The relationship between older adults' technology use, in-person engagement, and pandemic-related mental health.

OBJECTIVE: The objectives of this study are to 1) describe changes in in-person communication/activity and changes in older adult technology use during the COVID-19 pandemic and 2) examine whether less in-person communication/activity mediates the relationship between pandemic-related mental health and technology use. METHOD: Linear regressions (stratified by age and financial strain) and structural equation modeling were employed using a nationally representative, cross-sectional survey of 3,188 older adults from the 2020 National Health and Aging Trends Study's COVID-19 Questionairre. RESULTS: Older adults engaged in more technology-based activity (b = 0.24; p<.001), more technology-based health care communication (b = 0.22; p<.001), and more technology-based food acquisition (b = 0.21; p<.001) during the COVID-19 pandemic, as compared to before the pandemic. Results indicate that adults <80 years old demonstrated greater increases in technology-based activity, technology-based health communication, and technology-based food acquisition, compared to adults ≥80 years old. Change in in-person communication significantly mediated the relationship between pandemic-related mental health and technology-based communication (standardized coefficient= -0.012; p=.005), and change in in-person activity significantly mediated the relationship between pandemic-related mental health and technology-based activity (standardized coefficient= -0.017; p=.020). CONCLUSIONS: This study suggests that older adults are utilizing technology more, and therefore should be considered in technology design and dissemination. Technology use could be an important positive response to help those with pandemic related worries stay safely engaged with friends and family. Technologies should be produced that are modifiable for older adults with disabilities and affordable for older adults with fixed incomes.

Opioid-related variables did not improve suicide risk prediction models in samples with mental health diagnoses.

Background: Suicide risk prediction models derived from machine learning of electronic health records and insurance claims are an innovation in suicide prevention. Some models do not include opioid-related variables despite the relationship between opioids and suicide. This study evaluated whether inclusion of opioid-related variables improved suicide risk prediction models developed by the Mental Health Research Network. Methods: Approximately 630 opioid-related variables and interactions terms were introduced into existing suicide prediction models run in datasets of patient visits in mental health care (n = 27,755,401 visits) or primary care when a mental health diagnosis was given (n = 19,340,461 visits). Training and validation datasets were created. LASSO regression with 10-fold validation identified variables to be added to the models. Results: The new models predicting suicide attempts and suicide deaths in the mental health specialty visit sample performed as well as the existing models (new C-statistic for attempts model = 0.855, CI: 0.853-0.857 versus original C-statistic = 0.851, CI 0.848-0.853; death model = 0.868, CI: 0.856-0.879 versus 0.861, CI 0.848-0.875). The new model for suicide death in the primary care sample improved (0.855, CI: 0.837-0.874 versus 0.833, CI 0.813-0.853) while performance of the new model for suicide attempt in that sample degraded (0.843, CI: 0.839-0.847 versus 0.853, CI 0.849-0.857). Limitations: Analyses did not include patients without recent care, data did not include illicit opioid use or unrecognized opioid use disorder. Conclusions: Among patients with mental health diagnoses, inclusion of opioid-related variables did not improve prediction of suicide risk beyond mental health predictors.

Measuring social norms and attitudes about age-disparate transactional sex: Psychometric testing of the NAATSS.

Background: Transactional sex between girls under 18 years-old and adult men at least ten years older, known as age-disparate transactional sex (ADTS), is an established risk factor for HIV, STI and early pregnancy among girls and women. Social norms or beliefs about what others expect from you and what others do can sustain behaviours such as ADTS even when individuals may be personally against them. In order to evaluate interventions to change social norms, validated instruments for measuring change in personal beliefs and social norms regarding ADTS are needed. Methods: Items for the Norms and Attitudes on Age-Disparate Transactional Sex Scale (NAATSS) were generated based on qualitative interviews and expert panel review. The reliability and validity of the NAATSS was tested in a representative sample (N = 431) from Brazilian favelas. Factor analysis assessed construct validity, Cronbach's alpha assessed reliability, and t-tests and analysis of variances tested hypothesized differences between gender, age, and previous experience with ADTS in both the social norms and personal beliefs domains. Findings: Factor analysis revealed three factors in each domain. The factors were labelled "Attributions to Girls' Behaviour" which has 5 items, "Men's Motivations" with 5 items, and "Girls' Readiness to have Sex" with 3 items. The subscales evidenced acceptable reliability with Cronbach's alphas ranging from 0.72 to 0.83 for the social norms subscales and 0.59 to 0.82 for the personal beliefs subscales. Interpretation: The items were developed based on qualitative research and expert rankings and the resulting Norms and Attitudes on ADTS Scale exhibits strong psychometric properties. Each of the three subscales within the two domains illustrate good factor structure, acceptable internal consistency reliability, and are supported by the significance of the hypothesized group differences. Funding: This work was supported by the OAK Foundation [grant number OCAY-16-188].

Longitudinal Impact of the myPlan App on Health and Safety Among College Women Experiencing Partner Violence.

The objective of this study was to examine differences in change over time in health and safety outcomes among female college students randomized to myPlan, a tailored safety planning app, or usual web-based safety planning resources. Three hundred forty-six women (175 intervention, 171 control) from 41 colleges/universities in Oregon and Maryland completed surveys at baseline, 6- and 12-months from July 2015 to October 2017. Generalized estimating equations were used to test group differences across time. Both groups improved on four measure of intimate partner violence (IPV; Composite Abuse Scale [CAS], TBI-related IPV, digital abuse, reproductive coercion [RC]) and depression. Reduction in RC and improvement in suicide risk were significantly greater in the myPlan group relative to controls (p = .019 and p = .46, respectively). Increases in the percent of safety behaviors tried that were helpful significantly reduced CAS scores, indicating a reduction in IPV over time in the myPlan group compared to controls (p = .006). Findings support the feasibility and importance of technology-based IPV safety planning for college women. myPlan achieved a number of its objectives related to safety planning and decision-making, the use of helpful safety behaviors, mental health, and reductions in some forms of IPV.

Correlates of reproductive coercion among college women in abusive relationships: baseline data from the college safety study.

ObjectiveThe purpose of this study was to examine correlates of reproductive coercion (RC) among a sample of college women in abusive relationships. Participants: 354 college students reporting a recent history of intimate partner violence (IPV). Methods: This study examines baseline data from a randomized controlled trial testing effectiveness of an interactive safety decision aid (myPlan). Results: Almost a quarter (24.3%) of the sample reported RC. Associated factors included races other than White (p = 0.019), relationship instability (p = 0.022), missing class due to relationship problems (p = 0.001), IPV severity (p < 0.001), technology abuse (p < 0.001), traumatic brain injury-associated events (p < 0.001), and depression (p = 0.024). Conclusions: RC was a significant predictor of depression, with implications for providers working with abused college women regarding the need for mental health services concurrent with IPV/RC services. A larger proportion of women who experienced RC sought help from a healthcare provider for contraception, which suggests intervention opportunities for college health providers.

Objectively measured sleep and physical function: Associations in low-income older adults with disabilities.

OBJECTIVE: Late-life sleep health has been tied to physical function, but little is known about these associations among socially disadvantaged populations. DESIGN: We determined cross-sectional associations of sleep with physical function in low-income, predominantly Black older adults with disabilities. PARTICIPANTS: One hundred thirty-six older adults (mean age 76.0 years, 83.8% women, 82.4% Black). MEASUREMENTS: Primary predictors were actigraphic total sleep time (TST), wake after sleep onset (WASO), and subjective sleep complaints. Outcomes were objective physical performance (Short Physical Performance Battery (SPPB)) and participant-reported difficulties in basic and instrumental activities of daily living (ADLs and IADLs). RESULTS: In regression models adjusted for potential confounders, both longer TST and greater WASO were associated with lower SPPB scores and increased IADL difficulty. Participants with a mean TST in the longest (>7.5 hours) vs. intermediate (6.3-7.5 hours) tertile had 27% higher odds of additional IADL difficulty (incident rate ratio = 1.27, 95% confidence interval [CI] 1.03, 1.58). Each additional 10 minutes of WASO was associated with 0.13 point lower SPPB scores (B = -0.13, 95% CI -0.25, -0.01) and increased IADL difficulty (B = 0.02, 95% CI 0.0003, 0.04). Sex moderated the associations of WASO with IADL and ADL difficulties: associations were stronger for males. Subjective sleep complaints were not statistically significantly associated with function. CONCLUSIONS: Among disabled, low-income, mostly Black older adults, objective measures of long sleep and greater WASO are associated with poorer physical function. Effect sizes for the associations were modest; however, findings may have important implications given the significant consequences of decreased function on quality of life and caregiving demands.

Exterior housing conditions are associated with objective measures of poor sleep among low-income older adults with disabilities.

OBJECTIVE: To examine the association of housing and neighborhood conditions with sleep among disadvantaged older adults. METHODS: We used data from 136 low-income, predominantly Black older adults with disabilities. Predictors were indices of: interior housing conditions (eg, pests, tripping hazards); exterior housing conditions (eg, broken windows); and neighborhood disorder (eg, litter, vacant buildings). Outcomes were actigraphic total sleep time (TST), wake after sleep onset (WASO), and sleep efficiency (SE). RESULTS: In models adjusted for age, sex, education, living arrangement, comorbidities, and physical performance, each additional exterior housing problem was associated with 20.9-minutes less TST (95% confidence interval [CI]: -39.2, -2.6), 8.6-minutes more WASO (95% CI: 0.7, 16.5), and 2.3% lower SE (95% CI: -4.2, -0.4). The associations of interior housing conditions and neighborhood disorder with the sleep parameters were of smaller magnitude and not statistically significant. CONCLUSIONS: Future studies should examine the effects of housing repair on sleep health.

A Comparison of Safety, Health, and Well-Being Risk Factors Across Five Occupational Samples.

Objective: The aim of this study was to present safety, health and well-being profiles of workers within five occupations: call center work (N = 139), corrections (N = 85), construction (N = 348), homecare (N = 149), and parks and recreation (N = 178). Methods: Baseline data from the Data Repository of Oregon's Healthy Workforce Center were used. Measures were compared with clinical healthcare guidelines and national norms. Results: The prevalence of health and safety risks for adults was as follows: overweight (83.2%), high blood pressure (16.4%), injury causing lost work (9.9%), and reported pain (47.0%). Young workers were least likely to report adequate sleep (46.6%). Construction workers reported the highest rate of smoking (20.7%). All of the adult workers reported significantly lower general health than the general population. Conclusion: The number of workers experiencing poor safety, health and well-being outcomes suggest the need for improved working conditions.

Patterns and Usefulness of Safety Behaviors Among Community-Based Women Survivors of Intimate Partner Violence.

Women who experience intimate partner violence (IPV) use a variety of safety strategies to reduce the frequency and severity of violence, including both informal and formal help-seeking. The purpose of this study was to identifying patterns of engagement in safety behaviors by U.S. women from outside of formal service settings, examine which factors are associated with different patterns of use, and examine the perceived usefulness of safety strategies among women who used them. Cross-sectional data from 725 women experiencing IPV were used for these analyses. A cluster analysis revealed three clusters of safety behavior use among the IPV survivors: Exploring Safety Options, Avoiding the Justice System, and Trying Everything. The trying everything cluster had high rates of use across all of the safety behaviors; they also reported the highest levels of physical, sexual, and psychological IPV. The exploring safety options cluster used the fewest safety behaviors and had the lowest level of IPV. Higher violence was related to a higher likelihood of finding safety planning helpful and a lower likelihood of finding leaving home helpful. Women who were currently living with their partner were less likely to find talking with a professional, making a safety plan, or leaving home helpful. Higher decisional conflict-uncertainty about what safety decisions would be best-was almost universally related to greater likelihood of not finding safety behaviors helpful. The study findings reinforce the importance of working with survivors to tailor safety plans with strategies that reflect their situation, and provide insights into for which tailoring of resource recommendations may be made.

Distinct clusters of older adults with common neuropsychological symptoms: Findings from the National Health and Aging Trends Study.

This study aims to identify distinct clusters of community-dwelling older adults (N = 7580) based on characteristics of common neuropsychological symptoms and examine how these clusters differ in socio-demographics and health-related attributes. Four clusters were identified: 1-No Symptoms (41%), 2-Pain Only (32%), 3-Pain+Moderate+Insomnia+Mild Depression+Mild Anxiety (17%), and 4-Pain+Mild insomnia+Moderate Depression+Moderate Anxiety (10%). Compared to clusters 1 and 2, individuals in clusters 3 and 4 tended to be older, Hispanic or non-Hispanic Black, female, obese, have high school education or less, not live with anyone, and rate their health fair or poor. Compared to cluster 1, others were significantly associated with worse health-related attributes. This association was distinctly stronger in clusters with more symptoms that were more severe. Interventions focusing on pain may need to incorporate strategies to deal with sleep and psychological symptoms and the severity to improve associated health-related attributes and reduce health care burden.

Using natural language processing of clinical text to enhance identification of opioid-related overdoses in electronic health records data.

PURPOSE: To enhance automated methods for accurately identifying opioid-related overdoses and classifying types of overdose using electronic health record (EHR) databases. METHODS: We developed a natural language processing (NLP) software application to code clinical text documentation of overdose, including identification of intention for self-harm, substances involved, substance abuse, and error in medication usage. Using datasets balanced with cases of suspected overdose and records of individuals at elevated risk for overdose, we developed and validated the application using Kaiser Permanente Northwest data, then tested portability of the application using Kaiser Permanente Washington data. Datasets were chart-reviewed to provide a gold standard for comparison and evaluation of the automated method. RESULTS: The method performed well in identifying overdose (sensitivity = 0.80, specificity = 0.93), intentional overdose (sensitivity = 0.81, specificity = 0.98), and involvement of opioids (excluding heroin, sensitivity = 0.72, specificity = 0.96) and heroin (sensitivity = 0.84, specificity = 1.0). The method performed poorly at identifying adverse drug reactions and overdose due to patient error and fairly at identifying substance abuse in opioid-related unintentional overdose (sensitivity = 0.67, specificity = 0.96). Evaluation using validation datasets yielded significant reductions, in specificity and negative predictive values only, for many classifications mentioned above. However, these measures remained above 0.80, thus, performance observed during development was largely maintained during validation. Similar results were obtained when evaluating portability, although there was a significant reduction in sensitivity for unintentional overdose that was attributed to missing text clinical notes in the database. CONCLUSIONS: Methods that process text clinical notes show promise for improving accuracy and fidelity at identifying and classifying overdoses according to type using EHR data.

Identifying and classifying opioid-related overdoses: A validation study.

PURPOSE: The study aims to develop and validate algorithms to identify and classify opioid overdoses using claims and other coded data, and clinical text extracted from electronic health records using natural language processing (NLP). METHODS: Primary data were derived from Kaiser Permanente Northwest (2008-2014), an integrated health care system (~n > 475 000 unique individuals per year). Data included International Classification of Diseases, Ninth Revision (ICD-9) codes for nonfatal diagnoses, International Classification of Diseases, Tenth Revision (ICD-10) codes for fatal events, clinical notes, and prescription medication records. We assessed sensitivity, specificity, positive predictive value, and negative predictive value for algorithms relative to medical chart review and conducted assessments of algorithm portability in Kaiser Permanente Washington, Tennessee State Medicaid, and Optum. RESULTS: Code-based algorithm performance was excellent for opioid-related overdoses (sensitivity = 97.2%, specificity = 84.6%) and classification of heroin-involved overdoses (sensitivity = 91.8%, specificity = 99.0%). Performance was acceptable for code-based suicide/suicide attempt classifications (sensitivity = 70.7%, specificity = 90.5%); sensitivity improved with NLP (sensitivity = 78.7%, specificity = 91.0%). Performance was acceptable for the code-based substance abuse-involved classification (sensitivity = 75.3%, specificity = 79.5%); sensitivity improved with the NLP-enhanced algorithm (sensitivity = 80.5%, specificity = 76.3%). The opioid-related overdose algorithm performed well across portability assessment sites, with sensitivity greater than 96% and specificity greater than 84%. Cross-site sensitivity for heroin-involved overdose was greater than 87%, specificity greater than or equal to 99%. CONCLUSIONS: Code-based algorithms developed to detect opioid-related overdoses and classify them according to heroin involvement perform well. Algorithms for classifying suicides/attempts and abuse-related opioid overdoses perform adequately for use for research, particularly given the complexity of classifying such overdoses. The NLP-enhanced algorithms for suicides/suicide attempts and abuse-related overdoses perform significantly better than code-based algorithms and are appropriate for use in settings that have data and capacity to use NLP.

Fall Ascertainment and Development of a Risk Prediction Model Using Electronic Medical Records.

OBJECTIVES: To examine the use of electronic medical record (EMR) data to ascertain falls and develop a fall risk prediction model in an older population. DESIGN: Retrospective longitudinal study using 10 years of EMR data (2004-2014). A series of 3-year cohorts included members continuously enrolled for a minimum of 3 years, requiring 2 years pre-fall (no previous record of a fall) and a 1-year fall risk period. SETTING: Kaiser Permanente Hawaii, an ambulatory setting. PARTICIPANTS: A total of 57 678 adults, age 60 years and older. MEASUREMENTS: Initial EMR searches were guided by current literature and geriatricians to understand coding sources of falls as our outcome. Falls were captured by two coding sources: International Classification of Diseases, Ninth Revision (ICD-9) codes (E880-889) and/or a fall listed as a "primary reason for visit." A comprehensive list of EMR predictors of falls were included into prediction models enabling statistical subset selection from many variables and modeling by logistic regression. RESULTS: Although 72% of falls in the training data set were coded as "primary reason for visit," 22% of falls were coded as ICD-9 and 6% coded as both. About 80% were reported in face-to-face encounters (eg, emergency department). A total of 2164 individuals had a fall in the risk period. Using the 13 key predictors (age, comorbidities, female sex, other mental disorder, walking issues, Parkinson's disease, urinary incontinence, depression, polypharmacy, psychotropic and anticonvulsant medications, osteoarthritis, osteoporosis) identified through LASSO regression, the final model had a sensitivity of 67%, specificity of 69%, positive predictive value of 8%, negative predictive value of 98%, and area under the curve of .74. CONCLUSION: This study demonstrated how the EMR can be used to ascertain falls and develop a fall risk prediction model with moderate sensitivity/specificity. Concurrent work with clinical providers to enhance fall documentation will improve the ability of the EMR to capture falls and consequently may improve the model to predict fall risk.

How Equity-Oriented Health Care Affects Health: Key Mechanisms and Implications for Primary Health Care Practice and Policy.

Policy Points A consensus regarding the need to orient health systems to address inequities is emerging, with much of this discussion targeting population health interventions and indicators. We know less about applying these approaches to primary health care. This study empirically demonstrates that providing more equity-oriented health care (EOHC) in primary health care, including trauma- and violence-informed, culturally safe, and contextually tailored care, predicts improved health outcomes across time for people living in marginalizing conditions. This is achieved by enhancing patients' comfort and confidence in their care and their own confidence in preventing and managing health problems. This promising new evidence suggests that equity-oriented interventions at the point of care can begin to shift inequities in health outcomes for those with the greatest need. CONTEXT: Significant attention has been directed toward addressing health inequities at the population health and systems levels, yet little progress has been made in identifying approaches to reduce health inequities through clinical care, particularly in a primary health care context. Although the provision of equity-oriented health care (EOHC) is widely assumed to lead to improvements in patients' health outcomes, little empirical evidence supports this claim. To remedy this, we tested whether more EOHC predicts more positive patient health outcomes and identified selected mediators of this relationship. METHODS: Our analysis uses longitudinal data from 395 patients recruited from 4 primary health care clinics serving people living in marginalizing conditions. The participants completed 4 structured interviews composed of self-report measures and survey questions over a 2-year period. Using path analysis techniques, we tested a hypothesized model of the process through which patients' perceptions of EOHC led to improvements in self-reported health outcomes (quality of life, chronic pain disability, and posttraumatic stress [PTSD] and depressive symptoms), including particular covariates of health outcomes (age, gender, financial strain, experiences of discrimination). FINDINGS: Over a 24-month period, higher levels of EOHC predicted greater patient comfort and confidence in the health care patients received, leading to increased confidence to prevent and manage their health problems, which, in turn, improved health outcomes (depressive symptoms, PTSD symptoms, chronic pain, and quality of life). In addition, financial strain and experiences of discrimination had significant negative effects on all health outcomes. CONCLUSIONS: This study is among the first to demonstrate empirically that providing more EOHC predicts better patient health outcomes over time. At a policy level, this research supports investments in equity-focused organizational and provider-level processes in primary health care as a means of improving patients' health, particularly for those living in marginalizing conditions. Whether these results are robust in different patient groups and across a broader range of health care contexts requires further study.

Lifetime prevalence, correlates and health consequences of gender-based violence victimisation and perpetration among men and women in Somalia.

BACKGROUND: Humanitarian emergencies increase the risk of gender-based violence (GBV). We estimated the prevalence of GBV victimisation and perpetration among women and men in urban settings across Somalia, which has faced decades of war and natural disasters that have resulted in massive population displacements. METHODS: A population-based survey was conducted in 14 urban areas across Somalia between December 2014 and November 2015. RESULTS: A total of 2376 women and 2257 men participated in the survey. One in five men (22.2%, 95% CI 20.5 to 23.9) and one in seven (15.5%; 95% CI 14.1 to 17.0) women reported physical or sexual violence victimisation during childhood. Among women, 35.6% (95% CI 33.4 to 37.9) reported adult lifetime experiences of physical or sexual intimate partner violence (IPV) and 16.5% (95% CI 15.1 to 18.1) reported adult lifetime experience of physical or sexual non-partner violence (NPV). Almost one-third of men (31.2%; 95% CI 29.4 to 33.1) reported victimisation as an adult, the majority of which was physical violence. Twenty-two per cent (21.7%; 95% CI 19.5 to 24.1) of men reported lifetime sexual or physical IPV perpetration and 8.1% (95% CI 7.1 to 9.3) reported lifetime sexual or physical NPV perpetration. Minority clan membership, displacement, exposure to parental violence and violence during childhood were common correlates of IPV and NPV victimisation and perpetration among women and men. Victimisation and perpetration were also strongly associated with recent depression and experiences of miscarriage or stillbirth. CONCLUSION: GBV is prevalent and spans all regions of Somalia. Programmes that support nurturing environments for children and provide health and psychosocial support for women and men are critical to prevent and respond to GBV.

Experiences of Racism and Preterm Birth: Findings from a Pregnancy Risk Assessment Monitoring System, 2004 through 2012.

BACKGROUND: Racial disparities in birth outcomes represent a significant public health concern in the United States. Factors associated with racism have been posited as a mechanism underlying these disparities. Yet, findings from previous studies are mixed and based on small, geographically limited samples. This study aims to examine the relationship between experiences of racism and preterm birth in a population-based sample and to explore the role of adequacy of prenatal care within that relationship. METHODS: Data from the 2004 through 2012 Pregnancy Risk Assessment Monitoring System were analyzed. The sample included non-Hispanic Black mothers from 11 states and New York City who delivered neonates from 2004 to 2012 (n = 11,582). Survey-weighted regression analyses were used to examine the association between women feeling upset by experiences of racism in the 12 months before delivery and subsequent preterm birth. Adequacy of prenatal care was tested as an effect modifier. RESULTS: Feeling upset by experiences of racism was significantly associated with greater odds of preterm birth (adjusted odds ratio, 1.29; 95% CI, 1.04-1.59). Results from interaction models revealed that the associations of experiences of racism with preterm birth differed by level of prenatal care, although the interaction term was not significant. CONCLUSIONS: Findings suggest that, for non-Hispanic Black women, the emotional effect of experiences of racism may contribute to the risk of preterm birth. Future studies should consider the role of adequate prenatal care in this relationship. Racism is an important public health problem with a measurable impact on preterm birth and should be addressed to eliminate racial inequities in birth outcomes.

Effects of primary care clinician beliefs and perceived organizational facilitators on the delivery of preventive care to individuals with mental illnesses.

BACKGROUND: Although many studies have documented patient-, clinician-, and organizational barriers/facilitators of primary care among people with mental illnesses, few have examined whether these factors predict actual rates of preventive service use. We assessed whether clinician behaviors, beliefs, characteristics, and clinician-reported organizational characteristics, predicted delivery of preventive services in this population. METHODS: Primary care clinicians (n = 247) at Kaiser Permanente Northwest (KPNW) or community health centers and safety-net clinics (CHCs), in six states, completed clinician surveys in 2014. Using electronic health record data, we calculated preventive care-gap rates for patients with mental illnesses empaneled to survey respondents (n = 37,251). Using separate multi-level regression models for each setting, we tested whether survey responses predicted preventive service care-gap rates. RESULTS: After controlling for patient-level characteristics, patients of clinicians who reported a greater likelihood of providing preventive care to psychiatrically asymptomatic patients experienced lower care-gap rates (KPNW γ= - .05, p = .041; CHCs γ= - .05, p = .033). In KPNW, patients of female clinicians had fewer care gaps than patients of male clinicians (γ= - .07, p = .011). In CHCs, patients of clinicians who had practiced longer had fewer care gaps (γ= - .004, p = .010), as did patients whose clinicians believed that organizational quality goals facilitate preventive service provision (γ= - .06, p = .006). Case manager availability in CHCs was associated with higher care-gap rates (γ=.06, p = .028). CONCLUSIONS: Clinicians who report they are likely to address preventive concerns when their mentally ill patients present without apparent psychiatric symptoms had patients with fewer care gaps. In CHCs, care quality goals may facilitate preventive care whereas case managers may not.

Preventing risky behaviours among young adolescents in eastern Democratic Republic of Congo: A qualitative study.

This qualitative study explores and describes adolescent risk behaviours, specifically consumption of alcohol and use of violence; the perceived consequences of these behaviours on future well-being and relationships; and collaboratively identifies the essential components of a prevention intervention for risk behaviours (alcohol use, violence) among young adolescents while strengthening the protective individual and relationship factors in post-conflict Democratic Republic of Congo. One-on-one in-depth interviews were conducted with 28 male and female youth, 20 parents/guardians and 20 stakeholders in three rural villages of South Kivu Province. Trained interviewers conducted interviews and participated in daily debriefing. Descriptive qualitative analysis was used to analyse the data. Youth use of violence and alcohol was associated with a range of factors including peer influence, parent behaviours, school enrolment and poverty. The consequences of risk behaviour include damaged family and social bonds, reduced economic and educational productivity and promise. Community-based, multilevel prevention interventions that promote protective factors and reduce youth exposure and vulnerability to risk factors may have immediate and long-term impact on youth health and behaviour. Such a programme could engage youth, adults and local stakeholders in a range of social, educational and economic activities.

Association between self-reported sexually transmitted infection treatment and mental health symptoms in conflict-affected eastern Democratic Republic of the Congo.

Although poor mental health has been associated with sexual risk behavior, few studies have examined the association between mental health and sexually transmitted infections (STIs) in conflict-affected settings. With elevated symptoms of poor mental health in conflict-affected settings, it is important to consider if and how mental health may be a risk factor for STIs in these settings. We used cross-sectional logistic regression to examine the association between symptoms of depression, anxiety, and post-traumatic stress disorder (PTSD) with having been treated for an STI in rural South Kivu, Democratic Republic of the Congo. Among 753 adults, those with elevated self-reported symptoms of depression and anxiety (adjusted OR = 2.73, 95% CI 1.68, 4.44) and PTSD (adjusted OR = 1.89, 95% CI 1.17, 3.06) had higher odds of reporting ever being treated for an STI than those who were not symptomatic. Our findings suggest that future studies are needed to more rigorously examine the relationship between mental health and STIs.