{"id":"W4322719929","doi":"10.1080/10410236.2023.2185350","title":"Understanding Mental Health Organizations’ Instagram Through Visuals: A Content Analysis","year":2023,"lang":"en","type":"article","venue":"Health Communication","topic":"Social Media in Health Education","field":"Social Sciences","cited_by":20,"is_retracted":false,"has_abstract":true,"ca_institutions":"Mount Royal University","funders":"","keywords":"Mental health; Framing (construction); Content analysis; Psychology; Stigma (botany); Visual literacy; Population; Mental health literacy; Mental image; Social media; Media literacy; Applied psychology; Medicine; Computer science; Sociology; Mental illness; Psychiatry; Pedagogy; Environmental health; World Wide Web; Cognition; Geography","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":[0.002268392,0.0002805036,0.000179549,0.00373769,0.0008221102,0.002020039,0.0003215693,0.0003274269,0.003108544],"category_scores_gemma":[0.01159377,0.0001430421,0.0002317277,0.002687556,0.0008472751,0.002413843,0.001649109,0.0005406865,0.0003830609],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001072949,"about_ca_system_score_gemma":0.0005781507,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003432327,"about_ca_topic_score_gemma":0.005523078,"domain_scores_codex":[0.9988814,0.0005957881,0.00005714078,0.0001075165,0.0002175584,0.0001405479],"domain_scores_gemma":[0.9898049,0.007623211,0.001011063,0.0003291458,0.00106612,0.0001655724],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"qualitative","study_design_gemma":"qualitative","study_design_scores_codex":[0.0005756874,0.0003220866,0.1812488,0.002313154,0.00009020032,0.0006911194,0.4565097,0.0005160148,0.01731381,0.005873014,0.009355608,0.3251909],"study_design_scores_gemma":[0.00002532827,0.000311782,0.4064682,0.0009004636,0.0001386157,0.0004559769,0.5197411,0.004395599,0.006721723,0.002694084,0.05805884,0.00008828083],"study_design_candidate":"qualitative","study_design_consensus":"qualitative","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9824473,0.000211521,0.004170822,0.0005179259,0.00003324087,0.0003533571,0.001737551,0.00006934511,0.01045879],"genre_scores_gemma":[0.9868935,0.0003568023,0.008259261,0.0001840509,0.00006614943,0.0006558685,0.001238531,0.00006363251,0.002282281],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.00373769,"threshold_uncertainty_score":0.01199651,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.6496528522816464,"score_gpt":0.534257677324065,"score_spread":0.1153951749575813,"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."}}