Development and implementation of a Facebook-based peer-to-peer support group for caregivers of children with health care needs in New Brunswick
Bibliographic record
Abstract
Facebook has become an important gathering place for patients and caregivers to exchange health-related information and emotional support, otherwise known as peer-to-peer (P2P) support. Despite widespread use of Facebook groups across various patient and caregiver populations, the use of these groups by caregivers of children with complex care needs (CCCN) has not been previously reported. This paper describes the development and launch of a Facebook group for families of CCCN in New Brunswick, Canada, as well as the plans for evaluation and preliminary findings. The Facebook group was developed in consultation with various stakeholders, including a patient and family advisory council. The following factors were taken into consideration: group characteristics, moderators, language, recruitment, and implementation. The potential impact of the group on perceived knowledge of health services and/or resources and health literacy were assessed through semi-structured interviews with group members. The group, launched in October 2020, has been monitored for a period of 10 weeks for its use by caregivers. The group has attracted a total of 81 caregivers of CCCN, including two moderators. Inquiry-based posts were the most common type of posts made by members. The observed surge in group membership upon implementation suggests the need for additional P2P support platforms for caregivers of CCCN in New Brunswick. Ongoing monitoring and evaluation will determine how the group is used by members and whether it has any effect on health literacy and knowledge of resources and services. Keywords: peer-to-peer support, social support, social media, children with health care needs
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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 | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 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".