Study protocol: evaluation of specialized outpatient palliative care (SOPC) in the German state of Hesse (ELSAH study) – work package II: palliative care for pediatric patients
Bibliographic record
Abstract
BACKGROUND: In 2007, the European Association of Palliative Care (EAPC) provided a comprehensive set of recommendations and standards for the provision of adequate pediatric palliative care. A number of studies have shown deficits in pediatric palliative care compared to EAPC standards. In Germany, pediatric palliative care patients can be referred to specialized outpatient palliative care (SOPC) services, which are known to enhance quality of life, e.g. by avoiding hospitalization. However, current regulations for the provision of SOPC in Germany do not account for the different circumstances and needs of children and their families compared to adult palliative care patients. The "Evaluation of specialized outpatient palliative care (SOPC) in the German state of Hesse (ELSAH)" study aims to perform a needs assessment for pediatric patients (children, adolescents and young adults) receiving SOPC. This paper presents the study protocol for this assessment (work package II). METHODS/DESIGN: The study uses a sequential mixed-methods study design with a focus on qualitative research. Data collection from professional and family caregivers and, as far as possible, pediatric patients, will involve both a written questionnaire based on European recommendations for pediatric palliative care, and semi-structured interviews. Additionally, professional caregivers will take part in focus group discussions and participatory observations. Interviews and focus groups will be tape- or video-recorded, transcribed verbatim and analyzed in accordance with the principles of grounded theory (interviews) and content analysis (focus groups). A structured field note template will be used to record notes taken during the participatory observations. Statistical Package for Social Sciences (SPSS, version 22 or higher) will be used for descriptive statistical analyses. The qualitative data analyses will be software-assisted by MAXQDA (version 12 or higher). DISCUSSION: This study will provide important information on what matters most to family caregivers and pediatric patients receiving SOPC. The results will add valuable knowledge to the criteria that distinguish SOPC for pediatric from SOPC for adult patients, and will provide an indication of how the German SOPC rule of procedure can be optimized to satisfy the special needs of pediatric patients. TRIAL REGISTRATION: Internet Portal of the German Clinical Trials Register ( www.germanctr.de , DRKS-ID: DRKS00012431).
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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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.000 |
| Bibliometrics | 0.000 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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".