Data-Driven Assessment of Adolescents' Mental Health During the COVID-19 Pandemic.

OBJECTIVE: Adolescents' mental health was severely compromised during the COVID-19 pandemic. Longitudinal real-world studies on changes in the mental health of adolescents during the later phase of the pandemic are limited. We aimed to quantify the effect of COVID-19 pandemic on adolescents' mental health outcomes based on electronic health records. METHOD: This was a retrospective cohort study using the computerized database of a 2.5 million members, state-mandated health organization in Israel. Rates of mental health diagnoses and psychiatric drug dispensations were measured among adolescents 12 to 17 years of age with and without pre-existing mental history, for the years 2017 to 2021. Relative risks were computed between the years, and interrupted time series (ITS) analyses evaluated changes in monthly incidence rates of psychiatric outcomes. RESULTS: The average population size was 218,146 in 2021. During the COVID-19 period, a 36% increase was observed in the incidence of depression (95% CI = 25-47), 31% in anxiety (95% CI = 23-39), 20% in stress (95% CI = 13-27), 50% in eating disorders (95% CI = 35-67), 25% in antidepressant use (95% CI = 25-33), and 28% in antipsychotic use (95% CI = 18-40). A decreased rate of 26% (95% CI = 0.80-0.88) was observed in ADHD diagnoses. The increase of the examined outcomes was most prominent among youth without psychiatric history, female youth, general secular Jewish population, youth with medium-high socioeconomic status, and those 14 to 15 years of age. ITS analysis confirmed a significantly higher growth in the incidence of psychiatric outcomes during the COVID-19 period, compared to those in previous years. CONCLUSION: This real-world study highlights the deterioration of adolescents' mental health during the COVID-19 pandemic and suggests that youth mental health should be considered during health policy decision making. DIVERSITY & INCLUSION STATEMENT: We worked to ensure sex and gender balance in the recruitment of human participants. We worked to ensure race, ethnic, and/or other types of diversity in the recruitment of human participants. We actively worked to promote sex and gender balance in our author group. The author list of this paper includes contributors from the location and/or community where the research was conducted who participated in the data collection, design, analysis, and/or interpretation of the work.

Long covid outcomes at one year after mild SARS-CoV-2 infection: nationwide cohort study.

OBJECTIVES: To determine the clinical sequelae of long covid for a year after infection in patients with mild disease and to evaluate its association with age, sex, SARS-CoV-2 variants, and vaccination status. DESIGN: Retrospective nationwide cohort study. SETTING: Electronic medical records from an Israeli nationwide healthcare organisation. POPULATION: 1 913 234 Maccabi Healthcare Services members of all ages who did a polymerase chain reaction test for SARS-CoV-2 between 1 March 2020 and 1 October 2021. MAIN OUTCOME MEASURES: Risk of an evidence based list of 70 reported long covid outcomes in unvaccinated patients infected with SARS-CoV-2 matched to uninfected people, adjusted for age and sex and stratified by SARS-CoV-2 variants, and risk in patients with a breakthrough SARS-CoV-2 infection compared with unvaccinated infected controls. Risks were compared using hazard ratios and risk differences per 10 000 patients measured during the early (30-180 days) and late (180-360 days) time periods after infection. RESULTS: Covid-19 infection was significantly associated with increased risks in early and late periods for anosmia and dysgeusia (hazard ratio 4.59 (95% confidence interval 3.63 to 5.80), risk difference 19.6 (95% confidence interval 16.9 to 22.4) in early period; 2.96 (2.29 to 3.82), 11.0 (8.5 to 13.6) in late period), cognitive impairment (1.85 (1.58 to 2.17), 12.8, (9.6 to 16.1); 1.69 (1.45 to 1.96), 13.3 (9.4 to 17.3)), dyspnoea (1.79 (1.68 to 1.90), 85.7 (76.9 to 94.5); 1.30 (1.22 to 1.38), 35.4 (26.3 to 44.6)), weakness (1.78 (1.69 to 1.88), 108.5, 98.4 to 118.6; 1.30 (1.22 to 1.37), 50.2 (39.4 to 61.1)), and palpitations (1.49 (1.35 to 1.64), 22.1 (16.8 to 27.4); 1.16 (1.05 to 1.27), 8.3 (2.4 to 14.1)) and with significant but lower excess risk for streptococcal tonsillitis and dizziness. Hair loss, chest pain, cough, myalgia, and respiratory disorders were significantly increased only during the early phase. Male and female patients showed minor differences, and children had fewer outcomes than adults during the early phase of covid-19, which mostly resolved in the late period. Findings remained consistent across SARS-CoV-2 variants. Vaccinated patients with a breakthrough SARS-CoV-2 infection had a lower risk for dyspnoea and similar risk for other outcomes compared with unvaccinated infected patients. CONCLUSIONS: This nationwide study suggests that patients with mild covid-19 are at risk for a small number of health outcomes, most of which are resolved within a year from diagnosis.

Assessing Associations Between COVID-19 Symptomology and Adverse Outcomes After Piloting Crowdsourced Data Collection: Cross-sectional Survey Study.

BACKGROUND: Crowdsourcing is a useful way to rapidly collect information on COVID-19 symptoms. However, there are potential biases and data quality issues given the population that chooses to participate in crowdsourcing activities and the common strategies used to screen participants based on their previous experience. OBJECTIVE: The study aimed to (1) build a pipeline to enable data quality and population representation checks in a pilot setting prior to deploying a final survey to a crowdsourcing platform, (2) assess COVID-19 symptomology among survey respondents who report a previous positive COVID-19 result, and (3) assess associations of symptomology groups and underlying chronic conditions with adverse outcomes due to COVID-19. METHODS: We developed a web-based survey and hosted it on the Amazon Mechanical Turk (MTurk) crowdsourcing platform. We conducted a pilot study from August 5, 2020, to August 14, 2020, to refine the filtering criteria according to our needs before finalizing the pipeline. The final survey was posted from late August to December 31, 2020. Hierarchical cluster analyses were performed to identify COVID-19 symptomology groups, and logistic regression analyses were performed for hospitalization and mechanical ventilation outcomes. Finally, we performed a validation of study outcomes by comparing our findings to those reported in previous systematic reviews. RESULTS: The crowdsourcing pipeline facilitated piloting our survey study and revising the filtering criteria to target specific MTurk experience levels and to include a second attention check. We collected data from 1254 COVID-19-positive survey participants and identified the following 6 symptomology groups: abdominal and bladder pain (Group 1); flu-like symptoms (loss of smell/taste/appetite; Group 2); hoarseness and sputum production (Group 3); joint aches and stomach cramps (Group 4); eye or skin dryness and vomiting (Group 5); and no symptoms (Group 6). The risk factors for adverse COVID-19 outcomes differed for different symptomology groups. The only risk factor that remained significant across 4 symptomology groups was influenza vaccine in the previous year (Group 1: odds ratio [OR] 6.22, 95% CI 2.32-17.92; Group 2: OR 2.35, 95% CI 1.74-3.18; Group 3: OR 3.7, 95% CI 1.32-10.98; Group 4: OR 4.44, 95% CI 1.53-14.49). Our findings regarding the symptoms of abdominal pain, cough, fever, fatigue, shortness of breath, and vomiting as risk factors for COVID-19 adverse outcomes were concordant with the findings of other researchers. Some high-risk symptoms found in our study, including bladder pain, dry eyes or skin, and loss of appetite, were reported less frequently by other researchers and were not considered previously in relation to COVID-19 adverse outcomes. CONCLUSIONS: We demonstrated that a crowdsourced approach was effective for collecting data to assess symptomology associated with COVID-19. Such a strategy may facilitate efficient assessments in a dynamic intersection between emerging infectious diseases, and societal and environmental changes.