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Record W4411955281 · doi:10.1111/cch.70123

Caregiver Peer Support for Families of Autistic Children in France

2025· article· en· W4411955281 on OpenAlexafffund
Jeffrey McCrossin, Lucyna Lach, Sophie Biette, Émilie Cappe

Bibliographic record

VenueChild Care Health and Development · 2025
Typearticle
Languageen
FieldPsychology
TopicFamily and Disability Support Research
Canadian institutionsMcGill University
FundersFonds de Recherche du Québec - SantéConseil Régional, Île-de-FranceSocial Sciences and Humanities Research Council of CanadaMcGill University
KeywordsPeer supportAutismCLARITYPsychologyTerminologySocial supportService (business)Inclusion (mineral)Peer groupNursingMedical educationDevelopmental psychologyMedicineSocial psychologyPsychiatryBusiness

Abstract

fetched live from OpenAlex

BACKGROUND: Caring for autistic children presents significant emotional and practical challenges, impacting family well-being and creating a need for social supports. In France, these challenges are compounded by historical reliance on psychoanalytic approaches to autism care. This study aims to identify caregiver peer support programmes for families of autistic children in France and explore their contributions to autism care. METHODS: An environmental scan was conducted to identify relevant caregiver peer support programmes. This approach involved an internet search using keywords related to autism, caregiver peer support and France, supplemented by informal consultations in the autism support community to contextualize findings and refine the identification of programmes. Inclusion criteria focused on services offering ongoing support to caregivers by peers. Data extraction was performed on publicly available sources and through direct correspondence with service administrators. RESULTS: Sixteen organizations were identified, offering various forms of caregiver peer support, including group meetings and individual follow-ups. Most services were in-person, with some online options. Peer support roles varied between paid and volunteer positions. Few organizations reported offering training to peers. Key support formats included informal gatherings like discussion groups focusing on emotional support, sharing experiences and advocacy. However, inconsistencies in the availability of detailed information about services and peer training highlight limited clarity in programme descriptions, which may pose challenges for families seeking support. CONCLUSIONS: Caregiver peer support is underdeveloped in France. Insufficient detail regarding service delivery models, support structures and training hinders broader accessibility and adoption. Aligning terminology and promoting the value of caregiver peer support could enhance its role in autism care. Future research should evaluate the impact of these programmes on caregiver and family outcomes and explore stakeholder experiences to refine support mechanisms. SUMMARY: Caregiver peer support for autism is underdeveloped in France. Despite its recognized value in improving family well-being, these services remain limited and inconsistently implemented across the country. Many programmes lack peer support training for caregivers, highlighting opportunities to improve the quality and sustainability of the support provided to families of autistic children. There is significant variation in how caregiver peer support services are offered, ranging from informal gatherings to individualized support, with a recent shift towards professionalizing the role of peer supporters. Standardizing terminology, promoting caregiver expertise and researching programme outcomes could enhance the impact of caregiver peer support on family well-being and autism care in France. The unique challenges and developments in France's caregiver peer support system offer valuable insights into the broader processes and evolution of peer support on a global scale.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.169
Threshold uncertainty score0.478

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.020
GPT teacher head0.359
Teacher spread0.339 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations1
Published2025
Admission routes2
Has abstractyes

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