The case (n = 146) and control groups (n = 104) did not differ significantly with regards to sociodemographic characteristics. The majority of the participants who had attempted suicide did so with high intent to die, and expected to die without medical intervention. The primary method of attempt was pharmaceutical overdose among the case participants (73.3%). Results showed impulsivity (odds ratio [OR] = 1.15, 95% confidence interval [CI] = 1.03–1.30) and borderline personality symptoms (OR = 1.07, 95% CI = 1.01–1.13) were significantly associated with attempted suicide.

Moreover, given the difficulties of identifying those at risk of suicide from populations of psychiatric patients, identification of warning signs and behaviours associated with suicide among psychiatric patients can aid in suicide prevention. Patterns and behaviours associated with suicide attempts are important to characterize within psychiatric populations, in order to distinguish individuals in this group who attempt suicide from those with no history of suicide attempts. Identifying trends in behaviours and methods of suicidal attempts within a sample of patients with psychiatric disorders will aid in the movement towards developing large-scale suicide prevention methods in clinical settings.

While individuals with psychiatric illnesses represent the vast majority of the individuals who attempt suicide [ 4 ], only a small proportion of those with psychiatric illnesses attempt suicide. Known risk factors for suicidal behaviours are largely based on studies of general community populations and these factors include prior suicide attempts, underlying psychiatric and substance use disorders, single marital status, unemployment, and major life stressors [ 8 – 12 ]. However, reliable predictors of suicidal behaviour among populations with serious psychiatric disorders remain elusive. Wide-scale screening of psychiatric patients has been suggested as a method of early detection of suicidal behaviour [ 13 ], although feasibility greatly limits the ability to comprehensively screen all patients. Some studies have examined suicidal risk factors among patients with specific psychiatric disorders [ 14 – 16 ], yet suicidal risk factors among broad psychiatric populations who typically present to clinical settings, including patients with multiple psychiatric diagnoses, are not yet clearly established. Defining high-risk psychiatric patients will allow clinicians to effectively screen patients for suicidal behaviour.

Suicidal behaviours are complex and can be challenging to foresee even among patients receiving medical and psychiatric care [ 1 , 2 ]. Suicide is the second leading cause of death among 15–29 year olds worldwide [ 3 ], with an even greater prevalence of non-fatal suicidal behaviour [ 4 ]. Attempted suicide, defined as self-harm behaviour with intent to die [ 5 ], may occur up to 20 times more frequently than completed suicide [ 4 , 6 ]. Attempted suicide is associated with adverse, long-term outcomes, including psychiatric and medical comorbidity, hospitalization, repeated suicide attempts, poverty, chronic stress, and stigma [ 7 , 8 ]. Considering the personal and public health burden of suicide on global and local scales, it is necessary that preventative and rehabilitative strategies be developed to manage those presenting with suicidal behaviour.

Methods

The participants and data used in this investigation were collected for the Study of Determinants of Suicide Conventional and Emergent Risk (DISCOVER) [17], a case-control study designed to investigate risk factors of attempted suicide. Participants were recruited between March 2011 and November 2014 in Hamilton, Ontario, Canada. Data were collected at St. Joseph’s Healthcare and Hamilton Health Sciences hospitals. The study procedures were approved by the Hamilton Integrated Research Ethics Boards (HIREB) (REB number 10–661 for St. Joseph’s Healthcare Hamilton and 11–3479 for Hamilton Health Sciences Hospitals).

We included adults (≥ 18 years of age) who were able to provide written informed consent, communicate in English, and who were willing to follow study procedures. Fig 1 defines case and control groups and outlines the recruitment process. Cases included psychiatric inpatients who had made a suicide attempt, defined as self-directed injury with specific intent to die and that necessitated admission to a medical or psychiatric hospital ward. We had initially intended to recruit psychiatric inpatients who had made a suicide attempt within three months of recruitment (case-recent group). However, given the challenges of recruiting this particular patient population, we also included psychiatric inpatients who had a lifetime history of attempted suicide (case-past group). The control group consisted of adult psychiatric inpatients who had never attempted suicide and who were admitted to the same psychiatric hospital within the same time frame as the cases. The predefined study design included matching of case and control participants by sex and age (±5 years); however given the difficulties in recruiting case participants, matching was not implemented in order to reach our target sample size.

Clinical staff identified eligible hospitalized patients who had the mental capacity to provide written informed consent. These patients were consecutively approached by trained research staff who inquired about their interest in participating in the study and provided study information. Patients who agreed to participate were asked to read and sign consent forms describing study procedures. The local institutional ethics boards approved consent forms and procedures. Research assistants conducted a structured face-to-face interview consisting of validated questionnaires, described below. Participants were asked about sociodemographic characteristics including age, sex, education and socioeconomic status. We assessed intention to die as a result of the suicide attempt by asking the participants directly and measured level of intent in relation to participants’ most recent suicide attempt using the Pierce Suicide Intent Scale (P-SIS) [18]. The P-SIS consists of 12 questions assessing the circumstances during the suicide attempt, self-reported risk, and medical risk. The domain scores are tabulated to provide an overall assessment of level of intent to die as a result of a suicide attempt. This scale distinguishes self-harm behaviour from suicide attempts. The overall score on the P-SIS ranges from 0 to 25, with a maximum 3 or 4 points for each question, and higher scores corresponding to higher intent to die. Total scores of 0–3 represent low intent, 4–10 represent moderate intent, and 10 or more represent high intent to die. The scale has shown high test-retest reliability (r = 0.97).

Participants also completed the 30-item Barratt Impulsiveness Scale (BIS) [19] to assess trait impulsivity and the 23-item Borderline Symptom List (BSL) [20] to assess borderline personality symptoms. The BIS questionnaire was chosen to assess impulsivity as a risk factor independent of psychiatric diagnoses. The BIS measures impulsive behaviours on attentional, motor and nonplanning factors. Each question asks about an impulsive trait or behaviour on a 4-point Likert scale (Rarely/Never, Occasionally, Often, Almost Always/Always). The questionnaire has an overall maximum score of 120 and higher scores represent higher impulsivity, such that an increase of 4 points is indicative of an additional impulsive trait or behaviour. The questionnaire has shown good internal consistency (Cronbach’s α = 0.83) [19].

The BSL was used as a measure of borderline personality symptoms, with higher scores on representing increased severity of symptoms. Each question asks about a borderline personality symptom on a 5-point Likert scale (Not at all = 0, A little = 1, Rather = 2, Much = 3, Very strong = 4). The overall score is determined by dividing the sum of the individual item scores with the total number of items (overall score = sum/23 for this study). Although there is no clinical cut-off for diagnosis of borderline personality disorder on the BSL, researchers found a mean score of 2.05 (SD = 0.90) in a sample of borderline personality disorder patients. For the purposes of this study, we determined and reported the mean overall score for the case and control groups as described above, however we used the total sum of the individual questions as a continuous variable for the multivariable regression model (maximum score = 92). Therefore, a 4-point increase represented an additional borderline personality symptom. The questionnaire has shown good internal consistency (Cronbach’s α = 0.97) and test-retest reliability (r = 0.82, p<0.0001).

The Mini International Neuropsychiatric Interview (M.I.N.I.) [21] was administered to determine whether participants met criteria for DSM-IV Axis I psychiatric disorders. We used the M.I.N.I. to determine if participants had existing diagnoses of (1) mood disorders (major depressive disorder, bipolar disorder), (2) anxiety disorders (generalized anxiety disorder, panic disorder, social phobia, obsessive-compulsive disorder, post-traumatic stress disorder), (3) substance use disorders (alcohol dependence/abuse and substance dependence/abuse), and (4) psychotic disorders. The M.I.N.I. also determined if participants met the criteria for antisocial personality disorder. For this study, an experienced psychiatrist determined the participants’ primary Axis I psychiatric diagnosis using the hierarchical rules in the DSM-III [22] that were carried through to the DSM-IV classification system [23]. Therefore, the primary diagnosis was assigned using the following hierarchy: (1) substance use disorder, (2) psychotic disorder, (3) mood disorder, and (4) anxiety disorder.

STATA version 13 was used to perform all statistical analyses. For univariate analyses, we used independent sample t-tests to compare means of continuous variables and chi-square tests to compare proportions of categorical variables between cases and controls. Non-parametric equivalents (i.e. Mann-Whitney-U tests) were used for continuous variables that were not normally distributed. Fisher’s exact test was used to compare categorical variables that had an expected frequency of less than 5 in a particular cell. Simple Pearson’s correlations were used to assess the linear relationship between two normally distributed variables and Spearman correlations were used for non-normally distributed variables. Multivariable logistic regression analysis was utilized to assess clinical risk factors associated with suicidal attempts, by comparing cases to controls. The Hosmer-Lemeshow test was used to assess the goodness-of-fit of the regression model. Multi-collinearity between independent variables was assessed using the variance inflation factor (VIF), and variables with VIF>10 were considered for exclusion from the model. The level of significance was set at alpha = 0.05, and we included clinically important variables based on the literature regarding psychiatric populations in the logistic regression model [14–16, 24]. As a sensitivity analysis, we conducted multiple imputation using chained equations (MICE) to adjust for missing data in the multivariable regression model [25]. Age and sex were used to aid in the prediction of missing values in the imputed datasets. The reporting of this study is in accordance with the Strengthening of Reporting of Observational Studies in Epidemiology (STROBE) guidelines [26].