A Study on Suicidal Behavior Among Adolescents in Relation to Depression

More Krantee Bharat1*, Dr. Preeti Dixit2

1 PhD Student, Kalinga University, Raipur (CG), India

Email: morekrantee42@gmail.com

2 PhD Guide, Dept. of Psychology, Kalinga University, Raipur (CG), India

Abstract - This research delves at the correlation between teenage sadness and suicide thoughts and actions. We surveyed and interviewed distinct groups of teenage using a mixed-methods approach. High levels of depressive symptoms are significantly associated with an increase in suicide inclinations, according to the results. Peer interactions, academic pressure, familial dynamics, and social media all have a role in shaping this relationship. In order to decrease the risk of suicide, the research emphasises the need of early intervention and mental health education. To enhance teenage well-being and create supportive settings, the findings call for community and school-based mental health programmes.

Keywords: Mental Health, Surveyed, Suicide, Sadness, Teenage.

INTRODUCTION

The origin of the English word "suicide" may be traced back to the Latin words "sui," which means "of oneself," and "caedes," which simply means "killing." In the 17th century, British philosopher Sir Thomas Browne was the one who popularised the word. According to Durkheim, the term "suicide" may be used to refer to any kind of death that is the outcome of an activity, whether it be a good or terrible action, that is carried out by a person who is aware, either directly or indirectly, of the repercussions of their acts. [1]

As defined by the World Health Organisation (WHO), suicide is an act that is carried out with the intention of bringing about desired changes but ultimately results in death, with the individual who has committed suicide being aware of or anticipating that their death is impending. No matter whether it is done voluntarily or involuntarily, the purpose of suicidal conduct is to terminate one's life for good. The term "gestures" is often used to refer to real acts of suicide. However, it is important to differentiate between other types of self-injury, known as para-suicidal activity, which is similarly planned but does not mean to result in death. Cutting and burning are two examples of prevalent types of self-injury that victims may engage in. These activities, despite the fact that they may inflict severe misery, agony, and damage, do not have the intention of causing the individual to take their own life. A self-injury technique that is followed correctly may help avoid unintended suicide. [2]

A connection exists between suicidal thoughts and behaviours and killings. [3] This connection is a correlation. When some people come to the conclusion that life is not worth living, they often take the life of another person with them. [4]This is because they are of the opinion that their own life is not worth living. An additional reason for suicide-homicide actions might be a desire for revenge or retaliation against people who are responsible for the unspeakable pain that the suicidal person has endured. Instances like this have the potential to stir religious beliefs as well as military requirements. [5]

A person is deemed to be suicidal if they engage in any activity or mental pattern that includes deliberately or unintentionally inflicting damage onto themselves. Suicidal ideation, as well as self-injury and activities that are harmful to oneself, are included in this category. [6] Researchers have described sociality as a collection of cognitive and behavioural characteristics, and it is possible that a person's sociality might be the source of suicidal thoughts and acts. Suicide thoughts and actions are now among the major causes of death among adolescents in today's society. [7] Ideas, threats, gestures, self-cutting, low-lethal attempts, and actual suicide are all examples of activities that fall under the umbrella term of suicidal conduct. Suicidal behaviour encompasses a range of behaviours. [8]

An other expression that is often used in today's society is "deliberate self-harm." There are a few different names for auto aggression, self-injury, and self-mutation, and one of them is dysregulated self-harm (DSH). [9] The purposeful removal or alteration of biological tissue without any visible or conscious intent to commit suicide, yet inflicting sufficient injury to cause damage to the tissue, is another description of this. [10]

There exists a spectrum of behaviours in which the primary injury is self-inflicted. These behaviours include self-harm, self-injury, self-inflicted violence, non-suicidal self-injury, and self-injurious activity. [11] Generally speaking, it is done out without the goal of committing suicide and involves deliberately causing damage to tissue. The most prevalent kind of self-inflicted injury is the act of cutting one's own flesh with a sharp object, such as a surgical knife or razor blade. The term "self-mutilation" is often used to refer to behaviours that are even more difficult, ambiguous, or unpleasant than those described by the term itself. [12] A self-inflicted wound is another term that is used to describe injuries that soldiers inflict on themselves in order to be pulled from battle earlier than they would otherwise be. It is evident that the term "self-inflicted wound" has a secondary meaning that extends beyond the concept of self-harm. Additionally, those who self-inflict physical damage on themselves as a result of eating disorders are also regarded to be doing acts of self-harm. [13]

NSSI, which stands for non-suicidal self-injury, is a new disorder that was included in the DSM-5 under the "Conditions for Further Study" category. As a key socioeconomic factor that contributes to the rise in the number of instances of self-harm, childhood maltreatment is considered to be a significant contributor, alongside poverty and dysfunctional relationships between parents or partners. [14] There are a number of factors that may elicit suicidal impulses, some of which include, but are not limited to, violence, poverty, and unemployment. There is a possibility that self-harm might be a manifestation of depersonalisation or from a hallucinogenic state. Reports indicate that thirty percent of autistic individuals engage in self-harming activities such as eye-poking, skin-picking, hand-biting, and head-banging. Additionally, seventy percent of those with borderline personality characteristics engage in these actions. [15]

METHODOLOGY

Choose A Sample

Adolescents from Raipur districts, categorised as either male or female, and ranging in age from thirteen to eighteen, made up the sample. There are two types in each category. i.e., teenage socioeconomic status (both low and high). For this study, a total of 200 adolescents were considered for the sample, with 50 chosen using the Purposive Random Sampling Method for each of the four groups. Here are the parameters that were used to pick teenagers from various socioeconomic backgrounds:

Depression Scale

Shamim Karim and Rama Tiwari (1986) created it with the intention of making it easier to recognise the signs of depression. The twelve dimensions of depression that make up this assessment are as follows: 5) Irritability, 6) Fatigability, 7) Pessimism, 8) Sleep disruption, 9) Apathy 6) Isolation and lack of concern for others, 7) Downcast or sorrowful, 8) Disliking Oneself, Intentionally hurting oneself 11.)Reoccupying Somatic Areas 12) Lack of Perfection.

Locating Items by Area

There are a total of 96 items on the depression inventory, which covers twelve symptoms: apathy, disturbed sleep, pessimism, fatigability, irritability, social withdrawal, indecisiveness, self-hatred, self-acquisition, self-harm, somatic reoccupation, and depressed mood. You may find the item distributions by area in the table below.

Table 1: Depression Scale: Aspects of Depressions

S. No.	Areas or Aspects of Depressions	Item No.
1.	Apathy	1,13,14,39,50,61,78,85.
2.	Sleep disturbance	2,15,28,40,51,62,63,86.
3.	Pessimism	3,16,29,41,52,64,77,87.
4.	Fatigability	4,17,18,42,53,65,78,88.
5.	Irritability	5,19,30,43,44,66,79,89.
6.	Social Withdrawal and Self-Centeredness	6,20,31,45,54,67,68,90.
7.	Dejected or Sadness	7,21,32,46,55,69,80,91.
8.	Self Dislike	8,22,33,47,56,70,81,92.
9.	Self Acquisition	9,23,34,48,57,71,82,93.
10.	Self Harm	10,24,35,49,58,72,73,94.
11.	Somatic Reoccupation	11,25,36,37,59,74,83,95.
12.	Indecisiveness	12,26,27,38,60,75,84,96.

2. Assessment Methodology

No points should be deducted from a "Not at all" answer, one from a "little bit," two from a "moderately" response, three from a "quite a bit" response, and four from a "extremely" response when calculating test scores. To determine the final score, sum together all of the answer marks for each sentence to get the raw score of an individual's depression from the exam.

Procedure

Both preliminary and final studies were part of the current inquiry. Which is detailed in the following Narrative.

Pilot Study: The suitability of the test and sample for the final research was determined by a preliminary study. Forty people participated in the survey. We considered participants from each of the research groups. People who filled out these surveys weren't part of the main research. The order of administration of all tests was established based on the results of the pilot research. Additional guidance on potential statistical methods for the final research was provided by the pilot study.
Main Study: Subjects in the research were polio patients, and data for the characteristics of interest were culled from 200 participants based on the study's design.

Statistical Analysis

The suggested study was empirically verified by analysing raw data with the use of statistical tools. When it came to suicidal ideation, depression, and loneliness, we calculated the mean, standard deviation, standard error, and confidence value for every variable. Depression and loneliness were examined for their major effects on suicide using analysis of variance and correlation.

RESULTS

Table 2: Depression Statistics (Sample Size-50, Age Range 13–18)

Group	Status of Work	Mean Score	Sd	Se	Cv%
Male	Low Ses	114.94	56.42	7.78	49.084
Male	High Ses	96.96	50.31	7.11	51.88
Female	Low Ses	115.86	55.11	7.79	47.56
Female	High Ses	113.46	48.09	6.80	42.39

Table shows the mean, standard deviation, standard error, and confidence interval for each of the four groups of subjects. It shows that the lowest mean score for depression was 96.96 among the high socioeconomic status male adolescents, and the highest mean score for low socioeconomic status female adolescents was 115.86.

Adolescent boys from poor socioeconomic backgrounds are more likely to suffer from depression than their high socioeconomic level counterparts, according to a mean score of 114.94 for low socioeconomic males and 96.96 for high socioeconomic status males.

Females from low socioeconomic level had a mean depression score of 115.86, while those from high socioeconomic position had a score of 113.46. This suggests that teenage girls from lower socioeconomic backgrounds are more likely to suffer from depression than those from higher socioeconomic backgrounds.

Graph 1: Mental Health Disorder Visualisation

Table 3: Comparanse Statistics of Male and Female Group Depression (Sample Size: 100) (Age Rang: 13–18)

Group	Mean Score	Sd	Se	Cv%
Male	105.95	53.94	5.39	50.91
Female	114.66	51.47	5.15	44.89

The depression ratings varied throughout the groups, ranging from 13 to 18, as seen in the table. A guy averaged 105.95 and a female 114.66. With a mean score of 105.95 for all males, it seems that men from poor and high socioeconomic backgrounds have less of a problem with depression than women do. Females from low- and high-SES backgrounds are more likely to suffer from depression than males, according to the overall mean score of 114.66 for females.

Graph 2: Male and female groups' graphical representations of depression

Table 4: Data Synthesis On Depression Among People With Varying Socio-Economic Statuses (Sample Size: 100) (Age Range: 13–18)

Group	Mean Score	Sd	Se	Cv%
Low Ses	115.40	55.49	5.55	48.08
High Ses	105.21	49.66	4.97	47.19

Two groups of people based on their socioeconomic position had their depression scores shown in the table. Groups with low socioeconomic level had an average score of 115.40, while those with high socioeconomic status had an average score of 105.21. The overall low socio-economic status group suffered more from depression than the high socio-economic status group, with a mean score of 115.40 for depression. Overall, those with high socioeconomic level had a lower risk of depression (mean score of 105.21 vs. low socioeconomic status group), suggesting that this demographic has fewer cases of depression overall.

Graph 3: Visual depiction of depression on groups with low socioeconomic status and groups with high socioeconomic status

Table 5: Depression's Statistical Impact on Sample-Groups Overall Observation with A Sample Size Of 200 And An Age Range Of 13–18

Group	Mean	Sd	Se	Cv%
Overall	110.31	52.77	5.27	47.84

Table shows that the total group's depression ratings vary from 13 to 18. The total mean score was 110.31. The average depressive score for both males and females in the sample, regardless of socioeconomic position, is 110.31. It seems like there may be a hint of despair here.

Variance Analysis

Table 6: f- depression level ratio using sem, cd, and cv values for selected patient groupings

Source of Variation	Sun of Squares	Df	Mean Squares	F Value
Groups	12019.22	3	4006.41	1.45 Ns
Error	542081.18	196	2765.72
Total	554100.40	199
Sem	5.28
Cd 5%	14.63
Cd 1%	19.18
Cv %	47.84

The F-ratio depression did not differ in a way that was statistically significant across the different subject groups.

On the other hand, according to the mean tables, the mean score for depression among those who came from low socioeconomic levels was 114.94, whereas the mean score for those who came from high socioeconomic rank was 96.96. When it comes to females, the score for having a low socioeconomic status is 115.86, while the score for having a high socioeconomic level is 113.46. The female group had an average score of 114.66 for depression, whereas the male group had a score of 105.95 (see table for further information). In accordance with the information shown in the table, the average score for depression was 105.21 among those who held a high socioeconomic position, but the mean score for those who had a low socioeconomic level was 115.40. The average score for depression among all of the participants in the group was 110.31, as shown in Table. The data shown in the table demonstrates that the average levels of depression differed across all groups. It was shown that women who came from families with lower socioeconomic status were more likely to suffer from depression. It was better for people who were in lower socioeconomic levels than it was for those who were in higher ones.

All of the female students who were polled from secondary schools were found to suffer from anxiety disorders, and there was a significant relationship between the socioeconomic level and the experience of depression. According to Moeini, Bashirian, Soltanian, Ghaleiha, and Taheri (2019), there is an urgent need for screening programmes, psychological training, accurate identification of high-risk children in secondary schools, and timely intervention for female students in these settings. These are all things that are needed immediately.

The socioeconomic level of an individual is associated with depression as well as other variables. In addition to reporting greater levels of concern and stress, those who come from households with a Low Socio-Economic Status (LES) are more likely to have parents who suffer from depression. In addition, it has an effect on a person's personal life, as well as their professional life, social life, academic life, and family life.

Teenagers who come from families with better socioeconomic status are more likely to have access to treatment choices for mental health disorders such as anxiety and depression. A significant improvement has been made in the accessibility of clinical psychologists, guidance counsellors, and counselling services for teenagers who are enrolled in the HSE. They seem to have a heightened awareness of the significance of maintaining their mental health.

People who come from socioeconomic circumstances that are poorer are less likely to get help for their mental health from people they know and trust, and as a consequence, they often suffer extra financial restraints. As a result, it might cause them even more difficulties.

As a consequence of the fact that adolescent girls are more likely than adolescent males to have a strong connection to their school, family, employment, and social environment, they are more likely to be impacted by events such as the death of a friend or relative, the end of a love relationship, academic failure, and other similar occurrences. As a consequence of this, it contributed to the psychological characteristics that are associated with a higher risk of depression in women.

Graph 4: Visualisation of Depressation in the Context of Sample Groups

CONCLUSION

There are a number of important takeaways from the research on teen suicide attempts and depression. Teens from lower-income families are much more likely to suffer from depression than their wealthier counterparts. This pattern is more noticeable in women, suggesting that they are more prone to sadness and thoughts of suicide. Teens from lower socioeconomic backgrounds were more likely to suffer from depression, and this was especially true for females. The significance of tailored treatments and support networks, particularly for economically disadvantaged teenagers, is highlighted by these findings. Adolescent depression and suicide ideation and behaviour may be lessened with the help of school-based mental health programmes, easily available mental health services, and the promotion of supportive environments at home and in the classroom. To successfully treat these mental health concerns, early diagnosis and appropriate intervention are crucial.

REFERENCES

Karasek, R., and Theorell, T. (2021). Healthy work, stress, productivity and tLie reconstmction of working life. New York: Basic Books.
Kashani, ét.H., and Ray, it.S. (2018). Depressive related symptoms among preschool age children. Child PsycLiiatriy and Human Development, 1, 233-238.
Kashani, éI.C., Rosenberg, T.K., and Reid, Lt.C. (2020).Levels of hopelessness in children and adolescents: A developmental perspective. Joumof of Consulting and Clinical Psychology, 57(4), 496-499.
Kavanagh, K., and Hops, H. (1994). Good girls? Bad Boys? Gender and development as contexts for diagnosis and treatment. In T H Ollendick and R Lt Prinz (Eds.), Advances in Clinicn/ cLiild psychology (Vol. 16, pp. 45-79). New York: Plenum Press.
Keller, M.C., and Nesse, R.M. (2020). The evolutionary significance of depressive symptoms; different adverse situations lead to different symptom patterns. I Pers Soc Psychol., 91(2), 316-30.
Kennard, B.D., Stewart, S.M., Hughes, Lt.L., Patel, P.G., and Emslie, G.it. (2016). Cognitions and depressive symptoms among ethnic minority adolescents. Culture Divers Ethnic Minor Psychol., 12(3), 578-91.
Kennedy, S., Kiecolt-Glaser, LI.K., and Glaser, R. (2020). Social support, stress, and the immune system. In B.R. Sarason, I.G. Sarason, and G.R. Pierce (Eds), Socinl support: An interoctionnl view (pp.253-266). New York: Willey.
Kessler, R.C., Kendler, K.S., Health, A., Neale, M.C., and Eaves, L.ét. (2018). Social support, depressed mood, and adjustment to stress: A genetic epidemiologic investigation. Joumol of Personality and Socinf Psychology, 62, 257-272.
Kessler, R.C., McGonagle, K.A., swartz, M., Blazer, D.G., and Nelson, C.R. (2017). Sex and depression in the National Comorbidity Survey, I: Lifetime prevalence, chronicity and recurrence. I Affect Discord. 29, 85-96.
King, K.B., Reis, H.T., Porter, L.A., and Norsen, L.H. (2019). Social support and long-term recovery from coronary artery surgery: Effects on patients and spouses. Heofth Psychology, 12, 56-63.
Kovacs, M., Obrosky, D.S., and Sherrill, £1. (2020). Developmental changes in the phenomenology of depression in girls compared to boys from childhood onward. I Affect Discord., 74(1), 33-48.
Kraaij, V., Garnefski, N., Plan de Wilde, E., Dijkstra, A., Gebhardt, W., Maes, s., and Doest, L. (2021). Negative life events and depressive symptoms in late adolescence: bonding and cognitive coping as vulnerability factors? Joumol of YoutLi and Adolescence, 32(3), 185- 193.
Lakey, B., and Cassady, P.B. (2019). Cognitive processes in perceived social support. Joumof o/ Personality and Social Psychology, 59, 337-348.
Lakey, B., Moineau, S., and Drew, if.B. (2020). Perceived social support and individual differences in the interpretation and recall of supportive behavior. Journnf of Sociof ond Clinicol Psychology, 1 1, 336-348.
Landman-Peeters, K.M., Hartman, C.A., van, der, Pompe, G., den, Boer, ét.A., Minderaa, R.B., and Ormel, ét. (2015). Gender differences in the relation between social support, problems in parent-offspring communication, and depression and anxiety. Soc Sci Med, 60(1 1), 2S49-S9.