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Record W7024428202

Risk Assessment for suicide behaviour

2009· article· en· W7024428202 on OpenAlexaboutno aff

Bibliographic record

VenueScholarship@Western (Western University) · 2009
Typearticle
Languageen
FieldComputer Science
TopicPrivacy-Preserving Technologies in Data
Canadian institutionsnot available
Fundersnot available
KeywordsConceptualizationRisk assessmentBiopsychosocial modelRisk management toolsSuicidal ideationPsychopathologyPoison controlSuicide prevention
DOInot available

Abstract

fetched live from OpenAlex

This is an audio-visual about risk assessment of suicide behavior. Part 1. Reformulating the concept of RISK and a New instrument for assessment: Risk assessment is an important clinical responsibility, which can be ‘life-saving’. Literature on risk factors has become voluminous; however a traditional risk assessment does not take into account the most relevant factors. This reflects the prevailing conceptualization of risk, which has not been fully and completely tied to clinical outcomes. Psychopathology is currently understood in biopsychosocial terms. A more progressive conceptualization of risk should consider the interplay of both, risk and protective factors. The present work proposes a model of risk assessment depending upon ‘trait’ risk and ‘state’ risk factors. The joint impact of such risk is evaluated against protective factors. It conceptualizes that risk consists of several domains and each of these domains contribute to causation of suicidal ideation. These domains are biological, psychological, social-environmental, spiritual & protective. The present study examined the utilization of a new structured clinical interview called the Scale for Impact of Suicidality Management, Assessment and Planning of Care (SIS-MAP). SIS-MAP ratings were evaluated against a group of incoming psychiatric patients over a 6-month period. Participants consist of adult male and female patients at RMHC, St.Thomas, Canada, studied between February and August 2008. Preliminary analysis supported that the SIS-MAP is a valid and reliable tool to determine the level of psychiatric care needed for adults with suicidal ideation. Clinical cut-off scores were established from the observed mean differences in the patients’ total scores and level of care needed. A canonical discriminant function analysis was conducted in order to evaluate whether SIS-MAP total scores were predictive of admission. The analysis resulted in a total 74.0% of original grouped cases were correctly classified. (Wilks Lambda = .749, p<0.001). The specificity of the scale (correctly identifying individuals who did not require admission) was 78.1% while the sensitivity of the scale (correctly identifying individuals who required admission) was 66.7%. The false positive rate was 33.3% while 21.9% of cases resulted in a false negative. The measure also demonstrated moderate-high inter-rater reliability (between 0.70 and .81 (X= .76), N=20, p<. 001). Part 2. Background [Technical report presented in APA 2009] Strategies to improve risk assessment Suicide remains to be a distinct global public health problem and the no reduction in rate of suicide continues to be a major concern of the governments of many countries. It highlights common policy directions that appear to speak directly to the practice and/or educational needs of mental health professional and juxtaposes these against the realities of their practice and educational needs. (i) Initiatives to reduce access to lethal means; (ii) Improve surveillance systems; and iii) Training for caregivers to improve delivery of effective treatments. It is argued that the suicide policy literature should consider replacing ‘improving surveillance systems’ with ‘improving the ability and capacity of professionals to engage with people who are suicidal’. Lastly, the suicide policy literature might consider refining the policy direction on additional training to indicate the need for additional post-graduate (post-basic) education and training in care of the person with suicidal tendencies, which includes dialectical behavioral therapy; the work emanating from the University of Toronto; and the skills, attitudes, and knowledge perhaps captured with the terms, engagement, co-presenting, and inspiring hope. Health policy-makers and experts on mental health and suicidal behavior from 36 Member States in the WHO European Region discussed current evidence on, practices in and targets and settings for suicide prevention, and formulated recommendations for preventive strategies. The Meeting was part of the preparations for the WHO European Ministerial Conference on Mental Health, to be held in Helsinki, Finland in January 2005. 1. The prevention of suicide and attempted suicide requires a public health approach. The burden of suicide is so large that prevention could be considered the responsibility of an entire government, under the leadership of the health ministry. 2. Suicide-prevention programmes are needed and should consider specific interventions for different groups at risk (such as elderly people and new parents), allocate tasks to different sectors (such as education, labor and social affairs) and be evaluated. 3. Health-care professionals, especially in the emergency services, should be trained in the effective identification of suicide risk and proactive collaboration with mental health services. 4. Both health professionals and the general public should be educated about suicide as early as possible, with a focus on both risk and protective factors. 5. Policy-oriented research on and evaluation of suicide prevention programmes is needed. 6. The mass media should be involved in suicide prevention via training, and use of the WHO guidance on media treatment of suicide (in Appendix 5 of From the margins to the mainstream) should be promoted. Strategies to improve education and awareness Continued education in clinical setting, using web-based learning •\tContinuing medical education program Needs to be designed and conducted across all settings for service providers. •\tPsychiatrists •\tMental health professionals •\tFamily physicians •\tLaw enforcement personnel •\tCorrectional officers

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.012
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.039
Threshold uncertainty score0.129

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.012
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0020.001
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0010.002
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0390.011

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.103
GPT teacher head0.355
Teacher spread0.252 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

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Citations0
Published2009
Admission routes1
Has abstractyes

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