{"id":"W4404141346","doi":"10.2196/63057","title":"Digital Health Literacy and Attitudes Toward eHealth Technologies Among Patients With Cardiovascular Disease and Their Implications for Secondary Prevention: Survey Study","year":2024,"lang":"en","type":"article","venue":"JMIR Formative Research","topic":"Mobile Health and mHealth Applications","field":"Health Professions","cited_by":13,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Preprint; eHealth; Health literacy; Digital health; Literacy; Medicine; Psychology; Internet privacy; Gerontology; Computer science; Health care; World Wide Web; Political science; Pedagogy","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002113813,0.0002355482,0.0004716024,0.001538611,0.0006076634,0.0007866035,0.0002990755,0.0006318709,0.001835028],"category_scores_gemma":[0.004129924,0.00042209,0.000838467,0.001514474,0.0003948275,0.001059407,0.001071682,0.0008537442,0.0007051757],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004407785,"about_ca_system_score_gemma":0.0006329897,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004231893,"about_ca_topic_score_gemma":0.004817398,"domain_scores_codex":[0.9989404,0.0003509961,0.0002021659,0.0001224917,0.0001981865,0.0001857788],"domain_scores_gemma":[0.996748,0.0007510491,0.001081541,0.0001812205,0.000651381,0.0005868635],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00006484367,0.0003190062,0.9969022,0.00002807808,0.00003220644,0.00002869829,0.0009223086,0.00001456549,0.00008896496,0.000009911209,0.0001156122,0.001473553],"study_design_scores_gemma":[0.00002219558,0.0007746831,0.996185,0.0000153939,0.00002567333,0.0001177797,0.002334334,0.000119862,0.00005444911,0.00001156708,0.000331909,0.000007053408],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9988983,0.00005136613,0.00006161244,0.0000368064,0.000002061373,0.00009093024,0.0004640627,0.00000193332,0.0003929904],"genre_scores_gemma":[0.9987592,0.0001073923,0.0001536663,0.00009857843,0.000008247135,0.0001481615,0.000487305,0.000001670266,0.0002358584],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.004231893,"threshold_uncertainty_score":0.01117909,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.09538258868642509,"score_gpt":0.4959214134190326,"score_spread":0.4005388247326075,"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."}}