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Record W6940469927 · doi:10.7939/dvn/10913

Evaluating an Internet-based Program for Anxious Youth: a Pilot RCT

2016· dataset· en· W6940469927 on OpenAlexaff

Bibliographic record

VenueBorealis · 2016
Typedataset
Languageen
FieldAgricultural and Biological Sciences
TopicMycorrhizal Fungi and Plant Interactions
Canadian institutionsUniversity of OttawaUniversity of CalgaryUniversity of Alberta
Fundersnot available
KeywordsRandomized controlled trialIntervention (counseling)AnxietyTest (biology)Sample (material)Pilot trialSample size determinationCognitive behavioral therapyCognitive therapy

Abstract

fetched live from OpenAlex

This pilot trial aims to collect the necessary data to inform the planning of a full-scale randomized controlled trial (RCT) to test the effectiveness of the Internet-based CBT program Breathe (Being Real, Easing Anxiety: Tools Helping Electronically). Adolescents will be randomly assigned to either 8 weeks of Internet-based cognitive behaviour therapy (CBT) with telephone and e-mail support (the Breathe program), or a control (minimal intervention) group with 8 weeks of access to a static webpage with general anxiety resources and information. The pilot RCT will (1) define a minimal clinically important difference, as defined by adolescents, for the primary outcome measure, (2) determine a sample size for a full-scale RCT, (3) estimate recruitment and retention rates to determine the number of study sites needed, (4) measure intervention acceptability to inform critical intervention changes, (5) determine the use of co-interventions, and (6) conduct a cost-consequence analysis to inform a cost-effectiveness analysis for a full-scale RCT.

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)0.009
metaresearch head score (Gemma)0.035
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Randomized trial · Consensus signal: none
GenreCandidate signal: Dataset · Consensus signal: Dataset
Teacher disagreement score0.028
Threshold uncertainty score0.095

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0090.035
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0020.003
Bibliometrics0.0020.003
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0020.002
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0280.003

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 head0.084
GPT teacher head0.333
Teacher spread0.249 · 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 designRandomized trial
Domainnot available
GenreDataset

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
Published2016
Admission routes1
Has abstractyes

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