Archives of Advances in Biosciences

Investigating the correlation between general health components and marital satisfaction during the COVID-19 pandemic

2022-06-09T12:23:46+00:00

Background: COVID-19 is known as a general health threat. General health can play a significant role in marital adjustment and satisfaction and thus the strength of the family foundation. The current study aimed to determine the correlation between families’ general health components and marital satisfaction during the COVID-19 pandemic in Khaf.

Materials and Methods: This cross-sectional descriptive-analytical study was performed with 90 married individuals who were selected via a convenience sampling method. The study instruments involved a demographics form, a general health questionnaire, and a marital satisfaction questionnaire. Data analyses were performed in SPSS statistical software ver. 15, using the Kolmogorov-Smirnov, Pearson correlation coefficient, multiple regression, independent t-test, one-way analysis of variance, and Tukey’s post hoc tests. The level of significance was set at p <0.05.

Results: Among the general health components, the highest mean score belonged to depression (12.80 ± 4.65) and the lowest to social dysfunction (12.04 ± 4.24). The general health score was 49.70 ± 17.35, and the marital satisfaction mean score was 123.13 ± 34.02. Marital satisfaction was negatively and significantly associated with general health (r = -0.71) as well as the subcomponents of somatic symptoms (r = -0.64), anxiety (r = -0.71), social dysfunction (r = -0.66), and depression (-.067) (p <0.001).

Conclusion: As COVID-19 depression and anxiety have the most significant impact on individuals’ general health and marital satisfaction, healthcare managers and policymakers are advised to consider solutions to these disorders in families. As such, they can contribute to spouses’ general health and marital satisfaction and thus strengthen the family foundation.

Error Detection in Patients’ Pharmaceutical Data: Application of Ontology-Based Text Miner

2022-06-09T12:21:34+00:00

Introduction: Medication errors in patients’ medical records can influence the healthcare quality and cause risks for them. It is, therefore, crucial to apply appropriate procedures to reduce these errors. This study sought to developing a software for detecting medication errors through qualitative analysis of patients’ medical records.

Method: The software was developed using object-oriented analysis and Java. The text was first pre-analyzed using a framework known as Stanford Core NLP. In the next stage, the text was turned into a semi-structured passage to be connected to DrOnontology using Apache Jena framework. The name and dosage of available drugs were then extracted in the physician order forms and the patient progress notes. The areas of mismatch were identified through comparing the data obtained from these two forms.

Results: Software assessment was conducted in two stages. In the first stage, the capability of the software in proper recognition of medicine’s name was measured, as100 completed forms containing physician order forms with a total number of 1014 drugs were used for text mining and error detection. After running the analysis in the error detection software, 93% of the drugs were properly recognized. In the next stage, comparisons were made between the physician order forms and the patient progress notes to find possible mismatches. Out of 1000 recorded drugs in the analyzed forms, the software was able to properly detect mismatches in 91.8% of the cases. The medication data available in i2b2 were used for conducting the assessment.

Conclusion: Given that medical records are of paramount importance and their manual analysis is a complicated and time consuming process, deployment of a text miner with the capability of quality analysis could facilitate error detection efficiently and effectively.

Evaluation of the conceptual model of knowledge management audit in the Iranian medical universities’ libraries

2022-06-09T12:42:02+00:00

Introduction: Knowledge audit is a systematic evaluation of organizational knowledge health. The purpose of this study is to evaluate the conceptual model of knowledge management audit in the library of Iranian medical universities.

Materials and methods: The present study used a mixed method including qualitative and survey-analytical type. In order to identify the indicators of the conceptual model of knowledge management audit, the fuzzy Delphi technique was used by 12 experts during two stages; and to validate the identified indicators, the second-order confirmatory factor analysis of smart pls software was used. The statistical population to approve the model include 122 managers and librarians of university libraries of medical sciences.

Results: The conceptual model of knowledge management audit was obtained in three dimensions, 13 indicators and 55 sub-indicators. The three dimensions including the stage after knowledge management audit (0.8550), before knowledge management audit (0.8460) , and during knowledge management implementation (0.8430) were the most important, respectively.

Conclusion: The obtained criteria and indicators showed the approval and acceptable fit of the conceptual model of knowledge management audit in the library of Iranian universities of medical sciences.