Reducing Suicide A National Imperative (2002) / Chapter Skim
Currently Skimming:
10 Barriers to Research and Promising Approaches
10 Barriers to Research and Promising Approaches
Pages 375-422
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From page 375... ...
Special measures must be taken to increase the statistical power of intervention and prevention studies, since suicide is a relatively infrequent event. These approaches range from using alternate endpoints such as suicidal ideation to finding ways to increase the size of the population under study.
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As a result of this committee's work, operational definitions for basic terms such as suicidal ideation, suicide attempts, and completed suicide were proposed. Definitional issues were revisited in the mid-199Os at workshops held by the American Association of Suicidology, NIMH, and the Center for Mental Health Services, and through informal discussions among suicidologists (O'Carroll et al., 1996~.
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From page 377... ...
and proximal endpoints may provide solutions, but a large population base is preferable. Psychological Autopsy A psychological autopsy is the reconstruction of the events leading up to the death; ascertainment of the circumstances of the death, including suicidal intent; and an in-depth exploration of other significant risk factors for suicide (Beskow et al., 1991; Brent et al., 1988; Brent et al., 1993; Cooper, 1999; Hawton et al., 1998; Kelly and Mann, 1996; Vetting et al., 1998~.
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, and may very well be a consistent finding across different mental disorders. Conversely, psychological autopsy data may allow for the selection of relatively homoge
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Official suicide rates have been used to chart trends in suicide; monitor the impact of change in legislation, treatment policies, and social change; and to compare suicides across regions, both within and across countries. In addition, suicide rates have offered a way to assess risk and protective factors for geographical areas (counties, states and countries)
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Undetermined verdicts appear to be more likely if the victim is older, died by poisoning, and is female, perhaps because this profile may not fit the archetypal suicide completer (Ohberg and Lonnqvist, 1998; Ovenstone, 1973~. Studies suggest that the official suicide rate underestimates the true rate by about 30 percent, but that time trends are unaffected by classification errors (Brent et al., 1987; Gist and Welch, 1989; Sainsbury and Jenkins, 1982~.
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From page 381... ...
Understanding which specific qualities of the areas and populations tend to influence the suicide rate is critical for designing programs to enhance protective factors and reduce risk factors. Since many suicide prevention programs are implemented in community and school settings, more precise data are needed at these levels to be able to evaluate their effectiveness, recognize what services
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From page 382... ...
In the case of AIDS reporting, the CDC encouraged the states to pass such statutes by requiring the existence of surveillance regulation in order to receive funding for state AIDS prevention and treatment programs (Gostin et al., 1997~. Similarly, for suicide surveillance, data should be collected at the local and state levels in a standardized manner so that it can be aggregated for a national reporting system.
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National Violent Death Reporting System (NVDRS) A National Violent Death Reporting System (NVDRS)
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Surveillance of Attempted Suicides The quality of the data on suicide attempts is even more tenuous than that of completed suicides. The concerns about nomenclature (Garrison et al., 1991; O'Carroll et al., 1996)
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This section describes a few of the potential models and sources of information on suicide attempts: the National Electronic Injury Surveillance System, the Youth Risk Behavior Survey, and the Oregon State Adolescent Suicide Attempt Data System. National Electronic Injury Surveillance System (NEISS)
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In 1987, Oregon became the only state with a law requiring the reporting of suicide attempts by youth under 18 to the state health department (Hopkins et al., 1995~. Failure to comply with this regulation is a Class A misdemeanor; however, it has been unnecessary to charge any hospital thus far (personal communication, D
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For example, the number of permitted fields on reporting forms would need to be standardized since more than one field allows much more detailed and informative coding. The CDC is currently pilot-testing its National Electronic Disease Surveillance System (NEDSS)
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Because a previous suicide attempts is one of the strongest predictors of completed suicide, and repeat attempters are at higher risk for completed suicide, it is important to be able to track individuals over time. All of these factors contribute to the tension that exists between the need for quality surveillance to promote the public's health and an individual's right to privacy.
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This section reviews the issues of informed consent and safe conduct of clinical trials and presents a statistical approach that can facilitate clinical research with suicidal participants. Informed Consent As reviewed earlier (Chapter 3)
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There is a clear need for empirical research to test hypotheses on the capacity of suicidal patients to give informed consent. Some mental disorders are accompanied by fluctuating decision-making ability (like bipolar disorder)
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Finally, other risk reduction strategies may include experimental procedures such as the use of adaptive randomization,3 as well as early termination of a study when the null hypothesis has been disconfirmed. These practices are standard for all clinical trials and can apply to suicidal patients as well.
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Exclusion from Trials Because of the concerns about death by suicide, however, people who exhibit suicidal behaviors are often excluded from clinical trials (Pearson et al., 2000~. The practice of excluding these patients from trials limits the opportunity for this population to benefit from such research.
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Many of the issues presented are well known in the suicide literature (e.g., estimating prevalence) whereas some are new to the study of suicide (e.g., use of empirical Bayes estimates in studying geographic variation in suicide rates)
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It is hoped that these examples will provide a perspective on the power of appropriate statistical methodologies in suicide research. Lifetime Risk of Suicide Based on the work of Guze and Robins (1970)
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computed lifetime risk of suicide, using Bayes theorem, as the probability of suicide given death times the probability of death. For example, the overall probability of death in the 29 studies of affective disorder inpatients was 20 percent and of those, 20 percent died by suicide.
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Appendix A describes the general statistical theory and developments. Statistical Models for Assessment of Suicide Rates Poisson Regression Models In the analysis of suicide rate data, Poisson regression models are a natural choice.
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These categories were used so that there would be sufficient sample sizes available to compare observed and expected annual suicide rates for both GEE and mixed-effects Poisson regression models. In general, the GEE and mixed effect parameter estimates were remarkably similar.
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Inspection of Table 10-2 reveals remarkably close agreement between observed and expected numbers of suicides. This approach also allows the use of Bayes estimates directly to obtain county-level suicide rates adjusted for the effects of race, sex, and age.
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BARRIERS TO RESEARCH AND PROMISING APPROACHES TABLE 10-2 Observed and Expected Number of Suicides for 100 Randomly Selected Counties 399 Observed Expected Observed Expected State County # of Deaths # of Deaths State County # of Deaths # of Deaths 56 7 16 10.3 51 75 5 5.9 53 63 169 170.4 20 159 6 4.5 5 91 14 13.6 21 103 14 8.7 47 111 13 9.4 40 45 1 1.6 54 93 1 2.8 31 61 1 1.5 28 5 9 5.5 31 91 0 0.3 27 141 22 21.7 40 73 9 6.3 38 47 0 1.0 20 203 1 1.0 21 59 25 27.5 1 5 8 8.2 48 451 54 50.2 38 51 0 1.4 48 87 3 1.4 38 39 2 1.3 18 97 391 385.3 21 95 11 12.0 35 7 8 6.2 48 73 32 25.8 48 383 2 1.5 23 11 38 39.6 31 41 3 4.3 55 101 58 59.5 18 7 2 3.4 17 107 9 10.8 45 61 6 5.9 47 127 1 1.9 19 1 4 3.4 55 55 28 28.1 8 119 13 9.9 21 223 5 3.4 36 3 22 20.9 30 97 1 1.4 19 93 2 2.9 19 51 2 3.0 12 95 303 314.1 47 129 4 6.4 49 49 89 91.1 48 9 2 3.0 28 45 30 24.1 19 5 9 6.7 18 107 19 16.9 28 69 3 3.0 5 1 6 6.8 46 19 6 4.1 17 167 64 64.8 27 171 31 30.8 39 89 43 44.7 28 53 1 2.4 28 1 9 9.5 20 31 2 3.1 53 23 0 0.9 51 47 18 15.0 48 213 30 28.8 46 123 3 2.7 55 107 9 7.1 12 81 135 129.6 31 177 6 6.7 2 122 22 20.4 17 49 12 12.2 21 61 0 3.4 55 75 18 17.5 21 25 7 6.3 8 55 3 2.7 26 13 6 4.0 29 121 4 5.4 18 157 42 44.1 40 125 34 30.2 21 165 2 2.2 20 73 3 3.2 48 447 2 0.8 21 109 7 5.5 13 265 3 0.6 29 197 2 1.8 2 100 2 1.0 51 133 7 5.0 55 11 4 5.2 29 105 8 10.0 48 81 0 1.3 47 181 14 9.7 21 229 6 4.6 51 103 9 5.5 55 35 32 32.3 16 15 3 2.2 39 151 112 113.5 38 55 2 3.5 28 89 17 18.4 39 17 91 93.6 19 167 4 8.2 55 51 3 2.8 23 27 17 15.7 19 119 3 4.2 38 1 0 1.1
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Similarly, in the central United States where there is a high concentration of counties with the lowest suicide rates, a few counties exhibit the highest suicide rates. What are the risk and protective factors that have produced these spatial anomalies?
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has an impact on suicide rates. If the number of suicides in the month following the event exceeds the calculated prediction (in the example, 4 suicides)
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Parameters are estimated by subtracting the risk attributable to previous attempts from the overall risk and then modeling the residual risk over the rest of the risk factors using a logistic regression model. Innovative statistical approaches such as this are needed to deal with some of the special problems associated with the modeling of low-rate events such as completed suicide.
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The risk-based design also requires a prediction of what the outcomes would have been in the sicker patients if they had received the standard treatment. One example of such a model might be an appropriate regression model of the relationship between pre-treatment suicidal ideation on post-treatment suicidal ideation in a group of depressed patients treated with the standard antidepressant therapy.
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For a 90 percent confidence interval for a rate of 10 per 100,000 (plus or minus 5 per 100,000) , approximately 100,000 participants are needed.
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, a sample size of 3458 is required for precision of 1 percent, but only 139 participants are needed for precision of 5 percent. Study designs frequently compare suicide, or suicide attempts, or suicidal ideation as an outcome in two groups of individuals.
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CENTERS Because of its low base rate, the difficulties in assessment, and the long-term, interdisciplinary nature of the risk and protective factors, the optimal approach to learn about suicide is to use large populations with cultural and genetic diversity for long-duration, interdisciplinary studies. A centrally coordinated, population-based approach would provide the infrastructure necessary to estimate more reliably the incidence of suicidal behavior (including attempts and completions)
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has established Injury Control Research Centers to explore the prevention, care and rehabilitation needs presented by various types of injury. In fiscal year 2001, the CDC had plans to fund ten centers (Injury prevention, 2001)
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The centers might encompass basic science, clinical trials, population studies, and/or clinical care. They might be part of a university, freestanding institutes, or jointly run by multiple institutions (NCI, 2000a)
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Whatever structure is chosen, such centers would allow better estimates of incidence, improved evaluation of risk and protective factors, longitudinal studies that could assess intervention and prevention, and development of tissue repositories for genetic and other biological analyses. Ancillary benefits of such a center would be the wealth of data that would be collected on mental illness and substance abuse, major risk factors for suicide, and correlation with detailed social data.
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Adding suicide cores to centers focussed on mental illness might also increase the collection of data regarding suicide. But these less expensive alternatives will not address the most serious obstacle to understanding suicide: the need for a large, a well-characterized population that would allow links to be made about causes, risks, protective factors, and successful interventions.
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FINDINGS · Suicidology has faced serious methodological limitations, including inconsistencies in definitions and misclassification of deaths by medical examiners or coroners. The quality of the data on suicide attempts is even less reliable than that for completed suicide.
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Evidence-based treatment protocols for suicidality are seriously lacking, making clinical trials critical. Clinical trials of drug and psychotherapy treatment should include suicidal patients.
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1975. The comparability of suicide rates.
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1993. The validity of diagnoses obtained through the psychological autopsy procedure in adolescent suicide victims: Use of family history.
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1989. Certification change versus actual behavior change in teenage suicide rates, 1955-1979.
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2001. National Violent Injury Statistics System: Linking Data to Save Lives.
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1999. Prevalence of and risk factors for lifetime suicide attempts in the National Comorbidity Survey.
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1978. The certification of suicide in eleven western states: An inquiry into the validity of reported suicide rates.
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2002. Violent Death Reporting System Training Manual.
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1996. The psychological autopsy study of completed suicide: An experimental test of the impact of knowledge of the suicide upon informants' reports of psychopathology in the victim.
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American Journal of Epidemiology, 130: 1057-1064. Washington Department of Health.
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To be, or not to be: that is the Question: Whether 'tis Nobler in the Mind to suffer The Slings and Arrows of outrageous Fortune, Or to take Arms against a Sea of Troubles, And by opposing end them; to die to sleep No more, and by a Sleep to say we end The Hart-ache, and the thousand Natural Shocks That Flesh is heir to; 'tis a Consummation Devoutly to be wish'd to die to sleep, To Sleep, perchance to Jream; ay there's the Rub, For in that Sleep of Death what Dreams may Come .
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