Exploring the Determinants That Contribute to and Promote the Wellbeing of Immigrant and Refugee Children in Canada
Bibliographic record
Abstract
In 2023, Canada’s new Immigrant Levels Plan was introduced to support Canada’s economic recovery and growth, reunite families, and respond to humanitarian crises. As a result, Canada will welcome over 480,000 new immigrants annually during 2024-2026 including many families with children and youth. To date, most research with immigrant and refugee children has focused on the negative impacts of migration stressors over the factors that can support their wellbeing. Further, few studies include children as research participants despite the fact that children can play an active role in studies that examine issues affecting them. Rather, studies focused on children’s experiences are based on the perspective of institutions and adults. As such, the overall aim of this dissertation is to examine the determinants that contribute to and promote the wellbeing of immigrant and refugee children in Canada, considering their perceptions and subjective experiences. To meet this aim, this dissertation includes four papers, described below. \nPaper I is a scoping review, following Arksey and O’Malley’s methodology, that aimed to understand the psychosocial needs of resettled immigrant and refugee children and youth in Canada in the context of their school and community, and to identify the characteristics of school-/community-based mental health programs for this group. The findings of this review make contributions to the literature in terms of identifying approaches, particularly collaborative care models, school-community-family partnerships, and school-based creative expression programs, to addressing mental health issues in immigrant and refugee children and youth. Furthermore, this scoping review informed the methodology used in Paper II as it highlighted the value of using creative expression methods when working with immigrant and refugee children. \nPaper II, the empirical paper of this dissertation, used a multi-method qualitative approach, namely the Mosaic methodology, to explore and identify the determinants that contribute to and promote the wellbeing of immigrant and refugee children aged 6-13 settled in Canada. In this paper, I focused on immigrant and refugee children from the Middle East and North Africa (MENA) region, taking into account that Canada has resettled a large number of refugees from this region in recent years (over 120,000 from 2015 to 2023). Considering the multi-method approach of the Mosaic methodology, I used a visual method (drawing) combined with a verbal method (interviews) to collect data from children (n=16) and their parents (n=9). This study was informed by the social-ecological framework that considers a child within the context of family, community, and broader society. Accordingly, the findings of this study suggested that immigrant and refugee children’s wellbeing is influenced by individual characteristics, relationships with their surroundings, and organizational/community factors. Further, the results showed that wider societal policy and practice changes are necessary to enhance the wellbeing of this group. \nDrawing upon the findings of Paper II, Paper III examined and demonstrated the use of a multi-method approach in research with immigrant and refugee children in a virtual setting, making a methodological contribution to the literature. This methodological paper emphasized the importance of listening to children and involving them as active participants in research studies by using creative visual combined with traditional verbal methods to collect data from this group. This paper provides practical guidance for using a multi-method approach in research with immigrant and refugee children in a virtual setting. \nGiven the findings of Paper II, the conceptual paper of my dissertation (Paper IV) aimed to extend the PERMA model of wellbeing, a framework developed within a Western context and has five constructs: Positive emotions, Engagement, Relationships, Meaning, and Accomplishment, to respond to the needs of immigrant and refugee children of colour from the MENA region. This framework has been used to study and evaluate individuals’ wellbeing, however, its current constructs may not adequately represent the views and experiences of people with marginalized identities, such as racialized children and newcomers from non-Western nations. The findings of Paper IV contribute to the existing literature on wellbeing by identifying two new components, C for cultural and religious identity and S for safe and peaceful environment, to be added to the PERMA model of wellbeing (titled the PERMA-CS). The extended model can be used as a framework for research with immigrant and refugee children from the MENA region who resettled in a Western context, a novel population for this model. \nIn summary, through conducting a scoping review and a qualitative study that used a multi-method approach, I provide empirical, methodological, and conceptual contributions that will support the promotion of wellbeing of immigrant and refugee children in Canada. In particular, this thesis contributes to the literature by empirically identifying the factors that influence and promote the wellbeing of immigrant and refugee children in Canada. Moreover, the methodological approach of this thesis furthers our understanding of the use of a multi-method approach in research with immigrant and refugee children in a virtual setting. Additionally, my thesis makes conceptual contributions to the literature by proposing a framework of wellbeing that builds on a previously defined model.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.004 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.005 |
| Science and technology studies | 0.011 | 0.005 |
| Scholarly communication | 0.007 | 0.002 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.002 |
| 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".