{"id":"W2780043826","doi":"10.2196/mhealth.8758","title":"Methods for Evaluating the Content, Usability, and Efficacy of Commercial Mobile Health Apps","year":2017,"lang":"en","type":"article","venue":"JMIR mhealth and uhealth","topic":"Mobile Health and mHealth Applications","field":"Health Professions","cited_by":181,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"National Cancer Institute; National Heart, Lung, and Blood Institute; National Institute on Aging","keywords":"Usability; mHealth; Observational study; Mobile apps; Computer science; Behavior change; Internet privacy; World Wide Web; Medicine; Human–computer interaction; Psychological intervention; Nursing","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":["metaresearch"],"consensus_categories":[],"category_scores_codex":[0.1845773,0.002890129,0.002154716,0.01420183,0.002014231,0.003991016,0.002390475,0.002326366,0.00735285],"category_scores_gemma":[0.3000235,0.001308447,0.005184745,0.008247768,0.002790087,0.003779934,0.003387357,0.00209383,0.002343153],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.003061713,"about_ca_system_score_gemma":0.005541683,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002331786,"about_ca_topic_score_gemma":0.003748431,"domain_scores_codex":[0.76006,0.1114075,0.05158681,0.007330266,0.06776115,0.001854241],"domain_scores_gemma":[0.5066288,0.309995,0.05294809,0.02590199,0.1031429,0.001383188],"domain_codex":null,"domain_gemma":"methods","domain_candidate":"methods","domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.006691573,0.005626841,0.09612408,0.02410368,0.002547363,0.0002671573,0.01238956,0.001196236,0.009537196,0.01265165,0.01455536,0.8143093],"study_design_scores_gemma":[0.007074883,0.03733897,0.5444258,0.03375893,0.008677513,0.001550289,0.01994716,0.01766477,0.0608465,0.03688992,0.2302399,0.001585451],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.1754732,0.01366837,0.39022,0.00219544,0.001413879,0.3352142,0.01035844,0.001126317,0.0703301],"genre_scores_gemma":[0.1134629,0.004690694,0.4751578,0.0009112844,0.0003460121,0.3981865,0.002483116,0.0002564543,0.004505276],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.8154228,"threshold_uncertainty_score":0.9761495,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.4137223720672774,"score_gpt":0.6392994826270851,"score_spread":0.2255771105598077,"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."}}