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Enregistrement W2771756382 · doi:10.2196/resprot.8260

Implementing a Mental Health Care Program and Home-Based Training for Mothers of Children With Autism Spectrum Disorder in an Urban Population in Bangladesh: Protocol for a Feasibility Assessment Study

2017· article· en· W2771756382 sur OpenAlexvenueno aff
Aliya Naheed, Kamrun Nahar Koly, Helal Uddin Ahmed, Shaheen Akhter, MM Jalal Uddin, Mary C. Smith Fawzi, Subhash Chandir, Muzharul Mannan, Saima Hossain, Charles A. Nelson, Kerim Münir

Notice bibliographique

RevueJMIR Research Protocols · 2017
Typearticle
Langueen
DomainePsychology
ThématiqueFamily and Disability Support Research
Établissements canadiensnon disponible
Organismes subventionnairesEunice Kennedy Shriver National Institute of Child Health and Human DevelopmentFogarty International CenterNational Institute of Mental HealthInternational Centre for Diarrhoeal Disease Research, BangladeshUniversity of Dhaka
Mots-clésAutism spectrum disorderProtocol (science)AutismMental healthPopulationPsychologyMedicineClinical psychologyGerontologyPsychiatryEnvironmental healthAlternative medicine

Résumé

récupéré en direct d'OpenAlex

BACKGROUND: Mothers of children with autism spectrum disorder (ASD) have reported a higher level of depression than mothers of children with other neurodevelopmental disorders in both developed and developing countries. Mothers are the lifetime caregivers of children with ASD, and a high burden of depression can negatively impact their ability to provide care. However, access to mental health services in primary care is limited, given the scarcity of qualified providers in Bangladesh. OBJECTIVE: We aim to pilot the feasibility of integrating mental health services for the mothers of children with ASD attending schools offering ASD care and improve skills of mothers for child care through a home-based training program. METHODS: The study will be conducted in two selected schools in Dhaka in Bangladesh that have been offering services for ASD for more than 10 years. A female psychologist will be deployed at the schools to offer nonpharmacological services for all mothers having a depressive episode. Referral for pharmacological treatment will be made at the discretion of supervising psychiatrists. An ASD special educator will provide training to the mothers for enhancing their child care skills at home on a monthly basis. The proposed intervention package will be implemented over a period of 4-6 months, and the feasibility of the intervention will be assessed through a pre- and postintervention evaluation by obtaining the perspectives of various stakeholders involved in the implementation of mental health services and maternal training. The primary outcome will include assessment of acceptability, adaptability, demand, practicality, implementation, and integration of the package intervention in the school settings. The secondary outcomes will include assessment of: 1) the prevalence of maternal depression; 2) children's behavioral, social, and communication skills; and 3) the intervention participation costs incurred by institutions and families. RESULTS: Between February and March 2017, 188 mothers of children with ASD were screened for depression following a written informed consent. Based on the Diagnostic and Statistical Manual of Mental Disorders, 4th edition (DSM-IV), the Structured Clinical Interview for the DSM-IV (SCID-1) was administered to 66 mothers. In-depth interviews were conducted with 10 mothers and 8 various stakeholders. Between January-June 2017, the team finalized a draft psychosocial counseling module and a maternal training module. Between April-May 2017, mental health services were provided by psychologists to 41 mothers who attended the counseling centers at each school. Three special educators have been trained in June 2017 to initiate training of the participating mothers. CONCLUSIONS: This is the first study of a mental health intervention for mothers of children with ASD to reduce their burden of depression and improve the outcomes of their children. The findings will inform the provision of services for children with ASD and their mothers in Bangladesh and similar settings.

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)0,000
Version: codex-gemma-dda1882f352aStatut de validation: machine_predicted_unvalidated
Catégories candidatesaucune
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Observationnel · Signal consensuel: Observationnel
GenreSignal candidat: Protocole · Signal consensuel: Protocole
Score de désaccord entre enseignants0,057
Score d'incertitude au seuil0,990

Scores Codex et Gemma par catégorie

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

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 Opus0,320
Tête enseignante GPT0,633
Écart entre enseignants0,313 · 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.

Les modèles n’ont appliqué aucune catégorie : rien dans la taxonomie ne correspondait à ce travail.
Devis d'étudeObservationnel
Domainenon disponible
GenreProtocole

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

En bref

Citations12
Publié2017
Routes d'admission1
Résumé présentoui

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