Psychological impact of illness intrusiveness in epilepsy—Comparison of treatments
Bibliographic record
Abstract
Chronic illnesses are associated with multiple stressors that compromise quality of life (QOL). Implicit in many of these is the concept of illness intrusiveness, the disruption of lifestyles and activities attributable to constraints imposed by chronic disease and its treatment. This study tested the illness intrusiveness theoretical framework in epilepsy and compared the impact of pharmacological and surgical treatments on illness intrusiveness and QOL. Cross-sectional data compared three epilepsy groups (N = 145): (a) 40 patients admitted for presurgical evaluation to an Epilepsy Monitoring Unit; (b) 52 patients treated pharmacologically; and (c) 53 post-surgical patients. Illness intrusiveness differed significantly across epilepsy patients with the differences primarily related to seizure control. Illness intrusiveness varied inversely with seizure control (p < .05). Seizure freedom, whether achieved by surgical or pharmacological treatments, was associated with maximal reduction of illness intrusiveness. Increased illness intrusiveness correlated significantly with decreased QOL and increased depressive symptoms. Perceived control over diverse life domains correlated positively with QOL and psychosocial outcomes. Path analysis supported the validity of the illness intrusiveness theoretical framework in epilepsy. Illness intrusiveness is an important determinant of the psychosocial impact of epilepsy and its treatment. Effective pharmacological or surgical treatment may reduce illness intrusiveness in epilepsy. Findings also offer encouragement that QOL in epilepsy, as in other chronic conditions, may be enhanced by multidisciplinary bio-psychosocial efforts. Health care providers should consider multifaceted interventions to reduce illness intrusiveness and, thereby, improve QOL.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".