Supporting families and caregivers of children with disabilities through a parent peer mentor (PPM): experiences from a patient-oriented research network
Bibliographic record
Abstract
BACKGROUND: The CHILD-BRIGHT Network created a parent peer mentor (PPM) role to support other parents who were engaging as partners in the different research projects and activities of the network. We aim to describe how a PPM functioned to support parent-partners of children with disabilities in research projects within the Network. METHODS: In this case study, the PPM approached 50 parent-partners and scheduled a 1-on-1 initial telephone call to offer support for any issues arising. When consent was provided, the PPM recorded interactions with network parent-partners in a communication report in an Excel form. Also, verbatim transcription from one in-depth interview with the PPM was included for data analysis using qualitative description. The Guidance for Reporting Involvement of Patients and the Public (GRIPP2-SF) was used to report on involvement of patient-partners. RESULTS: A total of 55 interactions between 25 parent-partners and the PPM were documented between May 2018 and June 2021. The PPM's support and liaison role contributed to adaptation of meeting schedules for parent-partners, amendment of the compensation guidelines, and ensuring that internal surveys and the newsletter were more accessible and engaging. The PPM also facilitated community-building by keeping parent-partners connected with researchers in the Network. Families and caregivers in the Network were comfortable sharing their experiences and emotions with the PPM who was also a parent herself, allowing researchers and the Network to learn more about parents' experiences in partnering with them and how to improve engagement. CONCLUSIONS: We highlight the important complementary role that a PPM can play in enhancing patient engagement in research by better understanding the experiences and needs of parent-partners.
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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 | 0.010 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.004 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".