Digital peer-to-peer support programme for informal caregivers of people living with motor neuron disease: study protocol for a multi-centre parallel group, single-blinded (outcome assessor) randomised controlled superiority trial
Bibliographic record
Abstract
BACKGROUND: Peer support is effective in improving psychological well-being of family caregivers of people with conditions such as dementia, cancer, and brain injury. However, there are limited data on effective psychological interventions for family caregivers of people living with motor neurone disease. Our objective is to evaluate the efficacy of a virtual peer support programme for improving caregiver psychological wellbeing and caregiving related outcomes. METHODS: We will conduct a multi-centre parallel group randomised controlled superiority trial. Using a multi-modal recruitment strategy, we will recruit informal caregivers from UK MND clinics, in-patient units, and hospices. We will randomise (1:1, stratified by gender) participants to either a 12-week virtual peer support programme or usual care comprising provision of online information resources publicly available via the MND Association website. Peer support programme elements will be delivered via a secure digital e-platform aTouchAway™ (Aetonix, Canada). Our target sample size is 160 (80 each arm). Our primary outcome is the Hospital Anxiety and Depression Scale (HADS) assessed at 12 weeks (primary endpoint). Secondary outcomes that will also be assessed at 12 weeks include the Zarit Burden Interview, Pearlin Mastery Scale, Personal Gain Scale, Positive Affect Scale, and the Brief COPE. Outcome assessors will be blinded to allocation. Tertiary outcomes include perceived usability (1 item 9-point Likert scale) and acceptability (semi-structured qualitative interviews) of the peer support programme. Intervention fidelity measures will comprise frequency, type (text, audio, video), and duration (audio and video) of peer support contact downloaded from the aTouchAway AWS server. We will use a mixed-effects linear model to test the effect of the intervention on the primary outcome. Secondary outcomes will be analysed using linear regression. We have ethical approval (21/NW/0269) from the North-West Research Ethics Committee, UK. DISCUSSION: This single-blinded randomised controlled trial will determine the effect of a virtual peer support programme on caregiver psychological wellbeing and caregiver burden. This study will examine the impact of a virtual peer support intervention on quality-of-life measures in informal caregivers of individuals with MND living in the community. TRIAL REGISTRATION: ClinicalTrials.gov: NCT04695210.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.006 | 0.037 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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 teacher head, 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".