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. Author manuscript; available in PMC: 2007 Jul 17.
Published in final edited form as: Psychol Med. 2006 Aug 29;36(12):1747–1757. doi: 10.1017/S0033291706008786

Risk factors for twelve-month suicide attempts in the National Comorbidity Survey Replication (NCS-R)

Guilherme Borges 1, Jules Angst 1, Matthew K Nock 1, Ayelet Meron Ruscio 1, Ellen E Walters 1, Ronald C Kessler 1
PMCID: PMC1924761  NIHMSID: NIHMS19629  PMID: 16938149

Abstract

BACKGROUND

Clinical judgments about the likelihood of suicide attempt would be aided by an index of risk factors that could be quickly assessed in diverse settings. We sought to develop such a risk index for 12-month suicide attempts among suicide ideators.

METHOD

The National Comorbidity Survey Replication (NCS-R), a household survey of adults ages 18+, assessed 12-month occurrence of suicide ideation, plans, and attempts in a subsample of 5692 respondents. Retrospectively assessed correlates include history of prior suicidality, socio-demographics, parental psychopathology, and 12-month DSM-IV disorders.

RESULTS

Twelve-month prevalence estimates of suicide ideation, plans, and attempts are 2.6%, 0.7%, and 0.4%. Although ideators with a plan are more likely to make an attempt (31.9%) than those without a plan (9.6%), 43% of attempts were described as unplanned. History of prior attempts is the strongest correlate of 12-month attempts. Other significant correlates include shorter duration of ideation, presence of a suicide plan, and several socio-demographic and parental psychopathology variables. Twelve-month disorders are not powerful correlates. A four-category summary index of correlates is strongly related to attempts among ideators (AUC = .88). The distribution (conditional probability of attempt) of the risk index is 19.0% very low (0.0%), 51.1% low (3.5%), 16.2% intermediate (21.3%), and 13.7% high (78.1%). Two-thirds (67.1%) of attempts were made by ideators in the high risk category.

CONCLUSIONS

A short, preliminary risk index based on retrospectively reported responses to fully structured questions is strongly correlated with 12-month suicide attempts among ideators, with a high concentration of attempts among high-risk ideators.

Between 2% and 5% of people in the US attempt suicide sometime in their lives (Moscicki, 1999). Although only a small minority result in death, each attempt carries a chance of death, serious long-term physical injury, and psychological suffering. Moreover, history of prior attempts strongly predicts subsequent attempts and death (Fawcett et al., 1990; Neeleman et al., 2004; Schmidtke et al., 1996). Clinical judgments about likelihood of suicide attempts consequently have important clinical implications. Although considerable research has attempted to develop suicide prediction models to improve clinical judgments, results have been limited in four ways. Many (Beautrais et al., 1996; Bourgeois et al., 2004; Dilsaver et al., 1994; Gould et al., 1996; Hawton et al., 2003; Johnson et al., 2002; Jollant et al., 2005; Keilp et al., 2001; Koivumaa-Honkanen et al., 2001; Meltzer et al., 2003; Palmer et al., 2005; Shaffer et al., 1996; Strakowski et al., 1996), although not all (Kessler et al., 1999; Mann et al., 1999; Murphy et al., 1992), such studies focused on a restricted set of predictors. Many used clinical rating scales that may be infeasible to administer in some clinical settings. Many used narrowly defined samples (e.g., restricted age range, patients with prior attempts). Most focused on long-term prediction (5–20 years) rather than short-term risk.

This report presents results of a preliminary retrospective attempt to explore the feasibility of developing a clinically useful risk index for 12-month suicide attempts among ideators based on analysis of a cross-sectional survey of the US household population. We focus on individuals reporting suicidal ideation, as it is after evidence of ideation that most suicide risk assessments begin. Previous research has shown that up to 20% of ideators in a given year make a suicide attempt during that year (Kessler et al., 2005a; Kuo et al., 2001), justifying this focus. We use an actuarial, data-driven approach similar to the approach used successfully to develop prediction models for violent behavior (Dawes et al., 1989; Harris et al., 2004; Harris et al., 2003; Hilton et al., 2004; Mossman, 1994), and less successfully to predict repetitive suicidal behavior (Buglass & Horton, 1974; Corcoran et al., 1997; Hawton & Fagg, 1995; Kreitman & Foster, 1991). We focus on potential risk factors that clinicians can assess quickly using fully structured assessments.

METHOD

Sample

Data come from the National Comorbidity Survey Replication (NCS-R). The sample of 9,282 respondents ages 18 and older was based on a multi-stage clustered area probability sampling design representative of the US household population. Interviews were carried out between February 2001 and December 2003 (Kessler & Merikangas, 2004). The response rate was 70.9%. Sample households were mailed advance materials followed by an in-person interviewer visit to obtain informed consent. Consent was verbal rather than written to parallel procedures in the baseline NCS (Kessler et al., 1994). Respondents were given a $50 financial incentive. The Human Subjects Committees of both Harvard Medical School and the University of Michigan approved these recruitment and consent procedures.

The survey was administered in two parts. Part I included the core diagnostic assessment administered to all respondents. Part II, which assessed additional disorders and correlates, was administered to 5,692 respondents consisting of all who met lifetime criteria for a Part I disorder plus a probability subsample of others. The analyses reported here were carried out in the Part II sample, weighted to adjust for over-sampling Part I respondents with a mental disorder, differential probabilities of selection, systematic non-response, and residual socio-demographic and geographic differences between the sample and the 2000 Census. NCS-R sampling and weighting are discussed elsewhere (Kessler et al., 2004).

Measures of suicidal behavior

Suicidal behavior was assessed using questions from the baseline NCS (Kessler et al., 1999) about lifetime occurrence, age of onset, and recency of suicide ideation (“Have you ever seriously thought about committing suicide?”), suicide plans (“Have you ever made a plan for committing suicide?”), and suicide attempts (“Have you ever attempted suicide?”). Based on evidence that reports of such embarrassing behaviors are higher in self-administered than interviewer-administered surveys (Turner et al., 1998), these questions were printed in a self-administered booklet and referred to by letter. Interviewers asked respondents to report whether the experiences ever happened to them and, if so, to report the age of onset and recency of the experiences. Respondents who reported that “Experience C” (i.e., a suicide attempt) happened to them in the past 12 months were presented with three statements and asked to give the number of the statement that best described their experience. The three statements were: “1. I made a serious attempt to kill myself and it was only luck that I did not succeed; 2. I tried to kill myself, but knew that the method was not fool-proof; 3. My attempt was a cry for help. I did not intend to die.” Questions were read to respondents who were unable to read.

Consistent with contemporary definitions distinguishing suicidal from self-injurious behavior (American Psychiatric Association, 2003; O’Carroll et al., 1996), only respondents who endorsed statements 1 or 2 were considered suicide attempters. Respondents who endorsed statement 3 were considered to have made a suicide gesture. An earlier analysis of the baseline NCS (Nock & Kessler, in press) showed that correlates of endorsing the first two statements were similar to previously documented predictors of completed suicide, while correlates of endorsing the third statement were quite different, justifying the present classification scheme. Three measures of prior suicidal behavior were retrospectively evaluated as possible risk factors for 12-month attempts: presence-absence of any previous attempt (ignoring self-reported intent to die), age of onset of suicidal ideation, and years since onset of ideation.

Other possible risk factors

We examined three other sets of possible risk factors: socio-demographics, parental psychopathology, and 12-month respondent DSM-IV mental disorders. The socio-demographics included age, sex, race-ethnicity, marital status, education, religious affiliation, and family income. The measures of parental psychopathology included parent attempted-completed suicide and five disorders – major depression, panic disorder, generalized anxiety disorder, substance dependence, and antisocial personality disorder – exhibited during the respondent’s childhood. Parent disorders were assessed with the Family History RDC Interview (Andreasen et al., 1977) and its expansion (Kendler et al., 1997), a method known to have good test-retest reliability but uncertain validity (Zimmerman et al., 1988). Respondent disorders were assessed with Version 3.0 of the WHO Composite International Diagnostic Interview (CIDI) (Kessler & Ustun, 2004). The assessment included DSM-IV anxiety, mood, impulse-control, and substance use disorders. NCS-R clinical reappraisal interviews found CIDI diagnoses to have generally good concordance with blinded diagnoses based on the Structured Clinical Interview for DSM-IV (First et al., 2002) in a probability subsample of NCS-R respondents (Kessler et al., 2005b). Organic exclusion rules and diagnostic hierarchy rules were used in making all respondent diagnoses.

Statistical analyses

Cross-tabulations were used to estimate 12-month prevalence of ideation, plans, and attempts. Multivariate logistic regression analysis (Hosmer & Lemeshow, 1989) was used to estimate associations of retrospectively assessed risk factors with attempts. Logistic regression coefficients and 95% confidence intervals (CI’s) were converted to odd-ratios (OR’s) for ease of interpretation. We also estimated associations of the risk factors with 12-month suicide ideation and, among ideators, with suicide plans. Continuous variables were divided into categories to minimize effects of extreme values. Categories were collapsed to stabilize associations when OR’s did not differ meaningfully.

Although the NCS-R is a large survey, the number of respondents with 12-month suicidal ideation is relatively small (n = 236) and 12-month attempters even smaller (n = 37). Statistical power is consequently inadequate to detect meaningful OR’s of risk factors with low prevalence. For example, for risk factors with .05–.10 prevalence, the minimum OR’s detectable with .70 power using .05-level two-sided tests and correction for design effects are 3.3–4.4. We consequently focused on substantive rather than statistical significance in constructing the risk index, considering an OR of approximately 2.0 meaningful whether or not it was statistically significant. Standard errors and significance tests were estimated using the Taylor series method (Wolter, 1985) using SUDAAN software (Research Triangle Institute, 2002) to adjust for design effects. Multivariate significance was evaluated using Wald χ2 tests based on design-corrected coefficient variance-covariance matrices. Statistical significance was evaluated using two-tailed .05-level tests.

RESULTS

Prevalence

Twelve-month prevalence estimates of suicide ideation, plans, and attempts are 2.6%, 0.7%, and 0.4%. (Table 1) These are slightly lower than estimates previously reported for respondents ages 18–54 in the NCS-R (Kessler et al., 2005a), presumably because adults older than 54 have lower prevalence of these outcomes than younger adults. More than one in four respondents with 12-month suicide ideation reported having a plan. Ideators with a plan were more likely to make an attempt (31.9%) than those who reported not having a plan (i.e., impulsive suicide attempt; 9.6%) (χ21 = 9.1, p = .004). Despite the comparatively low conditional probability of making an attempt in the absence of reporting a plan, such cases constitute approximately 43% of all attempts.

Table 1.

Twelve-month prevalence of suicide ideation, plans, and attempts

Prevalence in the total sample
Prevalence among ideators1
Ideation Plan Attempt Plan Attempt with a plan Attempt without a plan
% (se) % (se) % (se) % (se) % (se) % (se)
Male 2.2 (0.2) 0.7 (0.2) 0.4 (0.1) 32.3 (6.2) 27.5 (9.5) 11.4 (5.1)
Female 3.0 (0.3) 0.8 (0.1) 0.5 (0.1) 25.8 (4.0) 35.4 (9.9) 8.5 (3.8)
Total 2.6 (0.2) 0.7 (0.1) 0.4 (0.1) 28.3 (3.4) 31.9 (7.4) 9.6 (3.4)
 (n) (5692) (5692) (5692) (236) (68) (168)
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1

The sample included 236 12-month ideators, 68 who reported a 12-month plan and 168 who reported not having a plan. A total of 37 ideators made a 12-month attempt (21 planned and 16 reported to be unplanned). These numbers are all considerably higher than their prevalence in the total sample might suggest because the Part II sample (to whom suicide questions were administered) over-sampled respondents with DSM-IV disorders from the larger Part I sample.

Correlates of 12-month suicide attempts among ideators

Socio-demographics

Significant socio-demographic correlates (OR’s in parentheses) of 12-month suicide attempts among ideators include being Non-Hispanic Black (5.0) and having low income (4.5). (Table 2) Three other socio-demographic variables also have elevated OR’s (2.9–3.6), although they are not statistically significant: age less than 45, 12 or more years education, and previously married. The first of these three is also significantly related to suicide ideation and plans.

Table 2.

Socio-demographic correlates of 12-month suicide ideation in the total sample, suicide plans among ideators, and suicide attempts among ideators1

Among ideators
Ideation Plan Attempt
OR (95% CI) OR (95% CI) OR (95% CI)
Age2
 18–44 2.2 (1.5–3.0) 2.6 (1.1–6.3) 2.9 (0.6–14.2)
 45+ 1.0 -- 1.0 -- 1.0 --
  χ21 (p-value) 20.3 (<.001)* 4.8 (.029)* 1.8 (.17)
Sex
 Female 1.3 (1.0–1.8) 0.7 (0.3–1.5) 1.2 (0.3–5.1)
 Male 1.0 -- 1.0 -- 1.0 --
  χ21 (p-value) 3.2 (.07) 0.9 (.33) 0.0 (.84)
Race-ethnicity
 Non-Hispanic White 1.0 -- 1.0 -- 1.0 --
 Non-Hispanic Black 0.9 (0.5–1.4) 0.9 (0.4–2.2) 5.0 (1.4–17.8)
 Hispanic 0.9 (0.5–1.6) 0.8 (0.2–3.0) 1.1 (0.2–6.1)
 Other 0.9 (0.5–1.4) 2.9 (0.8–10.5) 1.0 (0.1–21.4)
  χ23 (p-value) 0.7 (.88) 3.1 (.38) 10.3 (.016)*
Education
 Less than high school 1.0 -- 1.0 -- 1.0 --
 High school graduate or more 0.8 (0.6–1.3) 0.8 (0.3–2.1) 2.9 (0.6–13.5)
  χ23 (p-value) 0.8 (.37) 0.3 (.59) 1.9 (.16)
Family income3
 Poverty 1.8 (1.4–2.4) 1.0 (0.5–2.0) 4.5 (1.6–12.5)
 All others 1.0 -- 1.0 -- 1.0 --
  χ21 (p-value) 19.0 (<.001)* 0.0 (.95) 8.7 (.003)*
Marital status4
 Previously married 1.2 (0.8–1.8) 1.6 (0.7–3.5) 3.6 (0.8–16.4)
 All others 1.0 -- 1.0 -- 1.0 --
  χ21 (p-value) 0.6 (.43) 1.4 (.24) 2.8 (.09)
Religion
 Protestant 1.0 -- 1.0 -- 1.0 --
 Catholic 0.6 (0.4–0.9) 1.1 (0.5–2.4) 1.1 (0.2–5.4)
 All other religions 1.1 (0.6–1.8) 0.7 (0.3–1.6) 0.7 (0.1–6.3)
 None 1.5 (1.0–2.5) 0.8 (0.3–2.2) 1.1 (0.2–6.1)
  χ23 (p-value) 17.8 (<.001)* 0.9 (.82) 0.3 (.96)
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*

Significant at the .05 level, two-sided test

1

Based on multivariate logistic regression equations.

2

Age was originally classified into four categories (18–29, 30–44, 45–59, 60+) and collapsed into this dichotomy based on the OR’s in the collapsed categories not differing significantly.

3

Family income was originally classified into four categories based on the ratio of income to number of family members: less than or equal to the official Department of Labor federal poverty line (defined in the table as families living in poverty), 1–3, 3–6, and 6+ times the poverty line. The dichotomous classification used here is based on the OR’s in the collapsed categories not differing significantly.

4

Marital status was originally classified into separate categories of married, cohabiting, separated-divorced, widowed, and never married. The dichotomous classification used here is based on the OR’s in the collapsed categories not differing significantly.

History of suicidal behavior

Controlling for socio-demographics, respondents with a history of prior attempts have an extremely high OR (95% CI in parentheses) of 12-month attempts: 58.0 (19.8–169.8). Two other aspects of prior suicidal behavior also are meaningfully related to 12-month attempts among ideators: 0–15 years (the lower one-third of the distribution) since first onset of ideation [3.3 (0.7–15.3)], and 12-month suicide plan [3.1 (0.9–10.3)], although neither is statistically significant. Age of onset of ideation, in comparison, is not a significant correlate of 12-month attempts.

Parental psychopathology

The data are too sparse to evaluate the separate associations of retrospectively reported maternal-only, paternal-only, and both-parent psychopathology with adequate statistical power. We consequently used summary measures of disorders in either-both parents as correlates of 12-month suicide attempts among ideators. Significant correlates (OR’s in parentheses) include parental depression (15.7), generalized anxiety disorder (3.8), and panic disorder (6.0). (Table 3) Parental antisocial personality disorder also has a meaningfully elevated OR (1.9).

Table 3.

Associations of parental psychopathology during respondent’s childhood with 12-month suicide ideation in the total sample, suicide plans among ideators, and suicide attempts among ideators1

Among ideators
Ideation Plan Attempt
OR (95% CI) OR (95% CI) OR (95% CI)
Suicide attempt 3.0* (1.7–5.1)* 1.3 (0.4–4.1) 0.8 (0.3–2.2)
Major depression 2.4 (0.9–6.6) 0.5 (0.1–4.3) 15.7* (2.9–83.7)*
Panic disorder 2.1* (1.4–3.1)* 1.8 (0.7–4.5) 6.0* (1.1–31.4)*
Generalized anxiety disorder 2.5* (1.8–3.6)* 1.5 (0.6–3.8) 3.8* (1.2–11.4)*
Substance dependence 2.1* (1.3–3.4)* 1.0 (0.3–3.4) 0.2 (0.0–1.3)
Antisocial personality disorder 2.0* (1.3–3.0)* 1.0 (0.3–3.0) 1.9 (0.5–7.5)
 (n) (5692) (236) (236)
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*

Significant at the .05 level, two-sided test

1

Based on separate multivariate logistic regression equations for each indicator of parental psychopathology, controlling for socio-demographics and the respondent’s history of prior suicidal behavior.

Respondent 12-month DSM-IV disorders

Respondent 12-month DSM-IV disorders are consistently significant correlates (OR’s in the range 2.1–14.9) of 12-month ideation even after controlling for socio-demographics, prior suicidal behavior, and parental psychopathology. (Table 4) A strong dose-response relationship exists between number of disorders and odds of ideation (χ22 = 269.1, p < .001). The pattern is attenuated, though, in statistically predicting suicide plans among ideators, with only four of 19 disorders significant and the dose-response relationship with number of disorders considerably weaker (χ22 = 13.4, p = .001). The pattern is even more attenuated in statistically predicting suicide attempt among ideators after controlling for suicide plan, with only three disorders significant (4.5–7.4) and the dose-response relationship not significant (χ22 = 0.3, p = .960).

Table 4.

Associations of 12-month DSM-IV disorders with 12-month suicide ideation in the total sample, suicide plans among ideators, and suicide attempts among ideators1

Among ideators
Ideation Plan Attempt
OR (95% CI) OR (95% CI) OR (95% CI)
I. Anxiety disorders
 Panic disorder 8.5* (6.1–12.0) 2.0 (0.8–4.7) 1.0 (0.3–3.3)
 Agoraphobia without panic 5.1* (2.3–11.6) 3.3 (0.8–14.1) 1.5 (0.0–59.8)
 Generalized anxiety disorder 4.9* (2.9–8.1) 0.9 (0.4–1.8) 4.5* (1.4–14.4)
 Specific phobia 4.1* (3.0–5.5) 1.6 (0.7–3.4) 1.1 (0.4–3.3)
 Social phobia 6.6* (4.8–9.2) 3.5* (1.7–7.0) 1.7 (0.5–6.1)
 Post-traumatic stress disorder 6.4* (4.2–9.5) 2.2 (0.9–5.4) 1.0 (0.2–4.3)
 Obsessive-compulsive disorder 6.9* (2.1–22.4) 2.7 (0.3–26.5) 1.1 (0.1–8.9)
 Adult separation anxiety disorder 5.5* (2.3–13.1) 0.8 (0.1–4.3) 0.4 (0.0–5.9)
 Any anxiety disorder 7.2* (5.4–9.6) 3.2* (1.4–7.2) 1.0 (0.2–4.6)
II. Mood disorders
 Major depressive disorder 8.7* (6.6–11.4) 2.4* (1.1–5.0) 0.8 (0.3–2.0)
 Dysthymic disorder 6.2* (3.5–11.2) 2.6* (1.1–6.1) 1.1 (0.2–7.1)
 Bipolar disorder 9.6* (6.4–14.3) 1.7 (0.7–4.6) 1.7 (0.4–7.0)
 Any mood disorders 14.8* (10.5–20.9) 4.3* (2.0–9.4) 1.2 (0.4–3.8)
III. Impulse-control disorders
 Intermittent explosive disorder 2.1* (1.1–4.2) 0.7 (0.2–2.7) 0.3 (0.0–2.5)
 Attention-deficit hyperactivity disorder 4.4* (2.8–6.9) 2.0 (0.8–5.3) 0.5 (0.1–2.2)
 Conduct disorder 2.8* (1.1–7.2) 0.7 (0.1–7.6) 7.3* (1.4–37.2)
 Oppositional-defiant disorder 14.9* (7.2–31.0) 1.7 (0.4–7.3) 1.5 (0.4–6.2)
 Any impulse-control disorder 4.4* (3.1–6.3) 1.4 (0.6–3.2) 0.6 (0.2–1.6)
IV. Substance use disorders
 Alcohol abuse or dependence 4.8* (3.0–7.7) 0.9 (0.3–2.4) 0.9 (0.2–4.2)
 Alcohol dependence 7.4* (3.7–14.8) 3.2 (1.4–7.0) 0.6 (0.1–4.8)
 Illicit drug abuse or dependence 4.1* (2.1–8.0) 1.1 (0.3–3.9) 2.9 (0.7–11.6)
 Illicit drug dependence 11.2* (4.5–27.9) 1.6 (0.4–6.9) 7.4* (2.0–27.5)
 Any substance use disorder 5.1* (3.2–8.2) 1.2 (0.5–2.8) 0.9 (0.3–3.3)
V. Number of disorders
 Any 12.6* (8.5–18.7) 4.0* (1.1–15.0) 1.1 (0.1–8.8)
 Exactly one 5.8* (3.6–9.3) 2.1 (0.5–8.8) 0.9 (0.1–7.1)
 Exactly two 15.6* (9.6–25.5) 2.5 (0.5–12.6) 0.9 (0.1–9.8)
 Three or more 33.7* (21.2–53.7) 6.8* (1.7–27.1) 1.2 (0.1–11.4)
  (n) (5692) (236) (236)
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*

Significant at the .05 level, two-sided test

1

Based on separate multivariate logistic regression equations for each DSM-IV disorder and a single equation for number of disorders, controlling for a risk profile defined by the cross-classification of history of prior suicide attempts with a count of other predictors evidencing meaningful OR’s in previous equations (socio-demographics, respondent’s history of prior suicidal behavior, parental psychopathology).

A summary risk index for 12-month suicide attempt among ideators

A summary risk index was constructed by cross-classifying the dichotomy for history of prior attempts with a 0–11 count of the other risk factors with substantively meaningful OR’s. The latter include five socio-demographics (age 18–44, Non-Hispanic Black, 12 or more years education, low income, previously married), shorter duration of ideation (0–15 years since onset of ideation), having a suicide plan in the prior 12 months, and four indicators of parental psychopathology (depression, generalized anxiety disorder, panic disorder, antisocial personality disorder). History of prior attempts was distinguished from other risk factors because of its high OR. A 0–11 count of the other risk factors was used despite the wide range of OR’s (1.9–15.7) to avoid over-fitting the sparse data and to create a scoring rule that was simple and clinically feasible.

Inspection of the relationship between the 0–11 summary measure and 12-month attempts led us to collapse the summary measure into a trichotomy based on the number of risk factors present (0–2, 3–4, 5–11). A six-category risk index was created by cross-classifying this trichotomy with prior attempts. The area under the receiver operator characteristic curve (AUC) of this index is .89 in statistically predicting 12-month attempts among ideators. This means that a randomly selected ideator who attempted suicide in the 12 months before the interview could be distinguished after the fact with 89% accuracy from a randomly selected ideator who did not make a 12-month attempt based on their index scores. AUC increased only modestly (to .90) when we added information about 12-month DSM-IV disorders, leading us not to include respondent disorders in the final index.

Further evaluation showed that the six-category index could be collapsed to four categories without a meaningful loss of information (AUC = .88). (Table 5) The first category (very low risk; 19% of all ideators) includes ideators with no history of prior attempts and a low number of other risk factors, none of whom made a 12-month attempt. The second category (low risk; 51% of all ideators) includes ideators with no history of prior attempts and a medium number of other risk factors, 3.5% of whom made a 12-month attempt. The third category (intermediate risk; 16.2% of all ideators) combines ideators who have a history of prior attempts and a low number of other risk factors with ideators who have no history of prior attempts and a high number of other risk factors. Approximately one-fifth of respondents in this category (21.3%) made a 12-month attempt. The fourth category (high risk; 13.7% of all ideators) combines ideators who have a history of prior attempts and either a medium or high number of other risk factors. Respondents in this category had a 78.1% probability of making a 12-month attempt, accounting for 67.1% of all such attempts. Sensitivity analysis found only a small reduction in prediction accuracy (AUC = .84) when the sample of attempters was restricted to respondents who endorsed the most extreme of the three NCS-R intent statements (i.e., “I made a serious attempt to kill myself and it was only luck that I did not succeed.”).

Table 5.

Distribution of the summary risk index and association with 12-month suicide attempts among ideators (n=236)

Prevalence among ideators Probability of suicide attempt
% (se) % (se)
Risk category1
 Very low 19.0 (2.7) .000 --
 Low 51.1 (3.3) .035 (.017)
 Intermediate 16.2 (1.7) .213 (.073)
 High 13.7 (2.6) .781 (.077)
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1

Very low risk is defined as having no history of a prior suicide attempt and no more than two of the following 11 other risk factors: socio-demographics (age 18–44, Non-Hispanic Black, 12 or more years education, low income, previously married), history of prior suicidal behavior (0–15 years since first onset of ideation, 12-month suicide plan), and parental psychopathology (depression, generalized anxiety disorder, panic disorder, antisocial personality disorder). Low risk is defined as having no history of a prior suicide attempt and 3–4 of the 11 other risk factors. Intermediate risk is defined either as having no history of a prior suicide attempt and 5–11 other risk factors or as having a history of one or more prior suicide attempts and 0–2 of the 11 other risk factors. High risk is defined as having a history of one or more prior suicide attempts and 3–11 other risk factors.

DISCUSSION

Results are limited in four important ways. First, our analysis was based on retrospective reports. Enthusiasm for the strength of the risk index should consequently be reserved until it is cross-validated prospectively. Risk factors that vary over time (e.g., marital status, income) are of special concern because they might have changed after attempts. Retrospective recall of parental psychopathology also might have been influenced by attempts. Second, the single NCS-R question used to distinguish attempts from gestures may have yielded a less accurate classification of intent than one based on clinical assessment. Third, we considered only a restricted set of DSM-IV disorders and assessed neither their severity nor chronicity, which might have downplayed the associations between disorders and attempts. Fourth, the low base rate of attempts led to low statistical power, which caused us to work with coarse predictor classifications and an unweighted summary score to minimize risk of over-fitting the model, possibly resulting in underestimation of the strength of association between the risk index and attempts. Efforts to compensate for low power by including substantively meaningful variables in the risk index that were not statistically significant might have led to over-fitting.

It is noteworthy, in light of these limitations, that most of the significant socio-demographic risk factors – young age, low socio-economic status, previous marriage – are consistent with prior findings (Kessler et al., 1999; Moscicki, 1997, 1999; Petronis et al., 1990), as is the finding that past attempts are powerfully related to future attempts (Brown et al., 2000; Goldstein et al., 1991; Hulten et al., 2001; Moscicki, 1997, 1999). The elevated risk of attempts among Non-Hispanic Blacks, in comparison, is not consistent with previous findings, although no previous research has examined race-ethnicity as a correlate of attempts among ideators.

The finding that respondent mental disorders are not reliably associated with suicide attempt over and above reports of parental psychopathology is surprising, given previous evidence that respondent mental disorders mediate the relationship of parental psychopathology with offspring suicide attempts (Brent et al., 1996; Brent et al., 2002). Quite a different pattern was found in associations with ideation in the total sample and with plans among ideators, where OR’s of parent disorders were much smaller than those of respondent disorders. This pattern is most plausibly interpreted to mean that the associations of respondent disorders with attempts are mediated by ideation and plans, while respondent perceptions of parent disorders might be markers either of latent causes (e.g., genetic influences) (Brent & Mann, 2005; Statham et al., 1998) or of features of respondent disorders that are not assessed in the CIDI (e.g., severity, chronicity). Adjudication among these competing possibilities in future research will require a more rigorous assessment of parent disorders and a more fine-grained dimensional assessment of respondent disorders.

The finding that information about diagnosis is not strongly related to attempts among ideators controlling for plans has practical importance because it is much easier to administer the simple NCS-R questions about suicide ideation and plans than to carry out diagnostic interviews. However, as previous research found disorder severity, which was not considered in our analysis, to be an important predictor of suicide attempts (Fergusson et al., 2005; Oquendo et al., 2004; Sokero et al., 2005), future work is needed to evaluate whether measures of disorder severity would improve the accuracy of the risk index.

The presence of a suicide plan, often considered the preeminent indicator of imminent risk, did not emerge as the strongest correlate of attempts. This does not mean that plans need not be assessed, as they are important both for clinical management (e.g., treatment contracting, removing the means for suicide) and prediction of attempts. Yet 43% of attempters described their attempts as unplanned. This characterization has to be incorrect in a rigorous sense, as all suicide attempts, including impulsive attempts, are “planned” even if the “plan” occurred only a few seconds before the attempt. However, attempters who report not having a plan presumably mean that they lacked a plan conceived prior to the situation in which the attempt occurred. Future research should investigate this issue by debriefing “unplanned” attempters about the sequence of thoughts and decisions that led up to their attempts.

The finding that a simple retrospectively reported risk index is strongly related to 12-month suicide attempts among ideators would be of great clinical value if the index was corroborated prospectively, especially in light of concerns regarding the effectiveness of detecting and intervening with people at high risk of suicide attempts (Gaynes et al., 2004; Kessler et al., 2005a). These results are of special clinical value given that the risk factors in the final index can be assessed with relative ease in clinical settings and that most of the factors (e.g., age, ethnicity, income, marital status, history of parental psychopathology) are unaffected by attempts to “fake good.” The results reported here are sufficiently promising to warrant an attempt at large-scale prospective replication, for which a precedent exists (Pokorny, 1983). To ensure sufficient statistical power, such an investigation should focus on people with suicidal ideation who are assessed with an expanded version of the current risk index and tracked to document subsequent attempts. To maximize generalizability, this research would ideally be conducted with a minimally selected sample, such as patients who screen positive for suicidal ideation in primary care settings. Analyses should evaluate more refined coding of the current risk factors as well as risk factors not studied here (e.g., a broader set of disorders, measures of disorder severity or chronicity). It would be useful to develop the model in one subsample and cross-validate it in another. It would also be useful to consider alternative methods of data collection, such as computer-assisted self-assessment, to improve completeness and honesty of reports (Greist et al., 1973; Kobak et al., 1996; Turner et al., 1998).

Acknowledgments

The National Comorbidity Survey Replication (NCS-R) is supported by NIMH (U01-MH60220) with supplemental support from the National Institute on Drug Abuse (NIDA), the Substance Abuse and Mental Health Services Administration (SAMHSA), the Robert Wood Johnson Foundation (RWJF; Grant 044708), and the John W. Alden Trust. Collaborating NCS-R investigators include Ronald C. Kessler (Principal Investigator, Harvard Medical School), Kathleen Merikangas (Co-Principal Investigator, NIMH), James Anthony (Michigan State University), William Eaton (The Johns Hopkins University), Meyer Glantz (NIDA), Doreen Koretz (Harvard University), Jane McLeod (Indiana University), Mark Olfson (New York State Psychiatric Institute, College of Physicians and Surgeons of Columbia University), Harold Pincus (University of Pittsburgh), Greg Simon (Group Health Cooperative), Michael Von Korff (Group Health Cooperative), Philip Wang (Harvard Medical School), Kenneth Wells (UCLA), Elaine Wethington (Cornell University), and Hans-Ulrich Wittchen (Max Planck Institute of Psychiatry; Technical University of Dresden). The views and opinions expressed in this report are those of the authors and should not be construed to represent the views of any of the sponsoring organizations, agencies, or U.S. Government. A complete list of NCS publications and the full text of all NCS-R instruments can be found at http://www.hcp.med.harvard.edu/ncs. Send correspondence to ncs@hcp.med.harvard.edu. The NCS-R is carried out in conjunction with the World Health Organization World Mental Health (WMH) Survey Initiative. We thank the staff of the WMH Data Collection and Data Analysis Coordination Centres for assistance with instrumentation, fieldwork, and consultation on data analysis. These activities were supported by the National Institute of Mental Health (R01 MH070884), the John D. and Catherine T. MacArthur Foundation, the Pfizer Foundation, the US Public Health Service (R13-MH066849, R01-MH069864, and R01 DA016558), the Fogarty International Center (FIRCA R01-TW006481), the Pan American Health Organization, Eli Lilly and Company, Ortho-McNeil Pharmaceutical, Inc., GlaxoSmithKline, and Bristol-Myers Squibb. A complete list of WMH publications can be found at http://www.hcp.med.harvard.edu/wmh/.

References

  1. American Psychiatric Association. Practice guideline for the assessment and treatment of patients with suicidal behaviors. American Journal of Psychiatry. 2003;160:1–60. [PubMed] [Google Scholar]
  2. Andreasen NC, Endicott J, Spitzer RL, Winokur G. The family history method using diagnostic criteria. Reliability and validity. Archives of General Psychiatry. 1977;34:1229–1235. doi: 10.1001/archpsyc.1977.01770220111013. [DOI] [PubMed] [Google Scholar]
  3. Beautrais AL, Joyce PR, Mulder RT, Fergusson DM, Deavoll BJ, Nightingale SK. Prevalence and comorbidity of mental disorders in persons making serious suicide attempts: a case-control study. American Journal of Psychiatry. 1996;153:1009–1014. doi: 10.1176/ajp.153.8.1009. [DOI] [PubMed] [Google Scholar]
  4. Bourgeois M, Swendsen J, Young F, Amador X, Pini S, Cassano GB, Lindenmayer JP, Hsu C, Alphs L, Meltzer HY. Awareness of disorder and suicide risk in the treatment of schizophrenia: results of the international suicide prevention trial. American Journal of Psychiatry. 2004;161:1494–1496. doi: 10.1176/appi.ajp.161.8.1494. [DOI] [PubMed] [Google Scholar]
  5. Brent DA, Bridge J, Johnson BA, Connolly J. Suicidal behavior runs in families. A controlled family study of adolescent suicide victims. Archives of General Psychiatry. 1996;53:1145–1152. doi: 10.1001/archpsyc.1996.01830120085015. [DOI] [PubMed] [Google Scholar]
  6. Brent DA, Mann JJ. Family genetic studies, suicide, and suicidal behavior. American Journal of Medical Genetics Part C: Seminars in Medical Genetics. 2005;133C:13–24. doi: 10.1002/ajmg.c.30042. [DOI] [PubMed] [Google Scholar]
  7. Brent DA, Oquendo M, Birmaher B, Greenhill L, Kolko D, Stanley B, Zelazny J, Brodsky B, Bridge J, Ellis S, Salazar JO, Mann JJ. Familial pathways to early-onset suicide attempt: risk for suicidal behavior in offspring of mood-disordered suicide attempters. Archives of General Psychiatry. 2002;59:801–807. doi: 10.1001/archpsyc.59.9.801. [DOI] [PubMed] [Google Scholar]
  8. Brown GK, Beck AT, Steer RA, Grisham JR. Risk factors for suicide in psychiatric outpatients: a 20-year prospective study. Journal of Consulting and Clinical Psychology. 2000;68:371–377. [PubMed] [Google Scholar]
  9. Buglass D, Horton J. A scale for predicting subsequent suicidal behaviour. British Journal of Psychiatry. 1974;124:573–578. doi: 10.1192/bjp.124.6.573. [DOI] [PubMed] [Google Scholar]
  10. Corcoran P, Kelleher MJ, Keeley HS, Byrne S, Burke U, Williamson E. A preliminary statistical model for identifying repeaters of parasuicide. Archives of Suicide Research. 1997;3:65–74. [Google Scholar]
  11. Dawes RM, Faust D, Meehl PE. Clinical versus actuarial judgment. Science. 1989;243:1668–1674. doi: 10.1126/science.2648573. [DOI] [PubMed] [Google Scholar]
  12. Dilsaver SC, Chen YW, Swann AC, Shoaib AM, Krajewski KJ. Suicidality in patients with pure and depressive mania. American Journal of Psychiatry. 1994;151:1312–1315. doi: 10.1176/ajp.151.9.1312. [DOI] [PubMed] [Google Scholar]
  13. Fawcett J, Scheftner WA, Fogg L, Clark DC, Young MA, Hedeker D, Gibbons R. Time-related predictors of suicide in major affective disorder. American Journal of Psychiatry. 1990;147:1189–1194. doi: 10.1176/ajp.147.9.1189. [DOI] [PubMed] [Google Scholar]
  14. Fergusson DM, Horwood LJ, Ridder EM, Beautrais AL. Subthreshold depression in adolescence and mental health outcomes in adulthood. Archives of General Psychiatry. 2005;62:66–72. doi: 10.1001/archpsyc.62.1.66. [DOI] [PubMed] [Google Scholar]
  15. First MB, Spitzer RL, Gibbon M, Williams JBW. Structured Clinical Interview for DSM-IV-TR Axis I Disorders, Research Version, Non-Patient Edition (SCID-I/NP) Biometrics Research, New York State Psychiatric Institute; New York, NY: 2002. [Google Scholar]
  16. Gaynes BN, West SL, Ford CA, Frame P, Klein J, Lohr KN. Screening for suicide risk in adults: a summary of the evidence for the U.S. Preventive Services Task Force. Annals of Internal Medicine. 2004;140:822–835. doi: 10.7326/0003-4819-140-10-200405180-00015. [DOI] [PubMed] [Google Scholar]
  17. Goldstein RB, Black DW, Nasrallah A, Winokur G. The prediction of suicide. Sensitivity, specificity, and predictive value of a multivariate model applied to suicide among 1906 patients with affective disorders. Archives of General Psychiatry. 1991;48:418–422. doi: 10.1001/archpsyc.1991.01810290030004. [DOI] [PubMed] [Google Scholar]
  18. Gould MS, Fisher P, Parides M, Flory M, Shaffer D. Psychosocial risk factors of child and adolescent completed suicide. Archives of General Psychiatry. 1996;53:1155–1162. doi: 10.1001/archpsyc.1996.01830120095016. [DOI] [PubMed] [Google Scholar]
  19. Greist JH, Gustafson DH, Stauss FF, Rowse GL, Laughren TP, Chiles JA. A computer interview for suicide-risk prediction. American Journal of Psychiatry. 1973;130:1327–1332. doi: 10.1176/ajp.130.12.1327. [DOI] [PubMed] [Google Scholar]
  20. Harris GT, Rice ME, Camilleri JA. Applying a forensic actuarial assessment (the Violence Risk Appraisal Guide) to nonforensic patients. Journal of Interpersonal Violence. 2004;19:1063–1074. doi: 10.1177/0886260504268004. [DOI] [PubMed] [Google Scholar]
  21. Harris GT, Rice ME, Quinsey VL, Lalumiere ML, Boer D, Lang C. A multisite comparison of actuarial risk instruments for sex offenders. Psychological Assessment. 2003;15:413–425. doi: 10.1037/1040-3590.15.3.413. [DOI] [PubMed] [Google Scholar]
  22. Hawton K, Fagg J. The performance of the Edinburgh predictive scales in patients in Oxford. Archives of Suicide Research. 1995;1:261–272. [Google Scholar]
  23. Hawton K, Houston K, Haw C, Townsend E, Harriss L. Comorbidity of axis I and axis II disorders in patients who attempted suicide. American Journal of Psychiatry. 2003;160:1494–1500. doi: 10.1176/appi.ajp.160.8.1494. [DOI] [PubMed] [Google Scholar]
  24. Hilton NZ, Harris GT, Rice ME, Lang C, Cormier CA, Lines KJ. A brief actuarial assessment for the prediction of wife assault recidivism: the Ontario domestic assault risk assessment. Psychological Assessment. 2004;16:267–275. doi: 10.1037/1040-3590.16.3.267. [DOI] [PubMed] [Google Scholar]
  25. Hosmer DW, Lemeshow S. Applied Logistic Regression. Wiley & Sons; New York, NY: 1989. [Google Scholar]
  26. Hulten A, Jiang GX, Wasserman D, Hawton K, Hjelmeland H, De Leo D, Ostamo A, Salander-Renberg E, Schmidtke A. Repetition of attempted suicide among teenagers in Europe: frequency, timing and risk factors. European Child and Adolescent Psychiatry. 2001;10:161–169. doi: 10.1007/s007870170022. [DOI] [PubMed] [Google Scholar]
  27. Johnson JG, Cohen P, Gould MS, Kasen S, Brown J, Brook JS. Childhood adversities, interpersonal difficulties, and risk for suicide attempts during late adolescence and early adulthood. Archives of General Psychiatry. 2002;59:741–749. doi: 10.1001/archpsyc.59.8.741. [DOI] [PubMed] [Google Scholar]
  28. Jollant F, Bellivier F, Leboyer M, Astruc B, Torres S, Verdier R, Castelnau D, Malafosse A, Courtet P. Impaired decision making in suicide attempters. American Journal of Psychiatry. 2005;162:304–310. doi: 10.1176/appi.ajp.162.2.304. [DOI] [PubMed] [Google Scholar]
  29. Keilp JG, Sackeim HA, Brodsky BS, Oquendo MA, Malone KM, Mann JJ. Neuropsychological dysfunction in depressed suicide attempters. American Journal of Psychiatry. 2001;158:735–741. doi: 10.1176/appi.ajp.158.5.735. [DOI] [PubMed] [Google Scholar]
  30. Kendler KS, Davis CG, Kessler RC. The familial aggregation of common psychiatric and substance use disorders in the National Comorbidity Survey: a family history study. British Journal of Psychiatry. 1997;170:541–548. doi: 10.1192/bjp.170.6.541. [DOI] [PubMed] [Google Scholar]
  31. Kessler RC, Berglund P, Borges G, Nock M, Wang PS. Trends in suicide ideation, plans, gestures, and attempts in the United States, 1990-1992 to 2001-2003. JAMA. 2005a;293:2487–2495. doi: 10.1001/jama.293.20.2487. [DOI] [PubMed] [Google Scholar]
  32. Kessler RC, Berglund P, Chiu WT, Demler O, Heeringa S, Hiripi E, Jin R, Pennell BE, Walters EE, Zaslavsky A, Zheng H. The US National Comorbidity Survey Replication (NCS-R): design and field procedures. International Journal of Methods in Psychiatric Research. 2004;13:69–92. doi: 10.1002/mpr.167. [DOI] [PMC free article] [PubMed] [Google Scholar]
  33. Kessler RC, Berglund P, Demler O, Jin R, Walters EE. Lifetime prevalence and age-of-onset distributions of DSM-IV disorders in the National Comorbidity Survey Replication. Archives of General Psychiatry. 2005b;62:593–602. doi: 10.1001/archpsyc.62.6.593. [DOI] [PubMed] [Google Scholar]
  34. Kessler RC, Borges G, Walters EE. Prevalence of and risk factors for lifetime suicide attempts in the National Comorbidity Survey. Archives of General Psychiatry. 1999;56:617–626. doi: 10.1001/archpsyc.56.7.617. [DOI] [PubMed] [Google Scholar]
  35. Kessler RC, McGonagle KA, Zhao S, Nelson CB, Hughes M, Eshleman S, Wittchen HU, Kendler KS. Lifetime and 12-month prevalence of DSM-III-R psychiatric disorders in the United States. Results from the National Comorbidity Survey. Archives of General Psychiatry. 1994;51:8–19. doi: 10.1001/archpsyc.1994.03950010008002. [DOI] [PubMed] [Google Scholar]
  36. Kessler RC, Merikangas KR. The National Comorbidity Survey Replication (NCS-R): background and aims. International Journal of Methods in Psychiatric Research. 2004;13:60–68. doi: 10.1002/mpr.166. [DOI] [PMC free article] [PubMed] [Google Scholar]
  37. Kessler RC, Ustun TB. The World Mental Health (WMH) Survey Initiative Version of the World Health Organization (WHO) Composite International Diagnostic Interview (CIDI) International Journal of Methods in Psychiatric Research. 2004;13:93–121. doi: 10.1002/mpr.168. [DOI] [PMC free article] [PubMed] [Google Scholar]
  38. Kobak KA, Greist JH, Jefferson JW, Katzelnick DJ. Computer-administered clinical rating scales. A review. Psychopharmacology. 1996;127:291–301. doi: 10.1007/s002130050089. [DOI] [PubMed] [Google Scholar]
  39. Koivumaa-Honkanen H, Honkanen R, Viinamaki H, Heikkila K, Kaprio J, Koskenvuo M. Life satisfaction and suicide: a 20-year follow-up study. American Journal of Psychiatry. 2001;158:433–439. doi: 10.1176/appi.ajp.158.3.433. [DOI] [PubMed] [Google Scholar]
  40. Kreitman N, Foster J. The construction and selection of predictive scales, with special reference to parasuicide. British Journal of Psychiatry. 1991;159:185–192. doi: 10.1192/bjp.159.2.185. [DOI] [PubMed] [Google Scholar]
  41. Kuo WH, Gallo JJ, Tien AY. Incidence of suicide ideation and attempts in adults: the 13-year follow-up of a community sample in Baltimore, Maryland. Psychological Medicine. 2001;31:1181–1191. doi: 10.1017/s0033291701004482. [DOI] [PubMed] [Google Scholar]
  42. Mann JJ, Waternaux C, Haas GL, Malone KM. Toward a clinical model of suicidal behavior in psychiatric patients. American Journal of Psychiatry. 1999;156:181–189. doi: 10.1176/ajp.156.2.181. [DOI] [PubMed] [Google Scholar]
  43. Meltzer HY, Alphs L, Green AI, Altamura AC, Anand R, Bertoldi A, Bourgeois M, Chouinard G, Islam MZ, Kane J, Krishnan R, Lindenmayer JP, Potkin S. Clozapine treatment for suicidality in schizophrenia: International Suicide Prevention Trial (InterSePT) Archives of General Psychiatry. 2003;60:82–91. doi: 10.1001/archpsyc.60.1.82. [DOI] [PubMed] [Google Scholar]
  44. Moscicki EK. Identification of suicide risk factors using epidemiologic studies. Psychiatric Clinics of North America. 1997;20:499–517. doi: 10.1016/s0193-953x(05)70327-0. [DOI] [PubMed] [Google Scholar]
  45. Moscicki EK. Epidemiology of Suicide. In: Jacobs DG, editor. The Harvard Medical School Guide to Suicide Assessment and Intervention. Jossey-Bass; San Francisco, CA: 1999. pp. 40–51. [Google Scholar]
  46. Mossman D. Assessing predictions of violence: being accurate about accuracy. Journal of Consulting and Clinical Psychology. 1994;62:783–792. doi: 10.1037//0022-006x.62.4.783. [DOI] [PubMed] [Google Scholar]
  47. Murphy GE, Wetzel RD, Robins E, McEvoy L. Multiple risk factors predict suicide in alcoholism. Archives of General Psychiatry. 1992;49:459–463. doi: 10.1001/archpsyc.1992.01820060039006. [DOI] [PubMed] [Google Scholar]
  48. Neeleman J, de Graaf R, Vollebergh W. The suicidal process; prospective comparison between early and later stages. Journal of Affective Disorders. 2004;82:43–52. doi: 10.1016/j.jad.2003.09.005. [DOI] [PubMed] [Google Scholar]
  49. Nock MR, Kessler RC. Prevalence of and risk factors for suicide attempts versus suicide gestures: analysis of the National Comorbidity Survey. Journal of Abnormal Psychology. doi: 10.1037/0021-843X.115.3.616. in press. [DOI] [PubMed] [Google Scholar]
  50. O’Carroll PW, Berman AL, Maris R, Moscicki E. Beyond the tower of Babel: a nomenclature for suicidology. Suicide and Life-Threatening Behavior. 1996;26:237–252. [PubMed] [Google Scholar]
  51. Oquendo MA, Galfalvy H, Russo S, Ellis SP, Grunebaum MF, Burke A, Mann JJ. Prospective study of clinical predictors of suicidal acts after a major depressive episode in patients with major depressive disorder or bipolar disorder. American Journal of Psychiatry. 2004;161:1433–1441. doi: 10.1176/appi.ajp.161.8.1433. [DOI] [PubMed] [Google Scholar]
  52. Palmer BA, Pankratz VS, Bostwick JM. The lifetime risk of suicide in schizophrenia: a reexamination. Archives of General Psychiatry. 2005;62:247–253. doi: 10.1001/archpsyc.62.3.247. [DOI] [PubMed] [Google Scholar]
  53. Petronis KR, Samuels JF, Moscicki EK, Anthony JC. An epidemiologic investigation of potential risk factors for suicide attempts. Social Psychiatry and Psychiatric Epidemiology. 1990;25:193–199. doi: 10.1007/BF00782961. [DOI] [PubMed] [Google Scholar]
  54. Pokorny AD. Prediction of suicide in psychiatric patients. Report of a prospective study. Archives of General Psychiatry. 1983;40:249–257. doi: 10.1001/archpsyc.1983.01790030019002. [DOI] [PubMed] [Google Scholar]
  55. Research Triangle Institute. SUDAAN: Professional Software for Survey Data Analysis (Version 8.01) Research Triangle Park, NC: Research Triangle Institute; 2002. [Google Scholar]
  56. Schmidtke A, Bille-Brahe U, DeLeo D, Kerkhof A, Bjerke T, Crepet P, Haring C, Hawton K, Lonnqvist J, Michel K, Pommereau X, Querejeta I, Phillipe I, Salander-Renberg E, Temesvary B, Wasserman D, Fricke S, Weinacker B, Sampaio-Faria JG. Attempted suicide in Europe: rates, trends and sociodemographic characteristics of suicide attempters during the period 1989-1992. Results of the WHO/EURO Multicentre Study on Parasuicide. Acta Psychiatrica Scandinavica. 1996;93:327–338. doi: 10.1111/j.1600-0447.1996.tb10656.x. [DOI] [PubMed] [Google Scholar]
  57. Shaffer D, Gould MS, Fisher P, Trautman P, Moreau D, Kleinman M, Flory M. Psychiatric diagnosis in child and adolescent suicide. Archives of General Psychiatry. 1996;53:339–348. doi: 10.1001/archpsyc.1996.01830040075012. [DOI] [PubMed] [Google Scholar]
  58. Sokero TP, Melartin TK, Rytsala HJ, Leskela US, Lestela-Mielonen PS, Isometsa ET. Prospective study of risk factors for attempted suicide among patients with DSM-IV major depressive disorder. British Journal of Psychiatry. 2005;186:314–318. doi: 10.1192/bjp.186.4.314. [DOI] [PubMed] [Google Scholar]
  59. Statham DJ, Heath AC, Madden PA, Bucholz KK, Bierut L, Dinwiddie SH, Slutske WS, Dunne MP, Martin NG. Suicidal behaviour: an epidemiological and genetic study. Psychological Medicine. 1998;28:839–855. doi: 10.1017/s0033291798006916. [DOI] [PubMed] [Google Scholar]
  60. Strakowski SM, McElroy SL, Keck PE, Jr, West SA. Suicidality among patients with mixed and manic bipolar disorder. American Journal of Psychiatry. 1996;153:674–676. doi: 10.1176/ajp.153.5.674. [DOI] [PubMed] [Google Scholar]
  61. Turner CF, Ku L, Rogers SM, Lindberg LD, Pleck JH, Sonenstein FL. Adolescent sexual behavior, drug use, and violence: increased reporting with computer survey technology. Science. 1998;280:867–873. doi: 10.1126/science.280.5365.867. [DOI] [PubMed] [Google Scholar]
  62. Wolter K. Introduction to Variance Estimation. Springer-Verlag; New York, NY: 1985. [Google Scholar]
  63. Zimmerman M, Coryell W, Pfohl B, Stangl D. The reliability of the family history method for psychiatric diagnoses. Archives of General Psychiatry. 1988;45:320–322. doi: 10.1001/archpsyc.1988.01800280030004. [DOI] [PubMed] [Google Scholar]

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