The Influence of Absorbent Products on Skin Integrity
Bibliographic record
Abstract
PURPOSE: Absorbent products are commonly used to absorb urine and fecal matter and to mitigate potential skin complications such as incontinence-associated dermatitis (IAD). Evidence concerning the effect these products have on skin integrity is limited. This scoping review aimed to explore the evidence/literature on the effect of absorbent containment products on skin integrity. METHOD: A scoping literature review. SEARCH STRATEGY: The electronic databases CINAHL, Embase, MEDLINE, and Scopus were searched for published articles between 2014 and 2019. Inclusion criteria were studies that focused on urinary and/or fecal incontinence, use of incontinent absorbent containment products, impact on skin integrity, and published in English. The search identified a total of 441 articles that were identified for the title and abstract review. FINDINGS: Twelve studies met inclusion criteria and were included in the review. Variability in the study designs did not allow firm conclusions regarding which absorbent products contributed to or prevented IAD. Specifically, we found variations in assessment of IAD, study settings, and types of products used. IMPLICATIONS: There is insufficient evidence to support the effectiveness of one product category over another for maintaining skin integrity in persons with urinary or fecal incontinence. This paucity of evidence illustrates the need for standardized terminology, a widely used instrument for assessment of IAD, and identification of a standard absorbent product. Additional research using both in vitro and in vivo models, along with real-world clinical studies, is needed to enhance current knowledge and evidence of the impact of absorbent products on skin integrity.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.010 | 0.031 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.004 |
| Bibliometrics | 0.005 | 0.004 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.006 | 0.003 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.007 | 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".