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Record W4225271213 · doi:10.1186/s40814-021-00959-0

The feasibility of a strategy for the remote recruitment, consenting and assessment of recent referrals: a protocol for phase 1 of the On-Line Parent Training for the Initial Management of ADHD referrals (OPTIMA)

2022· article· en· W4225271213 on OpenAlexfundno aff
Katarzyna Kostyrka‐Allchorne, Claire Ballard, Sarah Byford, Samuele Cortese, David Daley, Johnny Downs, Blandine French, Cris Glazebrook, Kimberley Goldsmith, Madeleine J. Groom, Charlotte L Hall, Ellen Hedstrom, Zina Ibrahim, Christine Jarvis, Hanna Kovshoff, Jana Kreppner, Nancy Lean, Anna Morris, Walter Muruet Gutierrez, Kapil Sayal, James Shearer, Emily Simonoff, Margaret Thompson, Lukasz Zalewski, Edmund Sonuga‐Barke

Bibliographic record

VenuePilot and Feasibility Studies · 2022
Typearticle
Languageen
FieldMedicine
TopicAttention Deficit Hyperactivity Disorder
Canadian institutionsnot available
FundersSolent NHS TrustKing's College LondonNational Institute for Health Research Applied Research Collaboration South LondonDepartment of Health and Social CareNational Institute for Health and Care ResearchYork UniversityMenzies Centre for Australian Studies, King's College London, University of LondonSouth London and Maudsley NHS Foundation TrustUniversity of SouthamptonKing's College Hospital NHS Foundation TrustProgramme Grants for Applied ResearchMedical Research CouncilAarhus Universitet
KeywordsProtocol (science)Phase (matter)PsychologyFirst linePsychiatryClinical psychologyMedical educationMedicineAlternative medicine

Abstract

fetched live from OpenAlex

BACKGROUND: In the UK, children with high levels of hyperactivity, impulsivity and inattention referred to clinical services with possible attention-deficit/hyperactivity disorder (ADHD) often wait a long time for specialist diagnostic assessment. Parent training (PT) has the potential to support parents during this difficult period, especially regarding the management of challenging and disruptive behaviours that often accompany ADHD. However, traditional face-to-face PT is costly and difficult to organise in a timely way. We have created a low-cost, easily accessible PT programme delivered via a phone app, Structured E-Parenting Support (STEPS), to address this problem. The overall OPTIMA programme will evaluate the efficacy and cost-effectiveness of STEPS as a way of helping parents manage their children behaviour while on the waitlist. To ensure the timely and efficient evaluation of STEPS in OPTIMA, we have worked with children's health services to implement a remote strategy for recruitment, screening and assessment of recently referred families. Part of this strategy is incorporated into routine clinical practice and part is OPTIMA specific. Here, we present the protocol for Phase 1 of OPTIMA-a study of the feasibility of this remote strategy, as a basis for a large-scale STEPS randomised controlled trial (RCT). METHODS: This is a single arm observational feasibility study. Participants will be parents of up to 100 children aged 5-11 years with high levels of hyperactivity/impulsivity, inattention and challenging behaviour who are waiting for assessment in one of five UK child and adolescent mental health or behavioural services. Recruitment, consenting and data collection will occur remotely. The primary outcome will be the rate at which the families, who meet inclusion criteria, agree in principle to take part in a full STEPS RCT. Secondary outcomes include acceptability of remote consenting and online data collection procedures; the feasibility of collecting teacher data remotely within the required timeframe, and technical difficulties with completing online questionnaires. All parents in the study will receive access to STEPS. DISCUSSION: Establishing the feasibility of our remote recruitment, consenting and assessment strategy is a pre-requisite for the full trial of OPTIMA. It can also provide a model for future trials conducted remotely.

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.148
metaresearch head score (Gemma)0.100
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Protocol · Consensus signal: Protocol
Teacher disagreement score0.148
Threshold uncertainty score0.000

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.1480.100
Meta-epidemiology (narrow)0.0040.004
Meta-epidemiology (broad)0.0040.003
Bibliometrics0.0030.002
Science and technology studies0.0060.005
Scholarly communication0.0030.005
Open science0.0060.005
Research integrity0.0100.011
Insufficient payload (model declined to judge)0.0670.023

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 head0.919
GPT teacher head0.640
Teacher spread0.279 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreProtocol

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

Citations18
Published2022
Admission routes1
Has abstractyes

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