{"id":"W4229003221","doi":"10.2196/preprints.37046","title":"The Effects of the COVID-19 Pandemic on Mental Health Among Older Adults From Different Communities in Chengmai County, China: Cross-sectional Study (Preprint)","year":2022,"lang":"en","type":"preprint","venue":"","topic":"COVID-19 and Mental Health","field":"Psychology","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University Health Network","funders":"","keywords":"Anxiety; Mental health; Coronavirus disease 2019 (COVID-19); China; Depression (economics); Demography; Pandemic; Cross-sectional study; Medicine; Patient Health Questionnaire; Psychology; Gerontology; Psychiatry; Geography; Internal medicine; Depressive symptoms; Disease","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0007584124,0.0002884794,0.0002890173,0.0007377905,0.0008187664,0.0004895304,0.0003964446,0.0005108266,0.001342822],"category_scores_gemma":[0.001264534,0.0003892892,0.0006058019,0.001100361,0.0002438349,0.0005632701,0.000683081,0.0005092356,0.0001998716],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008677966,"about_ca_system_score_gemma":0.001094462,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.05988454,"about_ca_topic_score_gemma":0.09147191,"domain_scores_codex":[0.9995643,0.00006382706,0.00008489074,0.0001174592,0.00008265068,0.00008686219],"domain_scores_gemma":[0.9992374,0.00006800338,0.0002513575,0.0000514456,0.0001635636,0.0002282082],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00002724118,0.00003995131,0.9982263,0.00003539587,0.00004420364,0.00004458748,0.0004274216,0.00001070999,0.0000867173,0.000009886039,0.0002944975,0.0007529698],"study_design_scores_gemma":[0.000003834652,0.00004521271,0.9991459,0.00001124235,0.00001790053,0.00003114788,0.0005543749,0.00003851499,0.00001264519,0.000004098486,0.0001322322,0.000002898061],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9985685,0.0001375921,0.00002390444,0.0001089067,0.0000107146,0.00003366129,0.0008586601,0.000001664759,0.0002562874],"genre_scores_gemma":[0.9981273,0.0001584475,0.00007685284,0.0002336591,0.00001930504,0.00008389616,0.0009964342,0.000001176621,0.0003030515],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.05988454,"threshold_uncertainty_score":0.119072,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05595455280454229,"score_gpt":0.4147845154182316,"score_spread":0.3588299626136893,"validation_status":"score_only:v0-immature-baseline","note":"Baseline scores from an immature model (maturity gate not passed). Scores rank; they never assert a category."}}