Clinicians' decision making about involuntary commitment

Psychiatr Serv. 1998 Jul;49(7):941-5. doi: 10.1176/ps.49.7.941.

Abstract

Objective: Clinicians' decision making about involuntary commitment was examined, with a focus on the effects of patient and clinician characteristics and bed availability on decisions to detain patients, the first step in involuntary commitment.

Methods: Eighteen psychologists and social workers in the emergency service of a community mental health center completed the Risk Assessment Questionnaire for 169 consecutive patients they deemed to present some degree of risk. Forty-two patients were detained.

Results: Three underlying constructs were significantly associated with a patient's overall risk rating, which in turn predicted the decision to detain. Two were clinician characteristics: the clinician detention ratio, which reflects the proportion of patients detained by the clinician in the past three months, and the setting in which the evaluation occurred, either an in-house emergency service or a mobile crisis unit. The availability of detention beds in the community was also a significant predictor of whether a patient would be detained. No patient characteristic, including diagnosis, sex, age, or insurance status, was significantly related to the detention decision.

Conclusions: The findings suggest that the decision-making process is influenced by multiple factors, such as setting, the clinician's tendency to detain patients, and the availability of detention beds.

MeSH terms

  • Adult
  • Attitude of Health Personnel
  • Bed Occupancy
  • Chi-Square Distribution
  • Commitment of Mentally Ill*
  • Community Mental Health Centers / statistics & numerical data
  • Decision Making*
  • Emergency Services, Psychiatric* / legislation & jurisprudence
  • Emergency Services, Psychiatric* / methods
  • Factor Analysis, Statistical
  • Female
  • Health Care Rationing
  • Health Care Surveys
  • Humans
  • Male
  • Mentally Ill Persons*
  • Middle Aged
  • Models, Psychological
  • Process Assessment, Health Care
  • Regression Analysis
  • Risk Assessment
  • Triage / methods*
  • Virginia