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Record W6991108423

An Examination of an Adaptive Parent-Mediated Intervention delivered via Telehealth for Toddlers `At Risk' of Autism Spectrum Disorder in the United Arab Emirates.

2024· dissertation· en· W6991108423 on OpenAlexaff

Bibliographic record

VenueTrinity's Access to Research Output (TARA) (Trinity College Dublin) · 2024
Typedissertation
Languageen
FieldNeuroscience
TopicAutism Spectrum Disorder Research
Canadian institutionsTrinity College
Fundersnot available
KeywordsAutismTelehealthIntervention (counseling)Psychological interventionAutism spectrum disorderParent trainingApplied behavior analysisService delivery framework
DOInot available

Abstract

fetched live from OpenAlex

Best practice in interventions for children below the age of three years with suspected or confirmed autism diagnosis is to include behavioural and developmental approaches as early as possible, and ensure active involvement of parents (e.g., Zwaigenbaum et al., 2015). Naturalistic Developmental Behaviour Interventions (NDBIs) is an evidence-based approach that integrates the principles of both Applied Behaviour Analysis and developmental science (Schreibman et al., 2015). A crucial element in the success of early intervention, especially for toddlers, is parental involvement. Parent-mediated intervention is an approach whereby professionals support parents in fostering their child’s learning and development, by embedding intervention strategies across natural everyday activities (Wetherby et al., 2018). Despite strong evidence supporting the importance of early intervention in increasing positive outcomes, there are major barriers to accessing services. Utilising a telehealth model in the delivery of parent-mediated intervention, can potentially narrow the service- need gap. Given the heterogeneity of Autism clinical presentation, and the diversity within families and cultures, recent recommendations support a novel adaptive, ‘stepped care’, approach in delivering intervention (Lord et al., 2021). In the United Arab Emirates, Autism research and service provisions are still at their infancy, and there continues to be a gap between policy and practice, despite recent efforts of policy makers. The aim of the current research programme was to explore the introduction of a contextually fit, adaptive parent-mediated NDBI delivered via telehealth to parents of toddlers ‘at risk’ of autism in the UAE. In Chapter 1, an overview of the evidence base for early intervention in young children with Autism Spectrum Disorder is provided, including NDBIs, parent-mediated approaches, and the utilisation of telehealth. The barriers to accessing early intervention, and the resulting service-need gap are illustrated, specifically within the context of the United Arab Emirates. Chapter 2 describes early experiences from a pilot trial of a bilingual NDBI intervention program, conducted via telehealth during the COVID-19 pandemic, which informed the development of bilingual (Arabic and English) online learning modules based on the Early Start Denver Model, and the adaptation and translation of outcome measures to evaluate the intervention. Chapter 3 describes the outcomes from a pilot study conducted to examine the feasibility of individual and group-based coaching of parent mediated NDBI delivered via telehealth to parents of toddlers ‘at risk’ of Autism in the UAE. Outcomes support the initial feasibility and acceptability of the provided intervention, as well as a reported improvement in parent knowledge, and parent reported child outcomes. A discussion of the challenges and limitations of the study highlight the importance of an adaptive, ‘stepped care’, approach that takes into account the diversity and variability of parent needs and preferences. Chapter 4 investigates the implementation of an adaptive parent-mediated NDBI delivered via telehealth, adopting a Sequential Multiple Assignment Randomised Trial design. Reported outcomes support the feasibility and acceptability of the adaptive intervention. Utilising a rapid measure of response to intervention halfway through the intervention program was shown to be useful in identifying ‘slow responders’ to intervention. Subsequently augmenting intervention for slow responders with parent- coaching was shown to lead to a more positive outcome, including improved parent knowledge; decreased burden of autism on family experience; parent reported improvement in social engagement, communication, and play; and improved parent response to intervention. In Chapter 5, qualitative data from post-intervention semi- structured interviews are collated and analysed, and emerging themes related to parents’ opinions on the characteristics of the program, and their perceptions and attitudes towards intervention are described. Parents’ perceptions of the strengths and limitations of the intervention, as well as identified facilitators and barriers in implementation are discussed. Chapter 6 describes the process of developing and tailoring implementation strategies based on the barriers and facilitators identified in Chapter 5, utilising the EPIS framework. The implementations strategies are discussed within the context of the recent Lancet recommendations for ‘stepped care’ model for interventions in Autism (Lord et al., 2021).

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.011
metaresearch head score (Gemma)0.006
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Research integrity
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.607
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0110.006
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0090.013
Science and technology studies0.0010.001
Scholarly communication0.0010.002
Open science0.0050.001
Research integrity0.0010.004
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.115
GPT teacher head0.417
Teacher spread0.301 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations0
Published2024
Admission routes1
Has abstractyes

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