Clinical dimensions of people with co-occurring obsessive-compulsive and related disorders and multiple sclerosis: a scoping review protocol
Bibliographic record
Abstract
INTRODUCTION: Multiple sclerosis (MS) is an immune-mediated demyelinating disease with a significant burden of neuropsychiatric sequelae. These symptoms, including depression and anxiety, are predictors of morbidity and mortality in people with MS. Despite a high prevalence of obsessive-compulsive disorder in MS, potentially shared pathophysiological mechanisms and overlap in possible treatments, no review has specifically examined the clinical dimensions of people with obsessive-compulsive and related disorders (OCRD) and MS. In this scoping review, we aim to map the available knowledge on the clinical dimensions of people with co-occurring OCRD and MS. Understanding the characteristics of this population in greater detail will inform more patient-centred care and create a framework for future studies. METHODS AND ANALYSIS: We developed a search strategy to identify all articles that include people with co-occurring OCRD and MS. The search strategy (extending to the grey literature) was applied to MEDLINE, Embase, PsycINFO, Cochrane Central Register of Controlled Trials, CINAHL, Web of Science and ProQuest Dissertations & Theses. Records will undergo title and abstract screening by two independent reviewers. Articles meeting inclusion criteria based on title and abstract screening will go on to full-text review by the two independent reviewers. After reaching a consensus about articles for inclusion in the final review, data will be extracted using a standardised extraction form. The extracted data will include clinical characteristics of patients such as age, gender, medication use and severity of MS, among others. ETHICS AND DISSEMINATION: This scoping review does not require research ethics approval. Results will be shared at national and/or international conferences, in a peer-reviewed journal publication, in a plain language summary and in a webinar for the general public.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.065 | 0.051 |
| Meta-epidemiology (narrow) | 0.006 | 0.005 |
| Meta-epidemiology (broad) | 0.017 | 0.014 |
| Bibliometrics | 0.022 | 0.016 |
| Science and technology studies | 0.005 | 0.004 |
| Scholarly communication | 0.008 | 0.009 |
| Open science | 0.006 | 0.008 |
| Research integrity | 0.009 | 0.005 |
| Insufficient payload (model declined to judge) | 0.051 | 0.008 |
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".