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Enregistrement W4312129349 · doi:10.1111/1460-6984.12826

Do speech–language therapists support young people with communication disability to use social media? A mixed methods study of professional practices

2022· article· en· W4312129349 sur OpenAlexaff
Nichola Shelton, Natalie Munro, Melanie Keep, Julia Starling, Lyn Tieu

Notice bibliographique

RevueInternational Journal of Language & Communication Disorders · 2022
Typearticle
Langueen
DomaineHealth Professions
ThématiqueAssistive Technology in Communication and Mobility
Établissements canadiensUniversity of Toronto
Organismes subventionnairesnon disponible
Mots-clésThematic analysisPsychologySocial mediaMedical educationQualitative researchApplied psychologyMedicineSociology

Résumé

récupéré en direct d'OpenAlex

BACKGROUND: Social media is increasingly used by young people, including those with communication disability. To date, though, little is known about how speech-language therapists (SLTs) support the social media use of young people with communication disability. AIMS: To explore what services SLTs provide to facilitate the social media use of young people with communication disability, including what these services look like, and the factors that impact SLTs' professional practices. METHODS & PROCEDURES: A sequential mixed methods approach was employed including an online survey and in-depth semi-structured interviews. Participants were qualified practising SLTs in Australia with a caseload that included clients aged 12-16 years. Quantitative data were analysed with SPSS. A thematic analysis of qualitative data was conducted with NVivo. OUTCOMES & RESULTS: Survey responses from 61 SLTs were analysed. Interviews were conducted with 16 participants. Survey data indicated that SLTs do not systematically assess or treat young people's use of social media as part of their professional practice. Interview data revealed that where SLTs do support young people's use of social media, they transfer knowledge and practices typically used in offline contexts to underpin their work supporting clients' use of social media. In terms of factors that affect SLTs' practices, three major themes were identified: client/family factors, SLT factors, and societal factors. CONCLUSIONS & IMPLICATIONS: While young people with communication disability may desire digital participation in social media spaces, SLTs' current professional practices do not routinely address this need. Professional practice guidelines would support SLTs' practices in this area. Future research should seek the opinions of young people with communication disability regarding their use of social media, and the role of SLTs in facilitating this. WHAT THIS PAPER ADDS: What is already known on the subject Young people with communication disability use social media, but digital inequality means that they may not do so to the same extent as their typically developing peers. Services targeting a young person's social media use is within the SLT scope of practice. Whether or not SLTs routinely address the social media use of young people with communication disability as part of their professional practice is unknown. What this study adds to existing knowledge This study found that SLTs in Australia do not systematically provide professional services targeting young people's use of social media. When services do address a young person's use of social media, knowledge and practices typically used by SLTs in offline contexts are adapted to support their work targeting online social media contexts. What are the potential or actual clinical implications of this work? This study indicates that SLTs should consider a range of factors when deciding whether to address a young person's social media use. Adapting existing offline professional practices to online environments could support SLTs' work in providing services targeting social media use. Professional practice guidelines would support SLTs' work facilitating the social media use of young people with communication disability.

Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.

Comment cette classification a été obtenuedéplier

Prédiction distillée sur la base complète

Imitation des enseignants

Ni prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.

score de la tête « metaresearch » (Codex)0,006
score de la tête « metaresearch » (Gemma)0,003
Version: codex-gemma-dda1882f352aStatut de validation: machine_predicted_unvalidated
Catégories candidatesCharge utile insuffisante (le modèle a refusé de juger)
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Observationnel · Signal consensuel: Observationnel
GenreSignal candidat: Empirique · Signal consensuel: Empirique
Score de désaccord entre enseignants0,107
Score d'incertitude au seuil1,000

Scores Codex et Gemma par catégorie

CatégorieCodexGemma
Métarecherche0,0060,003
Méta-épidémiologie (sens strict)0,0000,000
Méta-épidémiologie (sens large)0,0010,000
Bibliométrie0,0000,001
Études des sciences et des technologies0,0010,000
Communication savante0,0000,001
Science ouverte0,0030,002
Intégrité de la recherche0,0000,002
Charge utile insuffisante (le modèle a refusé de juger)0,0010,000

Scores machine (provisoires)

Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.

Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.

Tête enseignante Opus0,069
Tête enseignante GPT0,513
Écart entre enseignants0,444 · la distance entre les deux têtes enseignantes sur ce seul travail
Statut de validationscore_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découle

Classification

machine, non validée

Prédiction automatique; un appel candidat d’une seule tête enseignante, pas un consensus.

Devis d'étudeObservationnel
Domainenon disponible
GenreEmpirique

Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».

En bref

Citations9
Publié2022
Routes d'admission1
Résumé présentoui

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