{"id":"W4210305655","doi":"10.2196/preprints.24180","title":"Mobile Sensing Apps and Self-management of Mental Health During the COVID-19 Pandemic: Web-Based Survey (Preprint)","year":2020,"lang":"en","type":"preprint","venue":"","topic":"Digital Mental Health Interventions","field":"Psychology","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Dalhousie University","funders":"","keywords":"Helpfulness; Mental health; Pandemic; Mobile apps; Preprint; Psychology; mHealth; Social media; Internet privacy; App store; Public health; Coronavirus disease 2019 (COVID-19); Medicine; Psychological intervention; Psychiatry; World Wide Web; Computer science; Social psychology; Nursing","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":[0.002356288,0.0001623331,0.0002722465,0.000996358,0.0004919188,0.0009157704,0.0002596851,0.0007461651,0.007717285],"category_scores_gemma":[0.01182325,0.0003119207,0.0006751604,0.001033423,0.0001899044,0.001637793,0.0008001621,0.0009765644,0.002041456],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004122774,"about_ca_system_score_gemma":0.0007270742,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.006723891,"about_ca_topic_score_gemma":0.009140727,"domain_scores_codex":[0.9990172,0.0003203101,0.0002233972,0.00009339228,0.0002242023,0.0001213978],"domain_scores_gemma":[0.9906257,0.004583389,0.002026284,0.0002406485,0.001709705,0.000814083],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0003094687,0.0008730026,0.8942507,0.0023573,0.0001555637,0.0001604928,0.00640332,0.00008980391,0.0004471333,0.0001274197,0.04827577,0.04654998],"study_design_scores_gemma":[0.00004888181,0.000519496,0.9785669,0.0008638353,0.00005379667,0.0001575302,0.008145516,0.0001942504,0.0001332847,0.00003477142,0.01125265,0.00002900267],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9456702,0.0009801144,0.0004500384,0.003707725,0.0002651663,0.001574299,0.04038606,0.0001054916,0.006861026],"genre_scores_gemma":[0.9581239,0.003864834,0.002981288,0.006525865,0.0004578941,0.005264394,0.0166163,0.00006985505,0.006095519],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.007717285,"threshold_uncertainty_score":0.02581686,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.08052152831202146,"score_gpt":0.4057377140909476,"score_spread":0.3252161857789261,"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."}}