Parent-to-Parent Support for Parents With Children Who Are Deaf or Hard of Hearing: A Conceptual Framework
Bibliographic record
Abstract
BACKGROUND: Parent-to-parent support for parents with children who are deaf or hard of hearing (D/HH) is identified as an important component of Early Hearing Detection and Intervention (EHDI) programs for children with hearing loss. PURPOSE: The specific aim of this review was to identify the constructs and components of parent-to-parent support for parents of children who are D/HH. RESEARCH DESIGN: An extensive scoping literature review identified 39 peer-reviewed articles published from 2000 to 2014. Studies were selected and reviewed based on standardized procedures. RESULTS: Data were identified, extracted, and organized into libraries of thematic and descriptive content. A conceptual framework of parent-to-parent support for parents of children who are D/HH was developed and presented in a comprehensive, bidirectional informational graphic. The constructs and components of the conceptual framework are (a) well-being: parent, family, and child; (b) knowledge: advocacy, system navigation, and education; and (c) empowerment: confidence and competence. CONCLUSION: The findings from this scoping review led to the development of a structured conceptual framework of parent-to-parent support for parents of children who are D/HH. The conceptual framework provides an important opportunity to explore and clearly define the vital contribution of parents in EHDI programs.
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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 | 0.009 | 0.011 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.009 | 0.007 |
| Science and technology studies | 0.002 | 0.004 |
| Scholarly communication | 0.005 | 0.006 |
| Open science | 0.003 | 0.004 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.001 | 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 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".