Chronic Health Conditions in the Classroom: A Pan-Canadian Assessment of Adolescent Psychosocial Functioning
Bibliographic record
Abstract
Due to a variety of factors (e.g., absence from school, being physically unable to take part in certain activities), students with Chronic Health Conditions (CHCs) are at a greater risk of low academic achievement and less fulfilling social relationships than their otherwise healthy peers (Hoffmann et al., 2018; Thies & McAllister, 2001). Teachers’ insufficient understanding of the psychosocial functioning (i.e., affective, cognitive, and behavioural characteristics) of students with CHCs results in a lack of educational programing to suit those students’ health and educational needs, compounding the risk of low academic achievement and less fulfilling social relationships (Hopkins & Hughes, 2016). The purpose of this research is to establish patterns of psychosocial functioning in order to inform teacher practice, and It has been guided by the following research question: Are there significant differences in psychosocial functioning (affective, behavioural, and cognitive) of Canadian adolescents with and without CHC? The methods involved the development of a model of affective functioning, one of the three domains of psychosocial functioning. The model comprised three factors: interpersonal home (feeling emotional support, understood, trusted, happy, listened to), interpersonal school (feeling trust, belonging, fairness, a nice place accepted), and general intrapersonal (feeling left out, lonely, hopeless, and the desire to be someone else), which speak to those inward feeling. Follow-up t-tests that adolescents with CHCs functioned significantly poorer than adolescents without CHCs on all affective factors, and ANOVAs revealed that specific affective functioning varied significantly among the types of CHCs. Additionally, sex and grade are significant factors in reported affective functioning. Measures should be taken to help support the affective functioning of adolescents with CHCs in the school environment. It is recommended that efforts should be taken to support students’ sense of belongingness, as it should in turn foster affective psychosocial experiences. Additionally, teachers should be made knowledgeable of students who are more at-risk of poor affective psychosocial functioning, namely, females, those in higher grades, and those with multiple CHCs.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.004 | 0.000 |
| Scholarly communication | 0.001 | 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".