Abstract
Social isolation is associated with higher mortality in studies comprising mostly white adults, yet associations among black adults are unclear. In this prospective cohort study, we ...evaluated whether associations of social isolation with all-cause, cardiovascular disease, and cancer mortality differed by race and sex. Adults enrolled in Cancer Prevention Study II in 1982/1983 were followed for mortality through 2012 (n = 580,182). Sex- and race-specific multivariable-adjusted hazard ratios and 95% confidence intervals were estimated for associations of a 5-point social isolation score with risk of death. Social isolation was associated with all-cause mortality in all subgroups (P for trend ≤ 0.005); for the most isolated versus the least isolated, the hazard ratios were 2.34 (95% confidence interval (CI): 1.58, 3.46) and 1.60 (95% CI: 1.41, 1.82) among black men and white men, respectively (P for interaction = 0.40) and 2.13 (95% CI: 1.44, 3.15) and 1.84 (95% CI: 1.68, 2.01) among black women and white women, respectively (P for interaction = 0.89). The association did not differ between black men and black women (P for interaction = 0.33) but was slightly stronger in white women than in white men (P for interaction = 0.01). Social isolation was associated with cardiovascular disease mortality in each subgroup (P for trend < 0.03) but with cancer mortality only among whites (P for trend < 0.0001). Subgroup differences in the influence of specific social isolation components were identified. Identifying and intervening with socially isolated adults could improve health outcomes.
Social media is an important information source for a growing subset of the population and can likely be leveraged to provide insight into the evolving drug overdose epidemic. Twitter can provide ...valuable insight into trends, colloquial information available to potential users, and how networks and interactivity might influence what people are exposed to and how they engage in communication around drug use.
This exploratory study was designed to investigate the ways in which unsupervised machine learning analyses using natural language processing could identify coherent themes for tweets containing substance names.
This study involved harnessing data from Twitter, including large-scale collection of brand name (N=262,607) and street name (N=204,068) prescription drug-related tweets and use of unsupervised machine learning analyses (ie, natural language processing) of collected data with data visualization to identify pertinent tweet themes. Latent Dirichlet allocation (LDA) with coherence score calculations was performed to compare brand (eg, OxyContin) and street (eg, oxys) name tweets.
We found people discussed drug use differently depending on whether a brand name or street name was used. Brand name categories often contained political talking points (eg, border, crime, and political handling of ongoing drug mitigation strategies). In contrast, categories containing street names occasionally referenced drug misuse, though multiple social uses for a term (eg, Sonata) muddled topic clarity.
Content in the brand name corpus reflected discussion about the drug itself and less often reflected personal use. However, content in the street name corpus was notably more diverse and resisted simple LDA categorization. We speculate this may reflect effective use of slang terminology to clandestinely discuss drug-related activity. If so, straightforward analyses of digital drug-related communication may be more difficult than previously assumed. This work has the potential to be used for surveillance and detection of harmful drug use information. It also might be used for appropriate education and dissemination of information to persons engaged in drug use content on Twitter.
The non-medical use of opioids has reached epidemic levels nationwide, and rural areas have been particularly affected by increasing rates of overdose mortality as well as increases in the prison ...population. Individuals with opioid use disorder (OUD) are at increased risk for relapse and overdose upon reentry to the community due to decreased tolerance during incarceration. It is crucial to identify barriers to substance use disorder treatment post-release from prison because treatment can be particularly difficult to access in resource-limited rural Appalachia.
A social ecological framework was utilized to examine barriers to community-based substance use treatment among individuals with OUD in Appalachian Kentucky following release from prison. Semi-structured qualitative interviews with 15 social service clinicians (SSCs) employed by the Department of Corrections were conducted to identify barriers at the individual, interpersonal, organizational/institutional level, community, and systems levels. Two independent coders conducted line-by-line coding to identify key themes.
Treatment barriers were identified across the social ecological spectrum. At the individual-level, SSCs highlighted high-risk drug use and a lack of motivation. At the interpersonal level, homogenous social networks (i.e., homophilious drug-using networks) and networks with limited treatment knowledge inhibited treatment. SSC's high case load and probation/parole officer's limited understanding of treatment were organizational/institutional barriers. Easy access to opioids, few treatment resources, and a lack of community support for treatment were barriers at the community level. SSC's noted system-level barriers such as lack of transportation options, cost, and uncertainty about the implementation of the Affordable Care Act.
More rural infrastructure resources as well as additional education for family networks, corrections staff, and the community at large in Appalachia are needed to address barriers to OUD treatment. Future research should examine barriers from the perspective of other key stakeholders (e.g., clients, families of clients) and test interventions to increase access to OUD treatment.
Drowning results in more than 360,000 deaths annually, making it the 3rd leading cause of unintentional injury death worldwide. Prior studies examining drowning internationally have reviewed factors ...surrounding drowning however in the U.S. limited data exists. This study evaluated the novel drowning elements collected in the Cardiac Arrest Registry to Enhance Survival (CARES) during the first 2 years of data collection.
A retrospective analysis of the CARES database identified cases of drowning etiology for the two years 2020 and 2021. Demographics and incident characteristics were collected. Characteristics included items such as body of water, precipitating event, and who extracted patients. Survival to hospital discharge and neurological outcomes were compared between groups based on who initiated CPR using Pearson's Chi-Squared tests.
Among 1,767 drowning cases, 69.7% were male, 47.1% white and 11.9% survived to hospital discharge. Body of water was often natural body (36.2%) or swimming pool (25.9%) and bystanders removed the patient in 42.7% of incidents. Swimming was the most common activity at time of submersion (18.6%) however in 50.2% of cases, activity was unknown or missing. When compared to EMS/First Responder initiating CPR, odds of neurologically favorable survival were significantly higher in the Bystander initiated CPR group (OR = 2.85, 95% confidence interval CI 2.02–4.01).
In this national cohort of drowning patients in cardiac arrest, the novel CARES drowning elements provide additional detail of epidemiological factors. Bystander CPR was associated with improved neurological outcomes. Future studies utilizing the drowning elements can inform injury prevention strategies.
The 2-1-1 system is a Federal Communications Commission nationally designated 3-digit telephone information and referral (I&R) system that connects callers with basic needs to health and social ...services in their community. In this issue, Hall et al. suggest the formation of a 2-1-1 Health, Service, Research, and Policy Consortium, and provide a thorough set of recommendations for 2-1-1 systems, researchers, policymakers, and funders, establishing a foundation for collaborative work addressing the health needs of low-income Americans. One of these recommendations is to develop guidelines and lessons learned for researchers looking to collaborate with 2-1-1. This paper provides a starting point for discussions that will establish these guidelines. We look forward to these principles being adapted, refined, and evolving over time as the body of published literature on 2-1-1 expands and as additional scientists and 2-1-1 partners engage in collaborative research. Copyright American Journal of Preventive Medicine; published by Elsevier Inc.
Background Delivering health information and referrals through 2-1-1 is promising, but these systems need efficient ways of identifying callers at increased risk. Purpose This study explores the ...utility of using 2-1-1 service request data to predict callers' cancer control needs. Methods Using data from a large sample of callers (N=4101) to United Way 2-1-1 Missouri, logistic regression was used to examine the relationship between caller demographics and type of service request, and cancer control needs. Results Of six types of service requests examined, three were associated with one or more cancer control needs. Two of the service request types were associated also with health insurance status. Conclusions Findings suggest routinely collected 2-1-1 service request data may be useful in helping to efficiently identify callers with specific cancer prevention and control needs. However, to apply this approach in 2-1-1 systems across the country, further research and ongoing surveillance is necessary.
Callers to 2-1-1 have greater need for and lesser use of cancer control services than other Americans. Integrating cancer risk assessment and referrals to preventive services into 2-1-1 systems is ...both feasible and acceptable to callers.
To determine whether callers will act on these referrals.
In a randomized trial, 2-1-1 callers (n=1200) received standard service and those with at least one cancer risk factor or need for screening were assigned to receive verbal referrals only, verbal referrals + a tailored reminder mailed to their home, or verbal referrals + a telephone health coach/navigator. All data were collected from June 2010 to March 2012 and analyzed in March and April 2012.
At 1-month follow-up, callers in the navigator condition were more likely to report having contacted a cancer control referral than those receiving tailored reminders or verbal referrals only (34% vs 24% vs 18%, respectively; n=772, p<0.0001). Compared to verbal referrals only, navigators were particularly effective in getting 2-1-1 callers to contact providers for mammograms (OR=2.10, 95% CI=1.04, 4.22); Paps (OR=2.98, 95% CI=1.18, 7.54); and smoking cessation (OR=2.07, 95% CI=1.14, 3.74).
Given the extensive reach of 2-1-1s and the elevated risk profile of their callers, even modest response rates could have meaningful impact on population health if proactive health referrals were implemented nationally.
Purpose.
Characterize mobile technology ownership, use, and relationship to self-reported cancer prevention behaviors and health status in a diverse, low-income sample of callers to 2-1-1.
Design.
...Secondary analyses of cross-sectional survey data from a larger trial collected from June 2010 to December 2012.
Setting.
United Way Missouri 2-1-1 serves 99 of 114 counties and received 166,000 calls in 2011.
Subjects.
The respondents (baseline, n = 1898; 4 month, n = 1242) were predominantly female, non-Hispanic Black, younger than 50 years, with high-school education or less and annual income < $20,000.
Measures.
Cell phone ownership and use and its relationship to cancer prevention services and health status were assessed via telephone-based survey, using items adapted from previous research and the Behavioral Risk Factor Surveillance System. Smartphone ownership and use were also assessed.
Analysis.
Descriptive statistics and bivariate and multivariate associations between cell phone ownership and prevention and health status are reported.
Results.
Three-fourths (74%) of study participants owned a cell phone and 23% owned a smartphone. Text messaging was the most popular use. Ownership was significantly associated with good to excellent health status and presence of smoke-free home policies in multivariate models.
Conclusion.
Cell phone ownership is growing and has potential to deliver health information to low-income populations. With 16 million calls annually, the national 2-1-1 system may be a promising model and platform.
Personal social networks have a profound impact on our health, yet collecting personal network data for use in health communication, behavior change, or translation and dissemination interventions ...has proved challenging. Recent advances in social network data collection software have reduced the burden of network studies on researchers and respondents alike, yet little testing has occurred to discover whether these methods are: (1) acceptable to a variety of target populations, including those who may have limited experience with technology or limited literacy; and (2) practical in the field, specifically in areas that are geographically and technologically disconnected, such as rural Appalachian Kentucky.
We explored the early-stage feasibility (Acceptability, Demand, Implementation, and Practicality) of using innovative, interactive, tablet-based network data collection and visualization software (OpenEddi) in field collection of personal network data in Appalachian Kentucky.
A total of 168 rural Appalachian women who had previously participated in a study on the use of a self-collected vaginal swab (SCVS) for human papillomavirus testing were recruited by community-based nurse interviewers between September 2013 and August 2014. Participants completed egocentric network surveys via OpenEddi, which captured social and communication network influences on participation in, and recruitment to, the SCVS study. After study completion, we conducted a qualitative group interview with four nurse interviewers and two participants in the network study. Using this qualitative data, and quantitative data from the network study, we applied guidelines from Bowen et al to assess feasibility in four areas of early-stage development of OpenEddi: Acceptability, Demand, Implementation, and Practicality. Basic descriptive network statistics (size, edges, density) were analyzed using RStudio.
OpenEddi was perceived as fun, novel, and superior to other data collection methods or tools. Respondents enjoyed the social network survey component, and visualizing social networks produced thoughtful responses from participants about leveraging or changing network content and structure for specific health-promoting purposes. Areas for improved literacy and functionality of the tool were identified. However, technical issues led to substantial (50%) data loss, limiting the success of its implementation from a researcher's perspective, and hindering practicality in the field.
OpenEddi is a promising data collection tool for use in geographically isolated and socioeconomically disadvantaged populations. Future development will mitigate technical problems, improve usability and literacy, and test new methods of data collection. These changes will support goals for use of this tool in the delivery of network-based health communication and social support interventions to socioeconomically disadvantaged populations.
In times of crises, 2-1-1 serves as a lifeline in many ways. These crises often cause a spike in call volume that can challenge 2-1-1's ability to meet its service quality standards. For researchers ...gathering data through 2-1-1s, a sudden increase in call volume might reduce accrual as 2-1-1 has less time to administer study protocols. Research activities imbedded in 2-1-1 systems may affect directly 2-1-1 service quality indicators.
Using data from a 2-1-1 research collaboration, this paper examines the impact of crises on call volume to 2-1-1, how call volume affects research participant accrual through 2-1-1, and how research recruitment efforts affect 2-1-1 service quality indicators.
t-tests were used to examine the effect of call volume on research participant accrual. Linear and logistic regressions were used to examine the effect of research participant accrual on 2-1-1 service quality indicators. Data were collected June 2010-December 2011; data were analyzed in 2012.
Findings from this collaboration suggest that crises causing spikes in call volume adversely affect 2-1-1 service quality indicators as well as accrual of research participants. Administering a brief (2-3 minute) health risk assessment did not affect service quality negatively, but administering a longer (15-18 minute) survey had a modest adverse effect on these indicators.
In 2-1-1 research collaborations, both partners need to understand the dynamic relationship among call volume, research accrual, and service quality and adjust expectations accordingly. If research goals include administering a longer survey, increased staffing of 2-1-1 call centers may be needed to avoid compromising service quality.
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