Knowing the entire story – a focus group study on patient experiences with chronic Lyme-associated symptoms (chronic Lyme disease)
Bibliographic record
Abstract
BACKGROUND: Healthcare providers frequently struggle to provide effective care to patients with chronic Lyme-associated symptoms (chronic Lyme disease, CLD), potentially causing these patients to feel misunderstood or neglected by the healthcare system. This study is the first to use a combined medical and communication science approach, and aims to assess patients' experiences with CLD & CLD-related care, identify themes and repertories in these patients' narrations, and provide potential ways to improve communication with them. METHODS: Informed by the principles of 'clean language', we conducted focus groups with self-identified CLD patients (N = 15). We asked participants about their experiences with CLD and CLD-related healthcare. We performed thematic analyses using a bottom-up approach based in discourse analysis. We also sought to identify specific types of verbalizations (repertoires) across themes. RESULTS: Participants thematised a heterogeneous set of CLD-associated symptoms, which they frequently labelled as 'invisible' to others. Their illness significantly affected their daily lives, impacting their work, social activities, relationships with loved ones, hobbies and other means of participating in society. Negative experiences with healthcare providers were near-universal, also in patients with short-lived CLD-associated symptoms. Verbalizations were notable for frequent use of communicative modes that implicitly create common ground between participants and that give a certain validity to personal experiences (impersonal 'you' and other forms of presupposition). CONCLUSION: Central themes found in CLD patients' communication are 1. the experience of significant symptoms, 2. for which adequate relief is only rarely found from conventional medical practitioners, and 3. that are largely invisible to the outside world. Verbalizing these themes, patients use various repertoires for their shared experiences, such as a feeling of abandonment or not being heard by the medical system, feelings of loss with respect to their previous health, and the idea that they might have been better off had they been diagnosed sooner. Working with these repertoires will enable healthcare providers to establish a shared perspective with their CLD patients, thus engaging in more fruitful doctor-patient communication. We hypothesize that these findings are not unique to CLD, but may also be applicable to other conditions with an uncertain aetiology, such as Long COVID.
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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 | 0.011 | 0.018 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.011 | 0.009 |
| Scholarly communication | 0.004 | 0.006 |
| Open science | 0.002 | 0.008 |
| Research integrity | 0.004 | 0.004 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".