Volume 16, Issue 2 (Jun 2022)
payavard 2022, 16(2): 172-182 |
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Ethics code: IR.TUMS.SPH.REC.1398.207
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Shahmoradi L, Kheradbin N, Farzanehnejad A R, Mohammadzadeh N, Ghanbari Jolfaei A. Data Elements for Screening Major Depression in Ages 10 To 25 Using a Clinical Decision Support System. payavard 2022; 16 (2) :172-182
URL: http://payavard.tums.ac.ir/article-1-7151-en.html
URL: http://payavard.tums.ac.ir/article-1-7151-en.html
Leila Shahmoradi1 
, Niloofar Kheradbin * 2, Ahmad Reza Farzanehnejad , Niloofar Mohammadzadeh3 , Atefeh Ghanbari Jolfaei4
, Niloofar Kheradbin * 2, Ahmad Reza Farzanehnejad , Niloofar Mohammadzadeh3 , Atefeh Ghanbari Jolfaei4
1- Professor, Department of Health Information Management, School of Allied Medical Sciences, Tehran University of Medical Sciences, Tehran, Iran
2- Master of Science in Health Information Management, School of Allied Medical Sciences, Tehran University of Medical Sciences, Tehran, Iran ,nkheradbin@razi.tums.ac.ir
3- Associate Professor, Department of Health Information Management, School of Allied Medical Sciences, Tehran University of Medical Sciences, Tehran, Iran
4- Associate Professor, Department of Psychiatry, School of Medicine, Iran University of Medical Sciences, Tehran, Iran; Psychiatrist, Minimally Invasive Surgery Research Center, Behavioral Sciences and Mental Health, Hazrat-e-Rasoul Hospital, Tehran, Iran
2- Master of Science in Health Information Management, School of Allied Medical Sciences, Tehran University of Medical Sciences, Tehran, Iran ,
3- Associate Professor, Department of Health Information Management, School of Allied Medical Sciences, Tehran University of Medical Sciences, Tehran, Iran
4- Associate Professor, Department of Psychiatry, School of Medicine, Iran University of Medical Sciences, Tehran, Iran; Psychiatrist, Minimally Invasive Surgery Research Center, Behavioral Sciences and Mental Health, Hazrat-e-Rasoul Hospital, Tehran, Iran
Abstract: (1400 Views)
Background and Aim: Identifying risk factors is recommended as the first step for depression management in children and adolescents. This study aims to determine the data elements required for developing a clinical decision support system for screening major depression in young people.
Materials and Methods: This research was a descriptive-analytical study. The research population included a variety of mental health specialists that were both psychologists and students in psychiatry and guidance & counseling majors as well as electronic databases including Scopus, Pubmed, Embase, PsychInfo, WOS and Clinical key. The data collection tool was a questionnaire designed in three main sections which was answered by a convenient sample of 8 people who were specialists in the field. To analyze the extracted data Content Validity Ratio (CVR) and Mean measures were calculated for each item in questionnaire. Content Validity Index (CVI) and Cronbach’s Alpha (using SPSS software) were calculated which were equal to 0.74 and 0.824 respectively which confirmed validity and reliability of the research tool.
Results: According to Lawshe’s table, data elements with CVR between 0 and 0.75 and Mean less than 1.5, like “Ethnicity and race” (CVR=-0.25, Mean=1.125), were rejected. Items such as “Gender” (CVR=0.5) with a CVR equal to or less than 0.75, as well as items with a CVR between 0 and 0.75 and a Mean equal to or more than 1.5, like “Marital status” (CVR=0.5, Mean=1.625) were retained and considered to be included as the minimum data set for screening major depression in ages 10 to 25 years. Data elements were categorized in three categories: Demographic, Clinical and Psychosocial
Conclusion: Clinical decision support systems can facilitate providing healthcare at different levels such as screening major depression. These systems can be used for screening major depression risk factors to improve accessibility to mental health practitioners, assure the implementation of guidelines and provide a common language between different levels of healthcare. Determining the minimum data set for screening major depression in ages 10 to 25 years, is the first step toward developing a clinical decision support system for screening individuals for major depression.
Materials and Methods: This research was a descriptive-analytical study. The research population included a variety of mental health specialists that were both psychologists and students in psychiatry and guidance & counseling majors as well as electronic databases including Scopus, Pubmed, Embase, PsychInfo, WOS and Clinical key. The data collection tool was a questionnaire designed in three main sections which was answered by a convenient sample of 8 people who were specialists in the field. To analyze the extracted data Content Validity Ratio (CVR) and Mean measures were calculated for each item in questionnaire. Content Validity Index (CVI) and Cronbach’s Alpha (using SPSS software) were calculated which were equal to 0.74 and 0.824 respectively which confirmed validity and reliability of the research tool.
Results: According to Lawshe’s table, data elements with CVR between 0 and 0.75 and Mean less than 1.5, like “Ethnicity and race” (CVR=-0.25, Mean=1.125), were rejected. Items such as “Gender” (CVR=0.5) with a CVR equal to or less than 0.75, as well as items with a CVR between 0 and 0.75 and a Mean equal to or more than 1.5, like “Marital status” (CVR=0.5, Mean=1.625) were retained and considered to be included as the minimum data set for screening major depression in ages 10 to 25 years. Data elements were categorized in three categories: Demographic, Clinical and Psychosocial
Conclusion: Clinical decision support systems can facilitate providing healthcare at different levels such as screening major depression. These systems can be used for screening major depression risk factors to improve accessibility to mental health practitioners, assure the implementation of guidelines and provide a common language between different levels of healthcare. Determining the minimum data set for screening major depression in ages 10 to 25 years, is the first step toward developing a clinical decision support system for screening individuals for major depression.
Keywords: Major Depression, Data Elements, Clinical Decision Support System, Young People, Adolescents
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