An investigation of smoking habits and mental well-being in healthcare personnel during COVID-19.

Perspect Psychiatr Care

Department of Nursing, Mental Health and Psychiatry Nursing, Faculty of Health Sciences, Erzincan Binali Yıldırım University, Erzincan, Turkey.

Published: January 2022

Aim: This study aimed to the smoking levels of the healthcare personnel (n = 761) in Turkey, the changes in their smoking levels, and their mental well-being levels.

Design And Methods: Data were collected via social networks from various cities in Turkey using a personal information form, the Fagerstrom test for nicotine dependence, the Warwick-Edinburgh mental well-being scale.

Findings: Their mean nicotine dependence score was 3.50 ± 2.57 and mental well-being score was 25.01 ± 5.44. The frequency of smoking during the pandemic was increased in 22.4% of the participants and was the same as that before the pandemic in 57.4% of the smokers.

Practice Implications: It is an introductory study of the current situation for healthcare professionals and researchers. It suggests protecting mental well-being and reducing smoking.

Download full-text PDF

Source
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8242534PMC
http://dx.doi.org/10.1111/ppc.12819DOI Listing

Publication Analysis

Top Keywords

mental well-being
20
healthcare personnel
8
smoking levels
8
nicotine dependence
8
mental
5
well-being
5
investigation smoking
4
smoking habits
4
habits mental
4
well-being healthcare
4

Similar Publications

Plasma phosphorylated tau biomarkers open unprecedented opportunities for identifying carriers of Alzheimer's disease pathophysiology in early disease stages using minimally invasive techniques. Plasma p-tau biomarkers are believed to reflect tau phosphorylation and secretion. However, it remains unclear to what extent the magnitude of plasma p-tau abnormalities reflects neuronal network disturbance in the form of cognitive impairment.

View Article and Find Full Text PDF

Exploring the Credibility of Large Language Models for Mental Health Support: Protocol for a Scoping Review.

JMIR Res Protoc

January 2025

Data and Web Science Group, School of Business Informatics and Mathematics, University of Manneim, Mannheim, Germany.

Background: The rapid evolution of large language models (LLMs), such as Bidirectional Encoder Representations from Transformers (BERT; Google) and GPT (OpenAI), has introduced significant advancements in natural language processing. These models are increasingly integrated into various applications, including mental health support. However, the credibility of LLMs in providing reliable and explainable mental health information and support remains underexplored.

View Article and Find Full Text PDF

Background: Mental health concerns have become increasingly prevalent; however, care remains inaccessible to many. While digital mental health interventions offer a promising solution, self-help and even coached apps have not fully addressed the challenge. There is now a growing interest in hybrid, or blended, care approaches that use apps as tools to augment, rather than to entirely guide, care.

View Article and Find Full Text PDF

Background: Psychologists have developed frameworks to understand many constructs, which have subsequently informed the design of digital mental health interventions (DMHIs) aimed at improving mental health outcomes. The science of happiness is one such domain that holds significant applied importance due to its links to well-being and evidence that happiness can be cultivated through interventions. However, as with many constructs, the unique ways in which individuals experience happiness present major challenges for designing personalized DMHIs.

View Article and Find Full Text PDF

Want AI Summaries of new PubMed Abstracts delivered to your In-box?

Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!