A Multi-Modal Assessment of Support Use Among Multiple Sclerosis Family Caregivers in Canada
Bibliographic record
Abstract
Family caregivers of individuals living with multiple sclerosis (MS) are essential to the wellbeing and independence of their care recipients. Despite the prevalence and importance of MS family caregivers, many struggle to maintain their wellbeing while also meeting demands for care. Most of the MS caregiving literature has focused on negative outcomes associated with the caregiving role; however, MS family caregivers also report benefits to caregiving that remain poorly understood. Resources are deeply implicated in salutogenic paradigms of health and could be used promote the wellbeing of caregivers through the creation of supportive environments. However, little is known about the current state of supports for MS family caregivers in Canada. Thus, this dissertation sought to establish a salutogenic paradigm for supporting MS family caregivers by identifying current caregiving resources and resource use dynamics. Included in this dissertation are three studies to achieve this goal. The first study of this dissertation examined the current landscape of caregiving resources in Canada as experience by family caregivers via an environmental scan of digital supports. This study identified mostly informational resources authored by provincial caregiving organizations. Findings highlighted a lack of diversity in the target audiences of current digital caregiving resources and a dearth of interactive and practical supports. The second study of this dissertation examined the content and feature priorities for a novel digital resource among MS family caregivers and service providers via online survey. Participants prioritized the ease of use of a future digital resource as a top priority. A wide range of content priorities were identified, with the most frequent being information on MS and its treatment. Findings emphasized the potential of a digital resource to provide a range of support to MS family caregivers and centred the importance of user testing to ensure the usability and uptake of the resource. The third study of this dissertation presented in Chapters 4 and 5, investigated current support structures and support use dynamics of MS family caregivers via online survey and semi-structured interviews. The content of support structures reported by caregivers highlighted the importance of natural support networks, including the care recipient. Levels of resilience and neuroticism were associated with the size of support structures. Through interviews, caregivers identified that cycles of resilience were mediated by supports and reported key facilitators and barriers to support use. Findings demonstrated the complex decision-making processes behind support use and highlighted the need for flexible support that can accommodate variable support needs and preferences of MS family caregivers. Collectively, the findings of this dissertation operationalize a salutogenic paradigm for supporting MS family caregivers. Key recommendations are given to create supportive environments for caregivers and optimize their wellbeing. Improvements in access to respite care and financial support, better visibility of digital resources, and bolstering natural support networks may all be valuable strategies to improving the wellbeing of MS family caregivers in Canada.
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 | 0.001 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.005 |
| Science and technology studies | 0.008 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.002 |
| 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".