{"id":"W2896550350","doi":"10.2196/11569","title":"A Fall Risk mHealth App for Older Adults: Development and Usability Study","year":2018,"lang":"en","type":"article","venue":"JMIR Aging","topic":"Balance, Gait, and Falls Prevention","field":"Health Professions","cited_by":79,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"National Institute on Aging","keywords":"Usability; mHealth; Fall prevention; Human factors and ergonomics; Poison control; Medicine; Injury prevention; System usability scale; Psychology; Risk perception; Gerontology; Applied psychology; Perception; Psychological intervention; Computer science; Medical emergency; Nursing; Web usability; Human–computer interaction","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":[0.01019016,0.0007027073,0.0007844099,0.001299679,0.000702063,0.0009414554,0.0005542054,0.0007579954,0.0007912812],"category_scores_gemma":[0.01639177,0.0004668954,0.001106149,0.0005523994,0.0004765842,0.00116085,0.001064216,0.0005594901,0.0002895642],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004730325,"about_ca_system_score_gemma":0.001385408,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001385589,"about_ca_topic_score_gemma":0.003267758,"domain_scores_codex":[0.9968256,0.001201976,0.0005165875,0.0002838557,0.0009165901,0.0002555414],"domain_scores_gemma":[0.9912909,0.004494848,0.0004690544,0.000361192,0.002834532,0.0005494698],"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":[0.002792011,0.02802973,0.1966462,0.009279132,0.0005983626,0.005547154,0.1094595,0.001471592,0.05014523,0.0004969223,0.006674158,0.5888599],"study_design_scores_gemma":[0.00222837,0.09445418,0.7778268,0.003275808,0.001864652,0.01034582,0.03523438,0.009340768,0.02739609,0.0005108329,0.03697995,0.0005424197],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9908347,0.000466443,0.003320412,0.0001033893,0.00002306732,0.004091108,0.0001582612,0.0001091528,0.0008934225],"genre_scores_gemma":[0.9285357,0.00217397,0.0566665,0.0003642092,0.00006066287,0.009042519,0.0008196779,0.0001100277,0.002226596],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01019016,"threshold_uncertainty_score":0.05389136,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03043539654196824,"score_gpt":0.3941466017074178,"score_spread":0.3637112051654495,"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."}}