A Mixed Methods Evaluation of a Web-based Program to Enhance Sport Parents’ Emotional Intelligence
Bibliographic record
Abstract
The purpose of this research was to deliver and evaluate the Sport Parent Emotions and Coping Support (SPECS) program with a group of ice hockey parents using a sequential explanatory mixed methods approach. The SPECS program consists of four web-based educational modules designed to enhance hockey parents’ emotional intelligence (EI). Twenty-nine Canadian ice hockey parents (23 mothers, 6 fathers) were randomized to either an experimental or control group with pre- and post-program measures of trait EI completed three-weeks apart. Qualitative interviews were also conducted with 11 parents from the experimental group following their completion of the program. The results from a mixed ANOVA indicated a significant group X time interaction effect (p = .027; η;p2 = .17) and probing the interaction using simple effects analyses revealed that parents in the experimental group significantly increased their levels of trait EI, with small-to-medium sized effects (p = .005, η;p2 = .26, d =.43). The qualitative results demonstrated parents’ positive perceptions of the program’s content and delivery (e.g., relevance, provision of tools and strategies, convenience, and interactivity) and highlighted parents’ experiences regarding lightbulb moments (e.g., learning about themselves, their children, and ice hockey). The integration of the quantitative and qualitative findings provides insight into how aspects of the program may have contributed to changes in parents’ EI. Overall, this research yields practical implications for youth sport stakeholders interested in delivering sport parent education and support initiatives.
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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 | 0.013 | 0.012 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".