No pain, just gain: Painless, easy, and fast dried blood spot collection from fingertip and upper arm in doping control
Bibliographic record
Abstract
This study aimed to determine and compare the perception, painfulness, and usability of the minimally invasive dried blood spot (DBS) collections from fingertip versus upper arm from different athlete populations: males and females representing sports dependent on hand/arm, sports less dependent on hand/arm and para-athletes. To accomplish this, 108 national level athletes from Denmark were recruited (♀ = 49, ♂ = 59, 25 ± 6 years; mean ± SD) and 11 Doping Control Officers (DCOs) collected manual fingerprick DBS (HemaSpot HF) and automated upper-arm DBS (Tasso-M20) from each athlete. Athletes and DCOs responded to questionnaires regarding the perception of sample collection procedures. On a 0-10 scale, the athletes reported a low pain score and a very good general experience for both sampling sites, but following upper-arm DBS collection, the associated pain was rated lower (-0.4 ± 1.6, p < 0.05), and the general experience rated better (+0.6 ± 2.3, p ≤ 0.001) than after the fingerprick DBS collection. The DCOs rated the general experience with the upper-arm DBS collection better (+1.6 ± 1.1, p ≤ 0.01) than the fingerprick DBS collection, partly because problems occurred more frequently during the DBS collection from the fingertip (28%) than from the upper arm (6%). In conclusion, it appears that DBS sampling is affiliated with minimal sensation of pain and is preferred by both DCOs and athletes, independent of gender and discipline, over conventional sample collection methods. Collection of DBS from the upper arm was preferred over fingerprick by both athletes and DCOs.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| 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".