{"id":"W4317765709","doi":"10.2196/43052","title":"A Mental Health and Well-Being Chatbot: User Event Log Analysis","year":2023,"lang":"en","type":"article","venue":"JMIR mhealth and uhealth","topic":"Digital Mental Health Interventions","field":"Psychology","cited_by":33,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Interreg; Munster Technological University; Luleå Tekniska Universitet; Ulster University; Itä-Suomen Yliopisto","keywords":"Chatbot; Cluster analysis; Computer science; World Wide Web; Mental health; Digital health; Mood; User experience design; mHealth; Psychology; Internet privacy; Psychological intervention; Human–computer interaction; Health care; Social psychology; Artificial intelligence","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00116,0.000303376,0.0006488098,0.0008439068,0.0007070504,0.00006889028,0.0001553632,0.0001394367,0.0002574591],"category_scores_gemma":[0.00001575864,0.0002996702,0.0001609866,0.001599858,0.0001350031,0.0001809156,0.0001512098,0.0003523887,0.0005216697],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002763463,"about_ca_system_score_gemma":0.0002231976,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001266196,"about_ca_topic_score_gemma":0.0005657506,"domain_scores_codex":[0.9961346,0.0003317605,0.001031396,0.0008074365,0.0003323615,0.001362477],"domain_scores_gemma":[0.9973603,0.0001206676,0.0003901459,0.0004349603,0.00003326172,0.001660606],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"observational","study_design_scores_codex":[0.001259056,0.002502131,0.2566306,0.007767906,0.001205679,0.00009688985,0.05380891,0.00001023238,0.000003263476,0.1441356,0.1821449,0.3504348],"study_design_scores_gemma":[0.003289996,0.003544508,0.8722361,0.0003809335,0.0002164995,0.0001208072,0.007497776,0.0007661569,0.000003684973,0.004238212,0.1070451,0.000660193],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9502036,0.003299383,0.0001058174,0.03767498,0.001380399,0.001442699,0.0001608332,0.0003905515,0.005341719],"genre_scores_gemma":[0.9848156,0.0009357649,0.0001225984,0.007150716,0.0001496984,0.0002554239,0.0003337534,0.00004820182,0.006188262],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.6156056,"threshold_uncertainty_score":0.9999455,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05001256040139479,"score_gpt":0.4472985097235205,"score_spread":0.3972859493221257,"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."}}