PMC:7537225 / 24897-26009 JSONTXT

{"project":"LitCovid-PD-MONDO","denotations":[{"id":"T47","span":{"begin":375,"end":383},"obj":"Disease"}],"attributes":[{"id":"A47","pred":"mondo_id","subj":"T47","obj":"http://purl.obolibrary.org/obo/MONDO_0100096"}],"text":"Having established configural, metric, and partly scalar invariance, we proceeded with multilevel models to examine whether the number of people (adults and children) our participants were staying with during the pandemic was associated with their perceived stress level, controlling for gender, age, education level, marital status, scores on the individualism measure, and COVID‐19 severity. Taking into consideration the four models we described in the Statistical Analyses section, based on the Bayesian Information Criterion, the fourth model (with random effects for both slopes and intercepts) showed a superior fit when compared to the others (i.e. ΔBIC \u003e 10; Raftery, 1999; Δ between the first and the fourth model BIC = 432, the second and fourth ΔBIC = 431, the third and fourth ΔBIC = 450). The model that included the squared number of adults and children surrounding the participants in their isolation had substantially worse fit than the second model (ΔBIC = −19); thus, we infer that there is a linear rather than a curvilinear relationship between the number of adults and children, and stress."}

{"project":"LitCovid-PD-CLO","denotations":[{"id":"T107","span":{"begin":608,"end":609},"obj":"http://purl.obolibrary.org/obo/CLO_0001020"},{"id":"T108","span":{"begin":1010,"end":1011},"obj":"http://purl.obolibrary.org/obo/CLO_0001020"},{"id":"T109","span":{"begin":1031,"end":1032},"obj":"http://purl.obolibrary.org/obo/CLO_0001020"}],"text":"Having established configural, metric, and partly scalar invariance, we proceeded with multilevel models to examine whether the number of people (adults and children) our participants were staying with during the pandemic was associated with their perceived stress level, controlling for gender, age, education level, marital status, scores on the individualism measure, and COVID‐19 severity. Taking into consideration the four models we described in the Statistical Analyses section, based on the Bayesian Information Criterion, the fourth model (with random effects for both slopes and intercepts) showed a superior fit when compared to the others (i.e. ΔBIC \u003e 10; Raftery, 1999; Δ between the first and the fourth model BIC = 432, the second and fourth ΔBIC = 431, the third and fourth ΔBIC = 450). The model that included the squared number of adults and children surrounding the participants in their isolation had substantially worse fit than the second model (ΔBIC = −19); thus, we infer that there is a linear rather than a curvilinear relationship between the number of adults and children, and stress."}

{"project":"LitCovid-PubTator","denotations":[{"id":"83","span":{"begin":375,"end":383},"obj":"Disease"}],"attributes":[{"id":"A83","pred":"tao:has_database_id","subj":"83","obj":"MESH:C000657245"}],"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":"Having established configural, metric, and partly scalar invariance, we proceeded with multilevel models to examine whether the number of people (adults and children) our participants were staying with during the pandemic was associated with their perceived stress level, controlling for gender, age, education level, marital status, scores on the individualism measure, and COVID‐19 severity. Taking into consideration the four models we described in the Statistical Analyses section, based on the Bayesian Information Criterion, the fourth model (with random effects for both slopes and intercepts) showed a superior fit when compared to the others (i.e. ΔBIC \u003e 10; Raftery, 1999; Δ between the first and the fourth model BIC = 432, the second and fourth ΔBIC = 431, the third and fourth ΔBIC = 450). The model that included the squared number of adults and children surrounding the participants in their isolation had substantially worse fit than the second model (ΔBIC = −19); thus, we infer that there is a linear rather than a curvilinear relationship between the number of adults and children, and stress."}

{"project":"LitCovid-sentences","denotations":[{"id":"T191","span":{"begin":0,"end":393},"obj":"Sentence"},{"id":"T192","span":{"begin":394,"end":802},"obj":"Sentence"},{"id":"T193","span":{"begin":803,"end":1112},"obj":"Sentence"}],"namespaces":[{"prefix":"_base","uri":"http://pubannotation.org/ontology/tao.owl#"}],"text":"Having established configural, metric, and partly scalar invariance, we proceeded with multilevel models to examine whether the number of people (adults and children) our participants were staying with during the pandemic was associated with their perceived stress level, controlling for gender, age, education level, marital status, scores on the individualism measure, and COVID‐19 severity. Taking into consideration the four models we described in the Statistical Analyses section, based on the Bayesian Information Criterion, the fourth model (with random effects for both slopes and intercepts) showed a superior fit when compared to the others (i.e. ΔBIC \u003e 10; Raftery, 1999; Δ between the first and the fourth model BIC = 432, the second and fourth ΔBIC = 431, the third and fourth ΔBIC = 450). The model that included the squared number of adults and children surrounding the participants in their isolation had substantially worse fit than the second model (ΔBIC = −19); thus, we infer that there is a linear rather than a curvilinear relationship between the number of adults and children, and stress."}