Towards a roadmap for implementing a self-management approach for people with multiple Sclerosis in Saudi Arabia
Bibliographic record
Abstract
Multiple sclerosis (MS) is one of the most disabling neurological conditions affecting young adults. MS is becoming more common in Saudi Arabia where specialized health services are still being developed. Many people with MS in Saudi Arabia look for help where they can and risk getting information from unreliable sources. In such a context, self-management would be crucial for reducing the impact of MS. Success at self-management requires acknowledging the specific problems, recognizing that solutions are possible, and contextualizing self-management for the individuals within their culture.This PhD thesis aims at setting a roadmap to aid in the translation of knowledge about self-management and MS in Saudi Arabia into an actionable implementation plan for a self-management intervention culturally relevant for people with MS. The overall objective is to contribute evidence towards the optimal structure, process, and outcomes for a self-management intervention for people with MS in Saudi Arabia.This PhD work comprises five studies. The first study aimed at identifying challenges related to current self-management interventions through a systematic literature and meta-analysis on how appealing are these programs to patients, and what contributes to participation in them. The second step in translating this knowledge was to explore the MS impact and challenges in self-management for women with MS in Saudi Arabia through a qualitative cross-sectional study. Women identified a range of symptoms similar to those reported worldwide, but the emotional burden predominated. Gaps in the healthcare system were identified and many had sought help elsewhere using internet sources. Stories narrated during discussions were found to be an effective source of revealing how values, goals, and expectations guided choices for personal strategies for self-management. Therefore, the third study used narrative analysis of stories and metaphors to illuminate women’s self-management journeys. Fatigue is one of the most distressing symptoms reported by people living with MS around the world and its impact was confirmed for people in Saudi Arabia. Therefore, identifying the best ways of measuring this complex construct was a prerequisite for developing effective interventions. Thus, the aim of the fourth study was to identify the best method of capturing information about fatigue in MS using items from patient-reported outcome measures. Taking advantage of existing data from a MS study conducted in Montreal on 189 people with MS, analyses identified two separate fatigue constructs, perception of physical fatigue and perception of mental fatigue, and items that reflected these distinct constructs. These four studies provided foundational information that shaped the final study, which was also centered on the importance of eliciting knowledge that is directly associated with real-world needs. Therefore, by following a participatory research approach, the fifth study aimed at identifying key pieces of information that need to be gathered from the MS population in Saudi Arabia to inform the structure, process and outcome of a self-management program. The partnership resulted in survey items that were pilot tested on 101 individuals with MS recruited in two ways: using social media and MS clinics in Saudi Arabia. The pilot survey provided preliminary estimates of prevalence and also information on clarity of items. Cognitive interviewing was conducted with a sub-sample of 13 individuals completing the survey to remedy unclear items. This thesis contributed evidence towards identifying care gaps that could be filled through a self-management approach and ascertained the extent to which existing MS self-management interventions could be adapted to cover this content in a manner that is culturally suitable to MS Saudi Arabian 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 | 0.029 | 0.034 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.003 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.004 | 0.001 |
| Scholarly communication | 0.007 | 0.007 |
| Open science | 0.003 | 0.009 |
| Research integrity | 0.005 | 0.008 |
| Insufficient payload (model declined to judge) | 0.013 | 0.002 |
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".