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Record W4413985296 · doi:10.2147/rmhp.s558011

Assessment of Hand Hygiene Knowledge, Attitude, and Practice Among Health Sciences Students in Herat, Afghanistan: A Cross-Sectional Study [Response to Letter]

2025· letter· en· W4413985296 on OpenAlexaff
Mohammad Masudi, Ali Rahimi, Enayatollah Ejaz, Khadejah Osmani, Nasar Ahmad Shayan

Bibliographic record

VenueRisk Management and Healthcare Policy · 2025
Typeletter
Languageen
FieldMedicine
TopicInfection Control in Healthcare
Canadian institutionsWestern University
Fundersnot available
KeywordsHygieneCross-sectional studyMedicineAlternative medicineEnvironmental healthFamily medicineMedical educationPsychologyPathology

Abstract

fetched live from OpenAlex

Among Health Sciences Students in Herat, Afghanistan", and for their insightful comments that foster a critical academic debate. 1 The opportunity to clarify our methodological decisions and elaborate on the unique context of our research is one we welcome.Our study's primary objective was to establish a crucial baseline understanding of hand hygiene (HH) knowledge, attitudes, and practices (KAP) among the next generation of healthcare professionals in Afghanistan. 2 In a nation grappling with a fragile health system, such foundational data are indispensable for developing targeted educational curricula and effective, context-specific infection prevention and control policies.While we appreciate the methodological ideals raised, which represent the gold standard in well-resourced environments, we remain confident that our research design was a deliberate and ethically necessary adaptation to the severe realities of conducting research in a conflict-affected setting. 3he correspondents rightly note the limitations of our multi-site convenience sampling strategy.However, a rigid insistence on probability sampling in a setting such as Herat would be both impractical and ethically untenable.The prerequisites for such methods, namely a comprehensive and accurate sampling frame, are nonexistent due to decades of conflict and population displacement. 4Additionally, attempting to create one would have posed unacceptable security risks to both our research team and the participants. 5Consequently, our approach was not a shortcut but the only feasible and ethical pathway to gather vital preliminary data in a constrained setting.Similarly, while we acknowledge that our reliance on self-reported data likely inflated adherence rates due to social desirability bias (SDB)-a limitation we explicitly noted in our manuscript-we argue the finding is still valuable. 6The high score indicates that students have successfully internalized professional norms; the critical challenge, therefore, is addressing the systemic barriers that prevent the translation of knowledge into practice, such as inconsistent supply access and overwhelming workloads. 7The critique regarding our instrument validation is also appreciated.Our multi-step process, involving review by local experts and a pilot study yielding strong reliability, represented the most rigorous approach feasible where large-scale psychometric studies are not possible.Regarding our analytical choices, the use of a median split to categorize KAP scores was a deliberate decision appropriate for this exploratory study, as no universal benchmarks exist for this population; this method enhances interpretability by identifying predictors of relatively better or worse performance within our specific cohort. 8We must also respectfully correct

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 distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.007
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Commentary · Consensus signal: none
Teacher disagreement score0.363
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0070.001
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0030.001
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.001
Research integrity0.0000.002
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.054
GPT teacher head0.483
Teacher spread0.429 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designObservational
Domainnot available
GenreCommentary

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".

Quick stats

Citations3
Published2025
Admission routes1
Has abstractyes

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