The impact of the episodic nature of chronic illness: A comparison of fibromyalgia, multiple sclerosis and human immunodeficiency virus
Bibliographic record
Abstract
The purpose of this narrative review was to describe and compare the characteristics and episodic nature of disability among three chronic illnesses: multiple sclerosis (MS), HIV and fibromyalgia (FM). Searches were performed in electronic databases using a combination of keywords including episodic, relapse, remission, and fluctuation. We included articles published between 2004–2014 that described health challenges and the episodic nature of the illness. Data were extracted from selected articles, including the authors, date of publication, study population, the aims of the study, outcome measures and main study findings, and then were charted and collated to the dimensions of disability in the episodic disability framework. The descriptive words about symptoms/impairments, difficulty in day to day functioning, challenges to social inclusion and uncertainty were compared across illnesses to identify similarities and differences. We reported findings as a narrative summation. Forty-seven articles were included in this review. The comparison of the three chronic illnesses demonstrated that some of the symptoms/impairments such as pain, fatigue, sleep disturbance, depression, stress, and anxiety were reported commonly across illnesses. Similarly, difficulty with day to day functioning, challenges to social inclusion and uncertainty were reported across illnesses. On the other hand, factors influencing the symptoms, difficulties in daily functioning, challenges to social inclusion and uncertainty were found to be different. The episodic nature of the illness was identified among the three chronic conditions. People living with FM or MS or HIV, experience some common dimensions of disability that may be similarly experienced as episodic in nature. These similarities may not be exclusive to these three chronic illnesses, but could apply to individuals living with other chronic and episodic illnesses. Pursuing ways to enhance rehabilitation services among the conditions that experience similar episodic disability may help collectively to address disability and improve the overall health of people living with chronic illnesses.
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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 | 0.031 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.007 | 0.008 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.004 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 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".