{"id":"W2095169448","doi":"10.2196/resprot.4099","title":"Development of a Fully Automated, Web-Based, Tailored Intervention Promoting Regular Physical Activity Among Insufficiently Active Adults With Type 2 Diabetes: Integrating the I-Change Model, Self-Determination Theory, and Motivational Interviewing Components","year":2015,"lang":"en","type":"article","venue":"JMIR Research Protocols","topic":"Physical Activity and Health","field":"Medicine","cited_by":41,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université Laval; Université du Québec à Trois-Rivières","funders":"Fonds de Recherche du Québec - Santé; Universiteit Maastricht","keywords":"Motivational interviewing; Physical activity; Intervention (counseling); Type 2 diabetes; Behavior change; Psychology; Self-management; Intervention mapping; Self-efficacy; Applied psychology; Health promotion; Medicine; Computer science; Diabetes mellitus; Physical therapy; Social psychology; Nursing; Public health","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":true,"about_ca":true,"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":[0.003607183,0.0006532095,0.0005996142,0.000754438,0.0006505539,0.00059317,0.001138757,0.0004580528,0.002377009],"category_scores_gemma":[0.004950893,0.0003079602,0.0009371185,0.0003688672,0.0003257177,0.000552678,0.001027061,0.0007290933,0.0003600295],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001760458,"about_ca_system_score_gemma":0.01094231,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02626487,"about_ca_topic_score_gemma":0.0423893,"domain_scores_codex":[0.9982588,0.0006666437,0.0001454798,0.0001952245,0.0005336446,0.0002002571],"domain_scores_gemma":[0.998752,0.0004688112,0.0001063657,0.00007891559,0.0003425679,0.0002514624],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.001342625,0.01784485,0.01187842,0.002382353,0.0001609426,0.0002544429,0.002613035,0.003778877,0.009397586,0.0005763555,0.004802878,0.9449676],"study_design_scores_gemma":[0.02451937,0.1184377,0.4871368,0.009643689,0.004492072,0.001215216,0.01090325,0.1109247,0.07153613,0.004017738,0.1562822,0.0008911702],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"protocol","genre_scores_codex":[0.7662012,0.0008442334,0.1174763,0.00264792,0.0003431595,0.09484895,0.001600569,0.003298787,0.01273892],"genre_scores_gemma":[0.3799964,0.001034202,0.5720074,0.000653561,0.00004721332,0.04034499,0.001100489,0.00007905537,0.004736722],"genre_candidate":"protocol","genre_consensus":null,"teacher_disagreement_score":0.02626487,"threshold_uncertainty_score":0.05222398,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2368366109847418,"score_gpt":0.4780745460188126,"score_spread":0.2412379350340708,"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."}}