{"id":"W3193904384","doi":"10.2196/28555","title":"Advancing Health Equity in Digital Mental Health: Lessons From Medical Anthropology for Global Mental Health","year":2021,"lang":"en","type":"article","venue":"JMIR Mental Health","topic":"Digital Mental Health Interventions","field":"Psychology","cited_by":20,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Society for Psychological Anthropology; University of California, San Diego","keywords":"Mental health; Global mental health; Digital health; Health care; Equity (law); Context (archaeology); Health equity; Mental illness; Global health; Psychology; Public relations; Nursing; Psychiatry; Medicine; Public health; Political science","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.01461138,0.0005589129,0.0005660321,0.00320508,0.00699711,0.01061844,0.001179655,0.003860599,0.006859222],"category_scores_gemma":[0.01263243,0.0003403461,0.0003705648,0.001906062,0.07337751,0.01871192,0.01149681,0.006602833,0.0003197985],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.006415613,"about_ca_system_score_gemma":0.004948676,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005428918,"about_ca_topic_score_gemma":0.006429887,"domain_scores_codex":[0.9952404,0.003681984,0.0001106143,0.0002714694,0.0003027051,0.0003928211],"domain_scores_gemma":[0.9865438,0.01105537,0.000392965,0.0006616885,0.0003843188,0.0009618867],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.00002024655,0.00005770632,0.001558074,0.0001868605,0.00001217211,0.0002483311,0.08136263,0.0002128422,0.00008169372,0.8845642,0.005619404,0.02607582],"study_design_scores_gemma":[0.00002560176,0.0000357909,0.001720645,0.0008399523,0.00001055013,0.0003126515,0.08491381,0.0003835563,0.0001158192,0.8028094,0.1088104,0.00002180237],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"commentary","genre_gemma":"empirical","genre_scores_codex":[0.07150443,0.05581997,0.02670599,0.6012592,0.002702355,0.0001647282,0.0001208748,0.00005649168,0.241666],"genre_scores_gemma":[0.9455795,0.01878007,0.007516951,0.01960773,0.002287034,0.0001629975,0.00004862957,0.00006381814,0.00595338],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01461138,"threshold_uncertainty_score":0.07727325,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06774448211019746,"score_gpt":0.5383072513704833,"score_spread":0.4705627692602858,"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."}}