PMC:7795972 / 7989-9492 JSONTXT

{"project":"LitCovid-PubTator","denotations":[{"id":"92","span":{"begin":573,"end":581},"obj":"Disease"},{"id":"93","span":{"begin":628,"end":636},"obj":"Disease"},{"id":"95","span":{"begin":1322,"end":1334},"obj":"Species"}],"attributes":[{"id":"A92","pred":"tao:has_database_id","subj":"92","obj":"MESH:C000657245"},{"id":"A93","pred":"tao:has_database_id","subj":"93","obj":"MESH:C000657245"},{"id":"A95","pred":"tao:has_database_id","subj":"95","obj":"Tax:9606"}],"namespaces":[{"prefix":"Tax","uri":"https://www.ncbi.nlm.nih.gov/taxonomy/"},{"prefix":"MESH","uri":"https://id.nlm.nih.gov/mesh/"},{"prefix":"Gene","uri":"https://www.ncbi.nlm.nih.gov/gene/"},{"prefix":"CVCL","uri":"https://web.expasy.org/cellosaurus/CVCL_"}],"text":"2.3. Statistical Analyses\nAll statistical analyses were performed using the software Stata SE 16 (StataCorp, College Station, TX, USA). Graphic presentations were produced in Microsoft Excel 15.26 (Microsoft, Redmond, WA, USA). The Pearson’s chi square test was used in order to determine the statistical significance of contingency tables on which graphic presentations were based. An ordered logistic regression model presented with odds ratios (OR) with 95% confidence intervals was used to predict the degree of emotional eating on a scale from 1 to 7 by the variables COVID-19-related worries, work-related consequences of COVID-19 and psychological distress, and sociodemographic factors. The odds ratios in ordinal logistic models give the change in odds for a one-unit increase in the Likert scale.\nAssumptions including correlation/collinearity between independent variables in the model and proportional odds were checked. The proportionality of odds assumption was assessed for all predictor variables separately. Criteria for proportional odds were met, although the assessment revealed small variations for certain predictors. For the sake of transparency, a multinomial logistic regression table is presented (Table S1). Results were considered statistically significant at p-values \u003c 0.05 for all analyses. Participants with missing answers on relevant items were excluded from all analyses. Descriptive statistics with percentages and medians (with 25–75 percentiles) are also presented."}

{"project":"LitCovid-sentences","denotations":[{"id":"T60","span":{"begin":0,"end":4},"obj":"Sentence"},{"id":"T61","span":{"begin":5,"end":25},"obj":"Sentence"},{"id":"T62","span":{"begin":26,"end":135},"obj":"Sentence"},{"id":"T63","span":{"begin":136,"end":227},"obj":"Sentence"},{"id":"T64","span":{"begin":228,"end":382},"obj":"Sentence"},{"id":"T65","span":{"begin":383,"end":694},"obj":"Sentence"},{"id":"T66","span":{"begin":695,"end":806},"obj":"Sentence"},{"id":"T67","span":{"begin":807,"end":932},"obj":"Sentence"},{"id":"T68","span":{"begin":933,"end":1024},"obj":"Sentence"},{"id":"T69","span":{"begin":1025,"end":1139},"obj":"Sentence"},{"id":"T70","span":{"begin":1140,"end":1234},"obj":"Sentence"},{"id":"T71","span":{"begin":1235,"end":1321},"obj":"Sentence"},{"id":"T72","span":{"begin":1322,"end":1406},"obj":"Sentence"},{"id":"T73","span":{"begin":1407,"end":1503},"obj":"Sentence"}],"namespaces":[{"prefix":"_base","uri":"http://pubannotation.org/ontology/tao.owl#"}],"text":"2.3. Statistical Analyses\nAll statistical analyses were performed using the software Stata SE 16 (StataCorp, College Station, TX, USA). Graphic presentations were produced in Microsoft Excel 15.26 (Microsoft, Redmond, WA, USA). The Pearson’s chi square test was used in order to determine the statistical significance of contingency tables on which graphic presentations were based. An ordered logistic regression model presented with odds ratios (OR) with 95% confidence intervals was used to predict the degree of emotional eating on a scale from 1 to 7 by the variables COVID-19-related worries, work-related consequences of COVID-19 and psychological distress, and sociodemographic factors. The odds ratios in ordinal logistic models give the change in odds for a one-unit increase in the Likert scale.\nAssumptions including correlation/collinearity between independent variables in the model and proportional odds were checked. The proportionality of odds assumption was assessed for all predictor variables separately. Criteria for proportional odds were met, although the assessment revealed small variations for certain predictors. For the sake of transparency, a multinomial logistic regression table is presented (Table S1). Results were considered statistically significant at p-values \u003c 0.05 for all analyses. Participants with missing answers on relevant items were excluded from all analyses. Descriptive statistics with percentages and medians (with 25–75 percentiles) are also presented."}