scholarly journals Heterogeneous Network Approach to Predict Individuals’ Mental Health

2021 ◽  
Vol 15 (2) ◽  
pp. 1-26
Author(s):  
Shikang Liu ◽  
Fatemeh Vahedian ◽  
David Hachen ◽  
Omar Lizardo ◽  
Christian Poellabauer ◽  
...  
Keyword(s):  
Mental Health ◽  
Logistic Regression ◽  
Health Conditions ◽  
Depression And Anxiety ◽  
Health States ◽  
Mental Health Conditions ◽  
Health Related ◽  
Types Of Information ◽  
The University ◽  
Critical Public Health

Depression and anxiety are critical public health issues affecting millions of people around the world. To identify individuals who are vulnerable to depression and anxiety, predictive models have been built that typically utilize data from one source. Unlike these traditional models, in this study, we leverage a rich heterogeneous dataset from the University of Notre Dame’s NetHealth study that collected individuals’ (student participants’) social interaction data via smartphones, health-related behavioral data via wearables (Fitbit), and trait data from surveys. To integrate the different types of information, we model the NetHealth data as a heterogeneous information network (HIN). Then, we redefine the problem of predicting individuals’ mental health conditions (depression or anxiety) in a novel manner, as applying to our HIN a popular paradigm of a recommender system (RS), which is typically used to predict the preference that a person would give to an item (e.g., a movie or book). In our case, the items are the individuals’ different mental health states. We evaluate four state-of-the-art RS approaches. Also, we model the prediction of individuals’ mental health as another problem type—that of node classification (NC) in our HIN, evaluating in the process four node features under logistic regression as a proof-of-concept classifier. We find that our RS and NC network methods produce more accurate predictions than a logistic regression model using the same NetHealth data in the traditional non-network fashion as well as a random-approach. Also, we find that the best of the considered RS approaches outperforms all considered NC approaches. This is the first study to integrate smartphone, wearable sensor, and survey data in a HIN manner and use RS or NC on the HIN to predict individuals’ mental health conditions.

scholarly journals Mental Health Conditions Among Struggling GME Learners: Results From a Single Center Remediation Program

2020 ◽  
Vol 12 (6) ◽  
pp. 773-777
Author(s):  
Karen M. Warburton ◽  
Amit A. Shahane
Keyword(s):  
Mental Health ◽  
Clinical Performance ◽  
Adjustment Disorder ◽  
Descriptive Statistics ◽  
Health Conditions ◽  
University Of Virginia ◽  
Single Center ◽  
Struggling Learners ◽  
Mental Health Conditions ◽  
The University

ABSTRACT Background Graduate medical education (GME) learners may struggle with clinical performance during training. A subset of these trainees has mental health conditions (MHCs). Objective To characterize the MHCs that underlie poor trainee performance and their relationship to specific clinical performance deficit (CPD). Methods At the University of Virginia (UVA), GME learners not meeting appropriate milestones, or who request help, have the option to self-refer or be referred to COACH (Committee on Achieving Competence Through Help). A physician remediation expert assesses the learner and identifies a primary CPD. If there is concern for an MHC, referral is made to a psychologist with expertise in working with trainees. All learners are offered remediation for the CPD. Using descriptive statistics, we tracked the prevalence of MHC and their correlation with specific CPDs. Results Between 2016 and 2019, COACH assessed 7% (61 of 820) of GME learners at UVA. Thirty-eight percent (23 of 61) had an MHC associated with the CPD. Anxiety was the most common MHC (48%), followed by depression (17%), cognitive dysfunction (17%), adjustment disorder (13%), and other (4%). Professionalism was the most identified CPD among learners with MHCs (52%). Of remediated learners, 47% have successfully finished remediation, 21% were terminated or voluntarily left their program, and 32% are still being remediated (83% of whom are in good standing). Conclusions MHCs were identified in nearly 40% of struggling learners referred to a centralized remediation program. Professionalism is the most identified CPD among learners with MHCs.

scholarly journals Addressing the Needs of Academic Staff in Supporting Students with Mental Health Conditions in Online Programmes at a Distributed University

2015 ◽  
Vol 3 (1) ◽  
Author(s):  
Rachel Stephanie Erskine ◽  
Eilidh MacPhail
Keyword(s):  
Mental Health ◽  
Policy Development ◽  
Online Teaching ◽  
Academic Staff ◽  
Health Conditions ◽  
Teaching Staff ◽  
Face To Face ◽  
Mental Health Conditions ◽  
Time Of Application ◽  
The University

Professional experience prompted the initial discussions of the need to identify increased research and further support for academic staff in teaching online with students who have mental health conditions whether these are disclosed or not at the time of application to a distributed university. With the prevalence of mental health conditions increasing in the general population, it stands to reason that increasing numbers of students with mental health conditions are entering higher education. Studying online is different than being in a face-to-face environment and online teaching staff need to have additional skills to be able to individualise their teaching to cater for their students as well as be able to support those with mental health conditions. It is proposed that research among programme leaders, module leaders and personal academic tutors within the University of the Highlands & Islands is undertaken to contribute the academic perspective to supportive policy development within the University for this group of students.

Food insecurity and mental health outcomes among homeless adults: a scoping review

2020 ◽  
pp. 1-12 ◽  
Author(s):  
Elizabeth I Loftus ◽  
James Lachaud ◽  
Stephen W Hwang ◽  
Cilia Mejia-Lancheros
Keyword(s):  
Mental Health ◽  
Food Security ◽  
Food Insecurity ◽  
Scoping Review ◽  
Health Conditions ◽  
Homeless Adults ◽  
Mental Health Conditions ◽  
Household Food ◽  
Potential Association ◽  
Health Related

Abstract Objective: This review summarises and synthesises the existing literature on the relationship between food insecurity (FS) and mental health conditions among adult individuals experiencing homelessness. Design: Scoping review. Papers published between 1 January 2008 and 2 November 2018, searched in PubMed, Web of Science, Scopus, PsycINFO, Cochrane Library and CINAHL, using homelessness, food security and mental health keywords. Setting: Global evidence. Participants: Homeless adults aged 18 years or more. Results: Nine articles (eight cross-sectional and one longitudinal) were included in the present review. FS was measured using the Household Food Insecurity Access Scale, the United States Department of Agriculture Household Food Security Survey Module, as well as single-item or constructed measures. Depression and depressive symptoms were the most common mental health conditions studied. Other mental health conditions assessed included alcohol and substance use, emotional disorders, mental health problems symptoms severity and psychiatric hospitalisations. Composite measures such as axis I and II categories and a cluster of severe mental conditions and mental health-related functioning status were also analysed. FS and mental health-related problems were considered as both exposure and outcome variables. The existing evidence suggests a potential association between FS and several mental health conditions, particularly depression, mental health symptoms severity and poor mental health status scores. Conclusions: This review suggests the potential association between some mental health conditions and FS among homeless adults. However, there is a need for more longitudinal- and interventional-based studies, in order to understand the nature and directionality of the links between FS and mental health in this population group.

scholarly journals Keep Calm and Study Abroad: The Effect of Learning Abroad on Student Mental Health

2016 ◽  
Vol 27 (1) ◽  
pp. 1-16 ◽  
Author(s):  
Amber Bathke ◽  
Yang-Hyang (Ryoka) Kim
Keyword(s):  
Mental Health ◽  
Study Abroad ◽  
International Education ◽  
Online Survey ◽  
Health Condition ◽  
Support Network ◽  
Health Conditions ◽  
Student Mental Health ◽  
Mental Health Conditions ◽  
The University

This research set out to discover whether statistics would support the belief in the international education field that the stress of going abroad (adjusting to a new culture, missing home, being away from support network, etc.) can trigger mental health conditions in students participating in learning abroad programs. The study sought to glean on overall picture of student mental health abroad, as well as determine the percentage of students studying abroad who reported experiencing a diagnosed mental health condition while abroad, the nature of these diagnosed mental health conditions, the frequency of relapse/recurrence of existing conditions while abroad, the frequency and type of treatment received, and local attitude toward mental health conditions. The research was conducted by means of an online survey administered by the University of Minnesota’s Office of Measurement Services, which was sent by email to people who had participated in study abroad through the University of Minnesota’s Learning Abroad Center between Summer 2009 and Spring 2012, a total of 7,191 students. As the Learning Abroad Center, while serving University of Minnesota students first and foremost, also acts as a program provider recruiting students nationally, the participants’ home institutions were likely dozens of universities nationwide (though home institution information was not collected). We received 613 responses for a response rate of 8.52%. The data from the survey suggest, surprisingly, that in general, student mental health actually improves while abroad, an in fact, that skills learned during an international experience may contribute to improved mental health upon return.

scholarly journals Trajectories of depressive symptoms among vulnerable groups in the UK during the COVID-19 pandemic

2020 ◽  
Author(s):  
Philipp Frank ◽  
Eleonora Iob ◽  
Andrew Steptoe ◽  
Daisy Fancourt
Keyword(s):  
Mental Health ◽  
Social Support ◽  
Depressive Symptoms ◽  
Human Condition ◽  
Health Conditions ◽  
Vulnerable Groups ◽  
Mental Health Conditions ◽  
Growth Mixture Modelling ◽  
Health Related ◽  
The Uk

ABSTRACTObjectiveThe coronavirus disease 2019 (COVID-19) pandemic has affected many aspects of the human condition, including mental health and psychological wellbeing. This study examined trajectories of depressive symptoms (DST) over time among vulnerable individuals in the UK during the COVID-19 pandemic.MethodsThe sample consisted of 51,417 adults recruited from the COVID-19 Social Study. Depressive symptoms were measured on seven occasions (21st March - 2nd April), using the Patient Health Questionnaire (PHQ-9). Sociodemographic vulnerabilities included non-white ethnic background, low socio-economic position (SEP), and type of work (keyworker versus no keyworker). Health-related and psychosocial vulnerabilities included pre-existing physical and mental health conditions, experience of psychological and/or physical abuse, and low social support. Group-based DST were derived using latent growth mixture modelling and multivariate logistic regression models were fitted to examine the association between these vulnerabilities and DSTs. Model estimates were adjusted for age, sex, and suspected COVID-19 diagnosis.ResultsThree DSTs were identified: low [N=30,850 (60%)] moderate [N=14,911 (29%)], and severe [N=5,656 (11%)] depressive symptoms. DSTs were relatively stable across the first 6 weeks of lockdown. After adjusting for covariates, experiences of physical/psychological abuse (OR 13.16, 95% CI 12.95-13.37), pre-existing mental health conditions (OR 13.00 95% CI 12.87-13.109), pre-existing physical health conditions (OR 3.41, 95% CI 3.29-3.54), low social support (OR 12.72, 95% CI 12.57-12.86), and low SEP (OR 5.22, 95% CI 5.08-5.36) were significantly associated with the severe DST. No significant association was found for ethnicity (OR 1.07, 95% 0.85-1.28). Participants with key worker roles were less likely to experience severe depressive symptoms (OR 0.66, 95% 0.53-0.80). Similar but smaller patterns of associations were found for the moderate DST.ConclusionsPeople with psychosocial and health-related risk factors, as well as those with low SEP seem to be most vulnerable to experiencing moderate or severe depressive symptoms during the COVID-19 pandemic.

scholarly journals Association of Depression and Anxiety with Social Network Types: Results from a Community Cohort Study

2021 ◽  
Vol 18 (11) ◽  
pp. 6120
Author(s):  
Saju Madavanakadu Devassy ◽  
Lorane Scaria ◽  
Natania Cheguvera ◽  
Kiran Thampi
Keyword(s):  
Mental Health ◽  
Social Networks ◽  
Social Network ◽  
Assessment Tools ◽  
Health Conditions ◽  
Depression And Anxiety ◽  
Lower Odds ◽  
Mental Health Conditions ◽  
Catchment Areas ◽  
Network Type

Social networks protect individuals from mental health conditions of depression and anxiety. The association between each social network type and its mental health implications in the Indian population remains unclear. The study aims to determine the association of depression and anxiety with different social network types in the participants of a community cohort. We conducted a cross-sectional household survey among people aged ≥30 years in geographically defined catchment areas of Kerala, India. We used cross-culturally validated assessment tools to measure depression, anxiety and social networks. An educated male belonging to higher income quartiles, without any disability, within a family dependent network has lower odds of depression and anxiety. Furthermore, 28, 26.8, 25.7, 9.8 and 9.7% of participants belonged to private restricted, locally integrated, wider community-focused, family-dependent and locally self-contained networks, respectively. Close ties with family, neighbours, and community had significantly lower odds of anxiety and depression than private restricted networks. The clustering of people to each social network type and its associated mental health conditions can inform social network-based public health interventions to optimize positive health outcomes in the community cohort.

scholarly journals Functional assessments in the UK social security system: the experiences of claimants with mental health conditions

2020 ◽  
pp. 1-18
Author(s):  
KATIE PYBUS ◽  
KATE. E. PICKETT ◽  
CHARLIE LLOYD ◽  
STEPHANIE PRADY ◽  
EMERITUS RICHARD WILKINSON
Keyword(s):  
Mental Health ◽  
Common Mental Disorders ◽  
Academic Research ◽  
Health Condition ◽  
Assessment Process ◽  
Health Conditions ◽  
Mental Health Conditions ◽  
Functional Assessments ◽  
Health Related ◽  
The Impact

Abstract Eligibility for health-related income benefits in the United Kingdom is now determined through the use of functional assessments conducted by healthcare professionals. Claimant satisfaction with both Personal Independence Payment (PIP) and Work Capability Assessments (WCA) has been mixed and concerns have been raised that mental health conditions are not well-understood in this context, but academic research has so far been limited. Individuals with a range of common mental disorders and severe mental illness were interviewed (n=18) about their experiences of undergoing eligibility assessments for health-related income benefits. Data were analysed using a thematic analysis approach. Eleven out of the 18 participants had been turned down for one or more income benefits and successful claims were more likely where supported by health and care professionals. Eligibility assessments were overwhelmingly perceived as focusing on physical health with limited scope to explore the impact of mental health on functioning. Evidence from this and other studies suggests that improvements are needed to the eligibility assessment process for all claimants but particularly those with a mental health condition.

Virtual Reality for Supporting Depression and Anxiety: A Scoping Review (Preprint)

2021 ◽  
Author(s):  
Nilufar Baghaei ◽  
Vibhav Chitale ◽  
Andrej Hlasnik ◽  
Lehan Stemmet ◽  
Hai-Ning Liang ◽  
...  
Keyword(s):  
Mental Health ◽  
Virtual Reality ◽  
Virtual Environment ◽  
Scoping Review ◽  
Google Scholar ◽  
Health Conditions ◽  
Depression And Anxiety ◽  
Virtual Reality Exposure Therapy ◽  
Mental Health Conditions ◽  
Virtual Reality Exposure

BACKGROUND Mental health conditions pose a major challenge to healthcare providers and society at large. The World Health Organization (WHO) predicts that by 2030, mental health conditions will be the leading disease burden globally. The current need for mental health care is overwhelming. In New Zealand, one in six adults have been diagnosed with common mental disorders such as depression, and anxiety disorders according to a national survey. Cognitive behavioral therapy (CBT) has been shown to effectively help patients overcome a wide variety of mental health conditions. Virtual Reality Exposure Therapy (VRET) might be one of the most exciting technology that is emerging in the clinical setting for the treatment of anxiety and depression. OBJECTIVE This study aimed to investigate what VR technologies are currently being used to help suppress depression and anxiety. Primarily we identified whether the CBT was included as part of the virtual reality exposure therapy treatment (VRET), and if so, how? Equally important, the focus was set not only on VR hardware and used software tools but also on what the participants did in the virtual environment and how the virtual environment looked like METHODS We performed a scoping review. To identify significant studies, we decided to use already aggregated sources in Google Scholar Database. Overall, the goal of our search strategy was to limit the number of initial results related to virtual reality in mental health to only a relevant minimum. RESULTS Using our defined key words, Google Scholar identified more than 17300 articles. After applying all inclusion and exclusion criteria, we identified a total of 369 articles for further processing. After manual evaluation, 34 articles were shortlisted, of which 9 reported the usage of CBT with VR. All these articles were published between 2017 and 2021. CONCLUSIONS Majority of the studies demonstrated the use of VR to be effective for suppressing anxiety or depression in a range of settings and recommended its potential as tool for usage in a clinical environment. As standalone headsets are much easier to work with and more suitable for home usage, the shift from tethered VR headsets to standalone headsets in the mental health environment was not observed. A total of 9 studies explicitly mentioned the usage of CBT. Out of these, CBT was conducted within a virtual reality environment in 5 studies while in the remaining 4 studies CBT was used as an addition to VRET. All 9 studies reported the use of CBT either in vivo or inside a virtual environment to be effective in suppressing anxiety or depression.

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