scholarly journals Prevalence of mental health conditions and relationship with general health in a whole-country population of people with intellectual disabilities compared with the general population

BJPsych Open ◽  
2017 ◽  
Vol 3 (5) ◽  
pp. 243-248 ◽  
Author(s):  
Laura A. Hughes-McCormack ◽  
Ewelina Rydzewska ◽  
Angela Henderson ◽  
Cecilia MacIntyre ◽  
Julie Rintoul ◽  
...  
Keyword(s):  
Mental Health ◽  
General Population ◽  
Intellectual Disabilities ◽  
General Health ◽  
Large Scale ◽  
Health Conditions ◽  
Mental Health Conditions ◽  
Study Results ◽  
Country Study ◽  
People With Intellectual Disabilities

BackgroundThere are no previous whole-country studies on mental health and relationships with general health in intellectual disability populations; study results vary.AimsTo determine the prevalence of mental health conditions and relationships with general health in a total population with and without intellectual disabilities.MethodNinety-four per cent completed Scotland's Census 2011. Data on intellectual disabilities, mental health and general health were extracted, and the association between them was investigated.ResultsA total of 26 349/5 295 403 (0.5%) had intellectual disabilities. In total, 12.8% children, 23.4% adults and 27.2% older adults had mental health conditions compared with 0.3, 5.3 and 4.5% of the general population. Intellectual disabilities predicted mental health conditions; odds ratio (OR)=7.1 (95% CI 6.8–7.3). General health was substantially poorer and associated with mental health conditions; fair health OR=1.8 (95% CI 1.7–1.9), bad/very bad health OR=4.2 (95% CI 3.9–4.6).ConclusionsThese large-scale, whole-country study findings are important, given the previously stated lack of confidence in comparative prevalence results, and the need to plan services accordingly.

scholarly journals Relative influence of intellectual disabilities and autism on mental and general health in Scotland: a cross-sectional study of a whole country of 5.3 million children and adults

BMJ Open ◽  
2019 ◽  
Vol 9 (8) ◽  
pp. e029040 ◽  
Author(s):  
Deborah Kinnear ◽  
Ewelina Rydzewska ◽  
Kirsty Dunn ◽  
Laura Anne Hughes-McCormack ◽  
Craig Melville ◽  
...  
Keyword(s):  
Mental Health ◽  
Intellectual Disabilities ◽  
General Health ◽  
Cross Sectional Study ◽  
Poor Health ◽  
Health Conditions ◽  
Sectional Study ◽  
Cross Sectional ◽  
Poor General Health ◽  
Mental Health Conditions

ObjectivesTo determine the relative extent that autism and intellectual disabilities are independently associated with poor mental and general health, in children and adults.DesignCross-sectional study. For Scotland’s population, logistic regressions investigated odds of intellectual disabilities and autism predicting mental health conditions, and poor general health, adjusted for age and gender.Participants1 548 819 children/youth aged 0-24 years, and 3 746 584 adults aged more than 25 years, of whom 9396/1 548 819 children/youth had intellectual disabilities (0.6%), 25 063/1 548 819 children/youth had autism (1.6%); and 16 953/3 746 584 adults had intellectual disabilities (0.5%), 6649/3 746 584 adults had autism (0.2%). These figures are based on self-report.Main outcome measuresSelf-reported general health status and mental health.ResultsIn children/youth, intellectual disabilities (OR 7.04, 95% CI 6.30 to 7.87) and autism (OR 25.08, 95% CI 23.08 to 27.32) both independently predicted mental health conditions. In adults, intellectual disabilities (OR 3.50, 95% CI 3.20 to 3.84) and autism (OR 5.30, 95% CI 4.80 to 5.85) both independently predicted mental health conditions. In children/youth, intellectual disabilities (OR 18.34, 95% CI 17.17 to 19.58) and autism (OR 8.40, 95% CI 8.02 to 8.80) both independently predicted poor general health. In adults, intellectual disabilities (OR 7.54, 95% CI 7.02 to 8.10) and autism (OR 4.46, 95% CI 4.06 to 4.89) both independently predicted poor general health.ConclusionsBoth intellectual disabilities and autism independently predict poor health, intellectual disabilities more so for general health and autism more so for mental health. Intellectual disabilities and autism are not uncommon, and due to their associated poor health, sufficient services/supports are needed. This is not just due to coexistence of these conditions or just to having intellectual disabilities, as the population with autism is independently associated with substantial health inequalities compared with the general population, across the entire life course.

Police Violence among Adults Diagnosed with Mental Disorders

2020 ◽  
Vol 45 (2) ◽  
pp. 81-89
Author(s):  
Hyun-Jin Jun ◽  
Jordan E DeVylder ◽  
Lisa Fedina
Keyword(s):  
Mental Health ◽  
Mental Illness ◽  
General Population ◽  
Mental Disorders ◽  
Severe Mental Illness ◽  
Violence Exposure ◽  
Health Conditions ◽  
Psychotic Symptoms ◽  
Police Violence ◽  
Mental Health Conditions

Abstract Police violence is reportedly common among those diagnosed with mental disorders characterized by the presence of psychotic symptoms or pronounced emotional lability. Despite the perception that people with mental illness are disproportionately mistreated by the police, there is relatively little empirical research on this topic. A cross-sectional general population survey was administered online in 2017 to 1,000 adults in two eastern U.S. cities to examine the relationship between police violence exposure, mental disorders, and crime involvement. Results from hierarchical logistic regression and mediation analyses revealed that a range of mental health conditions are broadly associated with elevated risk for police violence exposure. Individuals with severe mental illness are more likely than the general population to be physically victimized by police, regardless of their involvement in criminal activities. Most of the excess risk of police violence exposure related to common psychiatric diagnoses was explained by confounding factors including crime involvement. However, crime involvement may necessitate more police contact, but does not necessarily justify victimization or excessive force (particularly sexual and psychological violence). Findings support the need for adequate training for police officers on how to safely interact with people with mental health conditions, particularly severe mental illness.

scholarly journals Prevalence of long-term health conditions in adults with autism: observational study of a whole country population

BMJ Open ◽  
2018 ◽  
Vol 8 (8) ◽  
pp. e023945 ◽  
Author(s):  
Ewelina Rydzewska ◽  
Laura Anne Hughes-McCormack ◽  
Christopher Gillberg ◽  
Angela Henderson ◽  
Cecilia MacIntyre ◽  
...  
Keyword(s):  
Mental Health ◽  
Hearing Loss ◽  
Intellectual Disabilities ◽  
Physical Disability ◽  
Health Conditions ◽  
Adults With Autism ◽  
Age And Gender ◽  
Mental Health Conditions ◽  
Sight Loss ◽  
And Gender

ObjectivesTo investigate the prevalence of comorbid mental health conditions and physical disabilities in a whole country population of adults aged 25+ with and without reported autism.DesignSecondary analysis of Scotland’s Census, 2011 data. Cross-sectional study.SettingGeneral population.Participants94% of Scotland’s population, including 6649/3 746 584 adults aged 25+ reported to have autism.Main outcome measuresPrevalence of six comorbidities: deafness or partial hearing loss, blindness or partial sight loss, intellectual disabilities, mental health conditions, physical disability and other condition; ORs (95% CI) of autism predicting these comorbidities, adjusted for age and gender; and OR for age and gender in predicting comorbidities within the population with reported autism.ResultsComorbidities were common: deafness/hearing loss—17.5%; blindness/sight loss—12.1%; intellectual disabilities—29.4%; mental health conditions—33.0%; physical disability—30.7%; other condition—34.1%. Autism statistically predicted all of the conditions: OR 3.3 (95% CI 3.1 to 3.6) for deafness or partial hearing loss, OR 8.5 (95% CI 7.9 to 9.2) for blindness or partial sight loss, OR 94.6 (95% CI 89.4 to 100.0) for intellectual disabilities, OR 8.6 (95% CI 8.2 to 9.0) for mental health conditions, OR 6.2 (95% CI 5.8 to 6.6) for physical disability and OR 2.6 (95% CI 2.5 to 2.8) for other condition. Contrary to findings within the general population, female gender predicted all conditions within the population with reported autism, including intellectual disabilities (OR=1.4).ConclusionsClinicians need heightened awareness of comorbidities in adults with autism to improve detection and suitable care, especially given the added complexity of assessment in this population and the fact that hearing and visual impairments may cause additional difficulties with reciprocal communication which are also a feature of autism; hence posing further challenges in assessment.

Conceptualization of Intellectual Disability in Medieval English Law

2018 ◽  
Author(s):  
Wendy J. Turner
Keyword(s):  
Mental Health ◽  
Intellectual Disability ◽  
Intellectual Disabilities ◽  
Cognitive Ability ◽  
Intellectual Ability ◽  
Health Conditions ◽  
Complex Matrix ◽  
Mental Health Conditions ◽  
Difficult Time ◽  
A Site

Medieval terminology for mental health was a complex matrix of identifiers from legal, medical, and social sources and included terms for many mental, emotional, neurotic and psychotic conditions recognized today. Intellectual disability was one of those categories, especially in the legal realm, with the most-often used term being idiota. Governmental officials that became aware of properties in distress (unplanted, squatters ruining a site, etc) relieved individuals identified as idiota of their responsibilities and placed them into wardship with guardians, who not only cared for the wards but also their properties. The process of examination and civil ‘diagnosis’ of ability encompassed an individual’s intelligence, memory, cognitive ability, discretion, and, at times, appearance. The medieval terms, while not ‘intellectual disability’, certainly described differences in intellectual ability and used vocabulary appropriate for separate conditions, identifying a faulty memory, weak intelligence, difficult time managing property or goods, issue with coping day-to-day, or inability to have discretion. Medieval legal and administrative arms of the crown and local towns each used their own standards to judge competency and intelligence, yet all of them recognized the same wide variety of intellectual conditions and categories of symptoms for intellectual disabilities and other mental health conditions.

scholarly journals Activating the ‘ideal jobseeker’: Experiences of individuals with mental health conditions on the UK Work Programme

2020 ◽  
pp. 001872672093484
Author(s):  
Frederike Scholz ◽  
Jo Ingold
Keyword(s):  
Mental Health ◽  
Social Relations ◽  
Large Scale ◽  
Social Model ◽  
Health Conditions ◽  
Four Dimensions ◽  
Mental Health Conditions ◽  
Work Programme ◽  
The Uk ◽  
The Ideal

Active labour market programmes (ALMPs) are critical preparation mechanisms to assist people to enter the workplace. This article analyses qualitative data from a hard-to-access group of individuals with mental health conditions (MHCs) participating in a large-scale UK ALMP, the Work Programme (WP). Using the lens of the ‘extended social model of disability’ and the concept of the ‘ideal worker’, the article demonstrates that ableist norms of the ‘ideal jobseeker’ were embedded within the Programme’s design, prioritising individuals with certain abilities and behaviour over others. Second, the article extends Acker’s framework of inequality regimes to demonstrate that formal and informal inequality practices within the Programme maintained, rather than challenged, disability inequality. This was visible along four dimensions: (1) ALMPs as organising processes producing disability inequality; (2) the visibility of disability inequality; (3) the legitimacy of disability inequality; and (4) control and compliance derived from hierarchical social relations within ALMP design and implementation, involving either stabilising or destabilising effects on disabled jobseekers. The theoretical and practical contributions of this article demonstrate that the design of the WP as an employment preparation mechanism pushed disabled jobseekers further away from paid employment, rather than towards workplace inclusion.

scholarly journals Shifting culture and taking action to reduce smoking and premature death among people with a mental health condition

2016 ◽  
Vol 15 (4) ◽  
pp. 184-187 ◽  
Author(s):  
Katy Harker ◽  
Hazel Cheeseman
Keyword(s):  
Mental Health ◽  
General Population ◽  
Positive Impact ◽  
Health Condition ◽  
Poor Mental Health ◽  
Health Conditions ◽  
Mental Health Condition ◽  
Content Type ◽  
Mental Health Conditions ◽  
Wide Range

Purpose Mental health conditions affect almost a quarter of the population who die on average 10-20 years earlier than the general population. Smoking is the single largest cause of this gap in life expectancy. Smoking rates among people with mental health conditions have barely changed over the last 20 years during a time when rates have been steadily falling in the general population. Action is needed to address the growing difference in smoking rates among those with a mental health condition compared to the general population. The paper aims to discuss these issues. Design/methodology/approach This work has been informed by the input of a wide range of experts and professionals from across public health, mental health and the wider NHS. Findings People with a mental health condition are just as likely to want to stop smoking as other smokers but they face more barriers to quitting and are more likely to be dependant and therefore need more support. Quitting smoking does not exacerbate poor mental health; in fact the positive impact of smoking cessation on anxiety and depression appears to be at least as large as antidepressants. Originality/value The full report outlines the high-level ambitions and the specific actions that must be realised to drive down smoking rates among those with a mental health condition.

scholarly journals Machine learning in mental health: a scoping review of methods and applications

2019 ◽  
Vol 49 (09) ◽  
pp. 1426-1448 ◽  
Author(s):  
Adrian B. R. Shatte ◽  
Delyse M. Hutchinson ◽  
Samantha J. Teague
Keyword(s):  
Mental Health ◽  
Machine Learning ◽  
Scoping Review ◽  
Latent Dirichlet Allocation ◽  
Health Conditions ◽  
Support Vector ◽  
Mental Health Conditions ◽  
Big Data Applications ◽  
Study Results ◽  
Detection And Diagnosis

AbstractBackgroundThis paper aims to synthesise the literature on machine learning (ML) and big data applications for mental health, highlighting current research and applications in practice.MethodsWe employed a scoping review methodology to rapidly map the field of ML in mental health. Eight health and information technology research databases were searched for papers covering this domain. Articles were assessed by two reviewers, and data were extracted on the article's mental health application, ML technique, data type, and study results. Articles were then synthesised via narrative review.ResultsThree hundred papers focusing on the application of ML to mental health were identified. Four main application domains emerged in the literature, including: (i) detection and diagnosis; (ii) prognosis, treatment and support; (iii) public health, and; (iv) research and clinical administration. The most common mental health conditions addressed included depression, schizophrenia, and Alzheimer's disease. ML techniques used included support vector machines, decision trees, neural networks, latent Dirichlet allocation, and clustering.ConclusionsOverall, the application of ML to mental health has demonstrated a range of benefits across the areas of diagnosis, treatment and support, research, and clinical administration. With the majority of studies identified focusing on the detection and diagnosis of mental health conditions, it is evident that there is significant room for the application of ML to other areas of psychology and mental health. The challenges of using ML techniques are discussed, as well as opportunities to improve and advance the field.

scholarly journals Association of Social Media Use With Mental Health Conditions of Nonpatients During the COVID-19 Outbreak: Insights from a National Survey Study (Preprint)

2020 ◽  
Author(s):  
Bu Zhong ◽  
Zhibin Jiang ◽  
Wenjing Xie ◽  
Xuebing Qin
Keyword(s):  
Mental Health ◽  
Social Media ◽  
General Population ◽  
Psychiatric Disorders ◽  
Health Information ◽  
Media Use ◽  
Information Support ◽  
Health Conditions ◽  
Social Media Use ◽  
Mental Health Conditions

BACKGROUND Considerable research has been devoted to examining the mental health conditions of patients with COVID-19 and medical staff attending to these patients during the COVID-19 pandemic. However, there are few insights concerning how the pandemic may take a toll on the mental health of the general population, and especially of nonpatients (ie, individuals who have not contracted COVID-19). OBJECTIVE This study aimed to investigate the association between social media use and mental health conditions in the general population based on a national representative sample during the peak of the COVID-19 outbreak in China. METHODS We formed a national representative sample (N=2185) comprising participants from 30 provinces across China, who were the first to experience the COVID-19 outbreak in the world. We administered a web-based survey to these participants to analyze social media use, health information support received via social media, and possible psychiatric disorders, including secondary traumatic stress (STS) and vicarious trauma (VT). RESULTS Social media use did not cause mental health issues, but it mediated the levels of traumatic emotions among nonpatients. Participants received health information support via social media, but excessive social media use led to elevated levels of stress (<i>β</i>=.175; <i>P</i>&lt;.001), anxiety (<i>β</i>=.224; <i>P</i>&lt;.001), depression (<i>β</i>=.201; <i>P</i>&lt;.001), STS (<i>β</i>=.307; <i>P</i>&lt;.001), and VT (<i>β</i>=.688; <i>P</i>&lt;.001). Geographic location (or geolocation) and lockdown conditions also contributed to more instances of traumatic disorders. Participants living in big cities were more stressed than those living in rural areas (<i>P</i>=.02). Furthermore, participants from small cities or towns were more anxious (<i>P</i>=.01), stressed (<i>P</i>&lt;.001), and depressed (<i>P</i>=.008) than those from rural areas. Obtaining more informational support (<i>β</i>=.165; <i>P</i>&lt;.001) and emotional support (<i>β</i>=.144; <i>P</i>&lt;.001) via social media increased their VT levels. Peer support received via social media increased both VT (<i>β</i>=.332; <i>P</i>&lt;.001) and STS (<i>β</i>=.130; <i>P</i>&lt;.001) levels. Moreover, geolocation moderated the relationships between emotional support on social media and VT (<i>F</i><sub>2</sub>=3.549; <i>P</i>=.029) and the association between peer support and STS (<i>F</i><sub>2</sub>=5.059; <i>P</i>=.006). Geolocation also interacted with health information support in predicting STS (<i>F</i><sub>2</sub>=5.093; <i>P</i>=.006). CONCLUSIONS COVID-19 has taken a severe toll on the mental health of the general population, including individuals who have no history of psychiatric disorders or coronavirus infection. This study contributes to the literature by establishing the association between social media use and psychiatric disorders among the general public during the COVID-19 outbreak. The study findings suggest that the causes of such psychiatric disorders are complex and multifactorial, and social media use is a potential factor. The findings also highlight the experiences of people in China and can help global citizens and health policymakers to mitigate the effects of psychiatric disorders during this and other public health crises, which should be regarded as a key component of a global pandemic response.

Sign in / Sign up

Export Citation Format

Share Document