An examination of an anxiety intervention for young children: Little Champions
Bibliographic record
Abstract
Objective: Child anxiety is known for its high prevalence rates, early onset, and potentially devastating consequences for future functioning if left untreated (Mian, 2014).Researchers argue that early intervention can mitigate the negative consequences of anxiety (Hirshfeld-Becker & Biederman, 2002).This feasibility study examined an anxiety intervention, Little Champions (LC) --a 7-week group anxiety intervention for children ages 4-7 years and their parents --in reducing symptoms of child anxiety.Secondary objectives were to assess if results were maintained at 1-month post-test, assess the impact of LC on parent functioning, and determine the effectiveness of a LC intervention delivered to parents alone compared to when parents and children attended sessions together.Method: Non-identifying data from 46 children aged 48-to 90-months (M=75.90months, SD=12.20), and their parents from three community Child and Youth Mental Health (CYMH) centers in the Fraser Region (Chilliwack, Abbotsford, Mission) of BC were collected as part of a program review.Families were assigned to participate in the LC parent-child condition (n = 16), LC parent-only condition (n = 15) or waitlist condition (n = 15).Families were assessed at pre-test, post-test and 1-month follow-up assessment.Child outcome variables included anxiety, behavioural inhibition and global impressions of treatment gains by clinicians.Parent outcome variables were parent anxiety, parent stress and parent self-efficacy.Results: Children from both treatment groups failed to show differences in anxiety symptoms compared to the waitlist group.Parents from both treatment groups showed an increase in parent self-efficacy across time.Further there was a statistically detectable difference between the treatment conditions and the waitlist condition on parent efficacy.There were no differences between the two treatment conditions (LC delivered to parents with and without children present) for all measures.Conclusion: Despite improving parenting efficacy, the LC intervention is not acceptable at this time for use in clinical practice with young children with anxiety symptoms.Further there were no differences between the two intervention groups at post-test.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.004 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".