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Background Fewer than half of patients with major depressive disorder (MDD) respond to psychotherapy. Pre-emptively informing patients of their likelihood of responding could be useful as part of a patient-centered treatment decision-support plan. Methods This prospective observational study examined a national sample of 807 patients beginning psychotherapy for MDD at the Veterans Health Administration. Patients completed a self-report survey at baseline and 3-months follow-up (data collected 2018–2020). We developed a machine learning (ML) model to predict psychotherapy response at 3 months using baseline survey, administrative, and geospatial variables in a 70% training sample. Model performance was then evaluated in the 30% test sample. Results 32.0% of patients responded to treatment after 3 months. The best ML model had an AUC (SE) of 0.652 (0.038) in the test sample. Among the one-third of patients ranked by the model as most likely to respond, 50.0% in the test sample responded to psychotherapy. In comparison, among the remaining two-thirds of patients, Conclusions Patients with MDD could pre-emptively be informed of their likelihood of responding to psychotherapy using a prediction tool based on self-report data. This tool could meaningfully help patients and providers in shared decision-making, although parallel information about the likelihood of responding to alternative treatments would be needed to inform decision-making across multiple treatments.

Background Only a limited number of patients with major depressive disorder (MDD) respond to a first course of antidepressant medication (ADM). We investigated the feasibility of creating a baseline model to determine which of these would be among patients beginning ADM treatment in the US Veterans Health Administration (VHA). Methods A 2018–2020 national sample of n = 660 VHA patients receiving ADM treatment for MDD completed an extensive baseline self-report assessment near the beginning of treatment and a 3-month self-report follow-up assessment. Using baseline self-report data along with administrative and geospatial data, an ensemble machine learning method was used to develop a model for 3-month treatment response defined by the Quick Inventory of Depression Symptomatology Self-Report and a modified Sheehan Disability Scale. The model was developed in a 70% training sample and tested in the remaining 30% test sample. Results In total, 35.7% of patients responded to treatment. The prediction model had an area under the ROC curve (s.e.) of 0.66 (0.04) in the test sample. A strong gradient in probability (s.e.) of treatment response was found across three subsamples of the test sample using training sample thresholds for high [45.6% (5.5)], intermediate [34.5% (7.6)], and low [11.1% (4.9)] probabilities of response. Baseline symptom severity, comorbidity, treatment characteristics (expectations, history, and aspects of current treatment), and protective/resilience factors were the most important predictors. Conclusions Although these results are promising, parallel models to predict response to alternative treatments based on data collected before initiating treatment would be needed for such models to help guide treatment selection.

Background. Triple-negative (TNBC) is the most aggressive subtype of breast cancer and represents 12% of all cases in the US. In the Mexican population, the prevalence of TNBC is 23%. The prognosis is poor for most of these women, with a higher risk of locoregional recurrence, lower disease-free survival, and lower cancer-specific survival. The sociodemographic characteristics of Central American women, such as indigenous, afro descendants, and Hispanic descent, have been associated with factors such as high nuclear grade, high proliferation index, aggressive clinical presentation with advanced stages, high recurrence rates, and an increased risk of cancer fatality rate. Yet, no epidemiological characterization of women treated for TNBC in specialized hospitals in Central American countries exists to this date. Therefore, we describe the characteristics of women diagnosed with TNBC in three specialized hospitals in Guatemala and Honduras. Methods. We identify 1,501 women with breast cancer who attended three specialized hospitals, two in Guatemala and one in Honduras, from 2015 to 2021. Self-reported sociodemographic and clinical characteristics were determined, as well as pathologic data from medical records. Results. Of the 1,501 women, 272 (18.12%) were diagnosed with triple-negative phenotype. The median age was 49.5 years, with 25% under 40.5 years of age, 95.2% reported mestizo race, 51.5% were pre-menopausal, 49.6% had a high histologic grade (grade 3), and 98.8 had locally advanced disease (Table 1). Conclusions: The characteristics described in our sample were similar to those in other Hispanic populations. The prevalence of TNBC in our sample was lower than in Mexico but higher than that of the US. Our sample was made of primarily young women with locally advanced disease and pathologic factors associated with aggressive cancer behavior, such as high grade, lymphovascular invasion, and high Ki67 index. This first report is the product of a multidisciplinary team with interest in breast cancer subtypes. Our objectives include expanding the collaboration of clinical researchers to all the Central American and Caribbean countries and contributing to the understanding of molecular behavior of TNBC and support advances in treatment. Table 1.Characterization of women diagnosed with TNBC in three hospitals in Central AmericanCHARACTERISTIC% (95% CI)n = 272RaceMestizo95.2 (91.9 - 97.2)Indigenous4.8 (2.8 - 8.1)AgeMean (SD)49.5 years (11.7)IQR40.5 - 57Tobacco useYes3.7 (2.0 – 6.7)Number of pregnanciesMean (SD)1.5 (0.5)IQR1 – 2MenopauseYes48.5 (42.6 – 54.5)Use of contraceptivesYes14.0 (10.3 – 18.7)MulticentricYes19.2 (14.9 – 24.5)HypertensionYes8.4 (5.7 – 12.4)DiabetesYes8.8 (6.0 – 12.9)IMCLess than 3042.3 (36.5 – 48.3)Family history of cancerYes12.9 (9.4 – 17.5)Histologic grade15.5 (3.3 – 9.0)244.8 (39.0 – 50.8)349.6 (43.7 – 55.6)Lymphovascular invasionYes44.5 (38.6 – 50.5)Clinical stageI1.1 (0.3 – 3.4)II40.4 (34.7 – 46.4)III54.4 (48.4 – 60.8)IV4.0 (2.2 – 7.2)KI 67Mean (SD)46.9 (24.1)IQR30 - 70TherapyNeoadjuvant chemotherapy29.2 (21.3 – 38.7)RPC32.1 (23.9 – 41.6)Surgery97.4 (94.5 – 98.7)Adjuvant chemotherapy55.0 (49.0 – 60.8)Radiotherapy94.4 (90.8 – 96.6)MetastasisYes4.0 (2.2 – 7.2)BRCAMutated0.4 (0.0 – 2.6)WT2.2 (1.0 – 4.8) Citation Format: Agatha Reyes-Morales, Juan Francisco Alvarado-Muñoz, Suyapa Bejarano, Hugo Castro, Victor Puac-Polanco, Marco Chivalan, Silvana Torselli. Characterization of triple-negative breast cancer in two Central American countries [abstract]. In: Proceedings of the 2021 San Antonio Breast Cancer Symposium; 2021 Dec 7-10; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2022;82(4 Suppl):Abstract nr P3-12-23.

BackgroundThe most common treatment for major depressive disorder (MDD) is antidepressant medication (ADM). Results are reported on frequency of ADM use, reasons for use, and perceived effectiveness of use in general population surveys across 20 countries.MethodsFace-to-face interviews with community samples totaling n = 49 919 respondents in the World Health Organization (WHO) World Mental Health (WMH) Surveys asked about ADM use anytime in the prior 12 months in conjunction with validated fully structured diagnostic interviews. Treatment questions were administered independently of diagnoses and asked of all respondents.Results3.1% of respondents reported ADM use within the past 12 months. In high-income countries (HICs), depression (49.2%) and anxiety (36.4%) were the most common reasons for use. In low- and middle-income countries (LMICs), depression (38.4%) and sleep problems (31.9%) were the most common reasons for use. Prevalence of use was 2–4 times as high in HICs as LMICs across all examined diagnoses. Newer ADMs were proportionally used more often in HICs than LMICs. Across all conditions, ADMs were reported as very effective by 58.8% of users and somewhat effective by an additional 28.3% of users, with both proportions higher in LMICs than HICs. Neither ADM class nor reason for use was a significant predictor of perceived effectiveness.ConclusionADMs are in widespread use and for a variety of conditions including but going beyond depression and anxiety. In a general population sample from multiple LMICs and HICs, ADMs were widely perceived to be either very or somewhat effective by the people who use them.

Background Physician responsiveness to patient preferences for depression treatment may improve treatment adherence and clinical outcomes. Objective To examine associations of patient treatment preferences with types of depression treatment received and treatment adherence among Veterans initiating depression treatment. Design Patient self-report surveys at treatment initiation linked to medical records. Setting Veterans Health Administration (VA) clinics nationally, 2018–2020. Participants A total of 2582 patients (76.7% male, mean age 48.7 years, 62.3% Non-Hispanic White) Main Measures Patient self-reported preferences for medication and psychotherapy on 0–10 self-anchoring visual analog scales (0=“completely unwilling”; 10=“completely willing”). Treatment receipt and adherence (refilling medications; attending 3+ psychotherapy sessions) over 3 months. Logistic regression models controlled for socio-demographics and geographic variables. Key Results More patients reported strong preferences (10/10) for psychotherapy than medication (51.2% versus 36.7%, McNemar χ21=175.3, p Conclusions Mismatches between treatment preferences and treatment type received were common and associated with worse treatment adherence for psychotherapy. Future research could examine ways to decrease mismatch between patient preferences and treatments received and potential effects on patient outcomes.

INTRODUCTION: The Veterans Health Administration (VHA) supports the nation’s largest Primary Care-Mental Health Integration collaborative care model–(PC-MHI)–to increase treatment of mild to moderate common mental disorders in primary care and refer more severe-complex cases to specialty settings. It is unclear, though, how this treatment assignment works in practice. METHODS: 2,610 patients who sought incident episode VHA treatment for depression between December 2018 and June 2020 completed a baseline self-report questionnaire about depression severity-complexity. Patients with active suicidality or history of severe mental disorders were excluded. Administrative data were used to determine settings and types of treatment over the next 30 days. RESULTS: Thirty-four percent (34.2%) of depressed patients received treatment in a primary care (PC) setting and 65.8% in a specialty setting (SMH). PC patients had less severe and fewer comorbid depressive episodes than those in SMH. Patients with the lowest severity and/or complexity were most likely to receive PC antidepressant medication treatment, whereas those with the highest severity and/or complexity were most likely to receive combined (i.e., medication and psychotherapy) treatment in SMH settings. Although this assignment of patients across settings and types of treatment was stronger than found in previous civilian studies, it was less pronounced than expected (cross-validated AUC=.50-.68). DISCUSSION: By expanding access to evidence-based treatments, VHA’s PC-MHI increases consistency of treatment assignment with clinical characteristics of depressed patients. Increased understanding of reasons for this assignment being less pronounced than expected and implications for treatment response will require continued study.

Background: Breast cancer is the frequent neoplasia in young women, which in developing countries is associated with more adverse outcomes. In Latin America, reports have shown an increased incidence of breast cancer in young women. No information exist regarding breast cancer characteristics in young Guatemalan women. We aimed to describe the clinical-pathological features among women aged 45 years or less treated in a tertiary-level hospital in Guatemala. Methods: We examined data from 119 women aged 45 years or less diagnosed with primary invasive breast cancer at the Oncology Unit Roosevelt Hospital in Guatemala between 2016 and 2020. Data were drawn from medical files on sociodemographic characteristics, histology, clinical stage, and breast cancer subtypes.Results: Of the total sample, breast cancer in women aged 45 years or less represented 31.2% of the cases. Of these, 24.36% is before 35 years, 28.57% between 35 to 39 years, and 47.05% between 39 to 45 years. Advanced clinical stages affected 66.6% of young women (48.33% for stages III and 18.33% stage IV). Data from specific breast cancer molecular subtype showed that 72.35% of cases in young women expressed an aggressive molecular subtype (Her-2 positive 27.06%, triple-negative 21.76%, and luminal/Her-2 positive 23.53%). Regarding treatment, most young patients received surgical treatment, as well as neoadjuvant or adjuvant chemotherapy. Only 24.37% received hormonal and 26.89% radiation therapy. Conclusions: Our finding suggested that young women treated for breast cancer at a tertiary-level hospital in Guatemala had a high proportion of aggressive molecular subtypes and a high rate of locally advanced disease. This aggressive cancer behavior among young women is consistent with findings in other Latin American countries. Evidence examining risk factors for aggressive cancer in young women, such as delay in diagnosis and treatment timing, is warranted. Table 1. Distributions of socio-demographic and cancer-related characteristics variables% (SE)n = 119ETHNIC GROUPMayan Indigenous12.61 (3.05)No-Mayan Indigenous87.39 (3.05)HISTOLOGYDuctal96.64 (1.66)Lobular1.68 (1.18)Other1.68 (1.18)CLINICAL STAGE*I1.67 (1.17)II31.67 (4.26)III48.33 (4.58)IV18.33 (3.54)BREAST CANCER SUBTYPELuminal27.65 (4.76)Her2 positive27.06 (5.11)Triple-negative21.76 (5.05)Luminal/Her223.53 (6.61)TREATMENTSurgery55.46 (4.58)Neoadjuvant Chemotherapy82.35 (3.51)Adjuvant Chemotherapy47.06 (4.59)Radiotherapy26.89 (4.08)Hormonotherapy24.37 (3.95) Citation Format: Juan F Alvarado-Muñoz, Agatha Reyes-Morales, Alba J Kihn-Alarcón, Marco Chivalan, Silvana Torselli, Victor Puac-Polanco. Breast cancer in young women in a tertiary-level hospital in Guatemala [abstract]. In: Proceedings of the 2020 San Antonio Breast Cancer Virtual Symposium; 2020 Dec 8-11; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2021;81(4 Suppl):Abstract nr PS7-64.

Claims of dramatic increases in clinically significant anxiety and depression early in the COVID-19 pandemic came from online surveys with extremely low or unreported response rates.To examine trend data in a calibrated screening for clinically significant anxiety and depression among adults in the only US government benchmark probability trend survey not disrupted by the COVID-19 pandemic.This survey study used the US Centers for Disease Control and Prevention Behavioral Risk Factor Surveillance System (BRFSS), a monthly state-based trend survey conducted over the telephone. Participants were adult respondents in the 50 US states and District of Columbia who were surveyed March to December 2020 compared with the same months in 2017 to 2019.Monthly state COVID-19 death rates.Estimated 30-day prevalence of clinically significant anxiety and depression based on responses to a single BRFSS item calibrated to a score of 6 or greater on the 4-item Patient Health Questionnaire (area under the receiver operating characteristic curve, 0.84). All percentages are weighted based on BRFSS calibration weights.Overall, there were 1 429 354 respondents, with 1 093 663 in 2017 to 2019 (600 416 [51.1%] women; 87 153 [11.8%] non-Hispanic Black; 826 334 [61.5%] non-Hispanic White; 411 254 [27.8%] with college education; and 543 619 [56.8] employed) and 335 691 in 2020 (182 351 [51.3%] women; 25 517 [11.7%] non-Hispanic Black; 250 333 [60.5%] non-Hispanic White; 130 642 [29.3%] with college education; and 168 921 [54.9%] employed). Median within-state response rates were 45.9% to 49.4% in 2017 to 2019 and 47.9% in 2020. Estimated 30-day prevalence of clinically significant anxiety and depression was 0.4 (95% CI, 0.0 to 0.7) percentage points higher in March to December 2020 (12.4%) than March to December 2017 to 2019 (12.1%). This estimated increase was limited, however, to students (2.4 [95% CI, 0.8 to 3.9] percentage points) and the employed (0.9 [95% CI, 0.5 to 1.4] percentage points). Estimated prevalence decreased among the short-term unemployed (-1.8 [95% CI, -3.1 to -0.5] percentage points) and those unable to work (-4.2 [95% CI, -5.3 to -3.2] percentage points), but did not change significantly among the long-term unemployed (-2.1 [95% CI, -4.5 to 0.5] percentage points), homemakers (0.8 [95% CI, -0.3 to 1.9] percentage points), or the retired (0.1 [95% CI, -0.6 to 0.8] percentage points). The increase in anxiety and depression prevalence among employed people was positively associated with the state-month COVID-19 death rate (1.8 [95% CI, 1.2 to 2.5] percentage points when high and 0.0 [95% CI, -0.7 to 0.6] percentage points when low) and was elevated among women compared with men (2.0 [95% CI, 1.4 to 2.5] percentage points vs 0.2 [95% CI, -0.1 to 0.6] percentage points), Non-Hispanic White individuals compared with Hispanic and non-Hispanic Black individuals (1.3 [95% CI, 0.6 to 1.9] percentage points vs 1.1 [95% CI, -0.2 to 2.5] percentage points and 0.7 [95% CI, -0.1 to 1.5] percentage points), and those with college educations compared with less than high school educations (2.5 [95% CI, 1.9 to 3.1] percentage points vs -0.6 [95% CI, -2.7 to 1.4] percentage points).In this survey study, clinically significant US adult anxiety and depression increased less during 2020 than suggested by online surveys. However, this modest aggregate increase could mask more substantial increases in key population segments (eg, first responders) and might have become larger in 2021 and 2022.

Patient-reported helpfulness of treatment is an important indicator of quality in patient-centered care. We examined its pathways and predictors among respondents to household surveys who reported ever receiving treatment for major depression, generalized anxiety disorder, social phobia, specific phobia, post-traumatic stress disorder, bipolar disorder, or alcohol use disorder. Data came from 30 community epidemiological surveys - 17 in high-income countries (HICs) and 13 in low- and middle-income countries (LMICs) - carried out as part of the World Health Organization (WHO)'s World Mental Health (WMH) Surveys. Respondents were asked whether treatment of each disorder was ever helpful and, if so, the number of professionals seen before receiving helpful treatment. Across all surveys and diagnostic categories, 26.1% of patients (N=10,035) reported being helped by the very first professional they saw. Persisting to a second professional after a first unhelpful treatment brought the cumulative probability of receiving helpful treatment to 51.2%. If patients persisted with up through eight professionals, the cumulative probability rose to 90.6%. However, only an estimated 22.8% of patients would have persisted in seeing these many professionals after repeatedly receiving treatments they considered not helpful. Although the proportion of individuals with disorders who sought treatment was higher and they were more persistent in HICs than LMICs, proportional helpfulness among treated cases was no different between HICs and LMICs. A wide range of predictors of perceived treatment helpfulness were found, some of them consistent across diagnostic categories and others unique to specific disorders. These results provide novel information about patient evaluations of treatment across diagnoses and countries varying in income level, and suggest that a critical issue in improving the quality of care for mental disorders should be fostering persistence in professional help-seeking if earlier treatments are not helpful.

PURPOSE OF REVIEW: The adverse health and safety consequences of heavy alcohol consumption are a leading problem around the world. While many risk factors have been extensively studied and presented in comprehensive summaries, not all questions regarding risk factors for problematic drinking behaviors have been answered and presented in systematic reviews. As of March 2020, no review has summarized studies assessing the role of promotional price practices at on-premises alcohol outlets, known as drink specials. Also missing was systematic information of policies that regulated these promotional practices. We aimed to synthesize the available research evidence of the effects that drink specials and drink special laws have on different alcohol-related outcomes. RECENT FINDINGS: Twelve studies examined the effect of drink specials in seven countries between 1978 and 2018. Of these, 11 found a consistent positive association between drink specials and increased alcohol consumption, heavy drinking, and alcohol intoxication. Drink specials also increased reports of driving under the influence, fighting, and unprotected sex. Drink specials were also associated with expectations of higher consumption and modified attitudes and behaviors towards favorable views of drink specials. Effect sizes ranged from 1.80 to 4.43 increased odds for the examined alcohol-related outcomes. The only study examining the effects of a drink special law revealed mixed findings between prohibiting happy hours and three alcohol-related outcomes. SUMMARY: Drink specials were consistently associated with alcohol-related adverse outcomes, but almost nothing is known about the effects of laws restricting drink specials.

Synopsis: We review trend and cohort surveys and administrative data comparing prevalence of mental disorders during, versus, and before the COVID-19 pandemic along with changes in mental health disparities. The best evidence suggests that clinically significant anxiety-depression point prevalence increased by RR=1.3-1.5 during the pandemic compared to before. Although substantial, this level of increase is much less than the implausibly high RR=5.0-8.0 estimates reported in trend studies early in the pandemic based on less appropriate comparisons. Disparities in anxiety-depression prevalence appear to have increased since before the pandemic among people younger than 60 years of age, racial/ethnic minorities, and people with less than a 4-year college degree. Changes in prevalence also occurred during the pandemic, but relative prevalence appears not to have changed substantially over this time based on sex, age, education, or race/ethnicity.

To assess the baseline prevalence of mental health conditions and associated exposures in a cohort of health care workers (HCWs) in Guatemala.We analyzed baseline information from the 2020 Web-based COVID-19 Health Care Workers Study (HEROES)-Guatemala. Outcomes included mental distress and depressive symptoms. Exposures included COVID-19 experiences, sociodemographic characteristics, and job characteristics. We used crude and adjusted Poisson regression models in our analyses.Of the 1801 HCWs who accepted to participate, 1522 (84.5%) completed the questionnaire; 1014 (66.8%) were women. Among the participants, 59.1% (95% confidence interval [CI] = 56.6, 61.5) screened positive for mental distress and 23% (95% CI = 20.9, 25.2) for moderate to severe depressive symptoms. COVID-19 experiences, sociodemographic characteristics, and job characteristics were associated with the study outcomes. Participants who were worried about COVID-19 infection were at higher risk of mental distress (relative risk [RR] = 1.47; 95% CI = 1.30, 1.66) and depressive symptoms (RR = 1.51; 95% CI = 1.17, 1.96). Similarly, the youngest participants were at elevated risk of mental distress (RR = 1.80; 95% CI = 1.24, 2.63) and depressive symptoms (OR = 4.58; 95% CI = 1.51, 13.87).Mental health conditions are highly prevalent among Guatemalan.Avaliar a prevalência basal de condições de saúde mental e exposições associadas em uma coorte de trabalhadores da saúde (TS) na Guatemala.Analisamos as informações da linha de base do estudo on-line sobre trabalhadores da saúde e a COVID-19 (HEROES), realizado em 2020 na Guatemala. Os desfechos incluíram angústia debilitante e sintomas de depressão. As exposições incluíram experiências com a COVID-19, características sociodemográficas e características do trabalho. Usamos em nossas análises modelos de regressão bruta e ajustada de Poisson.Dos 1801 TS que concordaram em participar, 1522 (84,5%) preencheram o questionário, sendo que 1014 (66,8%) eram mulheres. Dentre esses participantes, 59,1% (intervalo de confiança [IC] de 95%=56,6; 61,5) apresentaram resultado positivo na triagem de angústia debilitante e 23% (IC 95%=20,9, 25,2) apresentaram resultado positivo para sintomas de depressão moderados a graves. Experiências com COVID-19, e características sociodemográficas e de trabalho apresentaram associação com os resultados do estudo. Os participantes que estavam preocupados com infecção por COVID-19 apresentaram maior risco de angústia debilitante (risco relativo [RR]=1,47; IC95%=1,30; 1,66) e sintomas de depressão (RR=1,51; IC 95% =1,17; 1,96). Da mesma maneira, os participantes mais jovens apresentaram alto risco de apresentarem angústia debilitante (RR=1,80; IC 95%=1,24; 2,63) e sintomas de depressão (OR=4,58; IC 95%=1,51; 13,87).Condições de saúde mental são altamente prevalentes entre os guatemaltecos.

Importance A substantial proportion of the 40 million people in the US who present to emergency departments (EDs) each year after traumatic events develop posttraumatic stress disorder (PTSD) or major depressive episode (MDE). Accurately identifying patients at high risk in the ED would facilitate the targeting of preventive interventions. Objectives To develop and validate a prediction tool based on ED reports after a motor vehicle collision to predict PTSD or MDE 3 months later. Design, Setting, and Participants The Advancing Understanding of Recovery After Trauma (AURORA) study is a longitudinal study that examined adverse posttraumatic neuropsychiatric sequalae among patients who presented to 28 US urban EDs in the immediate aftermath of a traumatic experience. Enrollment began on September 25, 2017. The 1003 patients considered in this diagnostic/prognostic report completed 3-month assessments by January 31, 2020. Each patient received a baseline ED assessment along with follow-up self-report surveys 2 weeks, 8 weeks, and 3 months later. An ensemble machine learning method was used to predict 3-month PTSD or MDE from baseline information. Data analysis was performed from November 1, 2020, to May 31, 2021. Main Outcomes and Measures The PTSD Checklist forDSM-5was used to assess PTSD and the Patient Reported Outcomes Measurement Information System Depression Short-Form 8b to assess MDE. Results A total of 1003 patients (median [interquartile range] age, 34.5 [24-43] years; 715 [weighted 67.9%] female; 100 [weighted 10.7%] Hispanic, 537 [weighted 52.7%] non-Hispanic Black, 324 [weighted 32.2%] non-Hispanic White, and 42 [weighted 4.4%] of non-Hispanic other race or ethnicity were included in this study. A total of 274 patients (weighted 26.6%) met criteria for 3-month PTSD or MDE. An ensemble machine learning model restricted to 30 predictors estimated in a training sample (patients from the Northeast or Midwest) had good prediction accuracy (mean [SE] area under the curve [AUC], 0.815 [0.031]) and calibration (mean [SE] integrated calibration index, 0.040 [0.002]; mean [SE] expected calibration error, 0.039 [0.002]) in an independent test sample (patients from the South). Patients in the top 30% of predicted risk accounted for 65% of all 3-month PTSD or MDE, with a mean (SE) positive predictive value of 58.2% (6.4%) among these patients at high risk. The model had good consistency across regions of the country in terms of both AUC (mean [SE], 0.789 [0.025] using the Northeast as the test sample and 0.809 [0.023] using the Midwest as the test sample) and calibration (mean [SE] integrated calibration index, 0.048 [0.003] using the Northeast as the test sample and 0.024 [0.001] using the Midwest as the test sample; mean [SE] expected calibration error, 0.034 [0.003] using the Northeast as the test sample and 0.025 [0.001] using the Midwest as the test sample). The most important predictors in terms of Shapley Additive Explanations values were symptoms of anxiety sensitivity and depressive disposition, psychological distress in the 30 days before motor vehicle collision, and peritraumatic psychosomatic symptoms. Conclusions and Relevance The results of this study suggest that a short set of questions feasible to administer in an ED can predict 3-month PTSD or MDE with good AUC, calibration, and geographic consistency. Patients at high risk can be identified in the ED for targeting if cost-effective preventive interventions are developed.

Prescription drug monitoring programs (PDMPs) are a crucial component of federal and state governments’ response to the opioid epidemic. Evidence about the effectiveness of PDMPs in reducing prescription opioid–related adverse outcomes is mixed. We conducted a systematic review to examine whether PDMP implementation within the United States is associated with changes in 4 prescription opioid–related outcome domains: opioid prescribing behaviors, opioid diversion and supply, opioid-related morbidity and substance-use disorders, and opioid-related deaths. We searched for eligible publications in Embase, Google Scholar, MEDLINE, and Web of Science. A total of 29 studies, published between 2009 and 2019, met the inclusion criteria. Of the 16 studies examining PDMPs and prescribing behaviors, 11 found that implementing PDMPs reduced prescribing behaviors. All 3 studies on opioid diversion and supply reported reductions in the examined outcomes. In the opioid-related morbidity and substance-use disorders domain, 7 of 8 studies found associations with prescription opioid–related outcomes. Four of 8 studies in the opioid-related deaths domain reported reduced mortality rates. Despite the mixed findings, emerging evidence supports that the implementation of state PDMPs reduces opioid prescriptions, opioid diversion and supply, and opioid-related morbidity and substance-use disorder outcomes. When PDMP characteristics were examined, mandatory access provisions were associated with reductions in prescribing behaviors, diversion outcomes, hospital admissions, substance-use disorders, and mortality rates. Inconsistencies in the evidence base across outcome domains are due to analytical approaches across studies and, to some extent, heterogeneities in PDMP policies implemented across states and over time.

Background Psychiatric comorbidities may complicate depression treatment by being associated with increased role impairments. However, depression symptom severity might account for these associations. Understanding the independent associations of depression severity and comorbidity with impairments could help in treatment planning. This is especially true for depressed Veterans, who have high psychiatric comorbidity rates. Methods 2,610 Veterans beginning major depression treatment at the Veterans Health Administration (VHA) were administered a baseline self-report survey that screened for diverse psychiatric comorbidities and assessed depression severity and role impairments. Logistic and generalized linear regression models estimated univariable and multivariable associations of depression severity and comorbidities with impairments. Population attributable risk proportions (PARPs) estimated the relative importance of depression severity and comorbidities in accounting for role impairments. Results Nearly all patients (97.8%) screened positive for at least one comorbidity and half (49.8%) for 4+ comorbidities. The most common positive screens were for generalized anxiety disorder (80.2%), posttraumatic stress disorder (77.9%), and panic/phobia (77.4%). Depression severity and comorbidities were significantly and additively associated with impairments in multivariable models. Associations were attenuated much less for depression severity than for comorbidities in multivariable versus univariable models. PARPs indicated that 15–60% of role impairments were attributable to depression severity and 5–32% to comorbidities. Limitations The screening scales could have over-estimated comorbidity prevalence. The cross-sectional observational design cannot determine either temporal or causal priorities. Conclusions Although positive screens for psychiatric comorbidity are pervasive among depressed VHA patients, depression severity accounts for most of the associations of these comorbidities with role impairments.

Background In the United States, every day, close to 30 people die in alcohol-impaired related crashes. Given the known role of alcohol in traffic injuries, we assessed the impact of drink special laws on alcohol- and non-alcohol-related fatal motor vehicle crash rates. Methods We performed a synthetic control analysis of US data from 1982 to 2017. We used publicly available data to evaluate the effects of implementing any drink special law at the state-level during the study period on fatality rates per 100 million vehicle-miles of travel. We used an enhanced version of the SC method for the analysis of multiple treated units. Results Overall, treated states with any drink special law reduced alcohol-related fatal crashes per 100 million VMT by 0.01 (p-value = 0.84) in year one, 0.10 (p-value = 0.14) in year three, 0.07 (p-value = 0.28) in year five, and 0.16 (p-value = 0.01) in year 10 post-implementation compared to the synthetic control trend. Implementation of any drink special law also produced reductions of non-alcohol-related fatal crashes per 100 million VMT by 0.19 (p-value = 0.11) in year one, 0.24 (p-value = 0.03) in year three, 0.25 (p-value = 0.00) in year five, and 0.18 (p-value = 0.00) in year 10 compared to the synthetic control trend. Findings for the number of laws implemented and each drink special laws were mixed. Conclusions Drink special laws appeared to be associated with larger reductions of non-alcohol-related fatal crashes but no with the hypothesized target population, the alcohol-related fatal crashes.

OBJECTIVES: To examine patterns and predictors of perceived treatment helpfulness for mania/hypomania and associated depression in the WHO World Mental Health Surveys.METHODS: Face-to-face interviews with community samples across 15 countries found n=2,178 who received lifetime mania/hypomania treatment and n=624 with lifetime mania/hypomania who received lifetime major depression treatment. These respondents were asked whether treatment was ever helpful and, if so, the number of professionals seen before receiving helpful treatment. Patterns and predictors of treatment helpfulness were examined separately for mania/hypomania and depression.RESULTS: 63.1% (mania/hypomania) and 65.1% (depression) of patients reported ever receiving helpful treatment. However, only 24.5-22.5% were helped by the first professional seen, which means that the others needed to persist in help-seeking after initial unhelpful treatments in order to find helpful treatment. Projections find only 22.9% (mania/hypomania) and 43.3% (depression) would persist through a series of unhelpful treatments but that the proportion helped would increase substantially if persistence increased. Few patient-level significant predictors of helpful treatment emerged and none consistently either across the two components (i.e., provider-level helpfulness and persistence after earlier unhelpful treatment) or for both mania/hypomania and depression. Although prevalence of treatment was higher in high-income than low/middle-income countries, proportional helpfulness among treated cases was nearly identical in the two groups of countries.CONCLUSIONS: Probability of patients with mania/hypomania and associated depression obtaining helpful treatment might increase substantially if persistence in help-seeking increased after initially unhelpful treatments, although this could require seeing numerous additional treatment providers. In addition to investigating reasons for initial treatments not being helpful, messages reinforcing the importance of persistence should be emphasized to patients.

With the growing recognition that diversity and inclusion are essential for the improvement of science and innovation, we provide some perspectives on 3 findings of DeVilbiss et al. (Am J Epidemiol. 2020;189(10):998–1010). We provide points of discussion on factors and strategies to consider when drafting diversity and inclusion programs for the Society for Epidemiologic Research.

To understand the mental health treatment gap in the Region of the Americas by examining the prevalence of mental health disorders, use of mental health services, and the global burden of disease.Data from community-based surveys of mental disorders in Argentina, Brazil, Canada, Chile, Colombia, Guatemala, Mexico, Peru, and the United States were utilized. The World Mental Health Survey published data were used to estimate the treatment gap. For Canada, Chile, and Guatemala, the treatment gap was calculated from data files. The mean, median, and weighted treatment gap, and the 12-month prevalence by severity and category of mental disorder were estimated for the general adult, child-adolescent, and indigenous populations. Disability-adjusted Life Years and Years Lived with Disability were calculated from the Global Burden of Disease study.Mental and substance use disorders accounted for 10.5% of the global burden of disease in the Americas. The 12-month prevalence rate of severe mental disorders ranged from 2% - 10% across studies. The weighted mean treatment gap in the Americas for moderate to severe disorders was 65.7%; North America, 53.2%; Latin America, 74.7%; Mesoamerica, 78.7%; and South America, 73.1%. The treatment gap for severe mental disorders in children and adolescents was over 50%. One-third of the indigenous population in the United States and 80% in Latin America had not received treatment.The treatment gap for mental health remains a public health concern. A high proportion of adults, children, and indigenous individuals with serious mental illness remains untreated. The result is an elevated prevalence of mental disorders and global burden of disease.Comprender la brecha en el tratamiento de la salud mental en la Región de las Américas mediante la revisión de la prevalencia de los trastornos de salud mental, el uso de los servicios de salud mental y la carga mundial de enfermedad.Se utilizaron datos de encuestas comunitarias de trastornos mentales de Argentina, Brasil, Canadá, Chile, Colombia, Estados Unidos, Guatemala, México y Perú. Se emplearon los datos publicados de la Encuesta Mundial de Salud Mental para estimar la brecha de tratamiento. Para Canadá, Chile y Guatemala, la brecha de tratamiento se calculó a partir de los archivos de datos. Se estimaron la brecha de tratamiento media, media ponderada, y mediana, y la prevalencia de 12 meses por gravedad y categoría de trastorno mental para las poblaciones generales de adultos, niños y adolescentes, e indígenas. Se calcularon los años de vida ajustados por discapacidad y los años vividos con discapacidad a partir del estudio Carga Global de Enfermedad.Los trastornos mentales y por consumo de sustancias representaron el 10,5% de la carga mundial de enfermedad en las Américas. La tasa de prevalencia de 12 meses de los trastornos mentales severos varió del 2% al 10% en los estudios. La brecha de tratamiento media ponderada en las Américas para los trastornos moderados a graves fue del 65,7%; en América del Norte de 53,2%; en América Latina de 74,7%; en Mesoamérica de 78,7%; y en América del Sur de 73,1%. La brecha de tratamiento para los trastornos mentales graves en niños y adolescentes fue superior al 50%. Un tercio de la población indígena en los Estados Unidos y el 80% en América Latina no recibieron tratamiento.La brecha de tratamiento para la salud mental sigue siendo un problema de salud pública. Una gran proporción de adultos, niños y personas indígenas con enfermedades mentales graves continúan sin tratamiento. El resultado implica una prevalencia elevada de trastornos mentales y de la carga mundial de enfermedad.Compreender a lacuna de tratamento em saúde mental na Região das Américas examinando a prevalência de transtornos mentais, o uso de serviços de saúde mental e a carga global de doença.Foram utilizados dados de inquéritos comunitários de transtornos mentais na Argentina, Brasil, Canadá, Chile, Colômbia, Guatemala, México, Peru e Estados Unidos. Os dados publicados na Pesquisa Mundial de Saúde Mental foram utilizados para estimar a lacuna de tratamento. Para o Canadá, Chile e Guatemala, a lacuna de tratamento foi calculada a partir de arquivos de dados. A lacuna de tratamento média, média ponderada e mediana, e a prevalência de 12 meses por gravidade e categoria de transtorno mental foram estimadas para as populações adulta, infantil-adolescente e indígena em geral. Os anos de vida ajustados por incapacidade e os anos de vida com incapacidade foram calculados a partir do estudo Carga Global de Doença.Os transtornos mentais e de uso de substâncias foram responsáveis por 10,5% da carga global de doença nas Américas. A taxa de prevalência de 12 meses de transtornos mentais graves variou de 2% a 10% entre os estudos. A lacuna de tratamento média ponderada nas Américas para transtornos moderados a graves foi de 65,7%; em América do Norte de 53,2%; em América Latina de 74,7%; em Mesoamérica de 78,7%; e na América do Sul de 73,1%. A lacuna de tratamento para transtornos mentais graves em crianças e adolescentes foi superior a 50%. Um terço da população indígena nos Estados Unidos e 80% na América Latina não recebeu tratamento.A lacuna de tratamento para a saúde mental continua sendo uma preocupação de saúde pública. Uma alta proporção de adultos, crianças e indígenas com doença mental grave permanece sem tratamento. O resultado é uma elevada prevalência de transtornos mentais e de carga global de doença.

Objectives. We analyzed a probability sample of Guatemalans to determine if a relationship exists between previous violent events and development of mental health outcomes in various sociodemographic groups, as well as during and after the Guatemalan Civil War. Methods. We used regression modeling, an interaction test, and complex survey design adjustments to estimate prevalences and test potential relationships between previous violent events and mental health. Results. Many (20.6%) participants experienced at least 1 previous serious violent event. Witnessing someone severely injured or killed was the most common event. Depression was experienced by 4.2% of participants, with 6.5% experiencing anxiety, 6.4% an alcohol-related disorder, and 1.9% posttraumatic stress disorder (PTSD). Persons who experienced violence during the war had 4.3 times the adjusted odds of alcohol-related disorders (P Conclusions. Violence that began during the civil war and continues today has had a significant effect on the mental health of Guatemalans. However, mental health outcomes resulting from violent events decreased in the postwar period, suggesting a nation in recovery.

Population health outcomes are directly related to robust public health programs, access to basic health services, and a well-trained health-care workforce. Effective health services need to systematically identify solutions, scientifically test these solutions, and share generated knowledge. The World Health Organization (WHO)'s Global Healthcare Workforce Alliance states that the capacity to perform research is an essential factor for well-functioning public health systems. Low- and middle-income countries have greater health-care worker shortages and lower research capacity than higher-income countries. International global health partnerships between higher-income countries and low-middle-income countries aim to directly address such inequalities through capacity building, a process by which human and institutional resources are strengthened and developed, allowing them to perform high-level functions, solve complex problems, and achieve important objectives. The Guatemala-Penn Partners (GPP) is a collaboration among academic centers in Guatemala and the University of Pennsylvania (Penn), in Philadelphia, Pennsylvania that echoes the vision of the WHO's Global Healthcare Workforce Alliance. This article describes the historical development and present organization of the GPP according to its three guiding principles: university-to-university connections, dual autonomies with locally led capacity building, and mutually beneficial exchanges. It describes the GPP activities within the domains of science, health-care education, and public health, emphasizing implementation factors, such as sustainability and scalability, in relation to the guiding principles. Successes and limitations of this innovative model are also analyzed in the hope that the lessons learned may be applied to similar partnerships across the globe.

Background Motorcyclists are known to be at substantially higher risk per mile traveled of dying from crashes than car occupants. In 2014, motorcycling made up less than 1 % of person-miles traveled but 13 % of the total mortality from motor-vehicle crashes in the United States. We assessed the cohort effect of the baby-boomers (i.e., those born between 1946 and 1964) in motorcycle crash mortality from 1975 to 2014 in the United States. Methods Using mortality data for motorcycle occupants from the Fatality Analysis Reporting System, we performed an age-period-cohort analysis using the multiphase method and the intrinsic estimator method. Results Baby-boomers experienced the highest mortality rates from motorcycle crashes at age 20-24 years and continued to experience excess mortality after age 40 years. After removing the effects of age and period, the estimated mortality risk from motorcycle crashes for baby-boomers was 48 % higher than that of the referent cohort (those born between 1930 and 1934, rate ratio 1.48; 95 % CI: 1.01, 2.18). Results from the multiphase method and the intrinsic estimator method were consistent. Conclusions The baby-boomers have experienced significantly higher mortality from motorcycle crashes than other birth cohorts. To reduce motorcycle crash mortality, intervention programs specifically tailored for the baby-boomer generation are warranted. Electronic supplementary material The online version of this article (doi:10.1186/s40621-016-0083-6) contains supplementary material, which is available to authorized users.

The authors reflect on the need for improved scientific literacy using the Spanish language. It states that while adopting English as a single language to communicate advances in health sciences allows faster dissemination of information, it has adverse public health effects in countries where a significant percentage of people do not speak English. It mentions in the U.S. Spanish-speaking communities tend to be excluded from the discussion of public health issues.