Clinical Practice and Epidemiology in Mental Health最新文献

Background: The perception of respect for users' rights is fundamental for organizational well-being in mental health services. This cross-sectional observational study examined the job satisfaction and perception of user rights among nursing staff compared to other health professionals across seven countries in the Mediterranean and Latin American regions. This research measures this perception among nursing staff in different countries, with a particular focus on regional differences and professional roles.

Methods: Data were collected from mental health services in four Mediterranean and three Latin American countries via a structured questionnaire (Well-Being at Work and Respect Rights Questionnaire - WWRR), administered both online and on paper. Using multivariable logistic regression, the study analyzed associations between job satisfaction, respect for rights, and various socio-demographic and professional factors.

Results: Among 408 nurses and 492 other health professionals, findings revealed significant cross-country variability. Nurses in North Macedonia reported higher job satisfaction and perceived respect for user rights than other professionals (p<0.0001 in all items of the questionnaire), while Tunisian nurses showed lower organizational satisfaction but higher respect for user rights (p=0.033 for respect for rights). However, in general, no significant differences were found between nurses and other professionals across all items.

Conclusion: The perception of respect for users' rights is fundamental for organizational well-being in mental health services. The study highlights differences in organizational well-being perceptions across various contexts, emphasizing the need for culturally and economically adapted policies to improve mental health service environments globally. The results indicate the variability in the perception of respect for rights and job satisfaction between different geographical and professional contexts. This indicates the need for policies adapted to specific cultural and economic realities to improve organizational well-being in mental health services.

Background: Many pharmacological treatments are considered effective in the treatment of panic disorder (PD), however, about 20 to 40% of the patients have treatment-resistant PD. Pharmacogenetics could explain why some patients are treatment-resistant.

Objective: Our objective was to gather preliminary data on the clinical usefulness of pharmacogenetic testing in this disorder.

Methods: Twenty patients with treatment-resistant PD were included in this observational study and submitted to commercial pharmacogenetic testing. Testing panel included gene polymorphisms related to CYP, genes EPHX1, UGT1A4, UGT2B15, ABCB1, ADRA2A, ANKK1, COMT, DRD2, FKBP5, GRIK4, GSK3B, HTR1A, HTR2A, HTR2C, MC4R, OPRM1, SCN1A, SLC6A4 and MTHFR. Participants received treatment-as-usual for PD before being enrolled in this study, including first-line and second-line medications for PD.

Results: In 30% of the patients, the tests indicated reduced chance of response to the prescribed drug, while they indicated very low serum levels of the prescribed drug in 20% of the subjects. The pharmacogenetic tests predicted reduction of MTHFR enzyme activity in 74% of the patients. ABCB1 gene alleles associated to drug resistance were found in 90% of the samples.

Conclusion: Commercial pharmacogenetic testing failed to predict negative treatment outcome in most patients with PD. The association between treatment-resistance in PD and the genes CYP2C19, MTHFR and ABCB1 deserves further study.

Background: Mental health well-being is a fundamental human right. However, mental health awareness is not yet considered as a main priority for the government and public in Indonesia. Thus, there is an urgent need for Indonesians to fully comprehend the importance of raising mental health awareness.

Methods: A discussion among 45 experts in September until October 2023 was conducted by the Community Caucus Caring for Mental Health to raise an awareness of the importance of mental health in Indonesia. The results were reported as an expert consensus.

Results: The discussion acknowledged the urgency of managing mental health issue along with its five key drivers and three essences. It identified nine specific themes of mental health issues in Indonesia by focusing on four high-risk population groups. The consensus proposed multi-pronged recommendations, i.e., developing personalized mental health-related campaigns and movements, conducting mental health-relevant studies at clinical and community settings, incorporating of mental health awareness in teaching curriculum and family's discussion, innovating technology for screening and diagnosing mental health issues, as well as an providing mental health first-aid with wide access to all population.

Conclusion: The expert consensus concluded that Indonesians must start to prioritize mental health awareness and to provide sufficient resources to screen, diagnose and treat individuals with mental health disorders. The expert consensus identified nine specific themes of mental health issues in Indonesia and subsequently proposed multi-pronged recommendations with an aim to improve mental health awareness in Indonesia.

Background: The coronavirus disease (COVID-19) has affected people psychologically worldwide, particularly healthcare personnel. Even though the COVID-19 pandemic situation has eased, healthcare personnel must still perform their duties, which has resulted in psychological impacts, particularly stress.

Objectives: This study aimed to examine the risk factors associated with stress among healthcare personnel post-COVID-19 pandemic in northeast Thailand.

Methods: A cross-sectional analytic design was conducted from January to April 2023. One thousand and three hundred healthcare workers were selected from primary, secondary, and tertiary hospitals across 16 districts within Chaiyaphum province. The questionnaires were used to collect data, and the stress test 5 (ST-5) questionnaire was used to investigate stress among healthcare personnel.

Results: The overall stress rate for healthcare workers was 15.47%, including very severe (8.85%) and severe (6.62%). The factors associated with stress consisted of work position, environment of work, personal life such as education level and income, and responsibility for taking care of family members, in addition to experiencing quarantine from COVID-19 were more likely to have a high risk of stress problems among healthcare workers.

Conclusion: This result highlighted that the mental health of personnel should be in critical situations, and those found severely afflicted should undergo professional care. To prevent psychological issues, particularly stress, health organizations should be concerned with strong organizational management, which includes supporting bonuses and providing high-quality personal protective equipment (PPE) to healthcare staff.

Background: Despite the increased interest from researchers in Postpartum depression (PPD) globally, related studies are limited in Palestine and do not provide a comprehensive understanding of PPD.

Objective: We examined the factors that determine post-partum depression among Palestinian mothers in Hebron governorate.

Methods: A cross-sectional study was conducted in 122 governmental primary healthcare clinics in Hebron Governorate. A convenient sampling method was used to collect data from 435 using a self-administered questionnaire using the Edinburg Postnatal Depression Scale.

Results: The mean EPDS scale score was 10.56 (SD 5.273), and 36.1% had a score of ≥13, indicating moderate to severe depression symptoms. The study results revealed that psychosocial factors were significantly associated with PPDS and play a crucial role in the development of PPD, such as the history of depression, being exposed to domestic violence before and during pregnancy, poor husband support, unplanned pregnancy, fear of infant's gender, and in addition to anemia than other factors.

Conclusion: A high prevalence of PPD was found among Palestinian women in this study. The study proposes screening women for trauma or domestic violence and assessing their social support, inquiring about pregnancy intention, and discussing family planning. Delivering iron supplements to pregnant or postpartum anemic women is important. Women who have a history of depression, domestic abuse, or lack social support should receive psychological and medical treatment. Mental health services must be included in the after-birth care protocol to train primary health clinic staff to recognize and treat PPD.

Background: The correlation between sleep disturbance and depression is widely recognized in developed countries but relevant evidence is lacking in developing countries.

Objective: This study aims to assess the correlation between sleep disturbance and depression levels among the general Indonesian population.

Methods: This national cross-sectional survey was conducted using the Indonesian Family Life Survey. Sleep disturbance was assessed based on the questions related to sleeping experience. Depression levels were assessed with a modified Center for Epidemiologic Studies-Depression scale. Sociodemographic factors as confounders were obtained from the self-reported data. Logistic regression was performed after adjusting for confounders.

Results: A total of 22,024 respondents were included. Respondents with severe, moderate, and mild sleep disturbance were associated with depression compared to those with none or slight sleep disturbance.

Conclusions: Respondents with sleep disturbance had a higher possibility of experiencing depression. Screening of sleep quality among the general population is important to reduce the risk of depression.

[This corrects the article on p. e17450179303653 in vol. 20 PMC11318155.].

Background: Internet gaming disorder is defined as "Persistent and recurrent use of the internet to engage in games, often with other players, leading to clinically significant impairment or distress." It is a new evolving disorder that affects many life aspects; therefore, it needs further investigation among different population groups. IGD was introduced for the first time in 2013 in the fifth edition of the Diagnostic and Statistical Manual of Mental Disorders, and it suggested carrying out further research among different populations. In 2018, Gaming Disorder (GD) has officially become a type of addiction as the World Health Organization released the 11th revision of the International Classification of Diseases (ICD-11).

Aims: The objective of this study is to investigate the prevalence of internet gaming disorder (IGD) and its association with sleep quality and academic performance among Jordanian university students aged 18-26. Our literature review revealed a lack of research on this topic concerning this specific population and culture. Therefore, our study aims to contribute to the existing literature and to provide insights that can inform prevention, assessment, and treatment strategies for those affected.

Methods: A cross-sectional study design was used by employing convenience and snowball sampling; a total of 2473 participants completed an electronic self-administered questionnaire that included the Internet Gaming Disorder Scale-SF (IGDS9-SF) and Pittsburgh Sleep Quality Index (PSQI). Of these, 432 were excluded based on our criteria. Our inclusion criteria required participants to be Jordanian university students between the ages of 18 and 26, enrolled as undergraduates at Jordanian universities, and free of neurological or psychiatric conditions.

Results: The prevalence of IGD in this study was 15.2% and was more prevalent among males compared to females (p= <0.001). Poor sleep quality was reported by 64.6% of the study population and was more frequently observed in females. Age and academic achievements (GPA) were not associated with having IGD. When binary logistic regression was used, IGD (OR=1.882) positively predicted poor sleep quality.

Conclusion: Internet gaming disorder is common among Jordanian university students and is associated with poor sleep quality, and our findings have significant implications for policymakers, educators, and healthcare providers in raising awareness about the IGD and its impact on sleep quality.

Background and aims: Family Caregivers (FCGs) of patients with schizophrenia (PwS) may face unanticipated sources of stress and responsibility, which can negatively impact their quality of life (QoL). This study aimed to assess FCGs' QoL and the impact of clinical characteristics of patients and sociodemographic factors on their QoL.

Patients and methods: A cross-sectional questionnaire-based study surveyed 340 FCGs from outpatient clinics of PwS in two large psychiatric hospitals in Saudi Arabia's eastern province using a convenience sampling approach. We used the Adult Carer Quality of Life (AC-QoL) scale, which has eight subscales and 40 items, to assess QoL. AC-QoL is translated into Arabic in this study.

Results: The study included 216 FCGs, with 127 (58.8%) being men, 117 (54.2%) being over 45 years old, 91 (42.1%) being a sibling of a PwS, and 82 (38%) being a parent of a PwS. The mean score in our sample was 78.2 ± 21.24 out of 120, indicating mid-range QoL. Lower QoL was associated with more time spent in caregiving per day, a lower educational level of FCG, and recent admission of PwS to an inpatient unit.

Conclusion: PwS FCGs have a mid-range QoL. FCGs reported a moderate financial burden and low levels of support from healthcare professionals. FCG's QoL and stress can be reduced through healthcare providers, participation in a community support group, and addressing an FCG's in an individual setting.

Introduction: This study aims to investigate the potential of machine learning in predicting mental health conditions among college students by analyzing existing literature on mental health diagnoses using various machine learning algorithms.

Methods: The research employed a systematic literature review methodology to investigate the application of deep learning techniques in predicting mental health diagnoses among students from 2011 to 2024. The search strategy involved key terms, such as "deep learning," "mental health," and related terms, conducted on reputable repositories like IEEE, Xplore, ScienceDirect, SpringerLink, PLOS, and Elsevier. Papers published between January, 2011, and May, 2024, specifically focusing on deep learning models for mental health diagnoses, were considered. The selection process adhered to PRISMA guidelines and resulted in 30 relevant studies.

Results: The study highlights Convolutional Neural Networks (CNN), Random Forest (RF), Support Vector Machine (SVM), Deep Neural Networks, and Extreme Learning Machine (ELM) as prominent models for predicting mental health conditions. Among these, CNN demonstrated exceptional accuracy compared to other models in diagnosing bipolar disorder. However, challenges persist, including the need for more extensive and diverse datasets, consideration of heterogeneity in mental health condition, and inclusion of longitudinal data to capture temporal dynamics.

Conclusion: This study offers valuable insights into the potential and challenges of machine learning in predicting mental health conditions among college students. While deep learning models like CNN show promise, addressing data limitations and incorporating temporal dynamics are crucial for further advancements.