How aware is the public of the existence, characteristics and causes of language impairment in childhood and where have they heard about it? A European survey
Bibliographic record
Abstract
Public awareness of language impairment in childhood (Developmental Language Disorder (DLD)) has been identified as an important determiner of research and clinical service delivery, yet studies directly assessing public awareness are lacking. This study surveyed awareness across 18 countries of Europe. METHOD: A questionnaire developed by an international team asked whether respondents had heard of language impairment affecting children, what they thought its manifestations and causes were and where they had heard of it. Respondents were also asked whether they had heard of autism, dyslexia, ADD/ADHD and speech disorder. The questionnaire was administered to members of the public in 18 European countries. A total of 1519 responses were obtained, spanning 6 age groups, 4 educational level groups and 3 income level groups. RESULTS: Across all but one country, significantly fewer people had heard of language impairment than any of the other disorders (or 60 % compared to over 90 % for autism). Awareness tended to be lowest in Eastern Europe and greatest in North-Western Europe, and was influenced by education level, age and income level. People in countries with overall low and overall high awareness differed in their views on manifestations and causes. People had heard of language impairment and autism the same way - most frequently through the media, including Internet, and less frequently through their child's school or a medical professional. DISCUSSION: The study confirms that awareness of language impairment and knowledge of the breadth of its manifestations are low. It also suggests opportunities for how to increase awareness, including greater media coverage of language impairment and more efficient use of venues such as schools and healthcare. Ways in which cultural and linguistic differences may influence public awareness efforts are discussed, including the translatability of clinical labels and scientific terms. These may impact the acceptance of a common term and definition across all countries. As awareness campaigns are gaining momentum, the findings of this study can serve as a baseline against which to compare future findings.
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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 | 0.004 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".