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☐ ☆ ✇ PLOS ONE Medicine&Health

Assessing community pharmacists’ responses to pregnancy-related nausea and vomiting: A national simulated patient study in Jordan

by Khalid Al Kubaisi, Derar H. Abdel-Qader, Nadia Al Mazrouei, Abduelmula R. Abduelkarem, Yahya H. Dallal Bashi Dallal Bashi, Moh’d Ahmad Shara

Background and aim

Nausea and vomiting of pregnancy (NVP) is the most common medical condition of gestation, affecting up to 90% of women and significantly impacting their quality of life. Community pharmacists (CPs) are often the first point of contact for these women, yet there is a lack of objective data on their practice quality in Jordan. This study aimed to conduct the first national, simulated patient study to assess objectively the assessment, management, counseling, satisfaction and predictors of appropriate practice among Jordanian community CPs when managing NVP.

Materials and methods

A national, cross-sectional study using a simulated patient methodology was conducted in 380 community pharmacies, selected via proportionate stratified random sampling. Two validated scenarios (mild NVP and severe NVP with red flags) were used. A validated structured data collection form documented CPs ‘ assessment, management, counseling, and patient satisfaction. Multivariable logistic regression was used to identify independent predictors of “Appropriate Practice.” All data were analysed using SPSS (V28.0).

Results

A significant gap between guideline-recommended care and actual practice was evident, particularly in high-risk situations. While most CPs (84.2%) initiated symptom inquiry, crucial assessment of red flags in the severe NVP scenario was dangerously low (e.g., inquiry about dehydration, 21.1%). This assessment failure translated directly to practice: only 56.8% of CPs correctly referred the high-risk patient, while 43.2% inappropriately sold an over-the-counter medication, delaying necessary medical care. Counseling on medication safety was consistently poor, with only 29.9% of CPs discussing potential side effects. Despite these clinical deficiencies, the overall patient satisfaction was high, appearing to be driven more by interpersonal skills than clinical accuracy. Multivariable analysis revealed that appropriate practice was independently predicted by prior maternal health training (aOR = 3.48, p p = 0.009). Conversely, a high pharmacy workload was a significant independent barrier, reducing the odds of providing appropriate care by 50% (aOR = 0.50, p = 0.018).

Conclusion

Jordanian community CPs are a critical but currently underperforming resource in maternal care. The prevalent gaps in clinical assessment and referral for severe NVP represent a significant patient safety risk. A one-size-fits-all approach to quality improvement is unlikely to succeed. Instead, a dual-pronged strategy is essential: (1) national professional pharmacy bodies must mandate targeted continuing professional development in maternal health, focusing on risk assessment and referral protocols; and (2) health policymakers and community pharmacy owners must address systemic barriers, particularly the detrimental impact of high workload on the delivery of safe and effective patient care.

☐ ☆ ✇ BMJ Open

Systematic protocol to identify 'clinical controls for paediatric neuroimaging research from clinically acquired brain MRIs

Por: Zimmerman · D. · Mandal · A. S. · Jung · B. · Buczek · M. J. · Schabdach · J. M. · Karandikar · S. · Kafadar · E. · Gardner · M. · Daniali · M. · Mercedes · L. · Kohler · S. · Abdel-Qader · L. · Gur · R. E. · Roalf · D. R. · Satterthwaite · T. D. · Williams · R. · Padmanabhan · V. · Seid — Octubre 15th 2025 at 09:50
Introduction

Progress at the intersection of artificial intelligence and paediatric neuroimaging necessitates large, heterogeneous datasets to generate robust and generalisable models. Retrospective analysis of clinical brain MRI scans offers a promising avenue to augment prospective research datasets, leveraging the extensive repositories of scans routinely acquired by hospital systems in the course of clinical care. Here, we present a systematic protocol for identifying ‘scans with limited imaging pathology’ through machine-assisted manual review of radiology reports.

Methods and analysis

The protocol employs a standardised grading scheme developed with expert neuroradiologists and implemented by non-clinician graders. Categorising scans based on the presence or absence of significant pathology and image quality concerns facilitates the repurposing of clinical brain MRI data for brain research. Such an approach has the potential to harness vast clinical imaging archives—exemplified by over 250 000 brain MRIs at the Children’s Hospital of Philadelphia—to address demographic biases in research participation, to increase sample size and to improve replicability in neurodevelopmental imaging research. Ultimately, this protocol aims to enable scalable, reliable identification of clinical control brain MRIs, supporting large-scale, generalisable neuroimaging studies of typical brain development and neurogenetic conditions.

Ethics and dissemination

Studies using datasets generated from this protocol will be disseminated in peer-reviewed journals and at academic conferences.

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