Bibliographic record
Abstract
MARCIA FINLAYSON,PHD, OT REG (ONT), OTRQueen’s UniversityKingston, Ontario, CanadaReaders of the International Journal of Multiple Sclerosis Care understand that multiple sclerosis (MS) affects more than just the person with the disease. It also affects family, friends, coworkers, and other members of their social network. Whatever term we use for these individuals—caregivers, care partners, or carers—they care. In the context of MS, the duration of caregiving is often lengthy, sometimes 40 years or more.1 And, as a result, they offer different types of social support (eg, emotional, instrumental, informational, appraisal)2 to enable persons with MS to manage their disease and its impact on everyday life. These various forms of support can be episodic, occasional, or regular and frequent.3Nevertheless, during the past 20 years, there have been relatively few articles about MS caregiving in the scientific literature.4 This scarcity of research has occurred despite the longstanding acknowledgment that comprehensive MS care includes education and assistance to caregivers.5 This special issue recognizes the importance of adding to our collective knowledge about MS caregiving, and hopefully will inspire more researchers and clinicians to contribute to this area of inquiry.The existing MS caregiver literature has several notable gaps, as described by Kenneth Pakenham, PhD, an internationally recognized researcher in MS caregiving, who was interviewed for this issue (see page 278). Current MS caregiving literature has a predominant focus on examining heterosexual spousal caregivers and psychological burden. This focus has resulted in little attention being paid to other types of caregivers (eg, same-sex partners, siblings, parents, children), understanding caregiving as a dyadic and interactive experience, or identifying effective strategies to support caregivers, whoever they may be. Although this issue does not address all these gaps, an article by Holden et al about parent caregivers highlights one of these unique carer groups. Douglas et al, Hoseinpour et al, and Kalb et al each offer an article about promising interventions. Caregiver resilience is addressed in an article by Cardwell et al, and this and the continuing education article about symptom management by care partners, also by Cardwell et al, have the potential to guide additional intervention development.We have much to learn about caregiving, caregivers, and how the relationships between caregivers and persons with MS evolve over time and influence how, when, and why support is offered and accepted. I hope this issue generates curiosity and commitment to advance our knowledge.
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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 | 0.020 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.011 | 0.014 |
| Insufficient payload (model declined to judge) | 0.067 | 0.035 |
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".