Well-Being of Children From Military Families: the Role of Parental Deployment
Bibliographic record
Abstract
Background: Research suggests that military life stressors have a negative impact on the well-being of children from military families. However, little research has been conducted to examine the well-being of children from military families in Canada. This study examined the impact of military stressors on the well-being of children in Canadian Armed Forces families. Methods: Focus groups were conducted with children between the ages of 8 and 13 (N=85 children). MAXQDA software was used for the thematic analysis of the qualitative data. Results: Parental deployment and frequent relocations were found to be the main stressors reported by children. The overall well-being of the children decreased during parental deployment. Nevertheless, the vast majority of the children believed it was good to be part of a military family. Moreover, several strategies, such as seeking social support, communication with the deployed parent, and active distraction were reported to buffer the stress related to military life. Discussion: It is crucial to understand how children from military families can maintain resiliency in the face of the military life stressors. This research shows that several factors, including effective coping strategies and supportive networks, may buffer the effects of military life stressors on child well-being. Recommendations to military family service providers are offered.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".