“I want to hear you talk with your heart”: perspectives on receiving and providing mental wellness supports during the COVID-19 pandemic within a First Nation community in Canada
Bibliographic record
Abstract
Abstract Background The COVID-19 pandemic presented unprecedented challenges to local health systems, widening gaps in support and disrupting available care. Within Canada, First Nations communities have been disproportionately affected by the pandemic, which exacerbated an already strained system of appropriate services and supports. As part of a broader community-based participatory research project (The First Nations Wellness Initiative), the aim of this research was to explore how the COVID-19 pandemic affected people seeking and providing mental wellness supports within a First Nations community, with an eye to informing ways to enhance community strengths to better address pandemic-related challenges and develop community-identified opportunities for mental wellness promotion. Methods From September 2020 to March 2022, one-to-one interviews with people with lived experiences with mental health and/or substance use challenges (n = 2) and individuals supporting loved ones with lived experiences (n = 7) as well as two focus group discussions (i.e., with community youth (n = 5) and frontline service providers (n = 5)) were conducted in Saugeen First Nation, Ontario, Canada by a local research coordinator/Knowledge Holder. Individuals shared experiences with mental wellness and/or substance use challenges and experiences accessing/providing mental wellness supports during the pandemic. Recommendations for improving supports during and beyond the pandemic were also provided. These qualitative data were analyzed thematically, using a hybrid inductive-deductive approach. Results Challenges faced during the pandemic included difficulties finding and navigating available supports; problems connecting via virtual services; and lack of access to cultural and/or spiritual supports. Participants described relational supports (kinship, friends, the broader community) as well as formal supports (culturally-embedded programs, group supports, youth support group) as key community strengths drawn upon during the pandemic to promote mental wellness. In terms of service provision, challenges balancing differing community needs and concerns were highlighted. Participants shared ideas for expanding and adapting mental wellness promotion and supports to develop a stronger system of care for mental wellness and substance use challenges. Conclusions The findings point to opportunities for building on existing community strengths and promoting locally-led, culturally-grounded supports for mental wellness and substance use challenges to enhance capacity of First Nations communities to support their members in the face of public health crises.
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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 | 0.006 | 0.009 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.049 | 0.017 |
| Scholarly communication | 0.009 | 0.003 |
| Open science | 0.003 | 0.009 |
| Research integrity | 0.003 | 0.007 |
| Insufficient payload (model declined to judge) | 0.004 | 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".