Articles: pandemics.
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We assess the effectiveness of paid ads on social media platforms as a research recruitment tool with Latino men who have sex with men (LMSM). We deployed four paid ad campaigns July-September 2022 in English and Spanish on Meta and Grindr featuring happy or risqué images of LMSM, documenting engagement and cost metrics. ⋯ Comparing platforms, Meta had higher engagement metrics than Grindr, while Grindr had higher proportions of those who completed the screener (57.9%) and were eligible (26.3%) than Meta (52.6% and 21.0%, respectively). Challenges to using paid ads as an LMSM recruitment tool included intersecting pandemics (Mpox, COVID-19), and limited connection between platforms and staff for study enrollment.
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Observational Study
Trends in the Diagnostic Prevalence of Mental Disorders, 2012-2022—Using Nationwide Outpatient Claims Data for Mental Health Surveillance.
Evaluations by the statutory health insurance carriers in Germany have revealed a rising prevalence of diagnoses of mental disorders, at varying levels and to varying extents. For mental health surveillance purposes, we analyzed prevalence trends across health insurance carriers, before and during the COVID-19 pandemic and stratified by diagnosis group, sex and age. ⋯ Trends in diagnostic prevalence differ across mental disorders and population subgroups and have changed in some diagnosis groups since the COVID-19 pandemic. Contextualizing research is needed for a better understanding of these developments.
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Pol. Arch. Med. Wewn. · May 2024
Predicting acute kidney injury onset using a random forest algorithm using electronic medical records of COVID-19 patients: the CRACoV-AKI model.
Acute kidney injury (AKI) is a serious and common complication of SARS‑CoV‑2 infection. Most risk assessment tools for AKI have been developed in the intensive care unit or in elderly populations. As the COVID‑19 pandemic is transitioning into an endemic phase, there is an unmet need for prognostic scores tailored to the population of patients hospitalized for this disease. ⋯ The CRACoV‑AKI model enables AKI risk stratification among hospitalized patients with COVID‑19. Machine learning-based tools may thus offer additional decision‑making support for specialist providers.
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Military veterans are at increased risk of substance use disorders. Limited research is available about veterans' cannabis use (CU) during the coronavirus disease 2019 (COVID-19) pandemic. This study estimated the prevalence of past 30-day CU, investigated individual-level correlates of past 30-day CU, and evaluated the reasons (medical, recreational, or both) of past 30-day CU among U.S. Veterans during the second wave of the COVID-19 pandemic. ⋯ CU is prevalent among veterans, and certain subgroups are at higher risk of CU. Thus, identifying high-risk subgroups of veterans and adequately educating them about CU's benefits, risks, and safety is crucial.