{"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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00145006,0.0001332487,0.0002174766,0.00005353602,0.001100112,0.0000112169,0.00009783237,0.00009029861,0.00001265459],"category_scores_gemma":[0.00007457512,0.0001149399,0.0000307869,0.0001019561,0.00004537785,0.0001018076,0.0001019031,0.0002753781,0.00006443733],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001244304,"about_ca_system_score_gemma":0.0001448494,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003487181,"about_ca_topic_score_gemma":0.001993883,"domain_scores_codex":[0.9982625,0.0002950338,0.0004578334,0.000399114,0.00013959,0.0004459617],"domain_scores_gemma":[0.9990775,0.0001980004,0.0002128132,0.0002478025,0.0001448262,0.0001190775],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0001034082,0.000690652,0.8704943,0.0006396769,0.00002513057,3.83153e-7,0.05100666,1.287299e-8,0.00001476928,0.0000440823,0.001867594,0.0751133],"study_design_scores_gemma":[0.002647647,0.000125243,0.9742485,0.0003099631,0.00001586203,2.783162e-7,0.0119354,0.0001848436,0.000001471614,0.0002155727,0.01018816,0.0001270706],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9930966,0.00008404577,0.001759447,0.0001327669,0.0003850787,0.003645769,0.00001178453,0.000123549,0.0007609983],"genre_scores_gemma":[0.9945233,0.00001374693,0.002871578,0.0003221556,0.0003857761,0.001202856,0.00001369672,0.00001957302,0.0006472896],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1037542,"threshold_uncertainty_score":0.8461282,"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."}}