Social media use by young people with language disorders: a scoping review
Bibliographic record
Abstract
Purpose: Social media are widely used by young people (YP), but how YP with language disorders use social media for social interaction remains insufficiently studied.This article provides an overview of the research on social media use by YP with language disorders.Materials and methods: A scoping review was conducted, guided by a five-stage framework.Ten databases were searched (CeNTRAL, CiNAHL, eRiC, LLBA, Medline, PsychiNFO, Scopus, speechBiTe, web of Science, ProQuest Dissertations & Theses Global).Chaining searches of papers identified for inclusion were conducted.Results: After screening 199 unique papers, 44 were included.Findings revealed that YP with language disorders use social media less compared to typically developing peers; their profile of communication difficulties may impact the types of social media with which they engage.Although intervention studies are limited, the results offer encouraging findings regarding the positive impact of support for use of social media.Barriers and facilitators for social media use are identified.Conclusions: YP with language disorders use social media for social purposes.However, co-designed research into what YP with language disorders perceive their social media needs to be is urgently needed.How to support YP with language disorders to use social media is subject to future investigation. h IMPLICATIONS FOR REHABILITATION• Young people with language disorders are likely using a range of social media to support their social participation, but they use social media less than typically developing peers.• The types of social media young people with language disorders choose to engage with may be impacted by their language/literacy difficulties.• There is preliminary evidence that intervention to support the use of social media by young people with language disorders is beneficial, but more research is required to identify the components to include in social media use training programs.• To support the access to and use of social media by young people with language disorders, healthcare professionals may need to collaborate with parents and schools.
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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 | 0.005 | 0.020 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.003 |
| Bibliometrics | 0.013 | 0.013 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".