{"id":"W4414401764","doi":"10.1080/02607476.2025.2562335","title":"Leveraging digital programming to support pre-service teachers’ stress management and well-being: evidence of effectiveness and acceptability","year":2025,"lang":"en","type":"article","venue":"Journal of Education for Teaching International Research and Pedagogy","topic":"Mindfulness and Compassion Interventions","field":"Psychology","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University","funders":"Rossy Foundation","keywords":"Stress (linguistics); Component (thermodynamics); Field (mathematics); Stress management; Digital health","routes":{"ca_aff":true,"ca_fund":false,"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":[0.0009390112,0.000260823,0.0002924365,0.0004728526,0.0002717211,0.000554832,0.0004383931,0.000319736,0.004488975],"category_scores_gemma":[0.004160641,0.0001246158,0.0003649867,0.0002714164,0.0002613924,0.0003456097,0.0007278118,0.0005470286,0.0003760889],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000243754,"about_ca_system_score_gemma":0.000573797,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0007595757,"about_ca_topic_score_gemma":0.001819829,"domain_scores_codex":[0.9994612,0.000227927,0.00003906692,0.00004539096,0.0001378921,0.00008854987],"domain_scores_gemma":[0.9981496,0.001098803,0.0002029215,0.0001126307,0.00009768813,0.0003383461],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"nonrandomized_trial","study_design_scores_codex":[0.003030853,0.02964123,0.02817329,0.002739324,0.0001760549,0.000231454,0.002395535,0.0003964555,0.007620538,0.0001926232,0.0009834889,0.924419],"study_design_scores_gemma":[0.006547773,0.1329537,0.7690342,0.00479197,0.001138369,0.002040867,0.0138797,0.00278182,0.0305462,0.001473985,0.03467711,0.0001343321],"study_design_candidate":"nonrandomized_trial","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9938244,0.0008004679,0.0006198667,0.0002404629,0.00005260863,0.0004268079,0.0000650189,0.00007054026,0.003899908],"genre_scores_gemma":[0.9881015,0.002883419,0.005734387,0.0001785249,0.00009203584,0.0007663256,0.0001057162,0.00001719537,0.002120897],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.004488975,"threshold_uncertainty_score":0.01501709,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.08300205649592121,"score_gpt":0.5128945345804291,"score_spread":0.4298924780845079,"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."}}