A systematic review on the impact of auditory functioning and language proficiency on psychosocial difficulties in children and adolescents with hearing loss
Bibliographic record
Abstract
Approximately 20% to 40% of children with hearing loss encounter psychosocial difficulties. This prevalence may be outdated, given the advancements in hearing technology and rehabilitation efforts to enhance the psychosocial well-being of these children. A systematic review of up-to-date literature can help to identify factors that may contribute to the children’s psychosocial well-being. A systematic review was conducted. Original articles were identified through systematic searches in Embase, Medline, PsychINFO, and Web of Science Core Collection. The quality of the papers was assessed using the Newcastle-Ottawa Quality Assessment Scale and custom Reviewers’ Criteria. A search was performed on 20 October 2022. A total of 1561 articles were identified, and 36 were included for review. Critical appraisal led to 24 good to fair quality articles, and 12 poor quality articles. Children with hearing loss have a twofold risk of experiencing psychosocial difficulties compared to normal hearing peers. Estimates for functioning in social interactions, like speech perception (in noise) or language proficiency, have proven to be more adequate predictors for psychosocial difficulties than the degree of hearing loss. Our findings can be useful for identifying children at risk for difficulties and offering them earlier and more elaborate psychological interventions.
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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 | 0.008 | 0.061 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.008 | 0.007 |
| Bibliometrics | 0.018 | 0.020 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.048 | 0.002 |
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".