Correlation Between Protective Factors and Previous Suicide Attempts - Lab Report Example

? Psychology Lab Report Affiliation Suicide is a major problem in modern societies. In order to avoid bias and transference and to better serve at-risk individuals, objective measurements of suicide risk have been devised. Questions remain regarding the superiority of implicit versus explicit measurements of suicide risk. This study consisted of Implicit Association Testing and four explicit self-reporting questionnaires which were presented to thirty-three adults presenting to an emergency room. The data was analyzed using correlation analysis and reports novel findings regarding implicit and explicit measures of suicide risk both in relation to what they are actually measuring and which is a superior predictive tool with significant implications for healthcare providers. Keywords: Suicide, Prediction, Implicit Association testing Introduction Hypotheses of the study There is a significant correlation between protective factors and previous suicide attempts There is a significant correlation between risk factors and previous suicide attempts There is a significant correlation between IAT score and protective factors There is a significant correlation between IAT score and risk factors There is a significant correlation between IAT score and previous suicide attempts. The objectives of the study To investigate whether there is a significant correlation between protective factors and previous suicide attempts To explore whether there is a significant correlation between risk factors and previous suicide attempts To find out if there is a significant correlation between IAT score and protective factors To explore the possibility that there is a significant correlation between IAT score and risk factors To investigate if there is a significant correlation between IAT score and previous suicide attempts. Literature review The fundamental goal of suicide prevention is to recognize those individuals who pose an elevated risk of attempting suicide. This early detection is complicated by a number of factors. One is myths, such as “Talking about suicide will only give someone ideas”. Another problem is a general lack of knowledge about the progression of suicide ideation and the driving causes which trigger it. Lastly, there is a general social embarrassment about learning about another person’s problems and impulses. In combination, these problems complicate early suicide detection and limit the suicidal person’s access to help.     The social cost of this inability to properly detect and deter suicide is tremendous worldwide but especially in Australia. In this country alone, over 2000 people successfully commit suicide each year (Australian Bureau of Statistics, 2011). Despite an increasing awareness regarding this issue, two key issues have compromised successful suicide prevention. Most importantly, professional help is still failing to reach the significant majority of those who commit suicide. In a survey of ten suicide prevention centers, only a third of the calls were made by people who had been considering suicide (Bertolote, 2004). In addition, physicians, teachers and clergymen all come into contact with people who are suicidal and regularly fail to identify the risk or attempt to effectively intervene once the risk is recognized (Pirkis et al., 1998). Secondly, suicide prevention personnel are confronted with a variety of non-objective emotions, and transference issues regarding the suicidal person, and may have significant difficulty quantifying the degree of risk. The healthcare professional may fail to ask pertinent questions, interpret the suicidal person’s responses in a biased fashion or fail to accurately weigh the individual risk factors in his final assessment of the risk. Therefore, an objective assessment is critical, as computers have been programmed to interact with patients presenting a variety of medical problems.     What makes suicide prediction so difficult is because the risk assessment relies almost entirely on explicit measures such as self-reporting and clinical judgment. These two items are unreliable as individuals are often inclined to lie about their suicidal intent, or not even be consciously aware of it. Therefore, to truly be able to make predictive remarks regarding suicide risk one must be able to objectively measure implicit variables (Greenwald et al, 1998). One critical area of research into implicit variables is in understanding the psychology of suicidal individuals. One potential way to study one’s psychological constructs (i.e. thoughts on death, etc.) is via the Implicit Association Test (IAT). This computer testing approach asks participants to categorize tasks via reaction association time. This activity quantifies the association of a binary contrast with an attributable personal dimension. In short, it measures how long a participant takes to group certain prompts (i.e. words Life, Death) into relevant categories (i.e. me or not me) (Lane et al, 2007; Nosek et al, 2007)). Two major studies support this IAT approach to suicide prevention via the measurement of implicit and explicit variables. Nock et al reports that in a population of adolescents drawn from psychiatric clinics, the IAT was able to correctly distinguish participants into non-suicidal, suicide ideators, and suicide attempters with significant accuracy by explicit questioning. Furthermore, IAT was able to predict these individuals suicide risk as not suicidal, suicide ideators and suicide attemptors with significant accuracy at 6-month follow up. This research was expanded in Nock et al 2010 research in which adult patients presenting acutely to psychiatric emergency rooms were examined. The IAT was able to properly distinguish between patient suicide risk levels and found that IAT identified attempters had a significantly high association with certain psychological concepts, such as Death, than those who simply hurt themselves or were not suicidal. Overall, however, significant problems exist with these two Nock papers as they rely solely on clinical populations, and not the general public. The fact that they used self-reporting questionnaires (explicit measures) to quantify protective factors, as well as the commonly assessed risk factors of suicide, makes them unreliable (Nosek et al, 2011). The current study’s objective is to identify participants’ suicide risk using the IAT approach, with the goal of answering two questions: 1) Are implicit (IAT) and explicit tests measuring the same phenomena; and 2) Which is better, implicit or explicit tests, at predicting suicide risk. Through properly understanding how to properly quantify suicide risk, significant emotional, economic and social benefits to suicide will be incurred in relation to saving lives. Study Methods The study consisted of the IAT and four self-reporting questionnaires which were presented to thirty-three adults presenting to the emergency room. These participants were broken into two groups: suicide ideators and attempters. The first two questionnaires, called Thoughts and Feelings about Life (TFL) and Reasons for Living (RFL), can be understood as protective explicit measures of the participant’s reasons for staying alive when thinking about suicide (Linehan et al, 1983), and both produce a quantifiable score. The other two tests measured the participants’ risk factors, and were the Self-Injurious Thoughts and Behaviors Interview (SITBI), which consists of questions regarding the frequency of suicidal thoughts, and the Depression, Anxiety, Stress Scales (DASS). This provides a separate measure for depression, anxiety and stress (Anthony et al, 1998). Implicit measures in the study were examined by IAT while explicit measures were measured by protective factors (TFL; RFL) and risk factors: (SITBI; DASS). Within the statistical analysis, in order to examine the implicit and explicit cognitive measures, it was necessary to create new variables. An overall ‘risk factors’ variable (SITBI scores added to DASS scores) was established along with an overall ‘protective factors’ variable (TFL scores added to RFL scores) to compare with the IAT. In addition, to examine how well the implicit and explicit cognitive measures are at predicting current behavior, it is necessary to examine the relationship between scores on the IAT and suicide attempts. The data was then analyzed using SPSS to obtain descriptive statistics and correlation analysis. Results Protective factors with risk factors -.681** Protective factors with IAT score .242** Protective factors with previous suicide attempts -.272** Risk factors with IAT score -.165** Risk factors with previous suicide attempts .465** IAT score with previous suicide attempts -.043 **.correlation is significant at the 0.01 level(2-tailed). The limitations encountered in this study could have been brought by lack of sincerity. It is very hard for someone to come out and admit they had thoughts of suicide or they have ever attempted suicide. As such, the limiting factor being that the study relies on self reporting; it might be greatly biased and tilted to wards the client. The table below shows how the subjects responded to the question of suicide attempts and self injurious thoughts. Number of previous suicide attempts Frequency Percent Valid Percent Cumulative Percent Valid Never 359 88.2 88.2 88.2 Once 31 7.6 7.6 95.8 Twice 10 2.5 2.5 98.3 Three or four 3 .7 .7 99.0 Five or more 4 1.0 1.0 100.0 Total 407 100.0 100.0 Number of previous self-injury attempt Frequency Percent Valid Percent Cumulative Percent Valid Never 269 66.1 66.1 66.1 Once 46 11.3 11.3 77.4 Twice 30 7.4 7.4 84.8 Three or four 35 8.6 8.6 93.4 Five or more 27 6.6 6.6 100.0 Total 407 100.0 100.0 Also, the issue of peer pressure may cause the population, who are students, to conform to one way of responding. However, strong points in the study are that it contains a cross-section of people of all races and gender so the results of the study would not deviate much in a general population. Discussion Overall, this study reports new findings regarding implicit and explicit measures of suicide risk, both in relation to what they are actually measuring, and which is a superior predictive tool. In regards to the first item, the implicit and explicit measures appear to be measuring the same phenomenon, though with some independent elements. The IAT and risk factor variables were found to measure a very small proportion of the same thing (small, negative, and non-significant). In contrast, the IAT and protective factor variable were found to be measuring a significant proportion of the same thing (medium, positive, significant relationship). In addition, the risk factor and protective factor variable seem to have a significant proportion of overlap with a medium, negative, significant relationship. This can be interpreted at the implicit and explicit measures in part measuring the same thing. However, there would be some factor independent of each measurement. Interestingly, the protective factor variable was able to significantly predict current suicide attempt status (medium, negative, significant relationship), but not self-injury attempt status (small - medium, negative, non-significant relationship), suggesting that this variable is better suited for a suicide focus. In short, it appears the explicit measures are better at predicting current behavior. Risk factors are better at predicting suicide attempts than self-injury attempts because these factors are primarily suicide focused, and protective factors are better at predicting suicide attempts than self-injury attempts, because these factors are only suicide focused. References Australian Bureau of Statistics (2011), Mental Health and Suicide Statistics, cat. no. 8147.0, retrieved on 12th April 2012, from AusStats Database. Bertolote J. (2004). Suicide Prevention: at what level does it work? World Psychiatry. 3(3):147-151. Greenwald A., McGhee D., & Schwartz J. (1998) Measuring individual differences in implicit cognition: The implicit association test.: Journal of Personality and Social Psychology, 74, 1464–1480. Lane  K. A., Banaji M. R., Nosek B. A., & Greenwald, A. G. (2007) Understanding and using the Implicit Association Test: IV. What we know (so far) (Pp. 59-102).  Nock M., & Banaji, M. (2007) Prediction of Suicide Ideation and Attempts Among Adolescents Using a Brief Performance-Based Test. Journal of Consulting and Clinical Psychology, 75(5), 707-715. Nock M., Park J., Finn, C., Deliberto T., Dour H., & Banaji M., (2010) Measuring the suicidal mind: Implicit cognition predicts suicidal behavior. Psychological Science, 21(4), 511-517. Nosek B. A., Greenwald A.G., & Banaji M.R. (2007) The Implicit Association Test at age 7: A methodological and conceptual review (pp. 265-292). In J. A. Bargh (Ed.), Automatic processes in social thinking and behavior. Psychology Press. Nosek B., Hawkins C., & Frazier R. (2011) Implicit social cognition: from measures to mechanisms. Trends in Cognitive Sciences, 15(4), 152-159. Pirkis J., and Burgess, P. (1998) Suicide and recency of health care contacts: A systematic review. The British Journal of Psychiatry: 173: 462–74. Read More