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Design and evaluation of a new mobile application to improve the management of minor ailments: a pilot study
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Abstract<sec> <title>Background

Seeking pharmacist advice about minor ailments is a common practice among Iraqi patients because such advice is free and quick. Unfortunately, the assessment and management of minor ailments by Iraqi pharmacists were inappropriate. Therefore, this study aimed to develop a model for a mobile application that can assist community pharmacists in the diagnosis and management of minor ailments.

Methods

The scientific content of the application was based on the information in the symptoms in the pharmacy and British National Formulary books. The design and content of the application were approved by two experts. Thereafter, the application was built for Android mobiles using flutter technology and dart language. A pre-post pilot study was conducted to assess outcomes associated with use of the application, including user acceptance and appropriateness of clinical recommendations. Fifteen students from the College of Pharmacy/University of Baghdad who had an Android mobile participated in this study. Two different scenarios about diarrhea were used during the pilot study, in which the researcher acted as a patient (SP) and the participant student as a pharmacist.

Results

After using the application, the number of questions asked by the participated student to the SP was significantly increased to about double. Additionally, providing the SP with appropriate non-pharmacological and pharmacological therapy along with optimum counseling and education were also significantly improved. All study participants agreed on the application’s ease of use and ability to reduce diagnosis and medication errors.

Conclusions

The implementation of the newly developed mobile application, diarrhea management step by step, was associated with improvements in assessment and recommended treatments for diarrhea cases with good acceptance by a pilot sample of pharmacy students at Baghdad University.

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Publication Date
Fri Jun 01 2012
Journal Name
Pharmacie Globale
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Sat Feb 01 2020
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International Journal Of Electrical And Computer Engineering (ijece)
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Publication Date
Sun Oct 01 2023
Journal Name
Iraqi Journal Of Pharmaceutical Sciences ( P-issn 1683 - 3597 E-issn 2521 - 3512)
Evaluation of Anxiety and Depression among a Sample of Hypothyroidism-Treated Iraqi Patients
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Publication Date
Sat Sep 01 2018
Journal Name
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A novel sol-gel silica formulation for management of methadone hydrochloride abuse
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Publication Date
Sun Jan 01 2023
Journal Name
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Publication Date
Fri Jun 01 2018
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Journal Of Accounting And Financial Studies ( Jafs )
The role of external audit in banking risk management: A typical framework for control testing and banking risk assessment
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Publication Date
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Publication Date
Tue Aug 01 2017
Journal Name
Journal Of Economics And Administrative Sciences
Post a reflection on the capabilities of personnel programs A prospective study of a sample of the views of the staff at the Ministry of Higher Education and Scientific Research
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Publication Date
Tue Jun 01 2021
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Https://www.researchgate.net/journal/iop-conference-series-materials-science-and-engineering-1757-899x
Application of multivariate statistical techniques in the evaluation of large-scale water treatment plants in Baghdad.
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Abstract<p>This paper aims to evaluate large-scale water treatment plants’ performance and demonstrate that it can produce high-level effluent water. Raw water and treated water parameters of a large monitoring databank from 2016 to 2019, from eight water treatment plants located at different parts in Baghdad city, were analyzed using nonparametric and multivariate statistical tools such as principal component analysis (PCA) and hierarchical cluster analysis (HCA). The plants are Al-Karkh, Sharq-Dijlah, Al-Wathba, Al-Qadisiya Al-Karama, Al-Dora, Al-Rasheed, Al-Wehda. PCA extracted six factors as the most significant water quality parameters that can be used to evaluate the variation in drinkin</p> ... Show More
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Publication Date
Mon Mar 31 2025
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The investigation of machine learning techniques for addressing missing well-log data has garnered considerable interest recently, especially as the oil and gas sector pursues novel approaches to improve data interpretation and reservoir characterization. Conversely, for wells that have been in operation for several years, conventional measurement techniques frequently encounter challenges related to availability, including the lack of well-log data, cost considerations, and precision issues. This study's objective is to enhance reservoir characterization by automating well-log creation using machine-learning techniques. Among the methods are multi-resolution graph-based clustering and the similarity threshold method. By using cutti

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