scholarly journals Experience of clinical services shapes attitudes to data sharing

2021 ◽  
Author(s):  
E.J. Kirkham ◽  
S. M. Lawrie ◽  
C.J. Crompton ◽  
M.H. Iveson ◽  
N. D. Jenkins ◽  
...  
Keyword(s):  
Mental Health ◽  
Mental Illness ◽  
Personal Experience ◽  
Public Support ◽  
Mental Health Research ◽  
Health Data ◽  
Mental Illnesses ◽  
Obsessive Compulsive ◽  
Compulsive Disorder ◽  
High Level

AbstractBackgroundRoutinely-collected mental health data could deliver novel insights for mental health research. However, patients’ willingness to share their mental health data remains largely unknown. We investigated factors influencing likelihood of sharing these data for research purposes amongst people with experience of mental illness.MethodsWe collected responses from a population-representative UK sample of National Health Service (NHS) users (n = 2187) of which about half (n = 1087) had lifetime experience of mental illness. Ordinal logistic regression was used to examine the influence of demographic factors, clinical service experience, and primary mental illness on willingness to share mental health data, contrasted against physical health data.ResultsThere was a high level of willingness to share mental (89.7%) and physical (92.8%) health data for research purposes. Higher levels of satisfaction with the NHS were associated with greater willingness to share mental health data. Furthermore, people with personal experience of mental illness were more willing than those without to share mental health data, once the effect of NHS satisfaction had been controlled for. Of the mental illnesses recorded, people with depression, anxiety, obsessive-compulsive disorder (OCD), personality disorder or bipolar disorder were significantly more likely to share their mental health data than people without mental illness.ConclusionsThese findings suggest that positive experiences of health services and personal experience of mental illness are associated with greater willingness to share mental health data. NHS satisfaction is a potentially modifiable factor that could foster public support for increased use of NHS mental health data in research.

Which biopsychosocial view of mental illness?

2020 ◽  
pp. 82-96
Author(s):  
Walter Sinnott-Armstrong ◽  
Jesse S. Summers
Keyword(s):  
Mental Illness ◽  
Social Engagement ◽  
Psychological Symptoms ◽  
Mental Illnesses ◽  
Post Traumatic Stress ◽  
Obsessive Compulsive ◽  
Compulsive Disorder ◽  
Disinhibited Social Engagement Disorder ◽  
Post Traumatic ◽  
Almost All

Biopsychosocial theories of mental illness claim that biological, psychological, and social factors are all central to every mental illness. This general approach cannot be assessed or employed properly without specifying the precise relation between mental illnesses and these three levels of understanding. This chapter distinguishes disjunctive, causal, explanatory, therapeutic (or treatment), and constitutive (or definitional) versions of biopsychosocial theories. However, all of these claims are uncontroversial and not distinctive of the biopsychosocial approach, except the constitutive claim. That constitutive claim is inaccurate, because almost all mental illnesses are and should be defined by their psychological symptoms instead of their biological or social causes. These lessons are applied to case studies of post-traumatic stress disorder, disinhibited social engagement disorder, obsessive–compulsive disorder, and scrupulosity.

scholarly journals Metaphors of mental illness: a corpus-based approach analysing first-person accounts of patients and mental health professionals

2021 ◽  
Vol 25 ◽  
pp. 85-104
Author(s):  
Marta Coll-Florit ◽  
Antoni Oliver ◽  
Salvador Climent
Keyword(s):  
Mental Health ◽  
Mental Illness ◽  
Mental Health Professionals ◽  
Health Professionals ◽  
Manual Annotation ◽  
Severe Mental Disorders ◽  
Obsessive Compulsive ◽  
Compulsive Disorder ◽  
Similarities And Differences ◽  
Patient Subgroups

In this paper we describe the building, manual annotation and analysis of a balanced corpus to assess conceptual metaphors on mental illness as used in Spanish blogger writing by patients and mental health professionals. The corpus was structured as eight subgroups: four patient subgroups (composed of persons who declared having been diagnosed with major depression, schizophrenia, bipolar disorder, or obsessive-compulsive disorder) and four mental health professional subgroups (psychiatrists, psychologists, social educators, nurses). The quantitative analysis identified similarities and differences between groups regarding the volume of metaphors produced and the topics linguistically expressed through metaphors. The most frequent metaphors used by each major group, patients and professionals, were qualitatively analysed, with the principal findings showing a set of source domains used to conceptualize all four severe mental disorders, thus pointing to a common conceptualization of mental suffering irrespective of the specific diagnosis, and two major types of metaphors, WAR and JOURNEY, used by all subgroups of patients and professionals to talk about their first-hand experiences.

Correctional Mental Health Research and Program Evaluation

2015 ◽  
Author(s):  
Nancy Wolff
Keyword(s):  
Mental Health ◽  
Mental Illness ◽  
Health Research ◽  
Mental Health Treatment ◽  
Mental Health Research ◽  
Psychosocial Treatment ◽  
Mental Illnesses ◽  
Health Treatment ◽  
Correctional Mental Health

Research in mental health issues in prisoner populations essentially stopped in the mid 1970’s. It is now re-emerging as a critical component of improving mental health care and helping toward recovery for the incarcerated mentally ill. Mental illness, ranging from acute anxiety to schizophrenia, is endemic within prisons and jails. Unlike their free world counterparts, however, incarcerated people have a constitutional right to mental health treatment. Yet, despite the need for and right to mental health treatment, remarkably little reliable and valid evidence is available on the nature and level of mental illness among incarcerated people, the effects of incarceration on symptomatology, the availability and quality of medication, cognitive, and psychosocial treatment for disorders, and how context impacts the effectiveness of the treatment that is available. Evidence is absent because corrections-based research is constrained by regulation, financing, and inexperience. In this chapter, the history of prisoner research and the evolution of federal regulations to protect prisoners as human subjects will be reviewed and then discussed in terms of how regulation has impacted correctional mental health research, after first defining what is meant by research and why research is needed to inform policy and practice decisions. This will be followed by recommendations for building the correctional mental health research evidence base. The intent here is to help researchers, in collaboration with stakeholders, develop, design, and implement research studies, and disseminate evidence to advance science and the quality of care available to incarcerated people with mental illnesses within the current regulatory environment.

scholarly journals Co-development of a best practice checklist for mental health data science: A Delphi study

2021 ◽  
Author(s):  
E.J. Kirkham ◽  
C.J. Crompton ◽  
M.H. Iveson ◽  
I. Beange ◽  
A. McIntosh ◽  
...  
Keyword(s):  
Mental Health ◽  
Mental Illness ◽  
Health Research ◽  
Delphi Study ◽  
Best Practice ◽  
Data Science ◽  
Mental Health Research ◽  
Health Data ◽  
The Future ◽  
Three Phases

AbstractBackgroundMental health research is commonly affected by difficulties in recruiting and retaining participants, resulting in findings which are based on a sub-sample of those actually living with mental illness. Increasing the use of Big Data for mental health research, especially routinely-collected data, could improve this situation. However, steps to facilitate this must be enacted in collaboration with those who would provide the data - people with mental health conditions.MethodsWe used the Delphi method to create a best practice checklist for mental health data science. Twenty participants with both expertise in data science and personal experience of mental illness worked together over three phases. In the Phase 1, participants rated a list of 63 statements and added any statements or topics that were missing. Statements receiving a mean score of 5 or more (out of 7) were retained. These were then combined with the results of a rapid thematic analysis of participants’ comments to produce a 14-item draft checklist, with each item split into two components: best practice now and best practice in the future. In Phase 2, participants indicated whether or not each item should remain in the checklist, and items that scored more than 50% endorsement were retained. In Phase 3 participants rated their satisfaction with the final checklist.ResultsThe final checklist was made up of 14 “best practice” items, with each item covering best practice now and best practice in the future. At the end of the three phases, 85% of participants were (very) satisfied with the two best practice checklists, with no participants expressing dissatisfaction.ConclusionsIncreased stakeholder involvement is essential at every stage of mental health data science. The checklist produced through this work represents the views of people with experience of mental illness, and it is hoped that it will be used to facilitate trustworthy and innovative research which is inclusive of a wider range of individuals.

scholarly journals Co-development of a Best Practice Checklist for Mental Health Data Science: A Delphi Study

2021 ◽  
Vol 12 ◽  
Author(s):  
Elizabeth J. Kirkham ◽  
Catherine J. Crompton ◽  
Matthew H. Iveson ◽  
Iona Beange ◽  
Andrew M. McIntosh ◽  
...  
Keyword(s):  
Mental Health ◽  
Mental Illness ◽  
Health Research ◽  
Delphi Study ◽  
Best Practice ◽  
Data Science ◽  
Mental Health Research ◽  
Health Data ◽  
The Future ◽  
Three Phases

Background: Mental health research is commonly affected by difficulties in recruiting and retaining participants, resulting in findings which are based on a sub-sample of those actually living with mental illness. Increasing the use of Big Data for mental health research, especially routinely-collected data, could improve this situation. However, steps to facilitate this must be enacted in collaboration with those who would provide the data - people with mental health conditions.Methods: We used the Delphi method to create a best practice checklist for mental health data science. Twenty participants with both expertise in data science and personal experience of mental illness worked together over three phases. In Phase 1, participants rated a list of 63 statements and added any statements or topics that were missing. Statements receiving a mean score of 5 or more (out of 7) were retained. These were then combined with the results of a rapid thematic analysis of participants' comments to produce a 14-item draft checklist, with each item split into two components: best practice now and best practice in the future. In Phase 2, participants indicated whether or not each item should remain in the checklist, and items that scored more than 50% endorsement were retained. In Phase 3 participants rated their satisfaction with the final checklist.Results: The final checklist was made up of 14 “best practice” items, with each item covering best practice now and best practice in the future. At the end of the three phases, 85% of participants were (very) satisfied with the two best practice checklists, with no participants expressing dissatisfaction.Conclusions: Increased stakeholder involvement is essential at every stage of mental health data science. The checklist produced through this work represents the views of people with experience of mental illness, and it is hoped that it will be used to facilitate trustworthy and innovative research which is inclusive of a wider range of individuals.

scholarly journals The Singaporean public beliefs about the causes of mental illness: results from a multi-ethnic population-based study

2017 ◽  
Vol 27 (4) ◽  
pp. 403-412 ◽  
Author(s):  
S. Pang ◽  
M. Subramaniam ◽  
S. P. Lee ◽  
Y. W. Lau ◽  
E. Abdin ◽  
...  
Keyword(s):  
Mental Health ◽  
Mental Illness ◽  
Factor Structure ◽  
Social Distance ◽  
Treatment Compliance ◽  
Southeast Asian ◽  
Mental Illnesses ◽  
Causal Beliefs ◽  
Compulsive Disorder ◽  
Awareness Campaigns

Aims.To identify the common causal beliefs of mental illness in a multi-ethnic Southeast Asian community and describe the sociodemographic associations to said beliefs. The factor structure to the causal beliefs scale is explored. The causal beliefs relating to five different mental illnesses (alcohol abuse, depression, obsessive-compulsive disorder (OCD), dementia and schizophrenia) and desire for social distance are also investigated.Methods.Data from 3006 participants from a nationwide vignette-based study on mental health literacy were analysed using factor analysis and multiple logistic regression to address the aims. Participants answered questions related to sociodemographic information, causal beliefs of mental illness and their desire for social distance towards those with mental illness.Results.Physical causes, psychosocial causes and personality causes were endorsed by the sample. Sociodemographic differences including ethnic, gender and age differences in causal beliefs were found in the sample. Differences in causal beliefs were shown across different mental illness vignettes though psychosocial causes was the most highly attributed cause across vignettes (endorsed by 97.9% of respondents), followed by personality causes (83.5%) and last, physical causes (37%). Physical causes were more likely to be endorsed for OCD, depression and schizophrenia. Psychosocial causes were less often endorsed for OCD. Personality causes were less endorsed for dementia but more associated with depression.Conclusions.The factor structure of the causal beliefs scale is not entirely the same as that found in previous research. Further research on the causal beliefs endorsed by Southeast Asian communities should be conducted to investigate other potential causes such as biogenetic factors and spiritual/supernatural causes. Mental health awareness campaigns should address causes of mental illness as a topic. Lay beliefs in the different causes must be acknowledged and it would be beneficial for the public to be informed of the causes of some of the most common mental illnesses in order to encourage help-seeking and treatment compliance.

scholarly journals Data Analytics in Mental Healthcare

2020 ◽  
Vol 2020 ◽  
pp. 1-9
Author(s):  
Ayesha Kamran Ul haq ◽  
Amira Khattak ◽  
Noreen Jamil ◽  
M. Asif Naeem ◽  
Farhaan Mirza
Keyword(s):  
Mental Health ◽  
Mental Illness ◽  
Data Analytics ◽  
Mental Health Problems ◽  
Mental Healthcare ◽  
Mental Health Research ◽  
Mental Illnesses ◽  
Mental Condition ◽  
Different Types ◽  
Extensive Growth

Worldwide, about 700 million people are estimated to suffer from mental illnesses. In recent years, due to the extensive growth rate in mental disorders, it is essential to better understand the inadequate outcomes from mental health problems. Mental health research is challenging given the perceived limitations of ethical principles such as the protection of autonomy, consent, threat, and damage. In this survey, we aimed to investigate studies where big data approaches were used in mental illness and treatment. Firstly, different types of mental illness, for instance, bipolar disorder, depression, and personality disorders, are discussed. The effects of mental health on user’s behavior such as suicide and drug addiction are highlighted. A description of the methodologies and tools is presented to predict the mental condition of the patient under the supervision of artificial intelligence and machine learning.

Assessment of antenatal anxiety, depression and obsessive-compulsive disorder in pregnant women in the COVID-19 era

2021 ◽  
pp. 1-7
Author(s):  
Catherine Hinds ◽  
Stephen W. Lindow ◽  
Mona Abdelrahman ◽  
Mark P. Hehir ◽  
Michael P. O’Connell
Keyword(s):  
Mental Health ◽  
Mental Illness ◽  
Pregnant Women ◽  
Obsessive Compulsive Disorder ◽  
Previous History ◽  
Obsessive Compulsive ◽  
Cross Sectional Survey ◽  
Cross Sectional ◽  
Compulsive Disorder ◽  
Anxiety Depression

Objective: To assess the mental health of pregnant women, with reference to anxiety, depression and obsessive-compulsive (OC) symptoms, during the COVID-19 pandemic. Methods: A cross-sectional survey was conducted in Ireland during the third wave of the pandemic between February and March 2021. Psychiatric, social and obstetric information was collected from pregnant women in a Dublin maternity hospital, alongside self-reported measures of mental health status. Results: Of 392 women responding, 23.7% had anxiety, scoring >9 for GAD-7 (7-item generalised anxiety disorder), 20.4% had depression, scoring >9 for PHQ-9 (9-item depression screening tool: Patient health questionnaire) and 10.3% had obsessive-compulsive disorder (OCD), scoring >13 for Yale–Brown obsessive-compulsive scale symptom checklist (Y-BOCS). Amongst self-reported OCD symptoms, there was a preponderance for obsessions rather than compulsions. Of 392 women, 36.2% described their mental health as worse during the pandemic, most frequently describing symptoms of anxiety and sleep disturbance. When analysed against test scores, self-reported worsening of mental health was significantly associated with higher scores on the GAD-7, PHQ-9 and Y-BOCS scales. The three scores were positively interrelated. Poor mental health scores were associated with self-reported strain in relationship with the baby’s father, and current or previous history of mental illness. Conclusion: This study found high levels of depression, anxiety and OC symptoms amongst pregnant women during COVID-19. This highlights the vulnerability of this group to mental illness and the importance of enhanced screening and support during pandemics.

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.

Overcoming the deficiency of refugee mental health research

2019 ◽  
Author(s):  
Kristina Kalfic ◽  
Glenn Mitchell ◽  
Lezanne Ooi ◽  
Sibylle Schwab ◽  
Natalie Matosin
Keyword(s):  
Mental Health ◽  
Mental Illness ◽  
Health Research ◽  
Asylum Seekers ◽  
Scientific Discovery ◽  
Mental Health Research ◽  
Psychiatric Research ◽  
Risk And Resilience ◽  
Refugee Mental Health ◽  
Refugees And Asylum Seekers

The growing number of refugees and asylum seekers are one of the most significant global challenges of this generation. We are currently witnessing the highest level of displacement in history, with over 65 million displaced people in the world. Refugees and asylum seekers are at higher risk to develop mental illness due to their trauma and chronic stress exposures, and particularly post-migration stressors. Yet global and Australian psychiatric research in this area is greatly lacking, particularly with respect to our understanding of the molecular underpinnings of risk and resilience to mental illness in traumatised populations. In this Viewpoint, we explore the reasons behind the lack of refugee mental health research and use this context to propose new ways forward. We believe that scientific discovery performed with a multidisciplinary approach will provide the broad evidence-base required to improve refugee mental health. This will also allow us to work towards the removal of damaging policies that prolong and potentiate mental health deterioration among refugees and asylum seekers, which impacts not only on the individuals but also host countries’ social, economic and healthcare systems.

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