Online Cognitive-Behavioral Programs for Women Living With Endometriosis: Protocol for a Scoping Review
Bibliographic record
Abstract
Background: Endometriosis is a chronic inflammatory condition experienced by approximately 10% of women worldwide. Women living with endometriosis experience multidimensional burdens often attributed to pain, fatigue, anxiety, and depression. Treatment patterns frequently focus on acute symptom management, while endometriosis is a lifelong condition. In addition, endometriosis-associated symptoms are complex, requiring multimodal treatment strategies. New complementary approaches for symptom management are needed, where further exploration of current online programs is a necessary next step. Online programs can be noninvasive and convenient, provide a sense of comfort, and are often more cost-effective than traditional in-person medicine. Mapping components within the online programs, using the behavior change ontologies, for women living with endometriosis is necessary for developing effective and long-lasting endometriosis management options. Objective: The aim of this scoping review is to examine the range and nature of online cognitive-behavioral programs created to manage endometriosis-associated symptoms and to identify key behavior change techniques (BCTs) within the online programs. Methods: We will conduct the proposed scoping review using the Arksey and O'Malley framework with an interpretive scoping review, consulting stakeholder methodology (6 stages) and referencing the Joanna Briggs Institute Evidence Synthesis Manual. The population-situation framework was used to develop our search strategy, focusing on women living with endometriosis (population) and online programs or online interventions (situation). The study must be a primary source of data, published in 2014 or later, the intervention must take place online and must seek long-term changes for symptom management. Original studies, including peer-reviewed and protocol studies, will be identified from Ovid MEDLINE, Ovid Embase, EBSCOhost CINAHL Complete, ProQuest Nursing and Allied Health Premium, EBSCOhost SPORTDiscus, and ProQuest PsycINFO. Preprints will be identified via the Web of Science Preprint Citation Index. We will also search for active clinical trials from multiple registries. EndNote (Clarivate) will be used for citation management, and Covidence (Veritas Health Innovation Ltd) software will be used for screening and extraction. Up to 5 reviewers will screen studies in Covidence using an inclusion checklist for title and abstract screening and then full-text review. Included studies will be coded to identify BCTs within the online intervention using the BCTs Taxonomy v1. Results will report on the characteristics of the included studies, the BCTs used in the online program or intervention, and the outcomes of the program. Results, including tables and the narrative, have been piloted prior to publication of this protocol using 4 studies that meet our criteria. Results: Data collection is scheduled to start in October of 2025, with results to be published by the Spring of 2026. This research is not directly funded. Conclusions: This review will collate information about online symptom management interventions for women living with endometriosis. Findings will identify gaps that can guide future intervention development.
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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 | 0.068 | 0.058 |
| Meta-epidemiology (narrow) | 0.004 | 0.004 |
| Meta-epidemiology (broad) | 0.009 | 0.012 |
| Bibliometrics | 0.011 | 0.010 |
| Science and technology studies | 0.005 | 0.003 |
| Scholarly communication | 0.006 | 0.006 |
| Open science | 0.005 | 0.007 |
| Research integrity | 0.007 | 0.006 |
| Insufficient payload (model declined to judge) | 0.079 | 0.012 |
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".