{"id":"W3024348737","doi":"10.1016/j.sapharm.2020.04.022","title":"Development of an electronic tool (e-AdPharm) to address unmet needs and barriers of community pharmacists to provide medication adherence support to patients","year":2020,"lang":"en","type":"article","venue":"Research in Social and Administrative Pharmacy","topic":"Medication Adherence and Compliance","field":"Medicine","cited_by":6,"is_retracted":false,"has_abstract":false,"ca_institutions":"AstraZeneca (Canada); Université de Montréal; Université Laval; The Quebec Population Health Research Network; Centre Hospitalier Universitaire de Sherbrooke; Centre Intégré Universitaire de Santé et de Services Sociaux du Centre-Sud-de-l'Île-de-Montréal","funders":"Université de Montréal","keywords":"Focus group; Medicine; Medication adherence; Medical prescription; Thematic analysis; Pharmacy; Family medicine; Qualitative research; Nursing","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.01198486,0.0006452248,0.0005188776,0.001925982,0.0005950332,0.001612167,0.001581665,0.001005185,0.01028167],"category_scores_gemma":[0.02876857,0.0004528305,0.0008478449,0.0009968099,0.0003120652,0.002439615,0.001742797,0.00106447,0.002144941],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005554529,"about_ca_system_score_gemma":0.004233567,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001664452,"about_ca_topic_score_gemma":0.002853189,"domain_scores_codex":[0.9934128,0.00322804,0.001155001,0.0004951151,0.001421889,0.0002872],"domain_scores_gemma":[0.971291,0.01666026,0.001802412,0.002091612,0.006597037,0.001557637],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.001023955,0.005399224,0.04993651,0.001237453,0.0001051439,0.0003082694,0.000958065,0.0006031872,0.006228371,0.00132545,0.01716037,0.9157139],"study_design_scores_gemma":[0.005346596,0.02248769,0.3825146,0.007123369,0.001579298,0.005701885,0.008307763,0.07476032,0.1046585,0.008644935,0.3778898,0.0009852542],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5774658,0.001505315,0.3047588,0.01213219,0.002219684,0.03293195,0.009751404,0.01476642,0.0444685],"genre_scores_gemma":[0.2795697,0.0007723045,0.6916945,0.002452998,0.0002297439,0.009312382,0.004047287,0.000329499,0.01159159],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01198486,"threshold_uncertainty_score":0.0633828,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.3570682049126789,"score_gpt":0.527307746235172,"score_spread":0.170239541322493,"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."}}