Inequality on the frontline: A multi-country study on gender differences in mental health among healthcare workers during the COVID-19 pandemic.

Healthcare workers (HCWs) were at increased risk for mental health problems during the COVID-19 pandemic, with prior data suggesting women may be particularly vulnerable. Our global mental health study aimed to examine factors associated with gender differences in psychological distress and depressive symptoms among HCWs during COVID-19. Across 22 countries in South America, Europe, Asia and Africa, 32,410 HCWs participated in the COVID-19 HEalth caRe wOrkErS (HEROES) study between March 2020 and February 2021. They completed the General Health Questionnaire-12, the Patient Health Questionnaire-9 and questions about pandemic-relevant exposures. Consistently across countries, women reported elevated mental health problems compared to men. Women also reported increased COVID-19-relevant stressors, including insufficient personal protective equipment and less support from colleagues, while men reported increased contact with COVID-19 patients. At the country level, HCWs in countries with higher gender inequality reported less mental health problems. Higher COVID-19 mortality rates were associated with increased psychological distress merely among women. Our findings suggest that among HCWs, women may have been disproportionately exposed to COVID-19-relevant stressors at the individual and country level. This highlights the importance of considering gender in emergency response efforts to safeguard women's well-being and ensure healthcare system preparedness during future public health crises.

What was the impact of tobacco taxes on smoking prevalence and coronary heart disease mortality in the United States -2005-2016, and did it vary by race and gender?

Tobacco taxes have reduced smoking and coronary heart disease (CHD) mortality, yet few studies have examined heterogeneity of these associations by race and gender. We constructed a yearly panel (2005-2016) that included age-adjusted cigarette smoking prevalence and CHD mortality rates across all 50 U.S. States and the District of Columbia using the Behavioral Risk Factor Surveillance System and Wide-ranging Online Data for Epidemiological Research. We examined associations between changes in total cigarette excise taxes (i.e., federal and state) and changes in smoking prevalence and CHD mortality, using linear regression models with state and year fixed effects. Each dollar of tobacco tax was associated with a reduction in age-adjusted smoking prevalence 1 year later of -0.4 [95% CIs: -0.6, -0.2] percentage points; and a relative reduction in the rate of CHD mortality 2 years later of -2.0% [95% CIs: -3.7%, -0.3%], or -5 deaths/100,000 in absolute terms. Associations between tobacco taxes and smoking prevalence were statistically significantly different by race and gender and were strongest among Black non-Hispanic women (-1.2 [95% CIs: -1.6, -0.8] percentage points). Associations between tobacco taxes and CHD mortality were not statistically significantly different by race and gender, but point estimates for percent changes were highest among Black non-Hispanic men (-2.9%) and Black non-Hispanic women (-3.5%) compared to White non-Hispanic men (-1.8%) and White non-Hispanic women (-1.5%). These findings suggest that tobacco taxation is an effective intervention for reducing smoking prevalence and CHD mortality among White and Black non-Hispanic populations in the United States.

Development of a model to predict antidepressant treatment response for depression among Veterans.

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.

Antidepressant use in low- middle- and high-income countries: a World Mental Health Surveys report.

BACKGROUND: The 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. METHODS: Face-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. RESULTS: 3.1% 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. CONCLUSION: ADMs 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.

Development of a model to predict combined antidepressant medication and psychotherapy treatment response for depression among veterans.

BACKGROUND: Although research shows that more depressed patients respond to combined antidepressants (ADM) and psychotherapy than either alone, many patients do not respond even to combined treatment. A reliable prediction model for this could help treatment decision-making. We attempted to create such a model using machine learning methods among patients in the US Veterans Health Administration (VHA). METHODS: A 2018-2020 national sample of VHA patients beginning combined depression treatment completed self-report assessments at baseline and 3 months (n = 658). A learning model was developed using baseline self-report, administrative, and geospatial data to predict 3-month treatment response defined by reductions in the Quick Inventory of Depression Symptomatology Self-Report and/or in the Sheehan Disability Scale. The model was developed in a 70 % training sample and tested in the remaining 30 % test sample. RESULTS: 30.0 % of patients responded to treatment. The prediction model had a test sample AUC-ROC of 0.657. A strong gradient was found in probability of treatment response from 52.7 % in the highest predicted quintile to 14.4 % in the lowest predicted quintile. The most important predictors were episode characteristics (symptoms, comorbidities, history), personality/psychological resilience, recent stressors, and treatment characteristics. LIMITATIONS: Restrictions in sample definition, a low recruitment rate, and reliance on patient self-report rather than clinician assessments to determine treatment response limited the generalizability of results. CONCLUSIONS: A machine learning model could help depressed patients and providers predict likely response to combined ADM-psychotherapy. Parallel information about potential harms and costs of alternative treatments would be needed, though, to inform optimal treatment selection.

Development of a model to predict psychotherapy response for depression among Veterans.

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, <25% responded to psychotherapy. The model selected 43 predictors, of which nearly all were self-report variables. 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.

Mental Health of Guatemalan Health Care Workers During the COVID-19 Pandemic: Baseline Findings From the HEROES Cohort Study.

Objectives. To assess the baseline prevalence of mental health conditions and associated exposures in a cohort of health care workers (HCWs) in Guatemala. Methods. 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. Results. 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). Conclusions. Mental health conditions are highly prevalent among Guatemalan HCWs. (Am J Public Health. 2022;112(S6):S602-S614. https://doi.org/10.2105/AJPH.2021.306648).

[Mental health of Guatemalan health care workers during the COVID-19 pandemic: baseline findings from the HEROES cohort studySaúde mental dos trabalhadores da saúde guatemaltecos durante a pandemia de COVID-19: constatações basais do estudo da coorte HEROES]. / La salud mental de los trabajadores de salud en Guatemala durante la pandemia de COVID-19: resultados de base del estudio de cohortes HÉROES.

Objectives: To assess the baseline prevalence of mental health conditions and associated exposures in a cohort of health care workers (HCWs) in Guatemala. Methods: 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. Results: 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). Conclusions: Mental health conditions are highly prevalent among Guatemalan.

Objetivos: Avaliar a prevalência basal de condições de saúde mental e exposições associadas em uma coorte de trabalhadores da saúde (TS) na Guatemala. Métodos: 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. Resultados: 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). Conclusões: Condições de saúde mental são altamente prevalentes entre os guatemaltecos.

Estimated Prevalence of and Factors Associated With Clinically Significant Anxiety and Depression Among US Adults During the First Year of the COVID-19 Pandemic.

Importance: 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. Objective: 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. Design, Setting, and Participants: 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. Exposures: Monthly state COVID-19 death rates. Main Outcomes and Measures: 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. Results: 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). Conclusions and Relevance: 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.

Patterns and correlates of patient-reported helpfulness of treatment for common mental and substance use disorders in the WHO World Mental Health Surveys.

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.

Changes in Prevalence of Mental Illness Among US Adults During Compared with Before the COVID-19 Pandemic.

The authors review trend and cohort surveys and administrative data comparing prevalence of mental disorders during, versus, and before the COVID-19 pandemic and changes in mental health disparities. Best evidence suggests clinically significant anxiety-depression point prevalence increased by relative-risk (RR) = 1.3 to 1.5 during the pandemic compared with before. This level of increase is much less than the implausibly high RR = 5.0 to 8.0 estimates reported in trend studies early in the pandemic based on less-appropriate comparisons. Changes in prevalence also occurred during the pandemic, but relative prevalence appears not to have changed substantially over this time.

The comparative importance of mental and physical disorders for health-related days out of role in the general population of Saudi Arabia.

BACKGROUND: A major component of illness burden is role impairment. As part of the recently-completed Saudi National Mental Health Survey (SNMHS), we compare the number of days out of role in the Saudi population associated with ten core mental disorders assessed in the survey to those associated with ten commonly occurring chronic physical disorders. METHODS: The SNMHS was a household survey that assessed prevalence of ten common anxiety, mood, disruptive behavior, and eating disorders in a nationally representative sample of n = 1981 citizens of the Kingdom of Saudi Arabia (KSA) ages 15-65. Comparison information was obtained on prevalence of ten common chronic physical disorders and number of health-related days out of role (DOR) in the 30 days before interview. Generalized linear models were used to examine univariate and multivariable associations of disorders with DOR and to calculate population attributable risk (PAR) separately and overall for the disorders controlling for socio-demographics. RESULTS: 19.9% of respondents had one or more of the selected mental disorders and 47.1% had one or more of the selected physical disorders. Nine mental disorders and two physical disorders were associated with increased DOR. PAR was 32.9% for mental disorders, 27.0% for physical disorders, and 59.9% for both combined. CONCLUSIONS: Mental disorders are associated with a substantial proportion of all health-related DOR in the Kingdom of Saudi Arabia. Programs to detect and treat mental disorders might lead to substantially decreased role impairment in the Kingdom.

The impact of the COVID-19 pandemic on the mental health of healthcare workers: study protocol for the COVID-19 HEalth caRe wOrkErS (HEROES) study.

BACKGROUND: Preliminary country-specific reports suggest that the COVID-19 pandemic has a negative impact on the mental health of the healthcare workforce. In this paper, we summarize the protocol of the COVID-19 HEalth caRe wOrkErS (HEROES) study, an ongoing, global initiative, aimed to describe and track longitudinal trajectories of mental health symptoms and disorders among health care workers at different phases of the pandemic across a wide range of countries in Latin America, Europe, Africa, Middle-East, and Asia. METHODS: Participants from various settings, including primary care clinics, hospitals, nursing homes, and mental health facilities, are being enrolled. In 26 countries, we are using a similar study design with harmonized measures to capture data on COVID-19 related exposures and variables of interest during two years of follow-up. Exposures include potential stressors related to working in healthcare during the COVID-19 pandemic, as well as sociodemographic and clinical factors. Primary outcomes of interest include mental health variables such as psychological distress, depressive symptoms, and posttraumatic stress disorders. Other domains of interest include potentially mediating or moderating influences such as workplace conditions, trust in the government, and the country's income level. RESULTS: As of August 2021, ~ 34,000 health workers have been recruited. A general characterization of the recruited samples by sociodemographic and workplace variables is presented. Most participating countries have identified several health facilities where they can identify denominators and attain acceptable response rates. Of the 26 countries, 22 are collecting data and 2 plan to start shortly. CONCLUSIONS: This is one of the most extensive global studies on the mental health of healthcare workers during the COVID-19 pandemic, including a variety of countries with diverse economic realities and different levels of severity of pandemic and management. Moreover, unlike most previous studies, we included workers (clinical and non-clinical staff) in a wide range of settings.

Are Veterans Getting Their Preferred Depression Treatment? A National Observational Study in the Veterans Health Administration.

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<0.001). A total of 32.1% of patients who preferred (7-10/10) medication and 21.8% who preferred psychotherapy did not receive these treatments. Patients who strongly preferred medication were substantially more likely to receive medication than those who had strong negative preferences (odds ratios [OR]=17.5; 95% confidence interval [CI]=12.5-24.5). Compared with patients who had strong negative psychotherapy preferences, those with strong psychotherapy preferences were about twice as likely to receive psychotherapy (OR=1.9; 95% CI=1.0-3.5). Patients who strongly preferred psychotherapy were more likely to adhere to psychotherapy than those with strong negative preferences (OR=3.3; 95% CI=1.4-7.4). Treatment preferences were not associated with medication or combined treatment adherence. Patients in primary care settings had lower odds of receiving (but not adhering to) psychotherapy than patients in specialty mental health settings. Depression severity was not associated with treatment receipt or adherence. 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.

La salud mental de los trabajadores de salud en Guatemala durante la pandemia de COVID-19: resultados de base del estudio de cohortes HÉROES / Mental health of Guatemalan health care workers during the COVID-19 pandemic: baseline findings from the HEROES cohort study / Saúde mental dos trabalhadores da saúde guatemaltecos durante a pandemia de COVID-19: constatações basais do estudo da coorte HEROES

RESUMEN Objetivos. Evaluar la prevalencia de base de los trastornos de salud mental y exposiciones conexas en una cohorte de trabajadores de salud de Guatemala. Métodos Se analizó la información de base del estudio HÉROES (por COVID-19 HEalth caRe wOrkeRs Study, sobre los trabajadores de salud durante la pandemia) en Guatemala, realizado en línea en el 2020. Las variables de resultado fueron malestar psicológico y síntomas depresivos. Las exposiciones incluyeron experiencias con la COVID-19, características sociodemográficas y características del trabajo. En los análisis se utilizaron modelos de regresión de Poisson brutos y ajustados. Resultados. De los 1801 trabajadores de salud que aceptaron participar, 1522 (84,5%) completaron el cuestionario; 1014 (66,8%) eran mujeres. De los participantes, 59,1% (intervalo de confianza de 95% [IC 95%] = 56,6-61,5) tuvo un tamizaje positivo para malestar psicológico y 23% (IC 95% = 20,9-25,2) para síntomas depresivos de moderados a graves. Las experiencias con la pandemia de COVID-19, las características sociodemográficas y las características del trabajo se correlacionaron con las variables de resultado del estudio. Los participantes que estaban preocupados por el contagio de la COVID-19 tuvieron un mayor riesgo de malestar psicológico (riesgo relativo [RR] = 1,47; IC 95% = 1,30-1,66) y síntomas depresivos (RR = 1,51; IC 95% = 1,17-1,96). Asimismo, los participantes más jóvenes presentaban un riesgo alto de malestar psicológico (RR = 1,80; IC 95% = 1,24-2,63) y síntomas depresivos (razón de posibilidades [OR] = 4,58; IC 95% = 1,51-13,87). Conclusiones. Las afecciones de salud mental tienen una prevalencia sumamente alta en los trabajadores de salud de Guatemala.

ABSTRACT Objectives. To assess the baseline prevalence of mental health conditions and associated exposures in a cohort of health care workers (HCWs) in Guatemala. Methods. 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. Results. 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). Conclusions. Mental health conditions are highly prevalent among Guatemalan.

RESUMO Objetivos. Avaliar a prevalência basal de condições de saúde mental e exposições associadas em uma coorte de trabalhadores da saúde (TS) na Guatemala. Métodos. 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. Resultados. 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). Conclusões. Condições de saúde mental são altamente prevalentes entre os guatemaltecos.

Development and Validation of a Model to Predict Posttraumatic Stress Disorder and Major Depression After a Motor Vehicle Collision.

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 for DSM-5 was 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.

Comorbid mental disorders, depression symptom severity, and role impairment among Veterans initiating depression treatment through the Veterans Health Administration.

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.

Treatment Differences in Primary and Specialty Settings in Veterans with Major Depression.

INTRODUCTION: The Veterans Health Administration (VHA) supports the nation's largest primary care-mental health integration (PC-MHI) collaborative care model to increase treatment of mild to moderate common mental disorders in primary care (PC) and refer more severe-complex cases to specialty mental health (SMH) settings. It is unclear how this treatment assignment works in practice. METHODS: Patients (n = 2610) who sought incident episode VHA treatment for depression completed a baseline self-report questionnaire about depression severity-complexity. Administrative data were used to determine settings and types of treatment during the next 30 days. RESULTS: Thirty-four percent (34.2%) of depressed patients received treatment in PC settings, 65.8% in SMH settings. PC patients had less severe and fewer comorbid depressive episodes. Patients with lowest severity and/or complexity were most likely to receive PC antidepressant medication treatment; those with highest severity and/or complexity were most likely to receive combined treatment in SMH settings. Assignment of patients across settings and types of treatment was stronger than found in previous civilian studies but less pronounced than expected (cross-validated AUC = 0.50-0.68). DISCUSSION: By expanding access to evidence-based treatments, VHA's PC-MHI increases consistency of treatment assignment. Reasons for assignment being less pronounced than expected and implications for treatment response will require continued study.

Perceived helpfulness of bipolar disorder treatment: Findings from the World Health Organization World Mental Health Surveys.

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.