Detection Of Mental Health Problems Research Articles

Implementasi Manajemen Konseling Kesehatan Mental bagi Mahasiswa Institut Teknologi dan Kesehatan Muhammadiyah Kalimantan Barat

Undergraduate students are individuals who experience a transition period that focuses on searching for self-identity. During this transition period, students will experience changes in their behavior, emotions and cognition. This change will affect the mental health status of students. Mental health problems in students are a serious problem to be handled because students' mental health problems are invisible but can have bad consequences if not treated immediately. Negative stigma towards mental health has an impact on students' awareness and initiative to resolve their mental health problems. Students feel embarrassed and think that this mental health problem can heal by itself. In fact, mental health problems will get worse if they are not handled well. The importance of mental health counseling services for students as a medium for early detection of mental health problems. Mental health screening can detect several mental health problems so that existing problems can be prevented and students' mental health status can improve. The role of the academic community is very important to support the existence of mental health counseling services. Moreover, policies and service standards do not yet exist at ITEKES Muhammadiyah West Kalimantan. Thus, this underlies strategic planning activities for mental health services that can be beneficial for students and have an impact on student welfare in maintaining their mental status.

Anxiety and depression symptoms in adolescents and young adults with juvenile idiopathic arthritis: results of an outpatient screening

BackgroundPrevious studies have shown that growing up with rheumatic conditions can fuel dissatisfaction and psychological distress, which in turn affects disease self-management and treatment adherence. Primary objective of this study was to estimate the prevalence of anxiety and depression symptoms in adolescents and young adults (AYA) with juvenile idiopathic arthritis (JIA) and to identify correlates of conspicuous screening results.MethodsInitiated as part of the COACH multicenter observational study, outpatients aged 12 to 21 years participating in the National Pediatric Rheumatological Database (NPRD) were prospectively screened for mental health using the Patient Health Questionnaire-9 (PHQ-9) and the Generalised Anxiety Disorder Scale-7 (GAD-7).ResultsData from 1,150 adolescents with JIA (mean age 15.6 ± 2.2 years; mean disease duration 7.2 ± 4.9 years, 69% female, 43% oligoarthritis, 26% polyarthritis) were analysed. Overall, 32.7% (n = 316) of AYA showed conspicuous screening results, of whom 30.4% reported clinically relevant suicidal or self-harm thoughts. About 19% of screened patients showed moderate to severe depressive or anxious symptoms. AYA with conspicuous screening results were older (15.8 vs. 15.2 years; p < 0.0001), more often female (81% vs. 64%; p < 0.0001) and more often overweight (25% vs. 17%; p = 0.006). They had higher disease activity (physician global assessment on NRS 0–10; 1.7 vs. 1.2; p < 0.0001), more functional limitations (CHAQ; 0.44 vs. 0.14; <0.0001) and rated their health status worse (NRS 0–10; 3.5 vs. 1.8; p < 0.0001) than AYA with inconspicuous screening results. Females (OR 2.33 [CI 1.53–3.56]; p < 0.0001), older age (OR 1.09 [CI 1.01–1.18]; p = 0.026), patients with more functional limitations (OR 3.36 [CI 1.98–5.72]; p < 0.0001), and patients with worse subjective health status (OR 1.17 [CI 1.07–1.27]; p < 0.0001) were more likely to have a conspicuous screening result. Regular sports participation was associated with a lower likelihood of conspicuous screening result (OR 0.69 [CI 0.49–0.98]; p = 0.039).ConclusionsA large-scale outpatient screening of AYA with JIA in Germany shows a high prevalence of anxiety and depression symptoms. The need for routine screening for early detection of mental health problems became apparent.

Detection and addressing of psychosocial issues in schools: an intersectoral approach for the Colombian Amazon

ABSTRACT Schools are scenarios for detection of mental problems and promotion of well-being. It is necessary to create intercultural processes that better respond to these needs. The objective of the present study was to collaboratively construct a route for the detection of mental health problems from the school environment from the Colombian Amazon. Nine focus groups were carried out, each made up of nine people, health professionals and ethnoeducators. The strengthening of one’s own culture is highlighted, such as the use of fishing and agriculture. The starting point of this process is the development of a pathway that defines roles to play in the support of specific cases of school mental health care with an ethnic focus. Intercultural school mental health calls for strengthening one’s own culture as a protective factor for mental health, which involves understanding aspects of the culture by those working with children and youth in the region.

Investigating machine learning and natural language processing techniques applied for detecting eating disorders: a systematic literature review.

Recent developments in the fields of natural language processing (NLP) and machine learning (ML) have shown significant improvements in automatic text processing. At the same time, the expression of human language plays a central role in the detection of mental health problems. Whereas spoken language is implicitly assessed during interviews with patients, written language can also provide interesting insights to clinical professionals. Existing work in the field often investigates mental health problems such as depression or anxiety. However, there is also work investigating how the diagnostics of eating disorders can benefit from these novel technologies. In this paper, we present a systematic overview of the latest research in this field. Our investigation encompasses four key areas: (a) an analysis of the metadata from published papers, (b) an examination of the sizes and specific topics of the datasets employed, (c) a review of the application of machine learning techniques in detecting eating disorders from text, and finally (d) an evaluation of the models used, focusing on their performance, limitations, and the potential risks associated with current methodologies.

Early Detection of Mental Health Problems in the Family: A Case Study of PRA Tirtonirmolo Selatan Bantul Yogyakarta

Abstract. The globalization era has entered the industrial revolution 4.0 which encourages increased connectivity, interaction, and optimal use of communication technology in human life. This development has the potential to empower individuals and communities as it can create new opportunities in economic, social, and personal development. However, this trend is also accompanied by a significant increase in the number of mental disorders. This problem is felt by PRA of Tirtonirmolo Selatan, where people in the neighborhood tend to be ignorant and unconcerned about mental health symptoms that are actually already owned by several people around them. Awareness of the importance of mental health only emerged when there was a case of murder of one of its cadres by his own family members who experienced mental disorders. To anticipate the potential threat of mental disorders in the future, it is necessary to explore how the community in the Tirtonirmolo Selatan neighborhood understands mental health and what efforts to increase community awareness about potential mental health problems. The approach used was to conduct promotion and prevention aimed at cadres and members of PRA Aisyiyah as the driving force for early detection. The result was that there were misconceptions and negative perspectives about mental health. After raising awareness about mental health, an early detection movement for symptoms of mental health problems was carried out through the formation of an information cluster on mental health problems involving PRA of Tirtonirmolo Selatan cadres.

Assessed and self-perceived unmet needs for mental health care in the general population in Antwerp

Introduction: A public mental health care approach requires knowledge about which proportion of the population needs mental health care, and which people need it but don’t seek or receive it and why.&#x0D; Who is it for? We investigated (unmet) needs for mental health care in the general population to optimize the distribution of mental health care services, which benefits all Antwerp citizens who need mental health care.&#x0D; Involvement and engagement: Important stakeholders who were involved are the (Antwerp) psychiatric hospitals, who funded the research and were involved in the design of the study and interpretation of results. The involvement and engagement of (ex) patients in mental health care was limited, but a pilot test of the survey was conducted with this group.&#x0D; Method: A representative sample was invited in 2021 to participate in a population survey about mental wellbeing and mental health care use in Antwerp. A total of 1208 individuals aged 15 – 80 years old participated. We investigated unmet needs for mental health care using a normative approach (assessed mental health problems) and subjective approach (self-perceived mental health problems)&#x0D; Results: A total of 10.4% of the sample was defined as having a need for mental health care but only half of them used health care for their mental health, resulting in a population prevalence of 5.5% clinically assessed unmet mental health needs. Among all people who did not use mental health care, 12.1% perceived a mental health need (fully unmet), and 23.3% of mental health care users perceived the care as insufficient (partially unmet), leading to a total population prevalence of 14.0% perceived unmet needs. However, more women and younger people perceived unmet needs, while clinically assessed unmet needs were higher among men and older people.&#x0D; Learning: Estimates of met and unmet mental health needs are complex given the diversity of operationalizations of different levels of need, and can only be established by a dialectic of individual and populational perspectives. Assessed and perceived (unmet) mental health needs are both relevant and complementary but are related to different factors. Nonetheless, a general conclusion is that the prevalence of unmet mental health needs is high. Some vulnerable groups should be targeted for detection of mental health problems and interventions, for example through outreaching care.&#x0D; Next steps: Further research should explore how assessed and perceived needs interact, and how this is predictive of help seeking and mental health outcomes.

Penyuluhan Kesehatan Jiwa Untuk Meningkatkan Pengetahuan Masyarakat Tentang Masalah Kesehatan Jiwa di Lingkungan Sekitar

Mental health is a condition where an individual can develop physically, mentally, spiritually and socially so that the individual is aware of their abilities, can deal with pressure, can work productively, and is able to contribute to their community. Conditions of inappropriate development in individuals are called mental disorders. Mental health education is an effort to influence or invite other people, whether individuals, groups or communities, to adopt healthy behavior. Community capacity can be improved through health education, especially early detection of mental health problems. The aim of this activity is to increase knowledge and insight and sources of information for mystery students about mental health. It is also hoped that the results of this service will be useful as input for increasing the standard achievement of promotional efforts provided to the community. The methods used are lectures, discussions, simulations and role plays. The number of participants in this activity was 15 people at the Maccini Sawah Community Health Center. The results show that the pre-test activity results in the good knowledge category are 2 people (13.33%) and less than 13 people (86.67%), then the post test results with good knowledge are 14 people (93.33%) and less than 1 person ( 6.67%). This shows that there has been an increase in knowledge in the community and changed the negative stigma towards clients with mental disorders.

Detecting signs of mental health problems in secondary school-aged youth

Objective: The study purpose was to describe secondary school nurses’, subject teachers’, special needs teachers’, study counselors’ and school social workers’ (n = 60) experiences of stressors that contribute to the development of mental health problems in secondary school pupils. Another purpose was to describe the professionals’ educational needs regarding mental health problems of secondary school pupils. The study aimed at producing information that can promote the detection of mental health problems and facilitate early interventions in secondary schools. The information collected came from the professionals only, not from the pupils or their parents.Methods: Data were collected in Finland using a Webropol online survey and analyzed by inductive content analysis.Results: According to the results, secondary school pupils’ mental health problems are associated with physical and psychosocial stressors, and with stressors pertaining to learning and studying, lifestyle, family, friend relationships and socioeconomic factors. In addition, the pupils’ mental health problems are associated with stressors pertaining to social media. Professionals working at secondary schools need education on how to identify pupils’ mental health problems, how to take up the concern with the pupil and parents, and how to support and counsel youth with a mental health problem.Conclusions: Although information packages, recommendations, materials and tools are available, encouragement and more specific and concrete mental health education for both pupils and professionals is required. New structures and practices, and possibly re-allocation of resources, may be necessary. The teachers’ role in mental health promotion and prevention of mental health problems should be supported and resourced more effectively. Psychiatric nurses should be employed at schools.

Prevalence of Depression, Anxiety, and Stress Among Medical Students before their Final Examinations at a Private Medical College of Tamil Nadu, India: A Cross-sectional Study

Introduction: Due to their susceptibility to mental health problems, medical students should have their prevalence of stress, anxiety, and depression checked before their final examinations. Aim: To assess the prevalence of stress, anxiety, and depression among medical students at a private medical college in Tamil Nadu, India, four weeks before their final examinations. Materials and Methods: A cross-sectional study was conducted at a private medical college, Tamil Nadu, India, including 297 Bachelor of Medicine and Bachelor of Surgery (MBBS) students, using Depression, Anxiety, and Stress Scale-21 (DASS-21) questionnaire in December 2022 The survey was completed independently by the students with verbal agreement obtained; the response rate was 68.2%. The short form and history of usage of the DASS-21 in comparable medical student research led to its selection. Results: The mean age of the study participants was 20.48±1.23 years. The DASS-21 revealed prevalence rates of 60.9% for depression, 72.7% for anxiety, and 40.4% for stress among 297 first- to third-year medical students. There was no discernible effect of gender on these rates. With a depression frequency of 69% and significantly higher rates of severe depression (18.6%), first-year students demonstrated the highest scores, which were statistically significant (p&lt;0.05). Conclusion: The study highlights the need for preventative actions, such as professional counselling, early detection of mental health problems, and educational programs on healthy coping mechanisms. To support medical students from the start of their academic journey and ultimately promote their resilience and mental health, these interventions should be specially designed.

Development of a Mobile Application for Detection of Adolescent Mental Health Problems and Feasibility Assessment with Primary Health Care Workers

Introduction: There has been a sharp increase in the use of digital health interventions in global health, particularly mobile health applications, in recent years. The extreme shortage of health care providers trained in mental health screening and intervention in low- and middle-income countries raises questions about the applicability of mobile applications to deliver these services due to their accessibility and availability. This exploratory paper describes the development and feasibility assessment of a mobile screening application for the detection of mental disorders among adolescents in Zambia and South Africa. Methods: Eighty-two health care workers (HCW) working in primary care evaluated the acceptability and practicality of the mobile screening application after receiving brief training. The evaluation included questions from the Mobile Application Rating Scale (MARS) as well as open-ended questions. Results: The acceptability of the screening app was high and study participants were positive about using the app in routine care. Problems with internet connectivity, and time and staff constraints were perceived as the main barriers to regular use. Conclusion: HCW in primary care were able and willing to use a mobile screening app for the detection of mental health problems among treatment-seeking adolescents. Implementation in clinical practice needs to be further evaluated.

Dialogue Based Early Detection-Development of a Novel Approach for Detection of Mental Health Problems Among Children in Daycare Centers.

BackgroundAmong 1–7 years old children the worldwide prevalence of mental disorders is ~20%. Without treatment, the prognosis of such disorders in children is poor. Early intervention is estimated to result in a positive return. However, traditional screening to detect children at need is particularly challenging due to the concerns by false positives. The aim of the current study was to develop a more acceptable though effective method using the existing annual evaluation meetings between parents and teachers in a more systematic and goal directed way. The method should build on the teacher's and parents' complementary knowledge and perception of the child, and fit into the everyday routines in daycare centers.MethodDuring a period of 6 years, a developmental process aiming for a novel screening method was carried out in cooperation with eight Norwegian daycare centers. After conception of the idea, the framework of the Dialogue Based Early Detection including the first version of the Early Worry Questionnaire (EWQ) was constructed. An iterative process involving parents and teachers completing workshops and subsequent testing facilitated a re-modeling of the method.ResultsIn the resulting Dialogue Based Early Detection a 36-item version of EWQ was completed by both parents and teachers ahead of the annual parent-teacher meeting. During that meeting the participants should try to reach a consensus whether there was a concern, some uncertainty, or no worry for the child, and which appropriate actions should be taken for a possible follow up. Both parents and teachers reported that the EWQ supported them in verbalizing already existing worries for the child. Teachers reported that parents were better prepared and participated more actively in the evaluation meetings. However, some parents complained that there was too much focus on possible worries. During the testing, challenges of language development, conduct, emotional reactions, toileting, attention, and eating were detected among the children.ConclusionThe Dialogue Based Early Detection method was endorsed by both teachers and parents and holds promise as a tool for improving early awareness and identification of developmental and mental health problems of preschool children in daycare centers.

Early Detection of Mental Health Problems Health Personnel During Covid-19 Pandemic

The determination of the pandemic condition by WHO has caused various public responses and psychosocial problems. This research is important because the spread of the virus is very fast, widespread and mass causes cases to increase and have an impact not only on physical but also psychological conditions, causing mental health problems. Various efforts have been made by the government to combat the epidemic, community participation involving individuals, families and community groups is urgently needed to solve this problem. The purpose of this study was to identify mental health problems experienced by health workers due to the COVID-19 pandemic and to develop a model for early detection of mental health problems. This research method uses a quantitative approach with three stages of research. The first research stage is the exploration of mental health problems experienced by health workers. The second stage is developing a model for early detection of mental health problems and providing mental health and psychosocial support. The third stage is the use of early detection models in handling mental health problems for health workers. The method of data collection was carried out using a Self-Reporting Questionnaire (SRQ) questionnaire and the implementation of Habit Adaptation met the criteria. The sample was taken using purposive sampling technique. Data was obtained using a questionnaire and analized by the paired t test. The results showed that there was a difference between pre-test and post-test, meaning that that interventions are effective in addressing physical and psychosocial health problems.

A scoping review on monitoring mental health using smart wearable devices.

With the continuous development of the times, social competition is becoming increasingly fierce, people are facing enormous pressure and mental health problems have become common. Long-term and persistent mental health problems can lead to severe mental disorders and even death in individuals. The real-time and accurate prediction of individual mental health has become an effective method to prevent the occurrence of mental health disorders. In recent years, smart wearable devices have been widely used for monitoring mental health and have played an important role. This paper provides a comprehensive review of the application fields, application mechanisms, common signals, common techniques and results of smart wearable devices for the detection of mental health problems, aiming to achieve more efficient and accurate prediction for individual mental health, and to achieve early identification, early prevention and early intervention to provide a reference for improving the level of individual mental health.

PRESCHOOL EDUCATORS’ VIEWS ON SUPPORTING CHILDREN WITH MENTAL HEALTH ISSUES IN EARLY CHILDHOOD EDUCATION

Schools are considered the ideal place to provide mental health services. International literature highlights the importance of early detection of mental health problems and the implementation of preventive interventions in school context. The present study aims to explore preschool teachers’ views regarding the involvement of the school in the prevention and treatment of students' mental health problems in preschool education and the ways in which the school can assist in supporting students. The sample of the research consisted of 115 preschool teachers. The method of data collection was a questionnaire. The results of the research showed that the majority of teachers believe that the school should be involved in the prevention and treatment of children's mental health problems. In addition, they defined the characteristics of mental health in preschool children. Simultaneously, they argue that enhancing a child's self-confidence, developing positive interpersonal relationships between teachers and students and collaborative relationships with parents are the main ways in which the school can support students with mental health problems. Research findings could be utilized in designing mental health promotion interventions.&#x0D; &#x0D; &lt;p&gt; &lt;/p&gt;&lt;p&gt;&lt;strong&gt; Article visualizations:&lt;/strong&gt;&lt;/p&gt;&lt;p&gt;&lt;img src="/-counters-/edu_01/0775/a.php" alt="Hit counter" /&gt;&lt;/p&gt;

Nurses' post-traumatic stress symptoms and growth by perceived workplace bullying: An online cross-sectional study.

The aim of this study was to explore the relationship between workplace bullying and mental health, focusing on the indirect effect of post-traumatic stress responses and moderation of nurses' perception of workplace bullying. Post-traumatic stress symptoms frequently result from workplace bullying, but how nurses' individual appraisals relate to negative consequences is unclear. A cross-sectional online survey was conducted with 319 Korean nurses; participants were divided into the perceived and non-perceived workplace bullying groups. Moderated mediation models were tested using structural equation modelling with Stata version 16. Regardless of nurses' appraisals, higher levels of workplace bullying were associated with poor mental health. Post-traumatic stress symptoms indirectly impacted the relationship in both groups, but post-traumatic growth did not. The perceived group showed a partial negative association between post-traumatic growth and mental health. It is necessary to develop systems for early detection of mental health problems to create safe work environments not only for nurses who perceive workplace bullying but also for those who do not. Staff education and institutional support that consider PTSS are recommended for all nurses.

Development an app for monitoring stress level and early detection of mental disorders in Indonesia

Abstract Background Stress may contribute to physical and mental health problems. The number of people with mental-emotional disorders has reached up to be 19 million people in Indonesia in 2018. Monitoring stress levels and early detection are important to prevent serious mental health problems. Therefore, we are developing De-stres©, a mobile app for monitoring the stress level and early detection of mental health disorders in Bahasa Indonesia. Methods De-stres© was developed for android OS and web-based app by using the web2py framework and PostgreSQL database. The app used the PSS-10 and Beck Depression-II questionnaires that were available in Bahasa Indonesia. It had six main functions: creating an account, approving the informed consent, filling the questionnaire, generating test results automatically, advice from psychologists based on the test result and saving test history. Results A month since its launch, the six functions test ran well on the Android OS and the website. A preliminary result showed that the app was downloaded more than 100 times from Google Playstore. Among the 420 data records, 71.6% (301) app users were students, with 60.7% (255) using the app to measure only stress level, 25.5% (107) resulting in severe stress and 4% (17) severe depression. Conclusions De-stres© is successfully developed and a promising instrument that can be implemented for Indonesia, by providing preliminary self-administered questionnaire. Key messages De-stres© is an app for monitoring stress levels and early detection of mental health problems and successfully developed with preliminary self-administered questionnaires in Bahasa Indonesia. De-stres© is a promising app that can be implemented for preventing serious mental health disorders in Indonesia.

Research on the Identification of College Students’ Mental Health Problems Based on Campus Big Data

In recent years, according to the survey, college students have frequent mental health problems, such as anxiety, depression, inferiority, inter-personal sensitivity and other psychological problems, even the idea of suicide. It has a very serious negative impact on the family and society. If mental health problems of college students can be detected early, counselors can pay more attention to these high-risk students. At the same time, the high-risk students can receive therapies as soon as possible, reducing the harm. Therefore, it is crucial to find an effective method for early detection of mental health problems. This paper proposes a new method to detect mental health problems by analyzing students ’behavior on campus. The datasets include Internet access logs, records of entering and leaving dormitories, and records of consumption in canteens. We built classification models for differentiating the mental health problems of students from normal students. The experimental results show that the proposed method may be useful to improve the performance of public mental health services.

Suicidal ideation and suicide attempt in a clinical sample of Mexican naval military

Introduction. Suicide represents the sixteenth cause of death worldwide. Until a few years ago the suicide rate in the US military has been below that of the civilian population, but in 2008 the suicide rate among US soldiers began to outpace the civilian population. To our knowledge, there are no studies that describe suicidal behavior among Mexican military personnel. Objective. To know the frequency of suicidal ideation and suicide attempt in the last 12 months in Mexican naval military and determine the variables associated with both ideation and suicide attempt. Method. This cross-sectional study included 246 outpatients who were sent for psychiatric assessment from their operating units. A psychiatric interview was conducted using the diagnostic criteria of the International Classification of Diseases in its tenth edition, which included the presentation of suicidal ideation and attempted suicide in the last 12 months. Results. Suicidal ideation in the last 12 months occurred in 60 cases (24.39%). Twenty-four cases (9.76%) presented a suicide attempt in the last 12 months. Variables associated with suicidal ideation were military grade (seaman and classes, p = .03), suicide family history (p &lt; .01), depressive disorders (p &lt; .01), and personality disorders (p &lt; .01). Regarding the presentation of attempted suicide, the mean age in the cases was lower (p &lt; .01). There was also a higher frequency of attempted suicide in singles or without a couple (p &lt; .01), in personnel with four years or less in service (p &lt; .01), and in patients with a personality disorder (p &lt; .01). Discussion and conclusion. Greater emphasis in the detection of mental health problems, including suicidality among the military population and more representative studies at the national level are needed.

Application of Machine Learning Methods in Mental Health Detection: A Systematic Review

This paper presents a critical assessment analysis on mental health detection in Online Social Networks (OSNs) based on the data sources, machine learning techniques, and feature extraction method. The appropriateness of the mental health detection was also investigated by identifying its data analysis method, comparison, challenges, and limitations. This study reviewed articles published in major databases between 2007 and 2018 through keyword searches. The articles were screened base on their titles and abstracts before the full texts were reviewed. The articles were coded in accordance with data set (e.g., data sources, keywords, and geographical locations), method of data analysis, machine learning or deep learning technique, classifier performance, and feature extraction method. 22 articles were selected for review from the total of 2770. As OSNs exhibit high potential as a data source in early detection of mental health problems, most researchers used text analysis on a new data set extracted from different OSNs sources. The extracted data were examined using a statistical analysis or machine learning techniques. Several studies also applied multimethod techniques, which included distributing questionnaires while requesting for the respondents’ consent to later access and extract information from his/her OSNs account. Big data in OSNs contribute on mental health problem detection. The presented method is an alternative approach to the early detection of mental health problems rather than using traditional strategies, such as collecting data through questionnaires or devices and sensors, which are time-consuming and costly. However, mental health problem detection through OSNs necessitates a comprehensive adoption, innovative algorithms, and computational linguistics to describe its limitations and challenges. Moreover, referrals from mental health specialists as subject matter experts are also required to help obtain accurate and effective information.

Retrospective cohort study of compliance with post-deployment screening in the Canadian Armed Forces

ObjectiveCanadian Armed Forces (CAF) personnel who return from certain international deployments are required to complete post-deployment screening (PDS) 90 to 180 days post-deployment; the primary goal of PDS is early...