19 research outputs found
Age-related changes in the relationship between alcohol use and violence from early adolescence to young adulthood
BACKGROUND: Despite the accumulation of studies examining the link between alcohol use and violence, no studies to our knowledge have systematically set out to detect age-related differences in these relationships. This limitation inhibits important insights into the stability of the relationship between alcohol use and violence among youth across varying ages.
METHOD: Study findings are based on repeated, cross-sectional data collected annually as part of the National Survey on Drug Use and Health between 2002 and 2013. We combined a series of nationally representative cross-sections to provide a multi-year string of data that, in effect, reflects a nationally representative non-traditional cohort. We conducted logistic regression analyses to examine the cross-sectional association between non-binge and binge drinking and violent attacks among youth between ages 12 (2002) and 24/25 (2013).
RESULTS: With respect to the association between non-binge alcohol use and violence, the only significant relationship identified—while controlling for sociodemographic and drug use factors—was for youth at age 13 (2003; OR = 1.97, 95% CI = 1.04–3.72). For binge drinking, we identified a distinct pattern of results. Controlling for sociodemographic, drug use factors, and school enrollment, binge drinking was significantly associated with violence between ages 13 (2003) and 20 (2010) with the largest odds ratios observed during the early adolescent period.
CONCLUSIONS: Non-binge drinking is associated with violent behavior at age 13. Binge drinking was found to be associated with violence among youth through age 20; however, the relationship dissipates when youth arrive at the legal drinking age of 21
Differences in Suicidality in Non–Treatment-Seeking and Treatment-Seeking Law Enforcement Officers: A Cross-sectional Study
Objective: Law enforcement officers (LEOs) are exposed to high levels of occupational trauma and face added stress from heightened public scrutiny and COVID-19, which may result in suicide. It is crucial to understand differences between LEOs who seek treatment and those who do not. Method: We compared LEOs from the same greater metropolitan area who sought treatment with those who did not. Participants completed validated measures assessing posttraumatic stress disorder, generalized anxiety, depression, and suicidality. Results: The treatment-seeking sample scores were higher on all standardized assessments. Bivariate logistic regression results indicated that the non–treatment-seeking sample\u27s odds of experiencing suicidality were 1.76 times the odds for the treatment seeking sample. Conclusions: This suggests that many LEOs experiencing suicidality may not be seeking treatment and highlights the role that posttraumatic stress disorder may play in determining whether LEOs seek treatment or not
Towards the development of a screening tool to enhance the detection of elder abuse and neglect by emergency medical technicians (EMTs): a qualitative study
Patient-Reported Barriers to Completing a Diagnostic Colonoscopy Following Abnormal Fecal Immunochemical Test Among Uninsured Patients
Bullying perpetration and victimization: The longidutinal relationship between bullying, reported injuries, and school absence among a cohort of children
Objective: The objective of this dissertation was to determine how the relationship between bullying and injury change over time and identify factors that influence those changes. More specifically, the three manuscripts that comprise this dissertation expanded our knowledge of self-reporting practices of bullying perpetration and victimization, evaluated the relationship between bullying, overall and intentional injury, and school absence, and assessed whether key mediating variables (substance use, depressive symptoms, weapon carrying) explained indirect pathways between bullying and violent injury. Methods: Healthy Passages was a longitudinal study of youth in 5th, 7th, and 10th grades and their primary caregivers during across three United States sites (Houston, Texas; Birmingham, Alabama; and Los Angeles, California) from 2002 to 2011. The sampling frame for Healthy Passages included all students enrolled in regular classrooms in public schools with an enrollment of at least 25 students (more than 99% of all regular classrooms in 118 public schools). Of the 11,532 parents contacted at baseline, 6,663 (58%) agreed to be contacted for the study and 5,147 (77%) of them completed an interview. A total of 4,296 children were interviewed in all three waves. At each wave of data collection, children were categorized into four mutually exclusive groups: ‘victim only’, ‘perpetrator only’, ‘victim-perpetrator’, and ‘neither victim nor perpetrator’. Mixed-effect regression models were used to test study hypotheses. Results: Results from Paper 1 suggested discordant victimization and perpetration reporting between a single-item recall measure and a multiple-item measure. Specifically, discordant victimization decreased over time, was higher among Blacks and boys. Discordant perpetration increased over time, was higher among Blacks and boys. In Paper 2, significant patterns in bullying perpetration and violent injury over time. Specifically, the more often a child reported being a bully perpetrator, the more likely they were to be absent from school and sustain a violent injury. There was no relationship between bullying group and overall injury. Finally, results from Paper 3 showed substance use and weapon carrying indirectly explained the relationship between bullying groups and intentional violent injury. Conclusion: By assessing the longitudinal relationship between bullying, school absence, and injury, we were able to advance our understanding of their complex inter-relationships. Future research should cognitively test bullying perpetration and victimization measures among a diverse group of children. Bullying prevention efforts should aim to include substance use, weapon carrying, and violent injury modules to maximize efforts and to prevent downstream consequences in children’s lives
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COVID-19 related employment change is associated with increased alcohol consumption during the pandemic
Dissecting the Complexities of the Relationship Between Police Officer–Civilian Race/Ethnicity Dyads and Less-Than-Lethal Use of Force
Objectives. To examine how sublethal use-of-force patterns vary across officer–civilian race/ethnicity while accounting for officer-, civilian-, and situational-level factors.
Methods. We extracted cross-sectional data from 5630 use-of-force reports from the Dallas Police Department in 2014 and 2015. We categorized each officer–civilian interaction into race/ethnicity dyads. We used multilevel, mixed logistic regression models to evaluate the relationship between race/ethnicity dyads and the types of use of force.
Results. Forty-eight percent of use-of-force interactions occurred between a White officer and a non-White civilian (White–non-White). In bivariate models, the odds of hard-empty hand control and intermediate weapon use were significantly higher among White–Black dyads compared with White–White dyads. The bivariate odds of intermediate weapon use were also significantly higher among Black–Black, Hispanic–White, Black–Hispanic, and Hispanic–Black dyads compared with White–White dyads. However, after we controlled for individual and situational factors, the relationship between race/ethnicity dyad and hard-empty hand control was no longer significant.
Conclusions. Although we observed significant bivariate relationships between race/ethnicity dyads and use of force, these relationships largely dissipated after we controlled for other factors
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Patient-Reported Barriers to Completing a Diagnostic Colonoscopy Following Abnormal Fecal Immunochemical Test Among Uninsured Patients.
BackgroundFor colorectal cancer (CRC) screening to improve survival, patients with an abnormal fecal immunochemical test (FIT) must follow-up with a diagnostic colonoscopy. Adherence to follow-up is low and patient-level barriers for suboptimal adherence have yet to be explored.ObjectiveTo characterize barriers for non-completion of diagnostic colonoscopy after an abnormal FIT reported by under- and uninsured patients receiving care in a safety-net health system.DesignA longitudinal, cohort study of CRC screening outreach to 8565 patients using mailed FIT kits. Patients with abnormal FIT results received telephonic navigation to arrange for a no-cost diagnostic colonoscopy.PatientsAdults aged 50-64 years receiving care at a North Texas safety-net health system.ApproachDescriptive analyses characterized the patient sample and reasons for lack of follow-up after abnormal FIT over the 3-year outreach program. Thematic qualitative analyses characterized reasons for lack of follow-up with a colonoscopy after the abnormal FIT.Key resultsOf 689 patients with an abnormal FIT, 45% (n = 314) did not complete a follow-up colonoscopy. Among the 314 non-completers, 184 patients reported reasons for not completing a follow-up colonoscopy included health insurance-related challenges (38%), comorbid conditions (37%), social barriers such as transportation difficulties and lack of social support (29%), concerns about FIT/colonoscopy process (12%), competing life priorities (12%), adverse effects of bowel preparation (3%), and poor health literacy (3%). Among the 314 non-completers, 131 patients did not report a barrier, as 51% reported that that had completed a previous colonoscopy in the past 10 years, 10% refused with no reason, and 10% were never reached by phone.ConclusionsFuture studies aimed at improving FIT screening and subsequent colonoscopy rates need to address the unique needs of patients for effective and sustainable screening programs.Trial registrationNCT01946282
Factors Influencing the Implementation of Social Determinants of Health Screening and Referral Processes in Pediatric Settings Serving Medically Complex Patients
Background: Equitable healthcare outcomes are compromised in the absence of strong medical care and social services linkages. In May 2019, Children’s Health, the largest health system for pediatric care in North Texas, initiated a three-pronged social determinants of health (SDOH) quality improvement (QI) project that included: 1) baseline and ongoing clinical team training; 2) implementation of an electronic health record (EHR)-embedded SDOH screening tool; and 3) patient referrals to community resources in three inpatient hospital units and one outpatient specialty clinic serving medically complex patients. The purpose of the study is to identify hospital unit/clinic-level implementation factors associated with effective utilization of a SDOH screening tool newly introduced into the clinical setting and outcomes associated with this screening such as referrals to community-based organizations.
Methods: A mixed-methods, descriptive study was conducted in the following four pediatric care settings: (1) intensive care unit (PICU); (2) acute, long-term hospitalized patients (LTP); (3) inpatient multi-specialty step-down facility serving patients with special healthcare needs (SHCN); and (4) cystic fibrosis clinic (CF). Quantitative measurement tools (i.e. clinical care team pre/post surveys, EHR data) were merged with focus groups to elucidate factors influencing implementation. The Consolidated Framework of Implementation Research guided assessment.
Results: Of the 506 eligible patients, SDOH screening rates (PICU=42%; CF=76%; LTP=85%; SHCN=93%) and referral to community resources rates (PICU=20%; CF=46%; SHCN=52%; LTP=91%) significantly differed across the various hospital units. Among the clinical care team surveys, PICU clinical team members reported significantly lower baseline confidence to discuss SDOH (mean=2.93; SD=0.95) and significantly lower knowledge of SDOH (mean=2.66; SD= 0.88) compared to the three other clinics. Qualitative data indicated that all hospital units prioritized the intervention, had clinical champions, and used thoughtful planning. Screening and referral rate differences were attributed to several factors; (1) settings (e.g., inpatient vs. outpatient setting, resistance to change); (2) individual characteristics (e.g., self-efficacy, baseline confidence, licensure of implementer); and (3) intervention characteristics (e.g. adaptability, compatibility).
Conclusions: Results suggest that the successful implementation of a SDOH screener in pediatric health care settings serving medically complex patients is a multifaceted process involving multilevel factors. These findings can guide feasibility of further dissemination and scalability efforts in particular