Bibliographic record
Abstract
Informal caregivers play a crucial role in the care for people with Amyotrophic Lateral Sclerosis (ALS). ALS is a motor neuron disease which leads to muscle weakness and respiratory failure. During the disease course patients become more and more dependent on their environment. The majority of care tasks are provided by informal caregivers such as partners or children. Research shows that these caregivers often experience feelings of psychological distress or caregiver burden, but there is a lack of supportive interventions for these caregivers. The overall aim of this theses is to improve the support for caregivers of people with ALS. In this study a support program for caregivers of people with ALS was developed and evaluated on its effectiveness. The aim of the support program was to increase the feeling of control over caregiving in order to decrease feelings of psychological distress. The support program was based on Acceptance and Commitment Therapy and consisted of one face-to-face contact, 6 online guided modules and one telephone call. Although caregivers evaluated the program positively, no effects on psychological distress were found. A positive intervention effect was found on caregivers ability to control upsetting thoughts related to caregiving. Caregivers reported that the program helped them to become more aware of their own situation, perceive control over their situation, accept negative emotions and thoughts, to be there for their partner and to feel acknowledged in their role. The support program will be adapted in line with the received feedback from caregivers and can be considered as one of the support options available for caregivers of people with ALS.
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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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".