{"id":"W3022393237","doi":"10.2196/15686","title":"Determining Factors Affecting Nurses’ Acceptance of a Care Plan System Using a Modified Technology Acceptance Model 3: Structural Equation Model With Cross-Sectional Data","year":2020,"lang":"en","type":"article","venue":"JMIR Medical Informatics","topic":"Electronic Health Records Systems","field":"Health Professions","cited_by":25,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Structural equation modeling; Usability; Technology acceptance model; Variance (accounting); Path coefficient; Path analysis (statistics); Psychology; Bivariate analysis; Health care; Nursing; Nursing care; Cross-sectional study; Applied psychology; Knowledge management; Medicine; Computer science; Business","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":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.000649673,0.0003249485,0.0007316442,0.0001926782,0.0006985815,0.00003016932,0.001049747,0.0007876143,0.00002740569],"category_scores_gemma":[0.0006399631,0.0002574884,0.00005241975,0.0005867548,0.0001800375,0.0009244413,0.0004141234,0.001724961,0.000007113887],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006999442,"about_ca_system_score_gemma":0.003299097,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00005077915,"about_ca_topic_score_gemma":0.0001152141,"domain_scores_codex":[0.9952819,0.0001675218,0.002066656,0.0003477047,0.001239742,0.0008964316],"domain_scores_gemma":[0.9965233,0.0003920628,0.001538572,0.0007108141,0.0003999151,0.0004353006],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0004720687,0.00003258138,0.5804573,0.02480893,0.0001419535,0.00000951998,0.1738764,0.2136688,0.0001996958,0.002308825,0.000135559,0.00388839],"study_design_scores_gemma":[0.001160738,0.0001465357,0.001077298,0.001146806,0.00001832277,0.00001864616,0.05100719,0.9451324,0.0000423688,0.00001932701,0.000006660169,0.000223734],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8153819,0.00004109539,0.1817964,0.00005107766,0.0003121427,0.001484915,0.0001790919,0.0002858695,0.0004674304],"genre_scores_gemma":[0.9861376,0.000003305531,0.01308307,0.0002258023,0.0002112097,0.00009401232,0.0001874607,0.00004637336,0.00001122206],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.7314636,"threshold_uncertainty_score":0.9999877,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1951280674665476,"score_gpt":0.4699179523696861,"score_spread":0.2747898849031385,"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."}}