Inequalities in the spiritual health of young Canadians: a national, cross-sectional study
Bibliographic record
Abstract
BACKGROUND: Spiritual health, along with physical, emotional, and social aspects, is one of four domains of health. Assessment in this field of research is challenging methodologically. No contemporary population-based studies have profiled the spiritual health of adolescent Canadians with a focus on health inequalities. In a 2014 nationally representative sample of Canadians aged 11-15 years we therefore: (1) psychometrically evaluated a series of items used to assess the perceived importance of spiritual health and its four potential sub-domains (connections with: self, others, nature and the natural environment, and the transcendent) to adolescents; (2) described potential inequalities in spiritual health within adolescent populations, overall and by spiritual health sub-domain, by key socio-demographic factors. METHODS: Cross-sectional analysis of survey reports from the 2014 (Cycle 7) of the Canadian Health Behaviour in School-aged Children study (weighted n = 25,036). Principal components analysis followed by confirmatory factor analysis were used to explore the psychometric properties of the spiritual health items and the associated composite scale describing perceived importance of spiritual health. Associations among this composite scale, its individual sub-domains, and key socio-demographic factors were then explored. RESULTS: The principal components analysis best supported a four-factor structure where the eight scale items loaded highly according to the original four domains. This was also supported in confirmatory factor analyses. We then combined the eight items into composite spiritual health score as supported by theory, principal components analysis findings, and acceptable tests of reliability. Further confirmatory factor analysis suggested the need for additional refinements to this scale. Based upon exploratory cross-sectional analyses, strong socio-demographic inequalities were observed in the spiritual health measures by age, gender, relative material wealth, immigration status, and province/territory. CONCLUSIONS: Study findings highlight potential inequalities in the spiritual health of young Canadians, as well as opportunities for methodological advances in the assessment of adolescent spiritual health in our population.
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.005 |
| Science and technology studies | 0.005 | 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) | 0.002 | 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".