The potential role of religiosity, psychological immunity, gender, and age group in predicting the psychological well-being of diabetic patients in Saudi Arabia within the Bayesian framework
This study aimed to investigate the differences in Religiosity (R), Mental Immunity (MI), and Psychological Well-Being (PWB) in patients with diabetes due to gender and age group variables, and to detect the best predictors of PWB in diabetic patients within the Bayesian framework. The study was con...
Gespeichert in:
| Veröffentlicht in: | PloS one 2024-08, Vol.19 (8), p.e0308454 |
|---|---|
| Hauptverfasser: | , , , , , , |
| Format: | Artikel |
| Sprache: | eng |
| Schlagworte: | |
| Online-Zugang: | Volltext |
| Tags: |
Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
|
| container_end_page | |
|---|---|
| container_issue | 8 |
| container_start_page | e0308454 |
| container_title | PloS one |
| container_volume | 19 |
| creator | Al Eid, Nawal A Arnout, Boshra A Al-Qahtani, Thabit A Pavlovic, Slavica AlZahrani, Mohammed R Abdelmotelab, Abdalla S Abdelmotelab, Youssef S |
| description | This study aimed to investigate the differences in Religiosity (R), Mental Immunity (MI), and Psychological Well-Being (PWB) in patients with diabetes due to gender and age group variables, and to detect the best predictors of PWB in diabetic patients within the Bayesian framework. The study was conducted from May 2022 to February 2023 on a random sample of 186 Saudis diagnosed with diabetes. After obtaining participants' consent, they completed three R, MI, and PWB scales. Bayesian Independent Samples t-test was performed to identify differences, and Bayesian linear regression analysis was used to reveal the best prediction model of PWB. The results of the Bayesian independent samples t-test indicated strong evidence supporting the alternative hypothesis H1, suggesting differences between male and female diabetic patients in R, MI, and PWB, with Bayesian factor values exceeding 10 (8.338×10+23, 1.762×10+25, and 1.866×10+24), and Cohen's δ of (-1.866, -1.934, -1.884). These results indicated that females with diabetes have higher means of R, MI, and PWB compared to males. However, the results also suggested evidence for the null hypothesis H0 of no differences in R, MI, and PWB among diabetic patients due to age group, with Bayesian factor values (0.176, 0.181, and 0.187) less than 1.00 and small Cohen's δ of (-0.034, -0.050, -0.063). Bayesian linear regression analysis detected strong evidence that the model including MI is the best predictive model (BF10 for mental immunity is 1.00 and for the other two models are 0.07 and 4.249×10-16) for the PWB of diabetic patients, however, there is no evidence that the model including R or the interaction between R and MI is the best predictor of PWB for diabetic patients. These findings highlight the need for direct psychological care services for male diabetic patients and the urgent need to enhance IM in diabetic patients to improve their PWB. Furthermore, results recommended that healthcare providers in Saudi Arabia integrate MI interventions into diabetes care programs. |
| doi_str_mv | 10.1371/journal.pone.0308454 |
| format | Article |
| fullrecord | <record><control><sourceid>gale_plos_</sourceid><recordid>TN_cdi_plos_journals_3096537235</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><galeid>A805873020</galeid><doaj_id>oai_doaj_org_article_78691b1fcc4241439ff7dc56c32d3167</doaj_id><sourcerecordid>A805873020</sourcerecordid><originalsourceid>FETCH-LOGICAL-d471t-3fa46d9c6860c375a1f57eb4d9e972007ee6322fa61d3fc4b57fb4fda77287693</originalsourceid><addsrcrecordid>eNqNkt1u1DAQhSMEoqXwBggsISGQuosTJ3ZyuVT8rFSpEi3cRhN7nHVJ4mA7WvbleDa8bUBd1AvkC1vjb86ZGU2SPE_pMmUifXdtJzdAtxztgEvKaJkX-YPkOK1YtuAZZQ_vvI-SJ95fU1qwkvPHyRGrUlFmgh0nv642SEYbcAgGOuJsh8Rq4rAzrbHehN0pGf1ObmxnWyMjYvp-Gm7iLQ4K3SmBQRFokbTOTiMxAxkdKiODGVoS9vIH-VvsukWD-89opAw0GIwkIwQTi_D7_EuYlCErB40BsjVhE2N7ofewQ29gINpBj1vrvj9NHmnoPD6b75Pk68cPV2efF-cXn9Znq_OFykUaFkxDzlUlecmpZKKAVBcCm1xVWImMUoHIWZZp4KliWuZNIXSTawVCZKXgFTtJXt7qjp319Tx6XzNa8YKJjBWRWN8SysJ1PTrTg9vVFkx9E7CurcHFRjusRcmrtEm1lHmWpzmrtBZKFlyyTLGUi6j1ZnZz9seEPtS98TLODQa002xblBWjEX31D3p_cTPVQvQ3g7bBgdyL1quSFqVgNNtrLe-h4lHYGxnXTJsYP0h4e5AQmYA_QwuT9_X68sv_sxffDtnXd9gNQhc23nZTMHbwh-CLufup6VH9Hfuf_Wa_ATRQ_Hc</addsrcrecordid><sourcetype>Open Website</sourcetype><iscdi>true</iscdi><recordtype>article</recordtype><pqid>3096537235</pqid></control><display><type>article</type><title>The potential role of religiosity, psychological immunity, gender, and age group in predicting the psychological well-being of diabetic patients in Saudi Arabia within the Bayesian framework</title><source>MEDLINE</source><source>DOAJ Directory of Open Access Journals</source><source>Public Library of Science (PLoS) Journals Open Access</source><source>EZB-FREE-00999 freely available EZB journals</source><source>PubMed Central</source><source>Free Full-Text Journals in Chemistry</source><creator>Al Eid, Nawal A ; Arnout, Boshra A ; Al-Qahtani, Thabit A ; Pavlovic, Slavica ; AlZahrani, Mohammed R ; Abdelmotelab, Abdalla S ; Abdelmotelab, Youssef S</creator><creatorcontrib>Al Eid, Nawal A ; Arnout, Boshra A ; Al-Qahtani, Thabit A ; Pavlovic, Slavica ; AlZahrani, Mohammed R ; Abdelmotelab, Abdalla S ; Abdelmotelab, Youssef S</creatorcontrib><description>This study aimed to investigate the differences in Religiosity (R), Mental Immunity (MI), and Psychological Well-Being (PWB) in patients with diabetes due to gender and age group variables, and to detect the best predictors of PWB in diabetic patients within the Bayesian framework. The study was conducted from May 2022 to February 2023 on a random sample of 186 Saudis diagnosed with diabetes. After obtaining participants' consent, they completed three R, MI, and PWB scales. Bayesian Independent Samples t-test was performed to identify differences, and Bayesian linear regression analysis was used to reveal the best prediction model of PWB. The results of the Bayesian independent samples t-test indicated strong evidence supporting the alternative hypothesis H1, suggesting differences between male and female diabetic patients in R, MI, and PWB, with Bayesian factor values exceeding 10 (8.338×10+23, 1.762×10+25, and 1.866×10+24), and Cohen's δ of (-1.866, -1.934, -1.884). These results indicated that females with diabetes have higher means of R, MI, and PWB compared to males. However, the results also suggested evidence for the null hypothesis H0 of no differences in R, MI, and PWB among diabetic patients due to age group, with Bayesian factor values (0.176, 0.181, and 0.187) less than 1.00 and small Cohen's δ of (-0.034, -0.050, -0.063). Bayesian linear regression analysis detected strong evidence that the model including MI is the best predictive model (BF10 for mental immunity is 1.00 and for the other two models are 0.07 and 4.249×10-16) for the PWB of diabetic patients, however, there is no evidence that the model including R or the interaction between R and MI is the best predictor of PWB for diabetic patients. These findings highlight the need for direct psychological care services for male diabetic patients and the urgent need to enhance IM in diabetic patients to improve their PWB. Furthermore, results recommended that healthcare providers in Saudi Arabia integrate MI interventions into diabetes care programs.</description><identifier>ISSN: 1932-6203</identifier><identifier>EISSN: 1932-6203</identifier><identifier>DOI: 10.1371/journal.pone.0308454</identifier><identifier>PMID: 39178273</identifier><language>eng</language><publisher>United States: Public Library of Science</publisher><subject>Adult ; Age ; Age (Psychology) ; Age Factors ; Age groups ; Aged ; Bayes Theorem ; Bayesian analysis ; Behavior ; Chronic illnesses ; COVID-19 ; Diabetes ; Diabetes mellitus ; Diabetes Mellitus - epidemiology ; Diabetes Mellitus - immunology ; Diabetes Mellitus - psychology ; Diabetics ; Disease ; Empowerment ; Female ; Females ; Gender ; Health care ; Humans ; Hypotheses ; Hypothesis testing ; Immune system ; Immunology ; Male ; Mathematical models ; Medical research ; Mental Health ; Middle Aged ; Neuropsychology ; Null hypothesis ; Prediction models ; Psychological aspects ; Psychological factors ; Psychological research ; Psychological Well-Being ; Regression analysis ; Regression models ; Religion ; Religious aspects ; Religiousness ; Saudi Arabia - epidemiology ; Sex differences (Psychology) ; Sex Factors ; Statistical analysis ; Statistical methods ; Stress ; Young Adult</subject><ispartof>PloS one, 2024-08, Vol.19 (8), p.e0308454</ispartof><rights>Copyright: © 2024 Al Eid et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.</rights><rights>COPYRIGHT 2024 Public Library of Science</rights><rights>2024 Al Eid et al. This is an open access article distributed under the terms of the Creative Commons Attribution License: http://creativecommons.org/licenses/by/4.0/ (the “License”), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.</rights><rights>2024 Al Eid et al. This is an open access article distributed under the terms of the Creative Commons Attribution License: http://creativecommons.org/licenses/by/4.0/ (the “License”), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><orcidid>0000-0003-3418-5667</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><link.rule.ids>315,781,785,865,2103,23870,27928,27929</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/39178273$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><creatorcontrib>Al Eid, Nawal A</creatorcontrib><creatorcontrib>Arnout, Boshra A</creatorcontrib><creatorcontrib>Al-Qahtani, Thabit A</creatorcontrib><creatorcontrib>Pavlovic, Slavica</creatorcontrib><creatorcontrib>AlZahrani, Mohammed R</creatorcontrib><creatorcontrib>Abdelmotelab, Abdalla S</creatorcontrib><creatorcontrib>Abdelmotelab, Youssef S</creatorcontrib><title>The potential role of religiosity, psychological immunity, gender, and age group in predicting the psychological well-being of diabetic patients in Saudi Arabia within the Bayesian framework</title><title>PloS one</title><addtitle>PLoS One</addtitle><description>This study aimed to investigate the differences in Religiosity (R), Mental Immunity (MI), and Psychological Well-Being (PWB) in patients with diabetes due to gender and age group variables, and to detect the best predictors of PWB in diabetic patients within the Bayesian framework. The study was conducted from May 2022 to February 2023 on a random sample of 186 Saudis diagnosed with diabetes. After obtaining participants' consent, they completed three R, MI, and PWB scales. Bayesian Independent Samples t-test was performed to identify differences, and Bayesian linear regression analysis was used to reveal the best prediction model of PWB. The results of the Bayesian independent samples t-test indicated strong evidence supporting the alternative hypothesis H1, suggesting differences between male and female diabetic patients in R, MI, and PWB, with Bayesian factor values exceeding 10 (8.338×10+23, 1.762×10+25, and 1.866×10+24), and Cohen's δ of (-1.866, -1.934, -1.884). These results indicated that females with diabetes have higher means of R, MI, and PWB compared to males. However, the results also suggested evidence for the null hypothesis H0 of no differences in R, MI, and PWB among diabetic patients due to age group, with Bayesian factor values (0.176, 0.181, and 0.187) less than 1.00 and small Cohen's δ of (-0.034, -0.050, -0.063). Bayesian linear regression analysis detected strong evidence that the model including MI is the best predictive model (BF10 for mental immunity is 1.00 and for the other two models are 0.07 and 4.249×10-16) for the PWB of diabetic patients, however, there is no evidence that the model including R or the interaction between R and MI is the best predictor of PWB for diabetic patients. These findings highlight the need for direct psychological care services for male diabetic patients and the urgent need to enhance IM in diabetic patients to improve their PWB. Furthermore, results recommended that healthcare providers in Saudi Arabia integrate MI interventions into diabetes care programs.</description><subject>Adult</subject><subject>Age</subject><subject>Age (Psychology)</subject><subject>Age Factors</subject><subject>Age groups</subject><subject>Aged</subject><subject>Bayes Theorem</subject><subject>Bayesian analysis</subject><subject>Behavior</subject><subject>Chronic illnesses</subject><subject>COVID-19</subject><subject>Diabetes</subject><subject>Diabetes mellitus</subject><subject>Diabetes Mellitus - epidemiology</subject><subject>Diabetes Mellitus - immunology</subject><subject>Diabetes Mellitus - psychology</subject><subject>Diabetics</subject><subject>Disease</subject><subject>Empowerment</subject><subject>Female</subject><subject>Females</subject><subject>Gender</subject><subject>Health care</subject><subject>Humans</subject><subject>Hypotheses</subject><subject>Hypothesis testing</subject><subject>Immune system</subject><subject>Immunology</subject><subject>Male</subject><subject>Mathematical models</subject><subject>Medical research</subject><subject>Mental Health</subject><subject>Middle Aged</subject><subject>Neuropsychology</subject><subject>Null hypothesis</subject><subject>Prediction models</subject><subject>Psychological aspects</subject><subject>Psychological factors</subject><subject>Psychological research</subject><subject>Psychological Well-Being</subject><subject>Regression analysis</subject><subject>Regression models</subject><subject>Religion</subject><subject>Religious aspects</subject><subject>Religiousness</subject><subject>Saudi Arabia - epidemiology</subject><subject>Sex differences (Psychology)</subject><subject>Sex Factors</subject><subject>Statistical analysis</subject><subject>Statistical methods</subject><subject>Stress</subject><subject>Young Adult</subject><issn>1932-6203</issn><issn>1932-6203</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2024</creationdate><recordtype>article</recordtype><sourceid>EIF</sourceid><sourceid>ABUWG</sourceid><sourceid>AFKRA</sourceid><sourceid>AZQEC</sourceid><sourceid>BENPR</sourceid><sourceid>CCPQU</sourceid><sourceid>DWQXO</sourceid><sourceid>GNUQQ</sourceid><sourceid>DOA</sourceid><recordid>eNqNkt1u1DAQhSMEoqXwBggsISGQuosTJ3ZyuVT8rFSpEi3cRhN7nHVJ4mA7WvbleDa8bUBd1AvkC1vjb86ZGU2SPE_pMmUifXdtJzdAtxztgEvKaJkX-YPkOK1YtuAZZQ_vvI-SJ95fU1qwkvPHyRGrUlFmgh0nv642SEYbcAgGOuJsh8Rq4rAzrbHehN0pGf1ObmxnWyMjYvp-Gm7iLQ4K3SmBQRFokbTOTiMxAxkdKiODGVoS9vIH-VvsukWD-89opAw0GIwkIwQTi_D7_EuYlCErB40BsjVhE2N7ofewQ29gINpBj1vrvj9NHmnoPD6b75Pk68cPV2efF-cXn9Znq_OFykUaFkxDzlUlecmpZKKAVBcCm1xVWImMUoHIWZZp4KliWuZNIXSTawVCZKXgFTtJXt7qjp319Tx6XzNa8YKJjBWRWN8SysJ1PTrTg9vVFkx9E7CurcHFRjusRcmrtEm1lHmWpzmrtBZKFlyyTLGUi6j1ZnZz9seEPtS98TLODQa002xblBWjEX31D3p_cTPVQvQ3g7bBgdyL1quSFqVgNNtrLe-h4lHYGxnXTJsYP0h4e5AQmYA_QwuT9_X68sv_sxffDtnXd9gNQhc23nZTMHbwh-CLufup6VH9Hfuf_Wa_ATRQ_Hc</recordid><startdate>20240823</startdate><enddate>20240823</enddate><creator>Al Eid, Nawal A</creator><creator>Arnout, Boshra A</creator><creator>Al-Qahtani, Thabit A</creator><creator>Pavlovic, Slavica</creator><creator>AlZahrani, Mohammed R</creator><creator>Abdelmotelab, Abdalla S</creator><creator>Abdelmotelab, Youssef S</creator><general>Public Library of Science</general><general>Public Library of Science (PLoS)</general><scope>CGR</scope><scope>CUY</scope><scope>CVF</scope><scope>ECM</scope><scope>EIF</scope><scope>NPM</scope><scope>IOV</scope><scope>ISR</scope><scope>3V.</scope><scope>7QG</scope><scope>7QL</scope><scope>7QO</scope><scope>7RV</scope><scope>7SN</scope><scope>7SS</scope><scope>7T5</scope><scope>7TG</scope><scope>7TM</scope><scope>7U9</scope><scope>7X2</scope><scope>7X7</scope><scope>7XB</scope><scope>88E</scope><scope>8AO</scope><scope>8C1</scope><scope>8FD</scope><scope>8FE</scope><scope>8FG</scope><scope>8FH</scope><scope>8FI</scope><scope>8FJ</scope><scope>8FK</scope><scope>ABJCF</scope><scope>ABUWG</scope><scope>AFKRA</scope><scope>ARAPS</scope><scope>ATCPS</scope><scope>AZQEC</scope><scope>BBNVY</scope><scope>BENPR</scope><scope>BGLVJ</scope><scope>BHPHI</scope><scope>C1K</scope><scope>CCPQU</scope><scope>COVID</scope><scope>D1I</scope><scope>DWQXO</scope><scope>FR3</scope><scope>FYUFA</scope><scope>GHDGH</scope><scope>GNUQQ</scope><scope>H94</scope><scope>HCIFZ</scope><scope>K9.</scope><scope>KB.</scope><scope>KB0</scope><scope>KL.</scope><scope>L6V</scope><scope>LK8</scope><scope>M0K</scope><scope>M0S</scope><scope>M1P</scope><scope>M7N</scope><scope>M7P</scope><scope>M7S</scope><scope>NAPCQ</scope><scope>P5Z</scope><scope>P62</scope><scope>P64</scope><scope>PATMY</scope><scope>PDBOC</scope><scope>PIMPY</scope><scope>PQEST</scope><scope>PQQKQ</scope><scope>PQUKI</scope><scope>PRINS</scope><scope>PTHSS</scope><scope>PYCSY</scope><scope>RC3</scope><scope>7X8</scope><scope>DOA</scope><orcidid>https://orcid.org/0000-0003-3418-5667</orcidid></search><sort><creationdate>20240823</creationdate><title>The potential role of religiosity, psychological immunity, gender, and age group in predicting the psychological well-being of diabetic patients in Saudi Arabia within the Bayesian framework</title><author>Al Eid, Nawal A ; Arnout, Boshra A ; Al-Qahtani, Thabit A ; Pavlovic, Slavica ; AlZahrani, Mohammed R ; Abdelmotelab, Abdalla S ; Abdelmotelab, Youssef S</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-d471t-3fa46d9c6860c375a1f57eb4d9e972007ee6322fa61d3fc4b57fb4fda77287693</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2024</creationdate><topic>Adult</topic><topic>Age</topic><topic>Age (Psychology)</topic><topic>Age Factors</topic><topic>Age groups</topic><topic>Aged</topic><topic>Bayes Theorem</topic><topic>Bayesian analysis</topic><topic>Behavior</topic><topic>Chronic illnesses</topic><topic>COVID-19</topic><topic>Diabetes</topic><topic>Diabetes mellitus</topic><topic>Diabetes Mellitus - epidemiology</topic><topic>Diabetes Mellitus - immunology</topic><topic>Diabetes Mellitus - psychology</topic><topic>Diabetics</topic><topic>Disease</topic><topic>Empowerment</topic><topic>Female</topic><topic>Females</topic><topic>Gender</topic><topic>Health care</topic><topic>Humans</topic><topic>Hypotheses</topic><topic>Hypothesis testing</topic><topic>Immune system</topic><topic>Immunology</topic><topic>Male</topic><topic>Mathematical models</topic><topic>Medical research</topic><topic>Mental Health</topic><topic>Middle Aged</topic><topic>Neuropsychology</topic><topic>Null hypothesis</topic><topic>Prediction models</topic><topic>Psychological aspects</topic><topic>Psychological factors</topic><topic>Psychological research</topic><topic>Psychological Well-Being</topic><topic>Regression analysis</topic><topic>Regression models</topic><topic>Religion</topic><topic>Religious aspects</topic><topic>Religiousness</topic><topic>Saudi Arabia - epidemiology</topic><topic>Sex differences (Psychology)</topic><topic>Sex Factors</topic><topic>Statistical analysis</topic><topic>Statistical methods</topic><topic>Stress</topic><topic>Young Adult</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Al Eid, Nawal A</creatorcontrib><creatorcontrib>Arnout, Boshra A</creatorcontrib><creatorcontrib>Al-Qahtani, Thabit A</creatorcontrib><creatorcontrib>Pavlovic, Slavica</creatorcontrib><creatorcontrib>AlZahrani, Mohammed R</creatorcontrib><creatorcontrib>Abdelmotelab, Abdalla S</creatorcontrib><creatorcontrib>Abdelmotelab, Youssef S</creatorcontrib><collection>Medline</collection><collection>MEDLINE</collection><collection>MEDLINE (Ovid)</collection><collection>MEDLINE</collection><collection>MEDLINE</collection><collection>PubMed</collection><collection>Gale In Context: Opposing Viewpoints</collection><collection>Gale In Context: Science</collection><collection>ProQuest Central (Corporate)</collection><collection>Animal Behavior Abstracts</collection><collection>Bacteriology Abstracts (Microbiology B)</collection><collection>Biotechnology Research Abstracts</collection><collection>Nursing & Allied Health Database</collection><collection>Ecology Abstracts</collection><collection>Entomology Abstracts (Full archive)</collection><collection>Immunology Abstracts</collection><collection>Meteorological & Geoastrophysical Abstracts</collection><collection>Nucleic Acids Abstracts</collection><collection>Virology and AIDS Abstracts</collection><collection>Agricultural Science Collection</collection><collection>Health & Medical Collection</collection><collection>ProQuest Central (purchase pre-March 2016)</collection><collection>Medical Database (Alumni Edition)</collection><collection>ProQuest Pharma Collection</collection><collection>Public Health Database</collection><collection>Technology Research Database</collection><collection>ProQuest SciTech Collection</collection><collection>ProQuest Technology Collection</collection><collection>ProQuest Natural Science Collection</collection><collection>Hospital Premium Collection</collection><collection>Hospital Premium Collection (Alumni Edition)</collection><collection>ProQuest Central (Alumni) (purchase pre-March 2016)</collection><collection>Materials Science & Engineering Collection</collection><collection>ProQuest Central (Alumni Edition)</collection><collection>ProQuest Central UK/Ireland</collection><collection>Advanced Technologies & Aerospace Collection</collection><collection>Agricultural & Environmental Science Collection</collection><collection>ProQuest Central Essentials</collection><collection>Biological Science Collection</collection><collection>ProQuest Central</collection><collection>Technology Collection</collection><collection>Natural Science Collection</collection><collection>Environmental Sciences and Pollution Management</collection><collection>ProQuest One Community College</collection><collection>Coronavirus Research Database</collection><collection>ProQuest Materials Science Collection</collection><collection>ProQuest Central Korea</collection><collection>Engineering Research Database</collection><collection>Health Research Premium Collection</collection><collection>Health Research Premium Collection (Alumni)</collection><collection>ProQuest Central Student</collection><collection>AIDS and Cancer Research Abstracts</collection><collection>SciTech Premium Collection</collection><collection>ProQuest Health & Medical Complete (Alumni)</collection><collection>Materials Science Database</collection><collection>Nursing & Allied Health Database (Alumni Edition)</collection><collection>Meteorological & Geoastrophysical Abstracts - Academic</collection><collection>ProQuest Engineering Collection</collection><collection>ProQuest Biological Science Collection</collection><collection>Agricultural Science Database</collection><collection>Health & Medical Collection (Alumni Edition)</collection><collection>Medical Database</collection><collection>Algology Mycology and Protozoology Abstracts (Microbiology C)</collection><collection>Biological Science Database</collection><collection>Engineering Database</collection><collection>Nursing & Allied Health Premium</collection><collection>Advanced Technologies & Aerospace Database</collection><collection>ProQuest Advanced Technologies & Aerospace Collection</collection><collection>Biotechnology and BioEngineering Abstracts</collection><collection>Environmental Science Database</collection><collection>Materials Science Collection</collection><collection>Publicly Available Content Database</collection><collection>ProQuest One Academic Eastern Edition (DO NOT USE)</collection><collection>ProQuest One Academic</collection><collection>ProQuest One Academic UKI Edition</collection><collection>ProQuest Central China</collection><collection>Engineering Collection</collection><collection>Environmental Science Collection</collection><collection>Genetics Abstracts</collection><collection>MEDLINE - Academic</collection><collection>DOAJ Directory of Open Access Journals</collection><jtitle>PloS one</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Al Eid, Nawal A</au><au>Arnout, Boshra A</au><au>Al-Qahtani, Thabit A</au><au>Pavlovic, Slavica</au><au>AlZahrani, Mohammed R</au><au>Abdelmotelab, Abdalla S</au><au>Abdelmotelab, Youssef S</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>The potential role of religiosity, psychological immunity, gender, and age group in predicting the psychological well-being of diabetic patients in Saudi Arabia within the Bayesian framework</atitle><jtitle>PloS one</jtitle><addtitle>PLoS One</addtitle><date>2024-08-23</date><risdate>2024</risdate><volume>19</volume><issue>8</issue><spage>e0308454</spage><pages>e0308454-</pages><issn>1932-6203</issn><eissn>1932-6203</eissn><abstract>This study aimed to investigate the differences in Religiosity (R), Mental Immunity (MI), and Psychological Well-Being (PWB) in patients with diabetes due to gender and age group variables, and to detect the best predictors of PWB in diabetic patients within the Bayesian framework. The study was conducted from May 2022 to February 2023 on a random sample of 186 Saudis diagnosed with diabetes. After obtaining participants' consent, they completed three R, MI, and PWB scales. Bayesian Independent Samples t-test was performed to identify differences, and Bayesian linear regression analysis was used to reveal the best prediction model of PWB. The results of the Bayesian independent samples t-test indicated strong evidence supporting the alternative hypothesis H1, suggesting differences between male and female diabetic patients in R, MI, and PWB, with Bayesian factor values exceeding 10 (8.338×10+23, 1.762×10+25, and 1.866×10+24), and Cohen's δ of (-1.866, -1.934, -1.884). These results indicated that females with diabetes have higher means of R, MI, and PWB compared to males. However, the results also suggested evidence for the null hypothesis H0 of no differences in R, MI, and PWB among diabetic patients due to age group, with Bayesian factor values (0.176, 0.181, and 0.187) less than 1.00 and small Cohen's δ of (-0.034, -0.050, -0.063). Bayesian linear regression analysis detected strong evidence that the model including MI is the best predictive model (BF10 for mental immunity is 1.00 and for the other two models are 0.07 and 4.249×10-16) for the PWB of diabetic patients, however, there is no evidence that the model including R or the interaction between R and MI is the best predictor of PWB for diabetic patients. These findings highlight the need for direct psychological care services for male diabetic patients and the urgent need to enhance IM in diabetic patients to improve their PWB. Furthermore, results recommended that healthcare providers in Saudi Arabia integrate MI interventions into diabetes care programs.</abstract><cop>United States</cop><pub>Public Library of Science</pub><pmid>39178273</pmid><doi>10.1371/journal.pone.0308454</doi><tpages>e0308454</tpages><orcidid>https://orcid.org/0000-0003-3418-5667</orcidid><oa>free_for_read</oa></addata></record> |
| fulltext | fulltext |
| identifier | ISSN: 1932-6203 |
| ispartof | PloS one, 2024-08, Vol.19 (8), p.e0308454 |
| issn | 1932-6203 1932-6203 |
| language | eng |
| recordid | cdi_plos_journals_3096537235 |
| source | MEDLINE; DOAJ Directory of Open Access Journals; Public Library of Science (PLoS) Journals Open Access; EZB-FREE-00999 freely available EZB journals; PubMed Central; Free Full-Text Journals in Chemistry |
| subjects | Adult Age Age (Psychology) Age Factors Age groups Aged Bayes Theorem Bayesian analysis Behavior Chronic illnesses COVID-19 Diabetes Diabetes mellitus Diabetes Mellitus - epidemiology Diabetes Mellitus - immunology Diabetes Mellitus - psychology Diabetics Disease Empowerment Female Females Gender Health care Humans Hypotheses Hypothesis testing Immune system Immunology Male Mathematical models Medical research Mental Health Middle Aged Neuropsychology Null hypothesis Prediction models Psychological aspects Psychological factors Psychological research Psychological Well-Being Regression analysis Regression models Religion Religious aspects Religiousness Saudi Arabia - epidemiology Sex differences (Psychology) Sex Factors Statistical analysis Statistical methods Stress Young Adult |
| title | The potential role of religiosity, psychological immunity, gender, and age group in predicting the psychological well-being of diabetic patients in Saudi Arabia within the Bayesian framework |
| url | https://sfx.bib-bvb.de/sfx_tum?ctx_ver=Z39.88-2004&ctx_enc=info:ofi/enc:UTF-8&ctx_tim=2024-12-17T01%3A49%3A52IST&url_ver=Z39.88-2004&url_ctx_fmt=infofi/fmt:kev:mtx:ctx&rfr_id=info:sid/primo.exlibrisgroup.com:primo3-Article-gale_plos_&rft_val_fmt=info:ofi/fmt:kev:mtx:journal&rft.genre=article&rft.atitle=The%20potential%20role%20of%20religiosity,%20psychological%20immunity,%20gender,%20and%20age%20group%20in%20predicting%20the%20psychological%20well-being%20of%20diabetic%20patients%20in%20Saudi%20Arabia%20within%20the%20Bayesian%20framework&rft.jtitle=PloS%20one&rft.au=Al%20Eid,%20Nawal%20A&rft.date=2024-08-23&rft.volume=19&rft.issue=8&rft.spage=e0308454&rft.pages=e0308454-&rft.issn=1932-6203&rft.eissn=1932-6203&rft_id=info:doi/10.1371/journal.pone.0308454&rft_dat=%3Cgale_plos_%3EA805873020%3C/gale_plos_%3E%3Curl%3E%3C/url%3E&disable_directlink=true&sfx.directlink=off&sfx.report_link=0&rft_id=info:oai/&rft_pqid=3096537235&rft_id=info:pmid/39178273&rft_galeid=A805873020&rft_doaj_id=oai_doaj_org_article_78691b1fcc4241439ff7dc56c32d3167&rfr_iscdi=true |