Psychiatric hospitalisation and the risk of suicide

Kapur, Navneet

doi:10.1192/bjp.2018.22

Cited by 46 publications

(22 citation statements)

References 29 publications

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…These findings suggest that the perception that psychiatric hospitalization was coerced serves as an indicator of somewhat increased risk that patients will make a suicide attempt after discharge. Previous studies have noted that some patients may feel violated, disrespected, humiliated, or dehumanized by the experience of coercion (Newton‐Howes & Mullen, ; Svindseth, Nøttestad, & Dahl, ; Large & Kapur, ).several studies have observed that perceived coercion is inversely associated with the quality of the therapeutic relationship or with treatment satisfaction (Katsakou et al, ; Sheehan & Burns, ; Strauss et al, ). Although there was no association between perceived coercion and treatment involvement in our sample, participation in treatment is not synonymous with a therapeutic alliance.…”

Section: Discussionmentioning

confidence: 99%

Perceived Coercion During Admission Into Psychiatric Hospitalization Increases Risk of Suicide Attempts After Discharge

Jordan

McNiel

2019

Suicide & Life Threat Behav

View full text Add to dashboard Cite

Objective There is an elevated risk for suicide in the year following psychiatric hospitalization. The present study examined whether perceived coercion during admission into psychiatric hospitalization increases risk for postdischarge suicide attempts. Methods Participants were 905 psychiatric inpatients from the MacArthur Violence Risk Assessment Study that were assessed every 10 weeks during the year following discharge. Perceived coercion during admission was assessed while hospitalized, and suicide attempts were assessed following discharge. Analyses adjusted for nonrandom assignment of groups via propensity score weighting and for established correlates of postdischarge suicidal behavior. Results Of 905 participants, 67% endorsed perception of coercion into psychiatric hospitalization, and 168 (19%) made a postdischarge suicide attempt. Patients who perceived coercion during hospitalization admission were more likely to make a suicide attempt after discharge than those who did not, even after adjusting for established covariates (OR = 1.29, |z| = 2.87, p = .004, 95% CI = 1.08, 1.54). There was no interaction between recent self‐harm or suicidal ideation at time of admission and perceived coercion on postdischarge suicide attempts. Conclusions Patients’ perception of the context in which they were hospitalized is associated with a small but significant increase in their likelihood of postdischarge suicide attempts.

show abstract

Section: Discussionmentioning

confidence: 99%

Perceived Coercion During Admission Into Psychiatric Hospitalization Increases Risk of Suicide Attempts After Discharge

Jordan

McNiel

2019

Suicide & Life Threat Behav

View full text Add to dashboard Cite

show abstract

“…Or it might be that some patients are helped and others hurt by hospitalization after an SRB. If the latter is the case, as many experts believe it is, careful weighing of risks and benefits is needed to determine which patients are likely to be helped and which ones harmed by hospitalization [120]. No guidance exists currently on how this weighing should be done.…”

Section: The Need For Individualized Treatment Rulesmentioning

confidence: 99%

Suicide prediction models: a critical review of recent research with recommendations for the way forward

et al. 2019

View full text Add to dashboard Cite

Suicide is a leading cause of death. A substantial proportion of the people who die by suicide come into contact with the health care system in the year before their death. This observation has resulted in the development of numerous suicide prediction tools to help target patients for preventive interventions. However, low sensitivity and low positive predictive value have led critics to argue that these tools have no clinical value. We review these tools and critiques here. We conclude that existing tools are suboptimal and that improvements, if they can be made, will require developers to work with more comprehensive predictor sets, staged screening designs, and advanced statistical analysis methods. We also conclude that although existing suicide prediction tools currently have little clinical value, and in some cases might do more harm than good, an even-handed assessment of the potential value of refined tools of this sort cannot currently be made because such an assessment would depend on evidence that currently does not exist about the effectiveness of preventive interventions. We argue that the only way to resolve this uncertainty

show abstract

“…Although theorizing exists about the patients most likely to be helped and those most likely to be hurt by hospitalization (129), little empirical research exists on these hypotheses (90). We are attempting to develop an ITR to provide guidance in making this decision in the immediate aftermath of an outpatient suicide attempt.…”

Section: Precision Treatmentmentioning

confidence: 99%

Using Administrative Data to Predict Suicide After Psychiatric Hospitalization in the Veterans Health Administration System

et al. 2020

View full text Add to dashboard Cite

There is a very high suicide rate in the year after psychiatric hospital discharge. Intensive postdischarge case management programs can address this problem but are not costeffective for all patients. This issue can be addressed by developing a risk model to predict which inpatients might need such a program. We developed such a model for the 391,018 short-term psychiatric hospital admissions of US veterans in Veterans Health Administration (VHA) hospitals 2010-2013. Records were linked with the National Death Index to determine suicide within 12 months of hospital discharge (n=771). The Super Learner ensemble machine learning method was used to predict these suicides for time horizon between 1 week and 12 months after discharge in a 70% training sample. Accuracy was validated in the remaining 30% holdout sample. Predictors included VHA administrative variables and small area geocode data linked to patient home addresses. The models had AUC=.79-.82 for time horizons between 1 week and 6 months and

show abstract

Psychiatric hospitalisation and the risk of suicide

Cited by 46 publications

References 29 publications

Perceived Coercion During Admission Into Psychiatric Hospitalization Increases Risk of Suicide Attempts After Discharge

Perceived Coercion During Admission Into Psychiatric Hospitalization Increases Risk of Suicide Attempts After Discharge

Suicide prediction models: a critical review of recent research with recommendations for the way forward

Using Administrative Data to Predict Suicide After Psychiatric Hospitalization in the Veterans Health Administration System

Contact Info

Product

Resources

About