How Can Students with Anxiety Be Supported with Cognitive Behavior Therapy and Nature-Based Therapy?
Bibliographic record
Abstract
COVID-19 has caused tremendous stress among children and adolescents and this stress could precipitate the development of anxiety, panic attacks, depression, mood disorders and other illnesses (Shah et at, 2020). Recent research reports that 60% of parents surveyed during the beginning of the pandemic were concerned or extremely concerned about their families, managing their child’s behavior regarding stress levels, anxiety, and emotions (Statistics Canada, 2020). These results support an urgent need for intervention and recovery efforts aimed at improving child and adolescent well-being (Jackson et al., 2021) (Racine et al., 2021). Research establishes a strong connection between exposure to nature and enhanced well-being. The purpose of this capstone is to provide therapeutic strategies for school counsellors involving the proven benefits of Cognitive Behavior Therapy and Nature Based Therapy for use with students with anxiety.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".