Quality of Life in Parkinson’s Disease: Insights from a Single-Session Focus Group in Southwestern Ontario
Bibliographic record
Abstract
Abstract Background Parkinson’s Disease (PD) is a chronic illness that profoundly impacts quality of life (QoL). While many qualitative studies on QoL in PD have been conducted in different countries and cities around the world, the impact on QoL varies by region and it is important to explore the diverse factors influencing these differences. Objectives This pilot study aims to explore the impact of PD on QoL for patients in Southwestern Ontario, Canada. These individuals may encounter unique challenges not currently addressed by the literature, potentially affecting their overall QoL. Methods A single-session focus group was conducted in a rural town in Southwestern Ontario, Canada. Line-by-line reflexive coding was used to identify iterative themes. Results Seven themes were explored from the participant’s contributions, with key themes focusing on patients’ experiences navigating the healthcare system, the impact of non-motor and motor symptoms, and the role of social support in their QoL. Conclusion Living with PD presents a variety of unique challenges that must be considered throughout future research and policy implementation. This pilot focus group study provides an in depth discussion of the key challenges faced by individuals with PD In Southwestern Ontario. The study is limited in reliability and generalizability due to the small sample size and homogeneity of participants. The initial exploratory findings can be used as a foundation for future research to expand on key themes with additional focus group sessions or complementary methodologies.
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 | 0.007 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.014 | 0.004 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".