The everyday experience of living with and managing a neurological condition (the LINC study): study design
Bibliographic record
Abstract
BACKGROUND: The impact of neurological conditions on individuals, families and society is increasing and having a significant economic impact in Canada. While some economic data is known, the human costs of living with a neurological condition are poorly understood and rarely factored into future burden analyses. The "Living with the Impact of a Neurological Condition (LINC)" study aims to fill this gap. It seeks to understand, for children and adults with neurological conditions, the supports and resources that make everyday life possible and meaningful. METHODS/DESIGN: The LINC study is a nested study using mixed methods. We are interested in the following outcomes specifically: health status; resource utilization; self-management strategies; and participation. Three studies captured data from multiple sources, in multiple ways and from multiple perspectives. Study One: a population-based survey of adults (n=1500), aged 17 and over and parents (n=200) of children aged 5 to 16 with a neurological condition. Study Two: a prospective cohort study of 140 adults and parents carried out using monthly telephone calls for 10 months; and Study Three: a multiple perspective case study (MPCS) of 12 adults and 6 parents of children with a neurological condition. For those individuals who participate in the MPCS, we will have data from all three studies giving us rich, in depth insights into their daily lives and how they cope with barriers to living in meaningful ways. DISCUSSION: The LINC study will collect, for the first time in Canada, data that reflects the impact of living with a neurological condition from the perspectives of the individuals themselves. A variety of tools will be used in a combination, which is unique and innovative. This study will highlight the commonalities of burden that Canadians living with neurological conditions experience as well as their strategies for managing everyday life.
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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 | 0.009 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.007 | 0.004 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 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".