2f:I[703058,["/_next/static/immutable/chunks/3bhq_5eh1d760.js","/_next/static/immutable/chunks/1855-ogyi8eh4.js","/_next/static/immutable/chunks/2pfsjpn6k6zlg.js","/_next/static/immutable/chunks/26c7v3_3uwnwu.js","/_next/static/immutable/chunks/25a3ozcrvi1ff.js","/_next/static/immutable/chunks/2r4wx50nvjh_4.js","/_next/static/immutable/chunks/23fsw06hsi5b1.js","/_next/static/immutable/chunks/06_yt270h41rg.js","/_next/static/immutable/chunks/3ezsiz-7shkna.js","/_next/static/immutable/chunks/20x2y96ldu5wx.js","/_next/static/immutable/chunks/2lxntcm3pd1_h.js","/_next/static/immutable/chunks/00dgco8irq3jw.js","/_next/static/immutable/chunks/00nwe-kq0rboc.js","/_next/static/immutable/chunks/2051ffx3xzio9.js"],"PaperListPageClient"] 30:T9f8,Medication nonadherence contributes to vision loss from glaucoma, a leading cause of irreversible blindness in the US. Intervention to improve adherence can benefit health outcomes and quality of life, while reducing health system and public health burden. To compare the Support, Educate, Empower (SEE) intervention with standard written education on glaucoma medication adherence. The SEE study was a parallel, nonmasked, 1:1 randomized clinical trial testing intervention superiority. Participants were recruited from the University of Michigan (UM) and Henry Ford Health System (HFHS) between April 27, 2021, and December 18, 2023. Adults with glaucoma taking 1 or more ocular hypotensive eye drop medications who self-reported adherence of 85% or lower were eligible. The SEE intervention is a 6-month motivational interviewing-based glaucoma health coaching program administered by a nonphysician counselor, including 3 in-person sessions, 4 between-visit phone calls, personalized multimedia glaucoma education, and automated medication reminders. The control consisted of usual care and 3 mailings of standard written glaucoma education. Medication adherence (primary outcome) was electronically monitored (AdhereTech) and calculated as the percentage of doses taken on time divided by those prescribed over the 6-month study period. Change in glaucoma-related distress (secondary outcome) was also investigated. Of 236 participants enrolled (108 in UM and 128 in HFHS), 235 (mean [SD] age, 67.3 [10.9] years; 124 [53%] female) were randomized to the SEE intervention (n = 117) or control (n = 118). Participant characteristics were balanced between groups. Mean (SD) self-reported adherence was 63.9% (17.9%). Medication adherence was significantly better in the SEE intervention group compared with that among control participants (mean [SD], 77.6% [19.7%]; n = 113 vs 58.0% [25.2%]; n = 114; difference, 19.7%; 95% CI, 13.7 to 25.6; P < .001), and more achieved 80% or greater adherence (62 of 113 [54.9%] vs 27 of 114 [23.7%]; P < .001). The difference in change in glaucoma-related distress between intervention and control was -0.3 (95% CI, -0.5 to -0.1) after adjusting for baseline distress. The SEE glaucoma coaching program improved glaucoma medication adherence and reduced glaucoma-related distress compared with standard written education. The SEE program represents an evidence-based method to improve medication adherence necessary to improve glaucoma outcomes. ClinicalTrials.gov Identifier: NCT04735653.31:T10b7, Importance Medication nonadherence contributes to vision loss from glaucoma, a leading cause of irreversible blindness in the US. Intervention to improve adherence can benefit health outcomes and quality of life, while reducing health system and public health burden. Objective To compare the Support, Educate, Empower (SEE) intervention with standard written education on glaucoma medication adherence. Design, Setting, and Participants The SEE study was a parallel, nonmasked, 1:1 randomized clinical trial testing intervention superiority. Participants were recruited from the University of Michigan (UM) and Henry Ford Health System (HFHS) between April 27, 2021, and December 18, 2023. Adults with glaucoma taking 1 or more ocular hypotensive eye drop medications who self-reported adherence of 85% or lower were eligible. Intervention The SEE intervention is a 6-month motivational interviewing-based glaucoma health coaching program administered by a nonphysician counselor, including 3 in-person sessions, 4 between-visit phone calls, personalized multimedia glaucoma education, and automated medication reminders. The control consisted of usual care and 3 mailings of standard written glaucoma education. Main Outcomes and Measures Medication adherence (primary outcome) was electronically monitored (AdhereTech) and calculated as the percentage of doses taken on time divided by those prescribed over the 6-month study period. Change in glaucoma-related distress (secondary outcome) was also investigated. Results Of 236 participants enrolled (108 in UM and 128 in HFHS), 235 (mean [SD] age, 67.3 [10.9] years; 124 [53%] female) were randomized to the SEE intervention (n = 117) or control (n = 118). Participant characteristics were balanced between groups. Mean (SD) self-reported adherence was 63.9% (17.9%). Medication adherence was significantly better in the SEE intervention group compared with that among control participants (mean [SD], 77.6% [19.7%]; n = 113 vs 58.0% [25.2%]; n = 114; difference, 19.7%; 95% CI, 13.7 to 25.6; P &lt; .001), and more achieved 80% or greater adherence (62 of 113 [54.9%] vs 27 of 114 [23.7%]; P &lt; .001). The difference in change in glaucoma-related distress between intervention and control was −0.3 (95% CI, −0.5 to −0.1) after adjusting for baseline distress. Conclusions and Relevance The SEE glaucoma coaching program improved glaucoma medication adherence and reduced glaucoma-related distress compared with standard written education. The SEE program represents an evidence-based method to improve medication adherence necessary to improve glaucoma outcomes. Trial Registration ClinicalTrials.gov Identifier: NCT04735653 32:T42d,Mental health disorders are some of the greatest contributors to the global disease burden, and healthcare systems are struggling to provide scalable care of high quality. Artificial intelligence (AI)-based tools and applications are some of the most significant technological advances in the mental healthcare field. Researchers have spent decades to build, evaluate, and refine AI models to conduct tasks such as identifying the treatment intervention and rating the quality of treatment. These models have been utilized to monitor treatment quality, enhance training, support clinical documentation, and supplement client treatment support. However, significant limitations include the potential for algorithmic biases and ethical concerns regarding patient data privacy. While AI shows promise in addressing the mental health workforce shortage and improving the quality of care, successful implementation requires thoughtful integration. This review examines research in which AI is a complement to, not replacement for, human providers in mental health treatment.33:T43e,Mental health disorders are some of the greatest contributors to the global disease burden, and healthcare systems are struggling to provide scalable care of high quality. Artificial intelligence (AI)-based tools and applications are some of the most significant technological advances in the mental healthcare field. Researchers have spent decades to build, evaluate, and refine AI models to conduct tasks such as identifying the treatment intervention and rating the quality of treatment. These models have been utilized to monitor treatment quality, enhance training, support clinical documentation, and supplement client treatment support. However, significant limitations include the potential for algorithmic biases and ethical concerns regarding patient data privacy. While AI shows promise in addressing the mental health workforce shortage and improving the quality of care, successful implementation requires thoughtful integration. This review examines research in which AI is a complement to, not replacement for, human providers in mental health treatment.25:[[["$","script","0",{"type":"application/ld+json","dangerouslySetInnerHTML":{"__html":"{\"@context\":\"https://schema.org\",\"@type\":\"CollectionPage\",\"name\":\"Motivational Interviewing: modality Research & Clinical Takeaways\",\"description\":\"Explore peer-reviewed papers on Motivational Interviewing (modality). Clinician-written summaries and actionable practice insights. 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All structured data were derived solely from the abstract. Key details such as step-up criteria, dropout rates, and detailed adverse events could not be verified from the full text.","value_numeric":null},{"paper_doi":"10.1097/hep.0000000000001796","tag_type":"warning","value":"The study population is predominantly male (86%) and VA-based, which may limit generalizability to broader or more diverse populations.","value_numeric":null}],"summaries":{"what_studied":"This RCT evaluated telehealth stepped alcohol treatment (SAT) vs. usual care (UC) in 157 patients with chronic liver disease (CLD) and unhealthy alcohol use, across one safety-net and two VA hepatology clinics, over 6 months (March 2022–February 2024).","key_result":"SAT did not outperform UC on the primary outcome (proportion drinking below moderate levels), but produced significantly greater reductions in drinks/week at both month 3 (estimate −0.66, P=0.03) and month 6 (estimate −0.67, P=0.03). Six-month abstinence rates were 29% (SAT) vs. 18% (UC), though this difference was not statistically significant (P=0.14).","limitations":"- Primary outcome showed no significant difference between arms, limiting conclusions about categorical drinking reduction.\n- Sample was predominantly male (86%) and older (median age 61), limiting generalizability to women and younger patients.\n- High-risk population (48% cirrhosis, 37% with decompensation) may limit engagement, and the study was conducted across only three healthcare systems.","practice_takeaway":"For patients with CLD and unhealthy alcohol use, a telehealth stepped care model starting with motivational interviewing can meaningfully reduce drinking compared to usual care — even in this hard-to-engage group. Patient motivation at baseline predicts response, so assessing and targeting readiness to change may help maximize benefit."}},{"doi":"10.22454/fammed.2026.487946","pmid":"42308632","title":"The Power of Presence","journal_title":"Family Medicine","journal_issn":"0742-3225","published_at":"2026-06-17T00:00:00.000Z","url":"https://doi.org/10.22454/fammed.2026.487946","source_score":1,"is_retracted":false,"is_open_access":true,"raw_metadata":{"pubmed":true,"crossref":true,"unpaywall":true},"created_at":"2026-06-25T13:25:29.266Z","updated_at":"2026-06-25T13:25:29.266Z","tags":[{"paper_doi":"10.22454/fammed.2026.487946","tag_type":"age_group","value":"adult","value_numeric":null},{"paper_doi":"10.22454/fammed.2026.487946","tag_type":"category","value":"Primary Health Care","value_numeric":null},{"paper_doi":"10.22454/fammed.2026.487946","tag_type":"condition","value":"Medical Education","value_numeric":null},{"paper_doi":"10.22454/fammed.2026.487946","tag_type":"impact_flag","value":"limited_evidence","value_numeric":null},{"paper_doi":"10.22454/fammed.2026.487946","tag_type":"level_of_evidence","value":"7","value_numeric":null},{"paper_doi":"10.22454/fammed.2026.487946","tag_type":"modality","value":"Motivational Interviewing","value_numeric":null},{"paper_doi":"10.22454/fammed.2026.487946","tag_type":"study_design","value":"Narrative Essay","value_numeric":null},{"paper_doi":"10.22454/fammed.2026.487946","tag_type":"warning","value":"No patient outcomes are measured; clinical applicability is inferred, not tested.","value_numeric":null},{"paper_doi":"10.22454/fammed.2026.487946","tag_type":"warning","value":"Study design classification as 'Narrative Essay' reflects the qualitative, reflective nature of the piece — it does not meet criteria for any higher evidence tier.","value_numeric":null},{"paper_doi":"10.22454/fammed.2026.487946","tag_type":"warning","value":"This is a narrative essay based on a single classroom experience by the instructor-author; no empirical data, sample size, or statistical findings are reported.","value_numeric":null}],"summaries":{"what_studied":"A narrative essay reflecting on a single motivational interviewing session with first-year medical students, examining how creating space for presence and reflection shapes early clinical formation.","key_result":"Students spontaneously named relational needs (e.g., 'grace,' 'empathy') when given unstructured reflective space, suggesting that early learners already grasp the relational core of medicine when given room to voice it.","limitations":"Single classroom observation by the instructor-author; no control group, outcome measures, or follow-up data; findings are not generalizable beyond this anecdotal experience.","practice_takeaway":"Medical educators can foster deeper relational learning by intentionally stepping back during skill-building sessions rather than filling every moment with instruction. Teaching OARS skills (Open-ended questions, Affirmations, Reflective listening, Summarizing) within a psychologically safe environment may help students internalize that trust — not speed — drives real clinical efficiency."}},{"doi":"10.1007/s10896-026-01115-z","pmid":null,"title":"The Effectiveness of Intervention with Intimate Partner Violence Perpetrators: An Umbrella Review","journal_title":"Journal of Family Violence","journal_issn":"0885-7482","published_at":"2026-05-18T00:00:00.000Z","url":"https://doi.org/10.1007/s10896-026-01115-z","source_score":11,"is_retracted":false,"is_open_access":true,"raw_metadata":{"pubmed":false,"crossref":true,"unpaywall":true},"created_at":"2026-05-22T13:22:19.643Z","updated_at":"2026-05-22T13:22:19.643Z","tags":[{"paper_doi":"10.1007/s10896-026-01115-z","tag_type":"age_group","value":"adult","value_numeric":null},{"paper_doi":"10.1007/s10896-026-01115-z","tag_type":"category","value":"Psychology, Clinical","value_numeric":null},{"paper_doi":"10.1007/s10896-026-01115-z","tag_type":"condition","value":"Intimate Partner Violence","value_numeric":null},{"paper_doi":"10.1007/s10896-026-01115-z","tag_type":"impact_flag","value":"limited_evidence","value_numeric":null},{"paper_doi":"10.1007/s10896-026-01115-z","tag_type":"level_of_evidence","value":"2","value_numeric":null},{"paper_doi":"10.1007/s10896-026-01115-z","tag_type":"modality","value":"Acceptance and Commitment Therapy","value_numeric":null},{"paper_doi":"10.1007/s10896-026-01115-z","tag_type":"modality","value":"Cognitive-Behavioral Therapy","value_numeric":null},{"paper_doi":"10.1007/s10896-026-01115-z","tag_type":"modality","value":"Motivational Interviewing","value_numeric":null},{"paper_doi":"10.1007/s10896-026-01115-z","tag_type":"modality","value":"Psychoeducation","value_numeric":null},{"paper_doi":"10.1007/s10896-026-01115-z","tag_type":"sample_size","value":"n=113907","value_numeric":113907},{"paper_doi":"10.1007/s10896-026-01115-z","tag_type":"sex","value":"mixed","value_numeric":null},{"paper_doi":"10.1007/s10896-026-01115-z","tag_type":"study_design","value":"Umbrella Review","value_numeric":null},{"paper_doi":"10.1007/s10896-026-01115-z","tag_type":"warning","value":"ACT findings are based on a limited number of primary studies within a single meta-analysis (Babcock et al., 2024) and should be considered preliminary.","value_numeric":null},{"paper_doi":"10.1007/s10896-026-01115-z","tag_type":"warning","value":"Level of evidence assigned as '2' reflects umbrella review of meta-analyses; actual strength of findings within the review was rated weak-to-suggestive for all included meta-analyses.","value_numeric":null},{"paper_doi":"10.1007/s10896-026-01115-z","tag_type":"warning","value":"The total sample size of 113,907 is the aggregate across all 11 included meta-analyses, with overlapping primary studies (CCA=0.071, moderate overlap); it does not represent unique individuals. Interpret pooled figures cautiously.","value_numeric":null}],"summaries":{"what_studied":"This umbrella review synthesized 11 meta-analyses (published 2004–2024) evaluating the effectiveness of perpetrator intervention programs (PIPs) for adults who committed IPV, covering approaches including the Duluth Model (DM), CBT, ACT, and motivational interviewing, across a combined sample of up to 113,907 individuals.","key_result":"Overall effect sizes for PIPs were small and non-significant across the 3 meta-analyses reporting general efficacy. Evidence strength was weak (n=5) or suggestive (n=4); none reached 'convincing' evidence. ACT-based programs showed the largest effect sizes in the most recent meta-analysis (Babcock et al., 2024), but findings are preliminary. Effects based on official/police records were consistently larger than those based on partner/victim reports.","limitations":"- Most included meta-analyses were rated weak or suggestive in evidence strength, and a second-order meta-analysis was not feasible due to incomplete statistical reporting.\n- Seven of 11 meta-analyses studied only male perpetrators, limiting generalizability to women.\n- Exclusion of grey literature and restriction to three languages may have introduced publication bias.","practice_takeaway":"Traditional DM and CBT programs show only small, inconsistent effects on IPV recidivism — clinicians and program developers should consider integrating ACT- and motivational interviewing-based components, while tailoring intensity to individual risk profiles per RNR principles. Routine structured assessment of perpetrator risk and responsivity factors should guide program selection and dosing."}},{"doi":"10.1177/21677026261425981","pmid":null,"title":"Empathy Regulation in Clinical Science: Regulating the Therapeutic Emotional Circuit","journal_title":"Clinical Psychological Science","journal_issn":"2167-7026","published_at":"2026-04-11T00:00:00.000Z","url":"https://doi.org/10.1177/21677026261425981","source_score":17,"is_retracted":false,"is_open_access":false,"raw_metadata":{"pubmed":false,"crossref":true,"unpaywall":true},"created_at":"2026-05-07T22:51:13.036Z","updated_at":"2026-05-07T22:51:13.036Z","tags":[{"paper_doi":"10.1177/21677026261425981","tag_type":"age_group","value":"mixed","value_numeric":null},{"paper_doi":"10.1177/21677026261425981","tag_type":"category","value":"Psychology, Clinical","value_numeric":null},{"paper_doi":"10.1177/21677026261425981","tag_type":"condition","value":"Mental Health Disorders","value_numeric":null},{"paper_doi":"10.1177/21677026261425981","tag_type":"impact_flag","value":"practice_changing","value_numeric":null},{"paper_doi":"10.1177/21677026261425981","tag_type":"level_of_evidence","value":"7","value_numeric":null},{"paper_doi":"10.1177/21677026261425981","tag_type":"modality","value":"Exposure Therapy","value_numeric":null},{"paper_doi":"10.1177/21677026261425981","tag_type":"modality","value":"Motivational Interviewing","value_numeric":null},{"paper_doi":"10.1177/21677026261425981","tag_type":"modality","value":"Psychotherapy","value_numeric":null},{"paper_doi":"10.1177/21677026261425981","tag_type":"study_design","value":"Theoretical/Conceptual Framework","value_numeric":null},{"paper_doi":"10.1177/21677026261425981","tag_type":"warning","value":"No sample size applies — this is not an empirical study.","value_numeric":null},{"paper_doi":"10.1177/21677026261425981","tag_type":"warning","value":"Study design is best described as a conceptual/opinion piece; level of evidence is set to 7 (expert opinion/narrative review).","value_numeric":null},{"paper_doi":"10.1177/21677026261425981","tag_type":"warning","value":"This paper presents a theoretical model without original empirical data; the impact_flag 'practice_changing' reflects the challenge to longstanding clinical intuition, but the framework awaits experimental validation.","value_numeric":null}],"summaries":{"what_studied":"This theoretical paper proposes a \"therapeutic emotional circuit\" framework examining how therapists regulate empathy to modulate emotional flow between therapist and client, with application to exposure therapy and motivational interviewing.","key_result":"The model argues that optimal empathy regulation differs by treatment context: exposure therapy calls for *down-regulating* affect sharing to avoid interfering with fear extinction, while motivational interviewing calls for *up-regulating* empathic processes to support client engagement and change.","limitations":"This is a conceptual/theoretical framework without primary empirical data; clinical predictions have not yet been tested in trials; generalizability beyond the two illustrated interventions is unestablished.","practice_takeaway":"Therapists should not default to maximum empathy in every context — calibrating empathic engagement to the specific treatment (e.g., pulling back during exposure, leaning in during motivational interviewing) may improve outcomes. Training programs could benefit from teaching empathy regulation as a distinct, active clinical skill."}},{"doi":"10.1001/jamaophthalmol.2026.0001","pmid":"41746659","title":"Effect of the Support, Educate, Empower Personalized Glaucoma Coaching Program on Medication Adherence","journal_title":"JAMA Ophthalmology","journal_issn":"2168-6165","published_at":"2026-02-26T00:00:00.000Z","url":"https://doi.org/10.1001/jamaophthalmol.2026.0001","source_score":35,"is_retracted":false,"is_open_access":true,"raw_metadata":{"ooir":{"day":"2026-04-19","doi":"10.1001/jamaophthalmol.2026.0001","days":"30","issn":"2168-6165","rank":"5","field":"Clinical Medicine","score":"35","category":"Ophthalmology","categories":["Ophthalmology"],"_categories":["Ophthalmology"]},"pubmed":{"doi":"10.1001/jamaophthalmol.2026.0001","title":"Effect of the Support, Educate, Empower Personalized Glaucoma Coaching Program on Medication Adherence: The SEE Program Randomized Clinical Trial.","journal":"JAMA ophthalmology","methods":"","results":"Of 236 participants enrolled (108 in UM and 128 in HFHS), 235 (mean [SD] age, 67.3 [10.9] years; 124 [53%] female) were randomized to the SEE intervention (n = 117) or control (n = 118). Participant characteristics were balanced between groups. Mean (SD) self-reported adherence was 63.9% (17.9%). Medication adherence was significantly better in the SEE intervention group compared with that among control participants (mean [SD], 77.6% [19.7%]; n = 113 vs 58.0% [25.2%]; n = 114; difference, 19.7%; 95% CI, 13.7 to 25.6; P < .001), and more achieved 80% or greater adherence (62 of 113 [54.9%] vs 27 of 114 [23.7%]; P < .001). The difference in change in glaucoma-related distress between intervention and control was -0.3 (95% CI, -0.5 to -0.1) after adjusting for baseline distress.","abstract":"$30","keywords":[],"pubmed_id":"41746659","conclusions":"","publication_date":"2026-02-26T00:00:00"},"crossref":{"DOI":"10.1001/jamaophthalmol.2026.0001","URL":"https://doi.org/10.1001/jamaophthalmol.2026.0001","ISSN":["2168-6165"],"link":[{"URL":"https://jamanetwork.com/journals/jamaophthalmology/articlepdf/2845609/jamaophthalmology_newmancasey_2026_oi_260001_1776173512.61667.pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"page":"299","type":"journal-article","issue":"4","score":1,"title":["Effect of the Support, Educate, Empower Personalized Glaucoma Coaching Program on Medication Adherence"],"author":[{"given":"Paula Anne","family":"Newman-Casey","sequence":"first","affiliation":[{"name":"Department of Ophthalmology and Visual Sciences, University of Michigan, Ann Arbor"}]},{"given":"Leslie M.","family":"Niziol","sequence":"additional","affiliation":[{"name":"Department of Ophthalmology and Visual Sciences, University of Michigan, Ann Arbor"}]},{"given":"Ming-Chen","family":"Lu","sequence":"additional","affiliation":[{"name":"Department of Ophthalmology and Visual Sciences, University of Michigan, Ann Arbor"}]},{"given":"Deborah","family":"Darnley-Fisch","sequence":"additional","affiliation":[{"name":"Department of Ophthalmology, Henry Ford Health System, Detroit, Michigan"}]},{"given":"Nauman","family":"Imami","sequence":"additional","affiliation":[{"name":"Department of Ophthalmology, Henry Ford Health System, Detroit, Michigan"}]},{"given":"Jamie","family":"Mitchell","sequence":"additional","affiliation":[{"name":"School of Social Work, University of Michigan, Ann Arbor"}]},{"given":"Chamisa","family":"MacKenzie","sequence":"additional","affiliation":[{"name":"Department of Ophthalmology and Visual Sciences, University of Michigan, Ann Arbor"}]},{"given":"Michele","family":"Heisler","sequence":"additional","affiliation":[{"name":"Department of Internal Medicine, University of Michigan, Ann Arbor"},{"name":"Department of Health Behavior and Health Equity, School of Public Health, University of Michigan, Ann Arbor"}]}],"issued":{"date-parts":[[2026,4,1]]},"member":"10","prefix":"10.1001","source":"Crossref","volume":"144","created":{"date-time":"2026-02-26T16:30:25Z","timestamp":1772123425000,"date-parts":[[2026,2,26]]},"indexed":{"date-time":"2026-04-17T04:11:01Z","timestamp":1776399061119,"date-parts":[[2026,4,17]]},"subject":[],"abstract":"$31","language":"en","relation":{},"resource":{"primary":{"URL":"https://jamanetwork.com/journals/jamaophthalmology/fullarticle/2845609"}},"subtitle":["The SEE Program Randomized Clinical 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ML-rated fidelity metrics explained 18–22% of variance in client retention/satisfaction and 1.7–5% of variance in symptom reduction across ~166,000 counseling clients. A ChatGPT-4 homework chatbot led to two more session attendances vs. control; AI-edited peer support responses increased empathy, especially among lower-skill peers.","limitations":"- Most studies rely on text-based or research-grade therapy samples that may not generalize to in-person, real-world community mental health settings.\n- LLM-generated clinical notes outperformed human notes on completeness but showed lower faithfulness (hallucinated session content).\n- Algorithmic bias is documented across race, ethnicity, nationality, religion, and gender, with limited corrective strategies tested in mental health contexts.","practice_takeaway":"AI tools for therapy quality monitoring and training show real promise—but clinicians should treat AI-generated fidelity scores, risk assessments, and session notes as one data source, not a final verdict, given known biases and occasional hallucinations. Informed consent, data privacy safeguards, and ongoing bias audits are essential before deploying these tools in practice."}}],"initialOffset":6,"fetchConfig":{"kind":"tags","tags":[{"tag_type":"modality","value":"Motivational Interviewing"}]},"breadcrumbItems":[{"name":"Home","href":"/"},{"name":"Research Hub","href":"/hub"},{"name":"Modalities","href":"/hub/tag/modality"},{"name":"Motivational Interviewing"}],"hrefConfig":{"basePath":"/hub/papers","webViewQueryParams":{"hub_ctx":"tag","hub_tag_type":"modality","hub_tag_value":"Motivational Interviewing"}}}]]

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