scholarly journals Use of sequence analysis for classifying individual antidepressant trajectories to monitor population mental health

2020 ◽  
Vol 20 (1) ◽  
Author(s):  
Mark Cherrie ◽  
Sarah Curtis ◽  
Gergő Baranyi ◽  
Stuart McTaggart ◽  
Niall Cunningham ◽  
...  
Keyword(s):  
Mental Health ◽  
Mental Illness ◽  
Sequence Analysis ◽  
Local Level ◽  
Population Level ◽  
The United States ◽  
Individual Risk ◽  
White Female ◽  
Prescription Data ◽  
Scottish Population

Abstract Background Over the past decade, antidepressant prescriptions have increased in European countries and the United States, partly due to an increase in the number of new cases of mental illness. This paper demonstrates an innovative approach to the classification of population level change in mental health status, using administrative data for a large sample of the Scottish population. We aimed to identify groups of individuals with similar patterns of change in pattern of prescribing, validate these groups by comparison with other indicators of mental illness, and characterise the population most at risk of increasing mental ill health. Methods National Health Service (NHS) prescription data were linked to the Scottish Longitudinal Study (SLS), a 5.3% sample of the Scottish population (N = 151,418). Antidepressant prescription status over the previous 6 months was recorded for every month for which data were available (January 2009–December 2014), and sequence dissimilarity was computed by optimal matching. Hierarchical clustering was used to create groups of participants who had similar patterns of change, with multi-level logistic regression used to understand group membership. Results Five distinct prescription pattern groups were observed, indicating: no prescriptions (76%), occasional prescriptions (10%), continuation of prior use of prescriptions (8%), a new course of prescriptions started (4%) or ceased taking prescriptions (3%). Young, white, female participants, of low social grade, residing in socially deprived neighbourhoods, living alone, being separated/divorced or out of the labour force, were more likely to be in the group that started a new course of antidepressant prescriptions. Conclusions The use of sequence analysis for classifying individual antidepressant trajectories offers a novel approach for capturing population-level changes in mental health risk. By classifying individuals into groups based on their anti-depressant medication use we can better identify how over time, mental health is associated with individual risk factors and contextual factors at the local level and the macro political and economic scale.

scholarly journals Use of sequence analysis for classifying individual antidepressant trajectories to monitor population mental health

2020 ◽  
Author(s):  
Mark Cherrie ◽  
Sarah Curtis ◽  
Gergő Baranyi ◽  
Stuart McTaggart ◽  
Niall Cunningham ◽  
...  
Keyword(s):  
Mental Health ◽  
Mental Illness ◽  
Sequence Analysis ◽  
Local Level ◽  
Population Level ◽  
The United States ◽  
Individual Risk ◽  
White Female ◽  
Prescription Data ◽  
Scottish Population

Abstract BackgroundOver the past decade, antidepressant prescriptions have increased in European countries and the United States, partly due to an increase in the number of new cases of mental illness. This paper demonstrates an innovative approach to the classification of population level change in mental health status, using administrative data for a large sample of the Scottish population. We aimed to identify groups of individuals with similar patterns of change in pattern of prescribing, validate these groups by comparison with other indicators of mental illness, and characterise the population most at risk of increasing mental ill health. MethodsNational Health Service (NHS) prescription data were linked to the Scottish Longitudinal Study (SLS), a 5.3% sample of the Scottish population (N=151,418). Antidepressant prescription status over the previous six months was recorded for every month for which data were available (January 2009-December 2014), and sequence dissimilarity was computed by optimal matching. Hierarchical clustering was used to create groups of participants who had similar patterns of change, with multi-level logistic regression used to understand group membership. ResultsFive distinct prescription pattern groups were observed, indicating: no prescriptions (76%), occasional prescriptions (10%), continuation of prior use of prescriptions (8%), a new course of prescriptions started (4%) or ceased taking prescriptions (3%). Young, white, female participants, of low social grade, residing in socially deprived neighbourhoods, living alone, being separated/divorced or out of the labour force, were more likely to be in the group that started a new course of antidepressant prescriptions.ConclusionsThe use of sequence analysis for classifying individual antidepressant trajectories offers a novel approach for capturing population-level changes in mental health risk. By classifying individuals into groups based on their anti-depressant medication use we can better identify how over time, mental health is associated with individual risk factors and contextual factors at the local level and the macro political and economic scale.

scholarly journals Use of sequence analysis for classifying individual antidepressant trajectories to monitor population mental health

2020 ◽  
Author(s):  
Mark Cherrie ◽  
Sarah Curtis ◽  
Gergő Baranyi ◽  
Stuart McTaggart ◽  
Niall Cunningham ◽  
...  
Keyword(s):  
Mental Health ◽  
Mental Illness ◽  
Sequence Analysis ◽  
Local Level ◽  
Population Level ◽  
The United States ◽  
Individual Risk ◽  
White Female ◽  
Prescription Data ◽  
Scottish Population

Abstract Background Over the past decade, antidepressant prescriptions have increased in European countries and the United States, partly due to an increase in the number of new cases of mental illness. This paper demonstrates an innovative approach to the classification of population level change in mental health status, using administrative data for a large sample of the Scottish population. We aimed to identify groups of individuals with similar patterns of change in pattern of prescribing, validate these groups by comparison with other indicators of mental illness, and characterise the population most at risk of increasing mental ill health. Methods National Health Service (NHS) prescription data were linked to the Scottish Longitudinal Study (SLS), a 5.3% sample of the Scottish population (N=151,418). Antidepressant prescription status over the previous six months was recorded for every month for which data were available (January 2009-December 2014), and sequence dissimilarity was computed by optimal matching. Hierarchical clustering was used to create groups of participants who had similar patterns of change, with multi-level logistic regression used to understand group membership. Results Five distinct prescription pattern groups were observed, indicating: no prescriptions (76%), occasional prescriptions (10%), continuation of prior use of prescriptions (8%), new course of prescriptions started (4%) or ceased taking prescriptions (3%). Young, white, female participants, of low social grade, residing in socially deprived neighbourhoods, living alone, being separated/divorced or out of the labour force, were more likely to be in the group that started a new course of antidepressant prescriptions.Conclusions The use of sequence analysis for classifying individual antidepressant trajectories offers a novel approach for capturing population-level changes in mental health risk. By classifying individuals into groups based on their anti-depressant medication use we can better identify how over time, mental health is associated with individual risk factors and contextual factors at the local level and the macro political and economic scale.

scholarly journals Use of sequence analysis for classifying individual antidepressant trajectories to monitor population mental health

2020 ◽  
Author(s):  
Mark Cherrie ◽  
Sarah Curtis ◽  
Gergő Baranyi ◽  
Stuart McTaggart ◽  
Niall Cunningham ◽  
...  
Keyword(s):  
Mental Health ◽  
Mental Illness ◽  
Sequence Analysis ◽  
Labour Force ◽  
Population Level ◽  
The United States ◽  
White Female ◽  
Prescription Data ◽  
Deprived Neighbourhoods ◽  
Scottish Population

Abstract Background Over the past decade, antidepressant prescriptions have increased in European countries and the United States, partly due to an increase in the number of new cases of mental illness. This paper demonstrates an innovative approach to the classification of population level change in mental health status, using administrative data for a large sample of the Scottish population. We aimed to identify groups of individuals with similar patterns of change in usage, validate these groups with other indicators of mental illness, and characterise the population most at risk of increasing mental ill health. Methods NHS prescription data were linked to the Scottish Longitudinal Study, a 5.3% sample of the Scottish population (N=151,418). Antidepressant prescription status over the previous six months was recorded for every month for which data were available (January 2009-December 2014), and sequence dissimilarity was computed by optimal matching. Hierarchical clustering was used to create groups of participants who had similar patterns of change, with multi-level logistic regression used to understand group membership. Results Five distinct prescription pattern groups were observed, indicating: no prescriptions (76%), occasional prescriptions (10%), continuation of prior use of prescriptions (8%), new course of prescriptions started (4%) or ceased taking prescriptions (3%). Young, white, female participants, of low social grade, residing in socially deprived neighbourhoods, living alone, being separated/divorced or out of the labour force, were more likely to have become prescribed a new course of antidepressants. Conclusions The use of sequence analysis for classifying individual antidepressant trajectories offers a novel approach for capturing population-level changes in mental health. By classifying individuals into groups based on their anti-depressant medication use we can better identify the determinants of changes in mental health, from compositional, contextual, to macro political and economic factors.

scholarly journals Associations between common mental disorders and the Mental Illness Needs Index in community settings

2007 ◽  
Vol 191 (2) ◽  
pp. 158-163 ◽  
Author(s):  
David L. Fone ◽  
Frank Dunstan ◽  
Ann John ◽  
Keith Lloyd
Keyword(s):  
Mental Health ◽  
Mental Illness ◽  
Mental Disorders ◽  
Mental Disorder ◽  
Small Area ◽  
Common Mental Disorders ◽  
Common Mental Disorder ◽  
Service Planning ◽  
Individual Risk ◽  
Community Settings

BackgroundThe relationship between the Mental Illness Needs Index (MINI) and the common mental disorders is not known.AimsTo investigate associations between the small-area MINI score and common mental disorder at individual level.MethodMental health status was measured using the Mental Health Inventory of the Short Form 36 instrument (SF-36). Data from the Caerphilly Health and Social Needs population survey were analysed in multilevel models of 10 653 individuals aged 18–74 years nested within the 2001 UK census geographies of 110 lower super output areas and 33 wards.ResultsThe MINI score was significantly associated with common mental disorder after adjusting for individual risk factors. This association was stronger at the smaller spatial scale of the lower super output area and for individuals who were permanently sick or disabled.ConclusionsThe MINI is potentially useful for small-area needs assessment and service planning for common mental disorder in community settings.

scholarly journals Holistic Health: Does It Really Include Mental Health?

2006 ◽  
Vol 6 ◽  
pp. 2092-2099 ◽  
Author(s):  
Kimberly K. McClanahan ◽  
Marlene B. Huff ◽  
Hatim A. Omar
Keyword(s):  
Mental Health ◽  
Mental Illness ◽  
Physical Health ◽  
The United States ◽  
Holistic Health ◽  
Public Perceptions ◽  
The Past ◽  
Mind And Body ◽  
Mental And Physical Health ◽  
The U.S

Holistic health, incorporating mind and body as equally important and unified components of health, is a concept utilized in some health care arenas in the United States (U.S.) over the past 30 years. However, in the U.S., mental health is not seen as conceptually integral to physical health and, thus, holistic health cannot be realized until the historical concept of mind-body dualism, continuing stigma regarding mental illness, lack of mental health parity in insurance, and inaccurate public perceptions regarding mental illness are adequately addressed and resolved. Until then, mental and physical health will continue to be viewed as disparate entities rather than parts of a unified whole. We conclude that the U.S. currently does not generally incorporate the tenets of holistic health in its view of the mental and physical health of its citizens, and provide some suggestions for changing that viewpoint.

scholarly journals 1539Australia’s worsening mental health – what’s next?

2021 ◽  
Vol 50 (Supplement_1) ◽  
Author(s):  
Shrinkhala Dawadi ◽  
Frances Shawyer ◽  
Helena Teede ◽  
Graham Meadows ◽  
Joanne Enticott
Keyword(s):  
Mental Health ◽  
Mental Illness ◽  
Secondary Analysis ◽  
Symptom Burden ◽  
Population Level ◽  
Policy And Strategy ◽  
Level Data ◽  
Related Symptom ◽  
Australian Census ◽  
Population Mental Health

Abstract Background The population prevalence of mental illness over time, and by sociodemographic subgroups, are important benchmark data. Examining reliable population level data can highlight groups with greater mental-illness related symptom burden and inform policy and strategy. Methods Secondary analysis of Australian National Health Surveys (n = 78,204) from 2001-02 to 2017-18. Trends in the prevalence of very high scores on the Kessler-10 (K10), a measure of psychological distress capturing symptoms of affective and anxiety disorders, were examined by time, age, gender, and socioeconomic status. Data were standardised to the 2001 Australian census population on the strata of sex and age. Results In 2017-18, the rate of probable mental illness was estimated at 5.1%, a 1.5% increase (representing an additional 367,000 Australians) since 2007. In 2017-18, the subgroups with the highest rates were women aged 18-24 (8.01%, 95% CI = 5.9%-10.2%), and the poorest fifth of Australians (8.02%, 95% CI = 7.0%-9.0%). Women aged 55-64 demonstrated the greatest increase in rates (2001: 3.5%, 95% CI = 2.5%-4.6%; 2017: 7.2%, 95% CI = 5.9%-8.5%; z = 4.10, p ≤ 0.001). Conclusions Despite efforts to improve population mental health, rates of probable mental illness in Australia have increased since 2007. Findings will be discussed in conjunction to extant social and health policies, and potential gaps in the delivery of gold-standard mental health care. Key messages The rate of probable mental illness in Australia seem to be increasing, especially in women aged 55-64, and those from low-SES backgrounds.

scholarly journals Bibliotherapy for Mental Health

2017 ◽  
Vol 2 (2) ◽  
pp. 67
Author(s):  
Jennifer Yontz-Orlando
Keyword(s):  
Mental Health ◽  
United States ◽  
Mental Illness ◽  
Medical Condition ◽  
Action Plan ◽  
The United States ◽  
World Health ◽  
Group Setting ◽  
Health Crisis ◽  
The Uk

The United States is facing an epidemic of mental illness, affecting nearly 60 million Americans annually (http://www.nami.org/ ). The World Health Organization describes mental health as “a long neglected problem” and has established an action plan for 2013-2020 (http://www.who.int/mental_health/action_plan_2013/en/). One way to combat mental illness is through bibliotherapy, which is the use of written materials including fiction, nonfiction, and poetry to support emotional and psychiatric healing.Bibliotherapy has been in existence since ancient times, but began in earnest in the United States in the 1850’s during the “Great Awakening.” At that time, mental illness began to be seen as a medical condition rather than a supernatural phenomenon. Since then, due to the changing nature of our institutions, interest in bibliotherapy waned until the 1950’s when there was a slight resurgence in its practice. However, in the last 20 years, bibliotherapy has gained a stronghold in the United Kingdom. To relieve the stress of an overcrowded mental health system, public policy in the UK has supported the use of bibliotherapy in a variety of its institutions. There are many ways to conduct bibliotherapy, but studies show that when the process is interactive, such as in a support group setting, the results are better. Also, bibliotherapy can be conducted by many sorts of professionals, including doctors, therapists, social workers, teachers, and librarians. Studies also show that when the bibliotherapists are trained in the best practices of bibliotherapy, results improve. Bibliotherapy is an effective, low-cost alternative for people in need of therapeutic assistance. The UK model should be studied and implemented in the United States and in other nations to help solve the mental health crisis.

A brief history of the criminalization of mental illness

CNS Spectrums ◽  
2020 ◽  
Vol 25 (5) ◽  
pp. 638-650 ◽  
Author(s):  
Joel A. Dvoskin ◽  
James L. Knoll ◽  
Mollie Silva
Keyword(s):  
Mental Health ◽  
United States ◽  
Mental Illness ◽  
Community Mental Health ◽  
Mental Disorders ◽  
The United States ◽  
Mental Illnesses ◽  
The People ◽  
History Of ◽  
Serious Mental Illnesses

This article traces the history of the way in which mental disorders were viewed and treated, from before the birth of Christ to the present day. Special attention is paid to the process of deinstitutionalization in the United States and the failure to create an adequately robust community mental health system to care for the people who, in a previous era, might have experienced lifelong hospitalization. As a result, far too many people with serious mental illnesses are living in jails and prisons that are ill-suited and unprepared to meet their needs.

scholarly journals The Great Recession and Mental Health in the United States

2019 ◽  
Vol 7 (5) ◽  
pp. 900-913 ◽  
Author(s):  
Miriam K. Forbes ◽  
Robert F. Krueger
Keyword(s):  
Mental Health ◽  
United States ◽  
Great Recession ◽  
Population Level ◽  
Safety Net ◽  
The United States ◽  
Panic Attacks ◽  
The Great Recession ◽  
Additional Support ◽  
The Impact

The full scope of the impact of the Great Recession on individuals’ mental health has not been quantified to date. In this study we aimed to determine whether financial, job-related, and housing impacts experienced by individuals during the recession predicted changes in the occurrence of symptoms of depression, generalized anxiety, panic attacks, and problematic alcohol use or other substance use. Longitudinal survey data ( n = 2,530 to n = 3,293) from the national Midlife in the United States study that were collected before (2003–2004) and after (2012–2013) the Great Recession were analyzed. The population-level trend was toward improvements in mental health over time. However, for individuals, each recession impact experienced was associated with long-lasting and transdiagnostic declines in mental health. These relationships were stronger for some sociodemographic groups, which suggests the need for additional support for people who suffer marked losses during recessions and for those without a strong safety net.

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