Effectiveness and cost-effectiveness of an optimized process of providing assistive technology for impaired upper extremity function: Protocol of a prospective, quasi-experimental non-randomized study (OMARM)
Why this work is in the frame
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Bibliographic record
Abstract
BACKGROUND: Impaired upper extremity function due to muscle paresis or paralysis has a major impact on independent living and quality of life (QoL). Assistive technology (AT) for upper extremity function (i.e. dynamic arm supports and robotic arms) can increase a client’s independence. Previous studies revealed that clients often use AT not to their full potential, due to suboptimal provision of these devices in usual care. OBJECTIVE: To optimize the process of providing AT for impaired upper extremity function and to evaluate its (cost-) effectiveness compared with care as usual. METHODS: Development of a protocol to guide the AT provision process in an optimized way according to generic Dutch guidelines; a quasi-experimental study with non-randomized, consecutive inclusion of a control group ( <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" alttext="n=" display="inline" overflow="scroll"> <mml:mrow> <mml:mi>n</mml:mi> <mml:mo>=</mml:mo> <mml:mi/> </mml:mrow> </mml:math> 48) receiving care as usual and of an intervention group (optimized provision process) ( <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" alttext="n=" display="inline" overflow="scroll"> <mml:mrow> <mml:mi>n</mml:mi> <mml:mo>=</mml:mo> <mml:mi/> </mml:mrow> </mml:math> 48); and a cost-effectiveness and cost-utility analysis from societal perspective will be performed. The primary outcome is clients’ satisfaction with the AT and related services, measured with the Quebec User Evaluation of Satisfaction with AT (Dutch version; D-QUEST). Secondary outcomes comprise complaints of the upper extremity, restrictions in activities, QoL, medical consumption and societal cost. Measurements are taken at baseline and at 3, 6 and 9 months follow-up.
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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 | 0.005 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.006 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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 it