Psychoeducational Interventions for Caregivers of Persons With Multiple Sclerosis: Protocol for a Randomized Trial
Bibliographic record
Abstract
BACKGROUND: Of the approximately 1 million people living with multiple sclerosis in the United States, more than half receive informal, unpaid care or support from family or friends (caregivers). These caregivers report high levels of stress, anxiety, and negative emotions. Few researchers have conducted psychoeducational interventions for these caregivers. OBJECTIVE: This paper presents a protocol for a randomized clinical trial that aims to test the efficacy of two interventions for improving stress, anxiety, depression, and negative emotions for caregivers of persons with multiple sclerosis. METHODS: Participants included any self-identified family or friend caregiver of a person with multiple sclerosis. Data collection began in April 2021 and is expected to continue until November 2021. Participants will be randomized to receive either a website-only or a website-coaching intervention delivered for 6 weeks. Data will be collected at baseline, 6 weeks after baseline (after delivery of intervention), and 6 weeks later. RESULTS: The protocol was approved by the institutional review board of the Case Western Reserve University on January 21, 2021 (protocol 20201484). As of May 2021, 66 participants were enrolled. CONCLUSIONS: Our findings will have implications for identifying the efficacy of two types of interventions developed for caregivers of persons with multiple sclerosis to reduce negative psychological outcomes associated with caregiving. TRIAL REGISTRATION: ClinicalTrials.gov NCT04662008; http://clinicaltrials.gov/ct2/show/NCT04662008. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): DERR1-10.2196/30617.
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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 | 0.042 | 0.041 |
| Meta-epidemiology (narrow) | 0.007 | 0.004 |
| Meta-epidemiology (broad) | 0.013 | 0.007 |
| Bibliometrics | 0.003 | 0.005 |
| Science and technology studies | 0.005 | 0.004 |
| Scholarly communication | 0.005 | 0.005 |
| Open science | 0.005 | 0.003 |
| Research integrity | 0.011 | 0.012 |
| Insufficient payload (model declined to judge) | 0.096 | 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".