{"doi":"10.36227/techrxiv.23256119","title":"Can an Unobtrusive, Multimodal Mixed-Effects Regressor Based on Open-Ended Interviews Predict OCD Severity?","abstract":"<p>Reliable, valid, efficient measurement of symptom severity in internalizing disorders is critical to gauge treatment response. Self-report and clinical interview are subjective and difficult to standardize, impose patient burden, and lack granularity. We tested the hypothesis that comprehensive sampling of audio and visual modalities during open-ended interviews can reveal severity of obsessive-compulsive disorder (OCD) and comorbid depression. Participants were six patients with chronic, refractory OCD that were treated with deep brain stimulation (DBS). They were recorded during open-ended interviews at pre- and post-surgery baselines and at 3-month intervals following activation of the DBS. Ground-truth severity was assessed by clinical interview and self-report. Visual and auditory modalities included facial action units, head and facial landmarks, speech behavior and content, and voice acoustics. Using mixed-effects random forest regression with Shapley feature reduction strongly predicted severity of OCD, severity of comorbid depression, and total electrical energy delivered by the DBS electrodes (ICC = 0.83, 0.87, and 0.81, respectively). Multimodal measures of behavior outperformed ones from single modalities. The approach could contribute to closed-loop DBS that would automatically titrate DBS based on affect measures. </p>","journal":null,"year":2023,"id":408355,"datarank":0.0,"base_score":0.0,"endowment":0.0,"self_citation_contribution":0.0,"citation_network_contribution":0.0,"self_endowment_contribution":0.0,"citer_contribution":0.0,"corpus_percentile":null,"corpus_rank":null,"citation_count":0,"citer_count":0,"citers_with_citation_signal":0,"citers_with_endowment":0,"datacite_reuse_total":0,"is_dataset":false,"is_dataset_confidence":0.9535,"is_data_producer":false,"deposit_databanks":null,"is_oa":true,"file_count":0,"downloads":0,"has_version_chain":false,"published_date":"2023-01-01","fair_score":null,"fair_percentile":null,"algorithm_id":"datarank_citation_only_1hop_v6","ranking_scope":"data_only","authors":[{"id":686567,"name":"Ali Darzi","orcid":"0000-0003-4529-9117","position":1,"is_corresponding":false},{"id":585358,"name":"Itır Önal Ertuğrul","orcid":"0000-0002-0999-8626","position":2,"is_corresponding":false},{"id":560662,"name":"Nicole R. Provenza","orcid":"0000-0002-6952-5417","position":3,"is_corresponding":false},{"id":1054836,"name":"Ron Gadot","orcid":"0000-0001-6480-3521","position":4,"is_corresponding":false},{"id":1188037,"name":"Eric Storch","orcid":null,"position":5,"is_corresponding":false},{"id":240427,"name":"Sameer A. Sheth","orcid":"0000-0001-8770-8965","position":6,"is_corresponding":false},{"id":430990,"name":"Wayne K. Goodman","orcid":"0000-0001-6717-082X","position":7,"is_corresponding":false},{"id":296056,"name":"Jeffrey F. Cohn","orcid":"0000-0002-9393-1116","position":8,"is_corresponding":false},{"id":986712,"name":"Saurabh Hinduja","orcid":"0000-0003-1637-5950","position":0,"is_corresponding":true}],"reference_count":92,"raw_metadata":null,"created_at":"2026-07-19T01:21:18.414003Z","pmid":null,"pmcid":null,"fwci":null,"citation_percentile":null,"influential_citations":0,"oa_status":null,"license":null,"views":0,"total_file_size_bytes":0,"version_count":0,"fair_f":null,"fair_a":null,"fair_i":null,"fair_r":null,"fair_zscore":null,"fair_rationale":null,"fair_model":null,"fair_agent_version":null,"fair_fulltext_source":null,"fair_has_llm":null,"fair_computed_at":null,"clinical_trials":[],"software_tools":[],"db_accessions":[],"linked_datasets":[],"topics":[]}