship between increased smoking and any worsening HRSVs (0.15, p = 0.004) and incident financial strain (0.19, p = 0.034). Traumatic stress was not a significant mediator of any tested relationship. Conclusions: Anxiety and depression symptoms partially explain the relationship between rising socioeconomic vulnerability and increased smoking among women early in the pandemic. Addressing HRSVs and mental health may help reduce increased smoking during a public health crisis.

Real-world integration of the protocol for responding to and assessing patients' assets, risks, and experiences tool to assess social determinants of health in the electronic medical record at an academic medical center.

Objective: To describe the real-world deployment of a tool, the Protocol for Responding to and Assessing Patients' Assets, Risks, and Experiences (PRAPARE), to assess social determinants of health (SDoH) in an electronic medical record (EMR). Methods: We employed the collection of the PRAPARE tool in the EMR of a large academic health system in the ambulatory clinic and emergency department setting. After integration, we evaluated SDoH prevalence, levels of missingness, and data anomalies to inform ongoing collection. We summarized responses using descriptive statistics and hand-reviewed data text fields and patterns in the data. Data on patients who were administered with the PRAPARE from February to December 2020 were extracted from the EMR. Patients missing ≥ 12 PRAPARE questions were excluded. Social risks were screened using the PRAPARE. Information on demographics, admittance status, and health coverage were extracted from the EMR. Results: Assessments with N = 6531 were completed (mean age 54 years, female (58.6%), 43.8% Black). Missingness ranged from 0.4% (race) to 20.8% (income). Approximately 6% of patients were homeless; 8% reported housing insecurity; 1.4% reported food needs; 14.6% had healthcare needs; 8.4% needed utility assistance; and 5% lacked transportation related to medical care. Emergency department patients reported significantly higher proportions of suboptimal SDoH. Conclusions: Integrating the PRAPARE assessment in the EMR provides valuable information on SDoH amenable to intervention, and strategies are needed to increase accurate data collection and to improve the use of data in the clinical encounter.

Diabetes distress in a Medicaid sample: The role of psychosocial and health-related factors.

AIMS: Diabetes-related distress can negatively affect disease management leading to worse complications, especially among marginalized populations. Prior studies mostly focus on distress' impact on diabetes outcomes, with few examining distress predictors. The current study examined the impact of social needs on distress on its own and after controlling for other socio-demographic, psychosocial, and health factors. METHODS: Adult Medicaid beneficiaries with type 2 diabetes and a recent HbA1c test documented in claims data (<120 days) were recruited for a 12-month social needs intervention trial. Baseline survey data assessed diabetes distress, social needs, psychosocial factors and health factors. Descriptive statistics were obtained, and bivariate and multivariable logistic regression analyses were used to identify predictors of moderate to severe distress. RESULTS: Bivariate analyses revealed social needs, stress, depression, comorbidity and comorbidity burden, poor self-rated health, insulin use, a self-reported HbA1c ≥ 9.0, and difficulty remembering to take diabetes medications were all positively associated with greater odds of diabetes distress; greater social support, diabetes self-efficacy, and age were negatively associated. Four variables remained significant in the multivariate model: depression, diabetes self-efficacy, self-reported HbA1c ≥ 9.0, and younger age. CONCLUSIONS: Targeted distress screening efforts might prioritize people with HbA1c values >9.0, greater depression, and worse diabetes self-efficacy.

An NLP approach to identify SDoH-related circumstance and suicide crisis from death investigation narratives.

OBJECTIVES: Suicide presents a major public health challenge worldwide, affecting people across the lifespan. While previous studies revealed strong associations between Social Determinants of Health (SDoH) and suicide deaths, existing evidence is limited by the reliance on structured data. To resolve this, we aim to adapt a suicide-specific SDoH ontology (Suicide-SDoHO) and use natural language processing (NLP) to effectively identify individual-level SDoH-related social risks from death investigation narratives. MATERIALS AND METHODS: We used the latest National Violent Death Report System (NVDRS), which contains 267 804 victim suicide data from 2003 to 2019. After adapting the Suicide-SDoHO, we developed a transformer-based model to identify SDoH-related circumstances and crises in death investigation narratives. We applied our model retrospectively to annotate narratives whose crisis variables were not coded in NVDRS. The crisis rates were calculated as the percentage of the group's total suicide population with the crisis present. RESULTS: The Suicide-SDoHO contains 57 fine-grained circumstances in a hierarchical structure. Our classifier achieves AUCs of 0.966 and 0.942 for classifying circumstances and crises, respectively. Through the crisis trend analysis, we observed that not everyone is equally affected by SDoH-related social risks. For the economic stability crisis, our result showed a significant increase in crisis rate in 2007-2009, parallel with the Great Recession. CONCLUSIONS: This is the first study curating a Suicide-SDoHO using death investigation narratives. We showcased that our model can effectively classify SDoH-related social risks through NLP approaches. We hope our study will facilitate the understanding of suicide crises and inform effective prevention strategies.

Social Risks, Social Needs, and Attitudes Toward Social Health Screening 1 Year Into the COVID-19 Pandemic: Survey of Adults in an Integrated Health Care Delivery System.

Introduction Information about demographic differences in social risks, needs, and attitudes toward social health screening in non-highly vulnerable adult populations is lacking. Methods The authors analyzed data for 2869 Kaiser Permanente Northern California non-Medicaid-covered members aged 35 to 85 who responded to a 2021 English-only mailed/online survey. The survey covered 7 social risk and 11 social needs domains and attitudes toward social health screening. The authors used data weighted to the Kaiser Permanente Northern California membership to estimate prevalence of risks, needs, and screening receptivity in the overall population, by race/ethnicity (White, Black, Latinx, Asian American/Pacific Islander) and age (35-65 years old, 66-85 years old). Multivariable regression was used to evaluate differences between groups. Results Overall, 26% of adults were financially strained, 12% food insecure, 12% housing insecure, and 5% transportation insecure. Additionally, 7%, 8%, and 17% had difficulty paying for utilities, medical expenses, and dental care, respectively. Over 40% of adults wanted help with ≥ 1 social need. Dental care, vision/hearing care, paying for medical expenses and utilities, and managing debt/credit card repayment surpassed food, housing, and transportation needs. Prevalence of social risks and needs was generally higher among middle-aged versus older and Black and Latinx versus White adults. Among the 70% of adults receptive to screening, 85% were willing to complete a questionnaire and 40% were willing to have staff ask questions; 18% did not want to be screened. Conclusion When implementing social health screening in diverse patient populations, the prevalence of social risks and needs, as well as the acceptability of social health screening and screening modalities, will vary among demographic subgroups.

A cross-sectional study of relationships between social risks and prevalence and severity of pediatric chronic conditions.

BACKGROUND: To examine the differential relationships between seven social risk factors (individually and cumulatively) with the prevalence and severity of asthma, attention deficit hyperactivity disorder (ADHD), autism spectrum disorder (ASD), and overweight/obesity in children. METHODS: Using the 2017-2018 National Survey of Children's Health, we examined associations between social risk factors (caregiver education, caregiver underemployment, discrimination, food insecurity, insurance coverage, neighborhood support, and neighborhood safety) and the prevalence and severity of asthma, ADHD, ASD, and overweight/obesity. We used multivariable logistic regression to assess the relationship between individual and cumulative risk factors with each pediatric chronic condition, controlling for child sex and age. RESULTS: Although each social risk factor was significantly associated with increased prevalence and/or severity of at least one of the pediatric chronic conditions we investigated, food insecurity was significantly associated with higher disease prevalence and severity for all four conditions. Caregiver underemployment, low social support, and discrimination were significantly associated with higher disease prevalence across all conditions. For each additional social risk factor a child was exposed to, their odds of having each condition increased: overweight/obesity (aOR: 1.2, 95% CI: [1.2, 1.3]), asthma (aOR: 1.3, 95% CI: [1.2, 1.3], ADHD (aOR: 1.2, 95% CI: [1.2, 1.3]), and ASD (aOR: 1.4, 95% CI: [1.3, 1.5]). CONCLUSIONS: This study elucidates differential relationships between several social risk factors and the prevalence and severity of common pediatric chronic conditions. While more research is needed, our results suggest that social risks, particularly food insecurity, are potential factors in the development of pediatric chronic conditions.

Unwanted sexual activity among United States women early in the COVID-19 pandemic.

BACKGROUND: Female sexual activity and, accordingly, birth rates tend to decline in times of stress, such as a pandemic. In addition, when resources are scarce or exogenous conditions are threatening, some women may engage in sexual activity primarily to maintain socioeconomic security. Having unwanted sex may indicate sexual activity in exchange for economic security. OBJECTIVE: This study aimed to describe patterns and correlates of unwanted sex, defined as having sex more frequently than desired, among US women early in the COVID-19 pandemic. STUDY DESIGN: The National US Women's Health COVID-19 Study was conducted in April 2020, using a nested quota sample design to enroll 3200 English-speaking women (88% cooperation rate) aged 18 to 90 years recruited from a research panel. The quota strata ensured sufficient sample sizes in sociodemographic groups of interest, namely, racial and ethnic subgroups. Patterns of sexual activity, including unwanted sex early in the pandemic, were described. To further elucidate the experiences of women reporting unwanted sex, open-ended responses to an item querying "how the coronavirus pandemic is affecting your sex life" were assessed using conventional content analysis. Logistic regression analyses-adjusting for sociodemographic characteristics, self-reported health, and prepandemic health-related socioeconomic risk factors, including food insecurity, housing instability, utilities and transportation difficulties, and interpersonal violence-were used to model the odds of unwanted sex by a pandemic-related change in health-related socioeconomic risk factors. RESULTS: The proportion of women who were sexually active early in the pandemic (51%) was about the same as in the 12 months before the pandemic (52%), although 7% of women became active, and 7% of women became inactive. Overall, 11% of sexually active women were having unwanted sex in the early pandemic. The rates of anxiety, depression, traumatic stress symptoms, and each of the 5 health-related socioeconomic risk factors assessed were about 2 times higher among women having unwanted sex than other women (P<.001). Women having unwanted sex were also 5 times more likely than other women to report an increased frequency of sex since the pandemic (65% vs 13%; P<.001) and 6 times more likely to be using emergency contraception (18% vs 3%; P<.001). Women reporting unwanted sex commonly described decreased libido or interest in sex related to mood changes since the pandemic, having "more sex," fear or worry about the transmission of the virus because of sex, and having sex to meet the partner's needs. Among sexually active women, the odds of unwanted sex (adjusting for demographic, reproductive, and health factors) were higher among women with 1 prepandemic health-related socioeconomic risk factor (adjusted odds ratio, 2.0; 95% confidence interval, 1.1-3.8) and 2 or more prepandemic health-related socioeconomic risk factors (adjusted odds ratio, 6.0; 95% confidence interval, 3.4-10.6). Among sexually active women with any prepandemic health-related socioeconomic risk factor, those with new or worsening transportation difficulties early in the pandemic were particularly vulnerable to unwanted sex (adjusted odds ratio, 2.7; 95% confidence interval, 1.7-4.3). CONCLUSION: More than 1 in 10 sexually active US women was having unwanted sex early in the COVID-19 pandemic. Socioeconomically vulnerable women, especially those with new or worsening transportation problems because of the pandemic, were more likely than others to engage in unwanted sex. Pandemic response and recovery efforts should seek to mitigate unwanted sexual activity and related health and social risks among women.