Introduction: Spiritual intelligence is better defined as a capacity to discover and develop true meaning, deep purpose, and vision in life. The purpose of the present study was to determine the predictive role of demographic variables affecting the overall spiritual intelligence in diabetic adolescents.
Methods: In 2016, a cross-sectional study was conducted involving 200 adolescents with type 1 diabetes referring to the Iranian Diabetes Association consenting to participate. The inclusion criteria were: age ranging from 15 to 21 years, more than a year since last diagnosed with diabetes, patients' full awareness of their disease, not having other physical-psychological illnesses, and not taking any psychiatric or narcotic drugs. Spiritual intelligence was measured using the Spiritual Intelligence Self Report Inventory questionnaire consisting of 24-questions. The alpha Cronbach's method was applied to validate the questionnaire in terms of content, form, and data with the reliability calculated as 0.903. Demographic data were analyzed using SPSS software version 18.
Results: On total, 56% of the participants were female, 17.10 ± 1.85, and the mean duration of diabetes was 5.98% ± 3.79%, 62.5% reported diabetes history among immediate relatives. Forty-two percent of the participants were the oldest child in the family first children of the family and 29.5% were studying at the university. The mean score of spiritual intelligence was 60.42 60.42 ing from 15 to 21 years regression test using the enter method (ANOVA: 0.703, F: 0.739) showed that none of the demographic components explored did not significantly alter the scores that assessed spiritual intelligence.
Conclusion: The outcome of the current study portrayed that demographic features do not necessarily alter the overall spiritual intelligence scores, thereby not necessarily affecting an individual's overall spirituality.
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http://dx.doi.org/10.4103/jehp.jehp_361_18 | DOI Listing |
JMIR Form Res
January 2025
Sheffield Teaching Hospitals NHS Foundation Trust, Sheffield, United Kingdom.
Background: Advancements in medical science have focused largely on patient care, often overlooking the well-being of health care professionals (HCPs). This oversight has consequences; not only are HCPs prone to mental and physical health challenges, but the quality of patient care may also endure as a result. Such concerns are also exacerbated by unprecedented crises like the COVID-19 pandemic.
View Article and Find Full Text PDFPLoS One
January 2025
Department of Pediatrics and Child Health, Makerere University, College of Health Sciences, Kampala, Uganda.
Background: Chat Generative Pre-trained Transformer (ChatGPT) is a 175-billion-parameter natural language processing model that uses deep learning algorithms trained on vast amounts of data to generate human-like texts such as essays. Consequently, it has introduced new challenges and threats to medical education. We assessed the use of ChatGPT and other AI tools among medical students in Uganda.
View Article and Find Full Text PDFTranscult Psychiatry
January 2025
Department of Population Health, London School of Hygiene and Tropical Medicine, London, UK.
Mental health service use by individuals of South Asian origin living outside of South Asia is influenced by cultural factors such as endorsing psycho-social-spiritual over biological explanations, somatisation, and stigma. The aim of this review is to synthesise the evidence about (a) explanatory models of common mental disorders (CMDs) among people of South Asian origin residing in high-income countries, and (b) their help-seeking for CMDs, including formal and informal care. The systematic review protocol was registered a priori on Prospero (registration number CRD42021287583).
View Article and Find Full Text PDFIran J Nurs Midwifery Res
November 2024
Department of Nursing, Nursing and Midwifery School, Iranian Research Center on Healthy Aging, Sabzevar University of Medical Sciences, Sabzevar, Iran.
Curr Oncol
December 2024
Advanced Data Analysis in Medicine (ADAM), Laboratory of Interdisciplinary Research Applied to Medicine (DReAM), University of Salento and ASL (Local Health Authority), 73100 Lecce, Italy.
Introduction: This qualitative literature review explored the intersection of art, creativity, and the nurse-patient relationship in the context of oncology nursing. It delved into the perceptions and reflections of nurses as captured by Generative Artificial Intelligence (GAI) analysis from two specialized nursing databases.
Methods: The protocol was registered on the Open Science Framework (OSF) Platform.
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