scholarly journals Estimation of psychological distress in Japanese youth through analyses of narrative writing (Preprint)

2021 ◽  
Author(s):  
Masae Manabe ◽  
Kongmeng Liew ◽  
Shuntaro Yada ◽  
Shoko Wakamiya ◽  
Eiji Aramaki
Keyword(s):  
Mental Illness ◽  
Psychological Distress ◽  
Sentiment Analysis ◽  
Language Processing ◽  
Mental Illnesses ◽  
Japanese Culture ◽  
Narrative Writing ◽  
Self Disclosure ◽  
Written Narratives ◽  
Japanese Youth

BACKGROUND Internalizing mental illnesses associated with psychological distress are often under-detected. Text-based detection using natural language processing methods are increasingly used to complement conventional detection efforts. However, these often rely on self-disclosure through autobiographical narratives, that may not always be possible, especially in collectivistic Japanese culture. As such, we propose the use of narrative writing as an alternative task for mental illness detection in youths. Accordingly, this study investigates the textual characteristics of narratives that are written by youths with psychological distress. OBJECTIVE Our research focuses on the detection of psychopathological tendencies in written imaginative narratives. We apply NLP tools, such as stylometric measures and lexicon-based sentiment analysis. METHODS Using stylometric measures and sentiment analyses, we examined short narratives from 52 Japanese youths (M = 19.81, SD = 20.01) through crowdsourcing. Participants wrote a short narrative introduction to an imagined story, before completing a questionnaire on their psychological distress tendencies. Based on this score, participants were categorized into Higher distress and Lower distress groups. Written narratives were then analyzed using stylometric measures and sentiment analysis, and examined for between-group differences. RESULTS Youths at higher tendencies towards psychological distress used significantly more positive (happiness-related) words, revealing differences in valence of the narrative content. This paves the way for online surveillance and detection efforts, particularly in Japan where youths may be hesitant to engage in self-disclosure. We discuss the implications of these findings in more detail. CONCLUSIONS Youths with tendencies towards mental illness were found to write more positive stories that contained more happiness-related terms. These results may potentially have more widespread implications on screening, particularly in cultures like Japan that are not accustomed to self-disclosure.

scholarly journals Estimation of psychological distress in Japanese youth through analyses of narrative writing (Preprint)

10.2196/29500 ◽  
2021 ◽  
Author(s):  
Masae Manabe ◽  
Kongmeng Liew ◽  
Shuntaro Yada ◽  
Shoko Wakamiya ◽  
Eiji Aramaki
Keyword(s):  
Psychological Distress ◽  
Narrative Writing ◽  
Japanese Youth

scholarly journals Psychosocial and lifestyle predictors of distress and well-being in people with mental illness during the COVID-19 pandemic

2021 ◽  
pp. 103985622110250
Author(s):  
Justin J Chapman ◽  
Eva Malacova ◽  
Sue Patterson ◽  
Nicola Reavley ◽  
Marianne Wyder ◽  
...  
Keyword(s):  
Mental Illness ◽  
Psychological Distress ◽  
Alcohol Intake ◽  
Healthy Lifestyle ◽  
Well Being ◽  
Exercise Programme ◽  
Mental Illnesses ◽  
Social Connection ◽  
People With Mental Illness ◽  
Improve Health

Objectives: People with mental illness may be vulnerable to psychological distress and reduced well-being during the COVID-19 pandemic. The aim of this study was to assess psychosocial and lifestyle predictors of distress and well-being in people with mental illness during the pandemic. Method: People with mental illness who participated in an exercise programme prior to the pandemic were invited to complete surveys about mental health and lifestyle corresponding to before and during the pandemic. Results: Social support reduced, alcohol intake increased, and sleep quality and diet worsened during the pandemic, contributing to distress. Psychological distress was associated with the two or more mental illnesses, and negatively associated with having a physical disease. Better diet appeared to protect against increases in distress; loneliness hindered improvements in well-being. Conclusions: Healthy lifestyle programmes designed to improve social connection may improve health for people with mental illnesses during and after the COVID-19 pandemic.

scholarly journals M225. EXPRESSED EMOTIONS AND PSYCHOLOGICAL DISTRESS AMONG CAREGIVERS OF PATIENTS WITH CHRONIC MENTAL ILLNESS ATTENDING PSYCHIATRIC DEPARTMENT OF BPKIHS

2020 ◽  
Vol 46 (Supplement_1) ◽  
pp. S221-S222
Author(s):  
Sanjita Fyak ◽  
Nirmala Pradhan ◽  
Sami Lama ◽  
Kriti Thapa ◽  
Rajesh Kumar
Keyword(s):  
Mental Illness ◽  
Psychological Distress ◽  
Expressed Emotion ◽  
Sampling Technique ◽  
Cross Sectional Study ◽  
Mental Illnesses ◽  
Chronic Mental Illness ◽  
Cross Sectional ◽  
Expressed Emotions ◽  
Distress Scale

Abstract Background Family expressed emotions had been shown to be predictive of outcome in mental illnesses in variety of cultural settings. Distressed caregivers who provide care to mentally ill relatives are at risk for developing mental health disorders. Methods A hospital based cross sectional study was conducted among 85 caregivers of chronic mental illness using purposive sampling technique. Caregivers were interviewed using Family Questionnaire (FQ) and Kessler Psychological Distress Scale (K10) to assess expressed emotions and psychological distress of caregivers respectively. Results More than half (55.3%) of the caregivers had low expressed emotions while 44.7% had high expressed emotions. More than half (55.3%) of the caregivers had low psychological distress, followed by medium risk (31.8%) and high risk (12.9%). Study revealed significant association between caregiver’s expressed emotion with caregiver’s relationship to patient, area of residence, socioeconomic status, age and gender of patients. Caregiver’s psychological distress had a significant association with their relationships with patient and educational qualification of patient. There was positive correlation between caregiver’s expressed emotions and psychological distress. Discussion This study illustrated that more than half (55.3%) of the caregivers had low expressed emotions and 44.7% had high expressed emotions while caring their patients with chronic mental illness. This finding is contradictory to the findings of a study conducted in India which depicts that most of the caregivers were designated as high EE (56%) as compared to low EE (44%). Another study conducted in Thailand indicated that large number of caregivers have high expressed emotion (87.5%).Another descriptive quantitative exploratory study done in Saudi Arabia had shown that majority of caregivers had low EE (85%). This differences in the results related to expressed emotions could be possibly due to variations in the sample size and tools used for data collection among these studies.

Explanatory Model of Mental Illness from the Perspective of Traditional Chinese Medicine (Preprint)

2021 ◽  
Author(s):  
Wan-Ling Lin ◽  
Yu-Chi Liang ◽  
Kuo-Hsuan Chung ◽  
Ping-Ho Chen ◽  
Yung-Chun Chang
Keyword(s):  
Mental Illness ◽  
Natural Language Processing ◽  
Chinese Medicine ◽  
Traditional Chinese Medicine ◽  
Natural Language ◽  
Language Processing ◽  
Mental Illnesses ◽  
Mind And Body ◽  
Huángdì Nèijīng ◽  
The Mind

UNSTRUCTURED The improvement of accurate management of mental illness has become an increasing concern in recent decades. Efforts to understand mental illness have progressed from treating the mind as an isolated system to involving both mind and body as an interactive response. This study attempts to express and ontologize the relationships between different mental illnesses and physical organ systems from the perspective of Traditional Chinese Medicine. In this paper, Natural Language Processing method was introduced to quantify the importance of different mental illness descriptions relative to the five Viscera and two bowels, Stomach and gallbladder through the classical medical text Huangdi Neijing and construct a mental illness network based on the TCM classic text. The results demonstrate that our proposed framework which integrates natural language processing and data visualization can enable clinicians to arrive at more comprehensive insights into mental health. According to the results of the correlation analysis for mental illnesses, viscera, and symptoms, the organs most affected by mental illness is the Heart, and the most two important factors to cause mental illness are Anger and Worry &Think. Moreover, the current findings promote the present comprehension of the association between the mind and body from the view of Traditional Chinese Medicine. We found the mental illness described in Traditional Chinese Medicine is always related to more than one organ.

Prescriptive Power: Biologism, Biopsychiatry and Drug-centred Psychopharmacology

Somatechnics ◽  
2019 ◽  
Vol 9 (2-3) ◽  
pp. 291-309
Author(s):  
Francis Russell
Keyword(s):  
Mental Health ◽  
Mental Illness ◽  
Social Justice ◽  
Cultural Theory ◽  
Human Experience ◽  
Mental Illnesses ◽  
False Consciousness ◽  
The Subject ◽  
Biological Ontology ◽  
Health Discourse

This paper looks to make a contribution to the critical project of psychiatrist Joanna Moncrieff, by elucidating her account of ‘drug-centred’ psychiatry, and its relation to critical and cultural theory. Moncrieff's ‘drug-centred’ approach to psychiatry challenges the dominant view of mental illness, and psychopharmacology, as necessitating a strictly biological ontology. Against the mainstream view that mental illnesses have biological causes, and that medications like ‘anti-depressants’ target specific biological abnormalities, Moncrieff looks to connect pharmacotherapy for mental illness to human experience, and to issues of social justice and emancipation. However, Moncrieff's project is complicated by her framing of psychopharmacological politics in classical Marxist notions of ideology and false consciousness. Accordingly, she articulates a political project that would open up psychiatry to the subjugated knowledge of mental health sufferers, whilst also characterising those sufferers as beholden to ideology, and as being effectively without knowledge. Accordingly, in order to contribute to Moncrieff's project, and to help introduce her work to a broader humanities readership, this paper elucidates her account of ‘drug-centred psychiatry’, whilst also connecting her critique of biopsychiatry to notions of biologism, biopolitics, and bio-citizenship. This is done in order to re-describe the subject of mental health discourse, so as to better reveal their capacities and agency. As a result, this paper contends that, once reframed, Moncrieff's work helps us to see value in attending to human experience when considering pharmacotherapy for mental illness.

Effective e-health design for those with, and without, mental health disorders: shallow navigation, concentrated contents, modest number of links, one screen area for links. (Preprint)

2018 ◽  
Author(s):  
Armando Rotondi ◽  
Jonathan Grady ◽  
Barbara H. Hanusa ◽  
Michael R. Spring ◽  
Kaleab Z. Abebe ◽  
...  
Keyword(s):  
Mental Illness ◽  
Severe Mental Illness ◽  
Success Rate ◽  
Fractional Factorial ◽  
Mental Illnesses ◽  
Schizophrenia Spectrum Disorders ◽  
Design Elements ◽  
Website Usability ◽  
Schizophrenia Spectrum ◽  
Health Applications

BACKGROUND E-health applications are an avenue to improve service responsiveness, convenience, and appeal, and tailor treatments to improve relevance, engagement, and use. It is critical to user engagement that the designs of e-health applications are intuitive to navigate. Limited research exists on designs that work for those with a severe mental illness, many of whom infrequently seek treatment, and tend to discontinuation medications and psychosocial treatments. OBJECTIVE The purpose of this study was to evaluate the influence of 12 design elements (e.g., website depth, reading level, use of navigational lists) on the usability of e-health application websites for those with, and without, mental health disorders (including severe mental illness). METHODS A 212-4 fractional factorial experimental design was used to specify the designs of 256 e-health websites, which systematically varied the 12 design elements. The final destination contents of all websites were identical, only the navigational pages varied. Three subgroups of participants comprising 226 individuals, were used to test these websites (those with schizophrenia-spectrum disorders, other mental illnesses, and no mental illness). Unique to this study was that the 12 design elements were manipulated systematically to allow assessment of combinations of design elements rather than only one element at a time. RESULTS The best and worst designs were identified for each of the three subgroups, and the sample overall. The depth of a website’s navigation, that is, the number of screens/pages users needed to navigate to find desired content, had the strongest influence on usability (ability to find information). The worst performing design for those with schizophrenia-spectrum disorders had an 8.6% success rate (ability to find information), the best had a 53.2% success rate. The navigational design made a 45% difference in usability. For the subgroup with other mental illnesses the design made a 52% difference, and for those with no mental illness a 50% difference in success rate. The websites with the highest usability all had several key similarities, as did the websites with the poorest usability. A unique finding is that the influences on usability of some design elements are variable. For these design elements, whether they had a positive or negative effect, and the size of its effect, could be influenced by the rest of the design environment, that is, the other elements in the design. This was not the case for navigational depth, a shallower hierarchy is better than a deeper hierarchy. CONCLUSIONS It is possible to identify evidence-based strategies for designing e-health applications that result in a high level of usability. Even for those with schizophrenia, or other severe mental illnesses, there are designs that are highly effective. The best designs have key similarities, but can also vary in some respects. Key words: schizophrenia, severe mental illness, e-health, design, website, usability, website design, website usability, fractional factorial design.

scholarly journals Twitter Sentiment Analysis towards COVID-19 Vaccines in the Philippines Using Naïve Bayes

Information ◽  
2021 ◽  
Vol 12 (5) ◽  
pp. 204
Author(s):  
Charlyn Villavicencio ◽  
Julio Jerison Macrohon ◽  
X. Alphonse Inbaraj ◽  
Jyh-Horng Jeng ◽  
Jer-Guang Hsieh
Keyword(s):  
Sentiment Analysis ◽  
Language Processing ◽  
Data Science ◽  
Naive Bayes ◽  
The Philippines ◽  
Naïve Bayes ◽  
Social Networking Site ◽  
Bayes Model ◽  
The Government ◽  
Processing Techniques

A year into the COVID-19 pandemic and one of the longest recorded lockdowns in the world, the Philippines received its first delivery of COVID-19 vaccines on 1 March 2021 through WHO’s COVAX initiative. A month into inoculation of all frontline health professionals and other priority groups, the authors of this study gathered data on the sentiment of Filipinos regarding the Philippine government’s efforts using the social networking site Twitter. Natural language processing techniques were applied to understand the general sentiment, which can help the government in analyzing their response. The sentiments were annotated and trained using the Naïve Bayes model to classify English and Filipino language tweets into positive, neutral, and negative polarities through the RapidMiner data science software. The results yielded an 81.77% accuracy, which outweighs the accuracy of recent sentiment analysis studies using Twitter data from the Philippines.

scholarly journals Use of a Consultation Service Following Pharmacogenomic Testing in Psychiatry

CNS Spectrums ◽  
2021 ◽  
Vol 26 (2) ◽  
pp. 179-180
Author(s):  
Daniel Dowd ◽  
David S. Krause
Keyword(s):  
Mental Illness ◽  
Drug Interactions ◽  
Metabolic Pathways ◽  
Patient Characteristics ◽  
Healthcare Resource Utilization ◽  
Machine Learning Algorithms ◽  
Mental Illnesses ◽  
Variable Response ◽  
Drug Induced ◽  
Commercial Laboratory

AbstractBackgroundThere is a plethora of drugs available to psychiatrists for treatment of mental illness, which can vary in efficacy, tolerability, metabolic pathways and drug-drug interactions. Psychotropics are the second most commonly listed therapeutic class mentioned in the FDA’s Table of Pharmacogenomic Biomarkers in Drug Labeling. Pharmacogenomic (PGx) assays are increasingly used in psychiatry to help select safe and appropriate medication for a variety of mental illnesses. Our commercial laboratory offers PGx expert consultations by PharmDs and PhDs to clinician-users. Our database contains valuable information regarding the treatment of a diverse and challenging population.MethodsGenomind offers a PGx assay currently measuring variants of 24 genes relevant for selection of drugs with a mental illness indication. Since 2012 we have analyzed > 250,000 DNA samples. Between 10/18 - 8/20 6,401 reports received a consult. The data contained herein are derived from those consults. Consultants record information on prior meds, reason for failure or intolerability, potential risk-associated or useful drugs based on the genetic variants. Consultants only recommend specific drugs and doses consistent with a published PGx guideline.ResultsThe 5 most commonly discussed genes were SLC6A4, MTHFR, CACNA1C, COMT and BDNF. The 3 most commonly discussed drugs were fluoxetine, lithium and duloxetine. The most common reasons for drug failure were inefficacy and drug induced “agitation, irritability and/or anxiety”. SSRIs were the most common class of discontinued drug; sertraline, escitalopram and fluoxetine were the three most commonly reported discontinuations and were also the 3 most likely to be associated with “no improvement”. Aripiprazole was the most commonly reported discontinued atypical antipsychotic. The providers rated 94% of consultations as extremely or very helpful at the time of consult. An independent validation survey of 128 providers confirmed these ratings, with 96% reporting a rating of “very helpful” or “extremely helpful”. In addition, 94% reported that these consults were superior to PGx consults provided through other laboratories. Patient characteristics captured during consults via a Clinical Global Impressions-Severity (CGI-S) scale revealed that the majority of patients were moderately (54%) or markedly ill (23%). The most frequent symptoms reported were depression, anxiety, insomnia and inattentiveness.DiscussionThe large variety of psychotropic drugs available to providers, and their highly variable response rates, tolerability, capacity for drug-drug interactions and metabolic pathways present a challenge for even expert psychopharmacologists. Consultation with experts in PGx provides additional useful information that may improve outcomes and decrease healthcare resource utilization. This database may provide future opportunities for machine learning algorithms to further inform implications of included gene variants.FundingGenomind, Inc.

Assessment of Agreement Between Human Ratings and Lexicon-Based Sentiment Ratings of Open-Ended Responses on a Behavioral Rating Scale

Assessment ◽  
2021 ◽  
pp. 107319112199646
Author(s):  
Olivia Gratz ◽  
Duncan Vos ◽  
Megan Burke ◽  
Neelkamal Soares
Keyword(s):  
Sentiment Analysis ◽  
Language Processing ◽  
Rating Scales ◽  
Clinical Decision Making ◽  
Rating Scale ◽  
Clinical Decision ◽  
Assessment System ◽  
Word Count ◽  
Positive Correlation ◽  
Sentiment Score

To date, there is a paucity of research conducting natural language processing (NLP) on the open-ended responses of behavior rating scales. Using three NLP lexicons for sentiment analysis of the open-ended responses of the Behavior Assessment System for Children-Third Edition, the researchers discovered a moderately positive correlation between the human composite rating and the sentiment score using each of the lexicons for strengths comments and a slightly positive correlation for the concerns comments made by guardians and teachers. In addition, the researchers found that as the word count increased for open-ended responses regarding the child’s strengths, there was a greater positive sentiment rating. Conversely, as word count increased for open-ended responses regarding child concerns, the human raters scored comments more negatively. The authors offer a proof-of-concept to use NLP-based sentiment analysis of open-ended comments to complement other data for clinical decision making.

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