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| ORIGINAL ARTICLE |
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| Year : 2018 | Volume
: 2
| Issue : 2 | Page : 101-108 |
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Is there a protective model against suicide?
Mona Srivastava1, Pradeep Yadav2
1 Department of Psychiatry, Institute of Medical Sciences, Banaras Hindu University, Varanasi, Uttar Pradesh, India
2 Department of Psychiatry, Saraswati Medical College, Lucknow, Uttar Pradesh, India
| Date of Web Publication | 30-Nov-2018 |
Correspondence Address:
Mona Srivastava
36/2 HIG, Kabir Nagar Colony, Durgakund, Varanasi - 221 005, Uttar Pradesh
India
 Source of Support: None, Conflict of Interest: None
DOI: 10.4103/aip.aip_3_18
Background: Suicide is a major concern to medical professionals because of the association of social, personal, occupational domains, and a dearth of effective interventions especially so in our set up. Aims: The aim of this study is to compare and correlate different factors influencing suicide attempts and draw a model regarding their role in suicidal behavior. Materials and Methods: A total of 80 consecutive suicide attempters were recruited in the study, in which the correlation analysis was performed between presumptive life events scale, social support scale and coping style questionnaire and partial regression analysis among eight factors influencing suicidal behavior. Results: Correlation between social support and coping mechanism showed a significant positive correlation between four components. Correlation between total life events and coping questionnaire, positive significant correlation was found in six set of factors and correlation between total life events and social support total 15 set of factors were having significant correlation only one of them is positively correlated. A linear regression model was drawn most influencing factor was psychiatric illness and least is perceived support. Conclusion: Suicide attempts are influenced by many factors some are protective, and some are risk factors. This analysis shows that not individually but many factors are correlated with each other significantly so that they can give additional risk or protection. Therefore, a common model set can be drawn to minimize risk factors and maximize protective factors to implement suicide prevention strategies. These steps can contribute in decreasing the morbidity of suicide significantly and also the burden associated with it.
Keywords: Presumptive life events scale, protective factors, regression model, social support, suicide
How to cite this article:
Srivastava M, Yadav P. Is there a protective model against suicide?. Ann Indian Psychiatry 2018;2:101-8 |
| Introduction | |  |
Suicide is the third leading cause of death among young people; however, the incidence of attempted suicide is much more. It has been observed that after puberty; rate of suicide increases with age until it stabilizes in young adulthood. This increase in suicide may be associated with the onset and increase in depressive and other disorders during adolescence as compared to childhood[1] as well as greater suicidal intent with age.[2] In comparison to adult males, adolescent males complete suicide at rates approximately five times higher than rates for adolescent females.[3] Suicide rates have shown a rise among the youths between age ranges of 15–19 years as a result of rise in rates of depression, the increased availability of firearms and other means among adolescents (Commission on Adolescent Suicide Prevention, 2005). India accounted for the highest estimated number of suicides in the world in 2012, as per a WHO report one person commits suicide every 40 s globally. In the WHO South-East Asia Region, the estimated suicide rate is the highest as compared to other WHO regions. Suicide rates show a peak among the young and the elderly, the report said. The WHO estimates that nearly 900,000 people worldwide die from suicide every year, including about 200,000 in China, 170,000 in India, and 140,000 in high-income countries.[4]
Findings from our nationally representative survey from the National Crime Records Bureau (NCRB), in context to the causes of deaths in India, show suicide to be an important cause of death; especially in young people aged 15–29 years.[5] Studies from high-income countries show male-to-female suicide death ratios of about three to one.[6] The age-related suicide rate in Indian women is more than two and a half times greater than it is in women in high-income countries and equal to that in China.[6],[7] India relies on its NCRB for national estimates, and these reports show fewer suicide deaths (about 135,000 suicide deaths in 2010)[8] that is estimated by WHO. Studies in India show varying results with rates of psychiatric disorders ranging from 9.5% to 24.9%.[9],[10] In one psychological autopsy study, 24% of suicides had a psychiatric diagnosis, namely, major depressive disorder, bipolar affective disorder, or schizophrenia; substance abuse was found in 18%.[11] In a study of attempted suicide, 11.6% had a psychiatric diagnosis of alcohol dependence followed by depression, schizophrenia, conduct, and personality disorder.[12]
The relationship of suicide to negative life events, stress, object loss, and negative interaction needs to be understood in the framework of a model of vulnerability, support, coping, and problem-solving. Rich and Bonner[13] found in a stress-vulnerability model that negative life events and stress accounted for 30% of the variance in suicidal ideation. Studies which measured stressful life events found that approximately 90% of suicide attempters reported negative life events[14] and about 35% experienced stressful life events in the previous 6 months.[12] However, in the absence of a control group, it is hard to interpret the significance of life events. Previous studies provide initial evidence that social support may confer resiliency against suicide ideation. Studies have found that social support is directly associated with lower occurrence of suicide ideation even in the presence of negative life events.[15],[16] Coping mechanisms serve as an internal source of emotional strength and mediate a positive reaction to any perceived stress, whether internal or external.[17] Individuals who attempt suicide have a higher difficulty in coping with interpersonal problems than nonsuicidal population.[17],[18],[19] Life events and coping styles can alter the situation and function of the social support system in terms of size, frequency of interaction, and stability and these then may be associated with suicidal behavior. There are limited data available from the Indian context regarding the interplay of life events, coping and social support and also their role in protection against suicide, hence the present study was undertaken.
| Material and Methods | | |
The present study was conducted in the Department of Psychiatry of a multi-disciplinary tertiary care center situated in the northern part of India. The sample consisted of 80 suicide attempters qualifying the criteria for suicide attempt as defined by the WHO. Cases were collected from the emergency outpatient department and other department where the likelihood of a case of attempted suicide to be referred was higher, for example, psychiatry, medicine, ENT, surgery, gastroenterology, and burn ward of plastic surgery department. The data were collected from the indoor and outdoor services of the hospital. Once the cases met the inclusion criteria, they were asked for a written informed consent. Group 1: Was the experimental group which comprised of 80 individuals who were selected in accordance with the inclusion criteria. They were consecutive individuals of attempted suicide presenting to the emergency and other outpatient services (Medicine, ENT, Psychiatry, and Surgery); those giving written informed consent; not having any chronic medical disorder. The exclusion criteria were, those not accompanied by family members. Group 2: Control group comprised of 80 individuals who were selected in accordance to the inclusion criteria, i.e., those not suffering from an axis I disorder on DSM IV-TR; matched with patient group on sociodemographic characteristics (sex, marital status, age, education, socioeconomic status, and domicile); those having optimal functioning on axis V of DSM IV-TR; giving written informed consent. The exclusion criteria were the presence of a history of a suicide attempt. The control group was recruited from the relatives and friends accompanying the patients presenting to the daily walk-in clinic of the department of psychiatry. Based on the previous 1-year record and the time limit of the study, the sample size was decided (the study was a part of the MD thesis). The study period was from November 2016 to November 2017. The Ethical Committee of the institute gave its consent for the study.
Tools
Presumptive stressful life events scale (Gurmeet Singh, 1984)
This scale was designed by Singh et al.[20] The scale consists of 51 life events commonly experienced by the normal Indian adult population. One hundred is the highest stress score and zero denotes no perceived stress. Scale items are further classified into desirable, undesirable or ambiguous and personal or impersonal (not dependent on the individual's action). This scale is widely used in research and has a good reliability and validity (0.8).
Social support questionnaire (Nehra et al., 1996)[21],[22]
This scale is a Hindi language adaptation of the Pollack and Harris scale[21],[22] which is used to measure the perceived social support. It has 18 items; a higher score indicates a better perceived social support. The items in the scale refer to help, concern, support, reinforcement, and criticism that a person gets from one's family, friends, social acquaintances, and working colleagues. It is a robust instrument in terms of both consistency and stability of scores. It can be used in a variety of situations where the social support has to be measured as an independent variable. It has a test-retest reliability of 0.59 and correlation with clinician's assessment at 0.80.
Cope inventory (Carver, 2007)
The full length version of the COPE Inventory[23] was used to measure stress coping skills. The COPE Inventory measures an individual's response to general life stressors. The original scale had 15 dimensions of coping. Five dimensions assess conceptually distinct aspects of problem-focused coping (active coping, planning, suppression of competing activities, restraint coping, and seeking of instrumental social support); five dimensions assess aspects of emotion-focused coping (seeking of emotional social support, positive reinterpretation, acceptance, denial, and turning to religion); and five dimensions assess coping responses (focus on and venting of emotions [venting], behavioral disengagement, mental disengagement [self-distraction], humor, and substance use). The COPE Inventory has 15 scales with 4 items each, a total of 60 items. The COPE items are measured using a 4-point Likert type scale including 1 (I usually do not do this at all), 2 (I usually do this a little bit), 3 (I usually do this to a medium amount), and 4 (I usually do this a lot).
General health questionnaire-12
The general health questionnaire-12[24] has been translated into Hindi by Gautam et al.[25] This is a 12-item self-administered questionnaire used extensively in clinical practice to measure changes in nonpsychotic psychiatric status over the past month. There are four possible responses to each question, which were scored 0-0-1-1. A score of ≤3 is the cutoff point for “psychiatric distress.”[25]
The individuals were examined on these tools and the data were analyzed using SPSS version 16.0 for windows.
| Results | | |
We took two groups for comparison: (a) attempters and (b) controls, in which the mean age of attempters was 26.42 with standard deviation 8.851 whereas in control group, mean age was 25.85 along with standard deviation 8.377, the difference was not significant and P value is found to be 0.674, this was expected as the two groups were compared for age and gender. In a gender-based comparison of persons who attempted suicide, it found that Group 1 had a higher proportion of the male population (n = 45, 56.2%) and marginally lower female population (n = 35, 43.8%) similar picture emerged in Group 2. The difference was not found significant (P = 1.000) and χ2 = 0.000. Similarly, there was no difference in the marital status also (P = 0.632). In Group 1, the number of married persons was higher (n = 44, 55%) in comparison to unmarried (n = 36, 45%) whereas in Group 2, married population was more (n = 47, 58.8%) than unmarried (n = 33, 41.2%) [Table 1]. As shown in [Table 1], a comparison between education levels of attempters and controls found a significant difference (P = 0.018). Maximum individuals had a 12th standard educational level, thereafter graduate level of education (n = 27, 33.8%) and least were in the illiterate group (n = 3, 3.8%). Somewhat similar findings emerged in the control group. On comparing the different income groups, the difference was found to be significant (P = 0.040). Maximum number of the individuals belonged to lower income range, i.e., Rs.<4500 (n = 40, 50%) in Group 1 and marginally higher (n = 56, 70%) in Group 2. The least number of individuals (n = 5, 6.2%) in each group belonged to highest income range, i.e., Rs.>30,000. χ2 value was found 8.330. On comparing the religion maximum number of individuals belonged to the Hindu community (n = 78, 97.5%) in attempters as well as controls. On comparing the domicile, there was no difference, (χ2 = 1.358). It was seen that more individuals in both groups hailed from the rural area. Our results show that majority of the individuals were either homemaker or students by occupation (62.5%). As per occupation the distribution was 13.8% skilled, 12.55% semiskilled, 6.2% unskilled, and 5% professionals. Results were more or less similar in the control group also homemaker or students were 65%. Professionally, 12.5% skilled, 11.2% semiskilled, and 6% unskilled. On comparing the coexisting psychiatric illness [Table 2] among cases as well as controls, the difference was found to be highly significant (P < 0.001) with χ2 = 103.9. Maximum number of suicide attempts were seen in psychotic group (n = 30, 37.5%) and least (n = 9, 11.2%) in substance-abusing individuals. Majority of suicide attempters was devoid of any medical illness (n = 61, 76.2%), this finding is because of the selection bias since we excluded medical illness during intake in the study. Control group was also free of medical illnesses (n = 65, 81.2%). Comorbidity of psychiatric illness was high (n = 68, 85%) in the experimental group. Regarding the presence of a positive family history between the two groups, there was no significant difference (P = 0.339).
The results showed a significant positive correlation among three variables namely emotional social support and desirable life events (r = 0.265, P = 0.017); substance use and personal life events (r = 0.277, P = 0.013); and between humor and personal life events (r = 0.332, P = 0.003). Positive correlation was seen between total life events and total social support (r = −0.285, P = 0.010), negative significant correlation among total life events with concern and support (r = −0.290, P = 0.009 and r = −0.315, P = 0.004). A positive correlation was found between total life events and criticism (r = 0.289, P = 0.009) [Table 3]. | Table 3: Correlation among various parameters in social support and coping methods
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Comparing the parameters on coping style and life events and social support [Table 4] and [Table 5] it was found that if the life events were more coping was affected. Negative life events as also the social support affected the coping in the presence of life events. Even in the face of adverse life events social support had a protective influence. In the partial linear regression model, suicide attempt was the dependent variable, and other parameters were taken as independent variables. The coefficient of determination value (r2) fitted to regression line [Table 5] and [Figure 1]. The value of r2 lies from 0.0 to 1.0. Among the 5 categories of presumptive life events scale (PSLES), four subcategories (desirable, undesirable, personal, and impersonal) [Figure 1] are present in this regression series. Along with this present, past psychiatric illness and medical illness were also among the series. Support in the social support scale was also significantly associated. All parameters were found to have a significant difference (P ≤ 0.001) [Table 6]. | Table 4: Correlation among total life events and different coping methods
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 | Table 5: Correlation between total life events and various social support parameters
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 | Table 6: Model Summary for partial linear regression among various factors affecting suicidal behavior
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| Discussion | | |
In the present study, a comparison between suicide attempters and normal controls was done on various parameters related to life event, coping and perceived social support to postulate the protective and harmful effects of various factors on an individual. After comparison of different components, some correlations were significantly associated, i.e., they were found to influence the suicidal tendency. There was a significant difference (P = 0.017) among active coping and help, mental disengagement with total social support and help (P = 0.015 and 0.016, respectively) and behavioral disengagement with total social support. Emotional social support was found to have a significant positive correlation with desirable life events (P = 0.042); similarly, other positive correlations were found in mental disengagement and desirable life events (P = 0.032), substance abuse and humor with personal life events (P = 0.013 and P = 0.003, respectively). A significant negative correlation (P = 0.027) was found between positive reinforcement and growth and undesirable life events, meaning that if positive reinforcement and growth coping method were exercised by the individuals, the life events had a lesser impact on the person's life. The analysis points toward a high correlation with criticism. The conclusion being that a healthy, noncritical social support system has a protective role against suicide. The current psychiatric illness was also a strong predictor of attempted suicide. If the correlation is significant, it clearly denotes that modification of one factor leads to modification of a related factor, meaning minimum intervention may be needed for planning and execution of interventions for suicide prevention strategies.
Analysis from partial linear regression shows that psychiatric illness is strongest risk factor for suicide attempts, followed by undesirable life events, desirable life events, past psychiatric illness, personal life events, and presence of medical illness, impersonal life events and support. The factors can be listed in the order of their significance as a risk factor for suicide:
- Presence of psychiatric illness
- Decreased undesirable life events
- Increased desirable life events
- Absence of past psychiatric illness
- Less number of personal life events
- No medical illness
- Less impersonal life events
- Increased social support.
The literature review of studies suggests that avoidance as a coping is more common in people who attempt suicide in general.[26],[27] The risk of suicide is a cumulative effect of multiple stressors, similar studies have found high rates of stressful life events using PSLES among suicide attempters as we have found.[12],[28] Gender is also a risk factor although we did not find a correlation; male had higher suicidal intent than females.[28] Domicile has also been considered a risk factor in some studies with rural women being disadvantaged, but in urban areas, men had higher psychiatric morbidity.[28] Studies have also found that suicidal subjects were able to generate as many adaptive strategies as controls for coping, but they actually used fewer and more likely to identify maladaptive behaviors as ways of coping.[29] Hagnell and Rorsman[30] found more objective losses and humiliating experience in the week before death among suicide victims than people dying from natural causes and more changes in living condition, work problems, and objects losses in the final year. The present study also found criticism and increased undesirable life events to be highly correlative to attempted suicide. The familial conflict was a risk factor in studies, and we also found a similar pattern.[31] Stresses stemming from social practices and perceptions are linked with a considerable number of suicide.[31] Social and family factors, negative life events, and medical illness may interact with psychiatric diagnosis and personality disorders, genetic variables, biological factors, and psychosocial stressors and ultimately act as predisposing and precipitating or contributing factors to suicidal behavior. Rudd[32] has postulated an integrative model of suicide in which influence of recent loss when paired with a perceived lack of family support and personal attributes compound the risk of suicide. Evidence for a “stress vulnerability” model of suicidal behavior can be understood in terms of being a risk factor or being a protective factor.[13]
| Conclusion | | |
Suicide is a serious public health problem. Multiple strategies are formed and implemented to prevent this, but till date, they are not robust enough to control it completely. It is not necessary that the factors related to suicidal behavior are always present individually, but they can be additive if combined, as shown in this study. To prevent suicide, all correlated factors should be taken into account. This can help make a complete strategy of suicide prevention and can reduce the public health burden.
Limitations
There are few limitations in this study, being a government hospital setting people representing a particular socioeconomic status may be over-represented. Cases belonged to a definite geographical area, and only serious patients are referred to this hospital, as it is a tertiary care center, hence generalization of results is not possible. Reliability of reporting of suicide may be difficult because of the social stigma associated with it; hence, cases may have been missed.
Future directions
Multicentric, longitudinal, and naturalistic studies would be the ideal way to comment on the risk factors, this can help in formulating better preventive strategies. In future studies taking multiple centers and community can be undertaken for a better conclusion.
Acknowledgment
We would like to acknowledge the participants.
Financial support and sponsorship
Nil.
Conflicts of interest
There are no conflicts of interest.
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[Figure 1]
[Table 1], [Table 2], [Table 3], [Table 4], [Table 5], [Table 6]
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