Functional consequences of haemophilia in adults: the development of the Haemophilia Activities List
Bibliographic record
Abstract
Several instruments can be used to evaluate the functional status of patients with haemophilia, but none of these instruments is specific for haemophilia. We developed a haemophilia-specific self-assessment questionnaire to evaluate and monitor a patient's perceived functional health status: the Haemophilia Activities List (HAL). In three separate but interlinked substudies, the questionnaire was constructed and tested for face, expert, and convergent validity, as well as internal consistency and patient-evaluated relevance. Items for the questionnaire were collected by interviewing 162 patients, using the McMaster-Toronto Arthritis Patient Preference Disability Questionnaire (MACTAR). The items were combined to generate the first version of the questionnaire [HAL(1)]. This version was evaluated and commented on by two focus groups (patients and caregivers), and then the questionnaire was adapted on the basis of these comments, forming the final version, HAL(2). This version was then validated in a pilot study with 50 consecutive patients using the Dutch Arthritis Impact Measurements Scales 2 (Dutch-AIMS2) and the Impact on Participation and Autonomy (IPA) questionnaires. The HAL(2) showed good convergent validity (Pearson correlation 0.80-0.91; P < 0.01), and the internal consistency was good for six of the eight domains (Cronbach's alpha 0.83-0.95). Patients considered the content of the HAL to be more relevant to their situation than the content of the other questionnaires (P < 0.01). Three major factors (upper extremity function, lower extremity function, key activities/major problem activities) were identified by factor analysis. The questionnaire seems to be a useful tool to identify problematic activities as part of the functional health status of patients with haemophilia. The construct validity, test-retest reliability, and responsiveness of the HAL will be established in the future.
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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 | 0.005 | 0.013 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".