Sociodemographic and Clinical Characteristics of Psychiatric Inpatients Hospitalized Involuntarily and Voluntarily in a Mental Health Hospital

Determinants of compulsory hospitalisation at admission and in the course of inpatient treatment in people with mental disorders-a retrospective analysis of health records of the four psychiatric hospitals of the city of Cologne

BACKGROUND

We aimed to identify differences in predictors of involuntary psychiatric hospitalisation depending on whether the inpatient stay was involuntary right from the beginning since admission or changed from voluntary to involuntary in the course of in-patient treatment.

METHODS

We conducted an analysis of 1,773 mental health records of all cases treated under the Mental Health Act in the city of Cologne in the year 2011. 79.4% cases were admitted involuntarily and 20.6% were initially admitted on their own will and were detained later during the course of in-patient stay. We compared the clinical, sociodemographic, socioeconomic and environmental socioeconomic data (ESED) of the two groups. Finally, we employed two different machine learning decision-tree algorithms, Chi-squared Automatic Interaction Detection (CHAID) and Random Forest.

RESULTS

Most of the investigated variables did not differ and those with significant differences showed consistently low effect sizes. In the CHAID analysis, the first node split was determined by the hospital the patient was treated at. The diagnosis of a psychotic disorder, an affective disorder, age, and previous outpatient treatment as well as the purchasing power per 100 inhabitants in the living area of the patients also played a role in the model. In the Random Forest, age and the treating hospital had the highest impact on the accuracy and decrease in Gini of the model. However, both models achieved a poor balanced accuracy. Overall, the decision-tree analyses did not yield a solid, causally interpretable prediction model.

CONCLUSION

Cases with detention at admission and cases with detention in the course of in-patient treatment were largely similar in respect to the investigated variables. Our findings give no indication for possible differential preventive measures against coercion for the two subgroups. There is no need or rationale to differentiate the two subgroups in future studies.

Socio-Demographic and Clinical Characteristics of Adults With Psychotic Symptomatology Under Involuntary Admission and Readmission for Compulsory Treatment in a Referral Psychiatric Hospital in Cyprus

Socio-demographic and clinical characteristics of adults under compulsory psychiatric treatment, have not been reported adequately in Southern European countries. We investigated the socio-demographic and clinical characteristics of adults with psychotic symptomatology who were involuntarily treated in the acute Mental Health Services in Cyprus. A descriptive cross-sectional study was applied. Data collection (December 2016 to February 2018) achieved via a structured questionnaire including demographic and clinical variables. Census sampling was applied in Cyprus referral center for compulsory psychiatric treatment. The sample included 406 individuals (262 males, 144 females). Approximately 86.2% were single, 77.6% were unemployed, and 24.9% held a bachelor's degree. The most frequent clinical diagnosis was schizophrenia or a relevant psychotic disorder (86.4%). The most frequent admission cause was non-adherence to pharmacotherapy along with disorganized behavior (agitation and/or self-care deficit, and/or aggressive behavior, and/or suicidal behavior) (53.6%). Moreover, 70.7% of the sample reported a positive personal history of mental health problems, while 42.1% reported a positive family history of mental health disorders. Half of the participants (52%) were previously involuntarily admitted for compulsory treatment. Adjusted associations of readmission status were reported with Cypriot ethnicity (OR: 4.40, 95%CI: 2.58-7.50), primary education only (OR: 3.70, 95%CI: 1.64-8.37), readmission due to disorganized behavior along with non-adherence to pharmacotherapy (OR: 10.84, 95%CI: 2.69-43.72), as well as along with substance use (OR: 6.39, 95%CI: 1.52-26.82). Readmission was almost five times more likely to occur due to suicidal behavior (OR: 5.01, 95%CI: 1.09-22.99) compared to disorganized behavior not otherwise specified. Additionally, those with a diagnosis of schizophrenia were more than 12 times more frequently readmitted for compulsory treatment compared to other diagnoses (OR 12.15, 95%CI: 1.04-142). Moreover, the participants with higher secondary education had 54.6% less odds to be involuntarily re-admitted compared to Bachelor degree holders (OR 0.442, 95%CI: 0.24-0.79). A high percentage of involuntary treatment was noted due to non-adherence to pharmacotherapy and substance use. Re-evaluation of the effectiveness of relevant community interventions is suggested, as well as implementation of structured educational programs on therapy adherence during psychiatric hospitalization.

Clinical and social factors associated with increased risk for involuntary psychiatric hospitalisation: a systematic review, meta-analysis, and narrative synthesis

BACKGROUND

Use of involuntary psychiatric hospitalisation varies widely within and between countries. The factors that place individuals and populations at increased risk of involuntary hospitalisation are unclear, and evidence is needed to understand these disparities and inform development of interventions to reduce involuntary hospitalisation. We did a systematic review, meta-analysis, and narrative synthesis to investigate risk factors at the patient, service, and area level associated with involuntary psychiatric hospitalisation of adults.

METHODS

We searched MEDLINE, PsycINFO, Embase, and the Cochrane Controlled Clinical Register of Trials from Jan 1, 1983, to Aug 14, 2019, for studies comparing the characteristics of voluntary and involuntary psychiatric inpatients, and studies investigating the characteristics of involuntarily hospitalised individuals in general population samples. We synthesised results using random effects meta-analysis and narrative synthesis. Our review follows Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines and is registered on PROSPERO, CRD42018095103.

FINDINGS

77 studies were included from 22 countries. Involuntary rather than voluntary hospitalisation was associated with male gender (odds ratio 1·23, 95% CI 1·14-1·32; p<0·0001), single marital status (1·47, 1·18-1·83; p<0·0001), unemployment (1·43, 1·07-1·90; p=0·020), receiving welfare benefits (1·71, 1·28-2·27; p<0·0001), being diagnosed with a psychotic disorder (2·18, 1·95-2·44; p<0·0001) or bipolar disorder (1·48, 1·24-1·76; p<0·0001), and previous involuntary hospitalisation (2·17, 1·62-2·91; p<0·0001). Using narrative synthesis, we found associations between involuntary psychiatric hospitalisation and perceived risk to others, positive symptoms of psychosis, reduced insight into illness, reduced adherence to treatment before hospitalisation, and police involvement in admission. On a population level, some evidence was noted of a positive dose-response relation between area deprivation and involuntary hospitalisation.

INTERPRETATION

Previous involuntary hospitalisation and diagnosis of a psychotic disorder were factors associated with the greatest risk of involuntary psychiatric hospitalisation. People with these risk factors represent an important target group for preventive interventions, such as crisis planning. Economic deprivation on an individual level and at the population level was associated with increased risk for involuntary hospitalisation. Mechanisms underpinning the risk factors could not be identified using the available evidence. Further research is therefore needed with an integrative approach, which examines clinical, social, and structural factors, alongside qualitative research into clinical decision-making processes and patients' experiences of the detention process.

FUNDING

Commissioned by the Department of Health and funded by the National Institute of Health Research (NIHR) via the NIHR Mental Health Policy Research Unit.