Mental Health of High-Risk Urban Youth: The Housing Subsidies Paradox

This chapter illustrates the mental health clinician’s relationship with behavioral emergencies. The chapter begins by distinguishing the terms behavioral emergency and behavioral crisis, and underlying themes among all behavioral emergencies are identified. Given that most clinicians will face a behavioral emergency in their careers, the importance of enhancing the process of educating and training practitioners for such situations far beyond the minimal training that currently exists is highlighted. The chapter continues by exploring various aspects of evaluating and managing high-risk patients (i.e., those who exhibit violent tendencies toward themselves or others, and those at risk for victimization). It includes a discussion of the benefits and limitations to estimating life-threatening risk factors and specific protective factors. The chapter concludes by discussing the emotional impact that working with high-risk patients has on clinicians, and an emphasis is placed on the importance of creating a supportive work environment.

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Treating sleep problems in young people at ultra-high-risk of psychosis: study protocol for a single-blind parallel group randomised controlled feasibility trial (SleepWell)

BMJ Open ◽

10.1136/bmjopen-2020-045235 ◽

2020 ◽

Vol 10 (11) ◽

pp. e045235

Author(s):

Felicity Waite ◽

Thomas Kabir ◽

Louise Johns ◽

Jill Mollison ◽

Apostolos Tsiachristas ◽

...

Keyword(s):

Mental Health ◽

High Risk ◽

Young People ◽

Sleep Problems ◽

Qualitative Interviews ◽

Feasibility Trial ◽

Psychotic Experiences ◽

Post Intervention ◽

Ultra High Risk ◽

Randomised Controlled

BackgroundEffective interventions, targeting key contributory causal factors, are needed to prevent the emergence of severe mental health problems in young people. Insomnia is a common clinical issue that is problematic in its own right but that also leads to the development and persistence of psychotic experiences. The implication is that treating sleep problems may prevent the onset of psychosis. We collected initial case series data with 12 young people at ultra-high-risk of psychosis. Post-intervention, there were improvements in sleep, depression and psychotic experiences. Now we test the feasibility of a randomised controlled trial, with a clinical aim to treat sleep problems and hence reduce depression, psychotic experiences, and prevent transition to psychosis.Methods and analysisA randomised controlled feasibility trial will be conducted. Forty patients aged 14 to 25 years who are at ultra-high-risk of psychosis and have sleep disturbance will be recruited from National Health Service (NHS) mental health services. Participants will be randomised to receive either a novel, targeted, youth-focussed sleep intervention in addition to usual care or usual care alone. Assessor-blinded assessments will be conducted at baseline, 3 months (post-intervention) and 9 months (follow-up). The eight-session psychological intervention will target the key mechanisms which disrupt sleep: circadian rhythm irregularities, low sleep pressure, and hyperarousal. To gain an in-depth understanding of participants’ views on the acceptability of the intervention and study procedures, 16 participants (n=10 intervention, n=6 control) will take part in qualitative interviews. Analyses will focus on feasibility outcomes (recruitment, retention, and treatment uptake rates) and provide initial CI estimates of intervention effects. Thematic analysis of the qualitative interviews will assess the acceptability of the intervention and trial procedures.Ethics and disseminationThe trial has received ethical approval from the NHS Health Research Authority. Findings will be disseminated through peer-reviewed publications, conference presentations, and lay networks.Trial registration numberISRCTN85601537.

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Association Between Mental Health Conditions and Care Fragmentation: A National Study of High-Risk Older Veterans

Innovation in Aging ◽

10.1093/geroni/igaa057.1202 ◽

2020 ◽

Vol 4 (Supplement_1) ◽

pp. 373-373

Author(s):

Ranak Trivedi ◽

Fernanda Rossi ◽

Sarah Javier ◽

Liberty Greene ◽

Sara Singer ◽

...

Keyword(s):

Mental Health ◽

High Risk ◽

Health Conditions ◽

Mental Health Provider ◽

National Study ◽

Mental Health Conditions ◽

Resource Center ◽

Physical Conditions ◽

Risk Patients ◽

Care Fragmentation

Abstract Fragmented healthcare causes information loss, duplicative tests, and unwieldy self-care regimens. These challenges may be amplified among older, high-risk patients with co-occurring mental health conditions (MHC). We compared healthcare fragmentation for chronic physical conditions among Veterans with and without MHC (depression, PTSD, schizophrenia, bipolar disorder, anxiety, personality disorder, or psychosis based on ICD-9 codes). Sample included Veterans who were □65y, at high risk for 1-year hospitalization, and had □4 non-MHC visits during FY14. Visits were covered by Veterans Affairs (VA), VA-purchased care (both from VA Corporate Data Warehouse), or Medicare Parts A/B (claims data from VA Information Resource Center). Outcomes were two fragmentation measures calculated in FY15: 1) non-mental health provider count, where a higher number indicates more fragmentation, and 2) Usual Provider of Care (UPC), the proportion of care with the most frequently seen provider, where a higher number indicates less fragmentation. We used Poisson regression and GLM with binomial distribution and logit link to test the association between MHC status and fragmentation, controlling for sociodemographic characteristics (e.g., age), medical comorbidity, and driving distance to VA. Of the 125,481 Veterans included, 47.3% had 1+ MHC. Compared to older, high-risk Veterans without MHC, those with MHC saw fewer providers (pseudo R2 = 0.02) and had a higher UPC (more concentrated care; OR = 1.07). Within the VA, older, high-risk Veterans with MHC do not experience greater healthcare fragmentation. Further research is needed to determine if this is due to different needs, underuse, or appropriate use of healthcare across the groups.

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Suicide risk assessment in a large public mental health service: do suicide risk classifications identify those at risk?

Australasian Psychiatry ◽

10.1177/1039856220984032 ◽

2021 ◽

pp. 103985622098403

Author(s):

Marianne Wyder ◽

Manaan Kar Ray ◽

Samara Russell ◽

Kieran Kinsella ◽

David Crompton ◽

...

Keyword(s):

Mental Health ◽

Risk Factors ◽

Risk Assessment ◽

High Risk ◽

Suicide Risk ◽

Public Mental Health ◽

Assessment Tools ◽

Suicide Risk Assessment ◽

Public Mental Health Service ◽

Risk Assessment Tools

Introduction: Risk assessment tools are routinely used to identify patients at high risk. There is increasing evidence that these tools may not be sufficiently accurate to determine the risk of suicide of people, particularly those being treated in community mental health settings. Methods: An outcome analysis for case serials of people who died by suicide between January 2014 and December 2016 and had contact with a public mental health service within 31 days prior to their death. Results: Of the 68 people who had contact, 70.5% had a formal risk assessment. Seventy-five per cent were classified as low risk of suicide. None were identified as being at high risk. While individual risk factors were identified, these did not allow to differentiate between patients classified as low or medium. Discussion: Risk categorisation contributes little to patient safety. Given the dynamic nature of suicide risk, a risk assessment should focus on modifiable risk factors and safety planning rather than risk prediction. Conclusion: The prediction value of suicide risk assessment tools is limited. The risk classifications of high, medium or low could become the basis of denying necessary treatment to many and delivering unnecessary treatment to some and should not be used for care allocation.

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