Clinical Practice and Epidemiology in Mental Health最新文献

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

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.

Background: Nomophobia is a public health issue that involves the fear of being without a mobile phone. The study aimed to estimate the prevalence of nomophobia and its relation to psychological factors, including depression and insomnia, among the general population in Makkah Province and Al-Madinah Province, Saudi Arabia.

Methods: This analytical cross-sectional study was conducted and data were obtained through a self-administered online questionnaire using the Patient Health Questionnaire-2 (PHQ-2) for depression, the Nomophobia Questionnaire (NMP-Q), and Insomnia Severity Index (ISI).

Results: A total of 1022 participants completed the questionnaire. The prevalence of nomophobia was 96.7%. Moderate nomophobia was prevalent (47.8%). Based on the PHQ-2, possible depression was identified in 47.3% of the respondents. 37.1% had sub-threshold insomnia. In terms of personal psychiatric history, the most common mental disorders in the participants included generalized anxiety disorder (9.9%) and major depressive disorder (9.7%). 61.6% of them used mobile devices for more than four hours per day.

Conclusion: Nomophobia is prevalent in the Makkah and Al-Madinah provinces in Saudi Arabia. The risk of nomophobia was significantly higher for participants who spent more hours using mobile devices, those with possible depression, and those having irritable bowel syndrome.

Background: Research has established a relationship between psychosis and physical harm in the early course of psychosis. However, little is known about the relationship between specific psychosis symptoms, such as hearing voices, and physical harm.

Objective: This study aimed to determine the prevalence and typology of physical harm related to hearing voices, as well as what aspects of the voice-hearing experience retrospectively predicted incidents of harm within an Early Intervention in Psychosis Service (EIPS).

Methods: We conducted a quality improvement project in a single EIPS. We reviewed case notes of patients and extracted information on the cognitive-phenomenological features of the voices patients heard, as well as any incidents of physical harm that were causally linked to these voices.

Results: It was found that 32.2% of EI patients had an actual incident of physical harm in their case notes that was causally linked to hearing voices. The most common type of physical harm was neglect. In terms of cognitive phenomenological binary correlations that retrospectively predicted physical harm in the case notes, patients were 20 and 7 times more likely to have harmed themselves if they heard self-harm commands (i.e., directions to harm themselves physically) and perceived the voice as omnipotent, respectively. Patients were 6 times more likely to have harmed someone else if they heard violent commands.

Conclusion: Verbal auditory hallucinations commonly influence physical harm in the early course of psychosis. Hearing commands and/or believing the voice to be omnipotent are strong retrospective-correlative predictors that may aid in the assessment and therapeutic intervention.

Background: Attention Deficit Hyperactivity Disorder (ADHD) is a mental health disorder that affects attention and behavior. People with ADHD frequently encounter challenges in social interactions, facing issues, like social rejection and difficulties in interpersonal relationships, due to their inattention, impulsivity, and hyperactivity.

Methods: A National Longitudinal Survey of Youth (NLSY) database was employed to identify patterns of ADHD symptoms. The children who were born to women in the NLSY study between 1986 and 2014 were included. A total of 1,847 children in the NLSY 1979 cohort whose hyperactivity/inattention score was calculated when they were four years old were eligible for this study. A trajectory modeling method was used to evaluate the trajectory classes. Sex, baseline antisocial score, baseline anxiety score, and baseline depression score were adjusted to build the trajectory model. We used stepwise multivariate logistic regression models to select the risk factors for the identified trajectories.

Results: The trajectory analysis identified six classes for ADHD, including (1) no sign class, (2) few signs since preschool being persistent class, (3) few signs in preschool but no signs later class, (4) few signs in preschool that magnified in elementary school class, (5) few signs in preschool that diminished later class, and (6) many signs since preschool being persistent class. The sensitivity analysis resulted in a similar trajectory pattern, except for the few signs since preschool that magnified later class. Children's race, breastfeeding status, headstrong score, immature dependent score, peer conflict score, educational level of the mother, baseline antisocial score, baseline anxious/depressed score, and smoking status 12 months prior to the birth of the child were found to be risk factors in the ADHD trajectory classes.

Conclusion: The trajectory classes findings obtained in the current study can (a) assist a researcher in evaluating an intervention (or combination of interventions) that best decreases the long-term impact of ADHD symptoms and (b) allow clinicians to better assess as to which class a child with ADHD belongs so that appropriate intervention can be employed.

This editorial explores the role of hyperactivity and social rhythm dysregulation in bipolar disorder (BD) and related syndromes. Social Rhythm Dysregulation Syndrome (DYMERS) is proposed as a common vulnerability across various disorders, including panic disorder (PD), attention deficit hyperactivity disorder, and post-traumatic stress disorder. A study conducted on a sample of elderly individuals participating in an active aging study investigated whether individuals with PD exhibit higher biological rhythm dysregulation compared to those without PD. The sample, consisting of 119 individuals, revealed that those with a lifetime PD diagnosis scored significantly higher on the dysregulation of biological rhythms scale compared to those without panic disorder. A higher prevalence of depressive episodes was found in individuals with PD at the time of the interview. Notably, a small sample of elderly individuals with panic disorder, voluntarily selected for a physical exercise trial, showed a significantly higher level of dysregulation of social rhythms compared to those without panic disorder. This study opens a debate on the accuracy of paper and pencil screening tests for bipolar disorders, especially regarding false positives in individuals with panic disorder. Our hypothesis is that DYMERS could be a shared vulnerability substrate for various disorders, serving as a basis for bipolar onset in the presence of a hyperactivity profile, even with genetic features. The data collected from older adults suggest that social rhythm dysregulation is a typical feature of PD, regardless of the coexistence of a depressive episode. While the study has limitations due to a small sample size, the findings warrant careful analysis and suggest the need for larger-scale replication studies. If confirmed, the dysregulation of rhythms and its association with depressive disorders highlight a significant area of vulnerability for serious psychopathological disorders, emphasizing the importance of extending research to younger populations.

Background: The area of palliative care is a setting in which the evaluation of the quality of life (QoL) is fundamental. However, the topic has been covered from many different points of view, and there is a lack of comprehensive synthesis of the evidence drawn from the available literature.

Objective: We carried out a meta-review of all available systematic reviews and meta-analyses that have dedicated part or most of the investigation to the assessment of QoL in palliative care to provide the most updated and comprehensive depiction of all available information about measurement and intervention aimed at improving QoL in palliative care.

Methods: A meta-review of all recent (5 years) available systematic reviews and meta-analyses on "palliative care" and "quality of life" was carried out. The quality of the extracted studies was assessed with the AMSTAR scale.

Results: The search extracted 24 systematic reviews, 14 systematic reviews followed by a meta-analysis on a subset of data, and 2 meta-analyses. In many studies, the investigation of QoL represented a secondary or even marginal outcome. In general, the results supported the efficacy of palliative care in terminal patients or patients with a permanent disability. However, the quality of the studies had a strong influence on the chance that some improvement in QoL was found in relation to palliative care. Studies of lower quality were more likely to report some efficacy of palliative care than studies with better quality.

Conclusion: The investigation of QoL in palliative care is understudied. In many studies, QoL is a secondary outcome, and there is some tendency to use a disparate range of tools to measure it, whose reliability and validity should still be established in some groups of patients.

Background: Stress management and biofeedback interventions have been shown to be effective in improving mental and physical health outcomes. However, previous research studies and synthesized models for applying these interventions in research utilization are insufficient.

Objective: This study aimed to synthesize a model for applying stress management and biofeedback interventions in research utilization.

Methods: A systematic review and meta-analysis were conducted according to the PRISMA guidelines.Multiple studies were used to assess the effectiveness of applying stress management and biofeedback interventions published from 2017 to 2023. The process included identifying the research questions, conducting a comprehensive literature search, assessing study quality, extracting data, synthesizing the data, analyzing and interpreting the findings, drawing conclusions, and making recommendations.

Results: The results indicated a significant mean effect size without evidence of publication bias. The effect sizes of the subgroups among the study variables were not significantly different [Q = 4.02, p = .26]. However, there were significant differences regarding the mean effect sizes among the studies [Q = 63.59, p < .001] and also in terms of the test of subgroups among the participants [Q = 8.49, p = .04].

Conclusion: The results emphasize the importance of evidence-based practice and highlight the need for ongoing evaluation and refinement of interventions. The proposed model was supported by related theories and research studies in order to ensure the robustness and reliability to guide practice and future research in the field of biofeedback interventions. By following this model, researchers and practitioners can ensure that stress management and biofeedback interventions are evidence-based and are effective in improving mental and physical health outcomes.

Background: Wegener's disease is an autoimmune condition affecting the respiratory tract and kidneys. Mental health assessment is crucial due to the impact of psychological disorders on the immune system. Despite this, there is limited community-based research on psychiatric disorders and personality traits among patients with Wegener's disease.

Objective: This study aimed to investigate the prevalence of psychiatric disorders and examine the predictive role of personality traits among patients with Wegener's disease.

Methods: A total of 100 patients met the inclusion and exclusion criteria, and all of them were selected to participate in the study. Out of them, 75 individuals completed the questionnaires. The instruments included the SCL-90 questionnaire and the NEO Big Five personality traits. The data were analysed using Stata software, and the prevalence of psychiatric disorders in different patient groups was determined using the chi-square method. The predictive role of personality traits in mental disorders was examined using multivariate regression.

Results: The results revealed that paranoia (53.3%) and depression (44%) had the highest prevalence in terms of psychiatric disorders, while psychosis (17.3%) and hostility (25.33%) had the lowest prevalence. Additionally, the findings demonstrated a positive correlation between most psychiatric disorders and the neuroticism personality trait.

Conclusion: Given the influence of mental disorders on the immune system in Wegener's disease, it is essential to provide psychological care for these patients.