Managing everyday life: Self-management strategies people use to live well with neurological conditions
Bibliographic record
Abstract
OBJECTIVE: This paper uses the Taxonomy of Everyday Self-management Strategies (TEDSS) to provide insight and understanding into the complex and interdependent self-management strategies people with neurological conditions use to manage everyday life. METHODS: As part of a national Canadian study, structured telephone interviews were conducted monthly for eleven months, with 117 people living with one or more neurological conditions. Answers to five open-ended questions were analyzed using qualitative content analysis. A total of 7236 statements were analyzed. RESULTS: Findings are presented in two overarching patterns: 1) self-management pervades all aspects of life, and 2) self-management is a chain of decisions and behaviours. Participants emphasized management of daily activities and social relationships as important to maintaining meaning in their lives. CONCLUSION: Managing everyday life with a neurological condition includes a wide range of diverse strategies that often interact and complement each other. Some people need to intentionally manage every aspect of everyday life. PRACTICE IMPLICATIONS: For people living with neurological conditions, there is a need for health providers and systems to go beyond standard advice for self-management. Self-management support is best tailored to each individual, their life context and the realities of their illness trajectory.
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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) | 0.000 | 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 teacher head, 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".