{"id":"W4386026291","doi":"10.2196/49775","title":"Predictors of the Use of a Mental Health–Focused eHealth System in Patients With Breast and Prostate Cancer: Bayesian Structural Equation Modeling Analysis of a Prospective Study","year":2023,"lang":"en","type":"article","venue":"JMIR Cancer","topic":"Cancer survivorship and care","field":"Medicine","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Medicine; Prostate cancer; Breast cancer; Anxiety; Structural equation modeling; Mental health; Depression (economics); Perceived Stress Scale; eHealth; Clinical psychology; Internal medicine; Cancer; Oncology; Psychiatry; Health care; Stress (linguistics)","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":[],"consensus_categories":[],"category_scores_codex":[0.0001370699,0.0001176096,0.0005141282,0.0002758069,0.00004374196,0.000004957745,0.00004785006,0.00003016633,0.000005187927],"category_scores_gemma":[0.000004825921,0.00007544515,0.00005714534,0.001670296,0.00004932375,0.00008570898,0.00003310759,0.00009358656,1.714937e-8],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005347082,"about_ca_system_score_gemma":0.0003594766,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.05059509,"about_ca_topic_score_gemma":0.07756934,"domain_scores_codex":[0.998594,0.0000917326,0.0004282612,0.0002312262,0.0004856027,0.0001691797],"domain_scores_gemma":[0.9991326,0.00001629129,0.0003538767,0.00020433,0.0002320607,0.00006086483],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.001478354,0.00007742128,0.9533265,0.0005630648,0.0005311937,2.596595e-7,0.0336276,0.008636725,0.000008769075,0.000004188173,0.000006169659,0.001739801],"study_design_scores_gemma":[0.002544135,0.0004442657,0.9212491,0.0006754248,0.0002815841,1.944175e-7,0.004858499,0.06987479,0.00001388264,7.971567e-7,9.602924e-7,0.00005635163],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.995909,0.0001274184,0.00001099461,0.0001419092,0.0001053478,0.002781246,0.0009055628,0.0000165153,0.000001946769],"genre_scores_gemma":[0.999553,0.00002706339,0.00000698864,0.00001562132,0.00001500892,0.0003186484,0.00003631173,0.00001509244,0.00001227588],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.06123807,"threshold_uncertainty_score":0.9557271,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01997440001684958,"score_gpt":0.29394557179194,"score_spread":0.2739711717750904,"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."}}