P0255 DEVELOPMENT OF A PEDIATRIC POST-LIVER TRANSPLANT DISEASE-SPECIFIC HEALTH-RELATED QUALITY OF LIFE QUESTIONNAIRE (ITEM GENERATION)
Bibliographic record
Abstract
Introduction: In pediatric patients who are post-liver transplant (post-OLT) the use of generic measures describes a health-related quality of life (HRQOL) slightly lower, but reasonable, compared with the same age general population. However these measures, although useful do not provide a detailed enough description of post-OLT children and their issues of well-being. Therefore to obtain a more discriminative and evaluative measure a disease specific questionnaire is required. We describe the initial development stage, item generation, of an ongoing project to create a disease-specific HRQOL measure for pediatric patients. Methods: All children and adolescents, up to age 18 inclusive, who are at least one-year post-OLT and are followed at the IWK Liver Transplant Clinic were approached and asked to participate in the process of item generation. Separate, individual interviews were held with the child and their parent(s). A non-healthcare team member with a psychology background conducted interviews. If a face-to-face interview was not possible a phone interview was conducted. Two separate focus groups were also held, one for patients and one for their family members. A descriptive analysis was used for this stage of item generation. Results: 16 of 23 potential patient participants (mean age 12.4 years (range 8.2 to 15.2) were interviewed. They had a mean age at transplant of 4.9 years (range 0.6 to 15.2). Focus groups included 9 patient participants and 23 parent and sibling participants. 112 novel items were generated. A judgmental process was used to categorize items into the following domains: social/functional impairment, emotional, tests/treatments, family functioning, and systemic functioning. Some general themes were noted: age at transplant appeared to influence how patients felt the transplant had affected their life (younger age at transplant, peceived less affect on current status), patients voiced more concerns about medication/treatments, parents had concerns about future health status. Conclusion: Numerous items covering five domains were identified by participants as influencing their HRQOL post-OLT. To ensure all potential, relevant items have been obtained, two transplant centres (Edmonton, Toronto) will carry out a similar item generation process. From this, an item reduction questionnaire will be developed and administered to patient and proxy participants to obtain the items to be included in the final questionnaire. Once developed this questionnaire will need to undergo rigorous validation, reliability, responsiveness and sensibility testing in a multi-centre study.
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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 | 0.003 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.013 | 0.003 |
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".