Collaborative Care to Improve Quality of Life for Anxiety and Depression in Posttraumatic Epilepsy (CoCarePTE): Protocol for a Randomized Hybrid Effectiveness-Implementation Trial
Bibliographic record
Abstract
BACKGROUND: Anxiety and depression in people with epilepsy are common and associated with poor outcomes; yet, they often go untreated due to poor mental health specialist access. Collaborative care is an integrated care model with a strong evidence base in primary care and medical settings, but it has not been evaluated in neurology clinics. Evaluating implementation outcomes when translating evidence-based interventions to new clinical settings to inform future scaling and incorporation into real-world practice is important. OBJECTIVE: The Collaborative Care for Posttraumatic Epilepsy (CoCarePTE) trial aims to evaluate the effectiveness (improvement in emotional quality of life) and implementation of a collaborative care intervention for people with anxiety or depressive symptoms and posttraumatic epilepsy. METHODS: CoCarePTE is a 2-site, randomized, single-blind, hybrid type 1 effectiveness-implementation trial that will randomize 60 adults to receive either neurology-based collaborative care or usual care. Adults receiving neurological care at participating centers with anxiety or depressive symptoms and a history of at least mild traumatic brain injury before epilepsy onset will be enrolled. The collaborative care intervention is a 24-week stepped-care model with video or telephone calls every 2 weeks by a care manager for measurement-based anxiety and depression care, seizure care monitoring, and brief therapy intervention delivery. This is supplemented by antidepressant prescribing recommendations by psychiatrists for neurologists via case conferences and care manager-facilitated team communication. In step 2 of the intervention, individuals with <50% symptom reduction by 10 weeks will receive an added 8-session remote cognitive behavioral therapy program. The study is powered to detect a moderate improvement in emotional quality of life. As a hybrid type 1 trial, effectiveness is the primary focus, with the primary outcome being a change in emotional quality of life at 6 months in the intervention group compared to control. Secondary effectiveness outcomes are 6-month changes in depression, anxiety, and overall quality of life. Implementation outcomes, including fidelity, acceptability, feasibility, and appropriateness, are evaluated before implementation and at 3 months. The primary effectiveness analysis will compare changes in emotional quality of life scores from baseline to 6 months between the intervention and control arms using multiple linear regression modeling, adjusting for study site and using an intent-to-treat approach. RESULTS: Enrollment commenced in 2023, with modifications in the inclusion and exclusion made after the first 6 enrollees due to slow recruitment. Enrollment is expected to continue at least into early 2025. CONCLUSIONS: The CoCarePTE trial is novel in its use of a hybrid effectiveness-implementation design to evaluate an evidence-based mental health intervention in epilepsy, and by incorporating seizure care into a collaborative care model. If a significant improvement in emotional quality of life is found in the intervention group compared to usual care, this would support next step scaling or clinical implementation. TRIAL REGISTRATION: ClinicalTrials.gov NCT05353452; https://www.clinicaltrials.gov/study/NCT05353452. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): DERR1-10.2196/59329.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.038 | 0.037 |
| Meta-epidemiology (narrow) | 0.007 | 0.004 |
| Meta-epidemiology (broad) | 0.010 | 0.008 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.004 | 0.004 |
| Scholarly communication | 0.005 | 0.005 |
| Open science | 0.004 | 0.003 |
| Research integrity | 0.007 | 0.010 |
| Insufficient payload (model declined to judge) | 0.106 | 0.017 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".