Efficiency of diagnostic model to predict recurrent suicidal incidents in diverse world communities

doi:10.4236/jbise.2009.27074

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J. Biomedical Science and Engineering, 2009, 2, 516-520

doi: 10.4236/jbise.2009.27074 Published Online November 2009 (http://www.SciRP.org/journal/jbise/ JBiSE

Published Online November 2009 in SciRes. http://www.scirp.org/journal/jbise

Efficiency of diagnostic model to predict recurrent suicidal

incidents in diverse world communities

Vatsalya Vatsalya1, Kan Chandras2, Shweta Sri va st a va3, Robert Karch1

1Health Promotion Management American University, Washington D.C., USA; 2Behavioral Sciences, Fort Valley State University,

Fort valley GA, USA; 3Department of Biology, Georgetown University, Washington D.C., USA.

Email: [email protected]

Received 16 July 2009; revised 26 August 2009; accepted 27 August 2009.

ABSTRACT

Suicidal attempts have a very significant effect on the

society, and they also reflect on the efforts of the

supporting health care and counseling facilities; and

the mental health professionals involved. The impact

of suicide is further magnified by the needs of per-

sons who attempt suicide multiple times, requiring

emergency health care and rehabilitation. Preve nt ing

such activ ities becomes a ma jor task for the support

providing agencies as soon as patient with such ten-

dencies are identified. There are repetitive traits

that can be observed during the entire therapeutic

program among the high-risk group individuals,

who are susceptible to this kind of activity and such

traits indicate for specific profiling. The aim of the

instrument is to prevent the occurrence of the re-

petitive suicidal attempts of the patients in various

world regions, which may have significantly higher

and concerning suicide rates. This profile has been

constructed on the various parameters recognized in

the statistical analysis of the patient population,

which have been identified or can be under treat-

ment for their suicidal behavior. This instrument is

developed to predict the probability of population

segments who may attempt suicide and repetitively,

by matching the parameters of the profile with that

of the patient pool. Building a profile for the purpose

of predicting behavior of this kind can strengthen the

intervention strategies more comprehensively and

reduce such incidents and health care requirements

and expenses.

Keywords: Instrument; Parameters; Predictor; Risk Cate-

gory; Suicidse

1. INTRODUCTION

Several world regions face the emerging concern of sui-

cidal incidents and such growth patterns have suggested

typical geographical factors playing major contributory

roles [1]. Many regions so far have been identified with

consistent year wise rising suicide rate and from such

locations, Washington State has been included in the

study to evaluate this phenomenon and derive a model to

investigate and predict suicidal incidents in the general

populations. Nationally, Washington State has the 16th

highest suicide rate and suicide is the eleventh leading

cause of death with 814 death reported in year 2005 with

a rate of 13.1 incidents per 100,000 (age adjusted) of

population, compared to the national US rate of ap-

proximately 11.0 [2]. Suicidal attempts can be five time

or more than the suicide death rate [3] (Figure 1).

There have been consistencies in reports that even af-

ter getting initial medical and other support services,

patients attempt suicide again in Washington State with

similar rate as without the interventions [4]. During

2003–2005, males in Washington accounted for 79% of

completed suicides, with the highest rate of suicide, observed

in the group among the age group of 75 years and more

[5]. In 2004; in the 15–24 age groups, suicide was the

second most leading cause of death and altogether 17%

deaths [6]. Nearly two-thirds of teens with clinical de-

pression go unnoticed and may not get treated; among

these, males 15 to 19 years old are five times more likely

Figure 1. Yearly suicide rate representation per 100,000 popu-

lations (Suicide attempt and death rate versus years as x:y co-

ordinates).

V. Vatsalya et al. / J. Biomedical Science and Engineering 2 (2009) 516-520 517

Figure 2. Age-group based comparisons of number of suicidal

incidents (Age-groups versus number of incidents as x:y coor-

dinates).

than females to complete suicides [7] (Figure 2). The

frequency of suicide attempts can increase, if the causa-

tive factors are not resolved. Extent for emotional and

physical pain cannot be assessed for individuals and

their relatives, though approximately three billion US

dollars of loss associated with the suicidal incidents has

been recorded so far during the year 2002–2006 [8].

Preventive procedures have been particularly promoted

to reduce such incidences, which have priority concern

to precisely identify target population. Development of a

predicting instrument, which can provide appropriate

behavioral evaluation, can be one of the choices to this

requirement.

This instrument is based on set of primary repetitive

characters, which can provide a predictable analysis of

such behavior among the high-risk group individuals,

who are susceptible to commit or attempt suicide. The

concept of predictor is to identify the patients with such

tendency or ideations and inform the healthcare profes-

sionals and people concerned, to prepare and implement

specific therapeutic plan to minimize such incidents fur-

ther. A predictor profile for the purpose of interpreting

specific behavior would strengthen the intervention

strategies, reduce the frequency of such incidents, and

regularize involvement of health care and financial re-

sources.

2. METHODOLOGY

Data source for the profile analysis has been collected

from yearly published hospitalization reports of suicide

incidents from Washington State public health statistical

data bank, Washington State Injury and Violence Pre-

vention Program, 2008; and GIS from 2002 to 2006 year.

Data from 15,826 cases with suicides and single or mul-

tiple identified attempts of history during the interval

2002–2006, betw een the age group of 15 and 75 + years,

have been included in the study (Figure 3). Significant

cohort parameters have been studied from the target

population for the development of the instrument,

namely gender, age groups, health condition, biological

and environmental factors (namely economic, academic,

social, ethnic and likewise). Statistical analysis has been

performed to identify repetitive characteristics of the

parameters with annual rate and frequency comparisons.

An analog model is constructed utilizing the parameters

and their characteristics under observations. The charac-

teristics have been broadly grouped as parameters of

interests and highly repetitive prevalent characteristics

observed in the evaluation have been consigned under

high risk category (Colored in red, Figure 6); average

repeating characteristics as intermediate and less fre-

quently occurring as low risk category. These parameters

were constructed in the form a pathway with the promi-

Figure 3. Methodology illustration for investigating model parameters.

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V. Vatsalya et al. / J. Biomedical Science and Engineering 2 (2009) 516-520

518

nent parameters evaluated initially within which all the

characteristics of each parameter undergo comparison

for in track corresponding profile similarities.

Characteristics which have not demonstrated signifi-

cant prevalence in the analysis or are not significantly

identifiable in the data search and evaluations have not

been included in the development of the analog at this

stage of the study. A follow up evaluation assessment has

been conducted for comparing this profile with the data

from new reports to evaluate the predictability th e evalu-

ations and to develop the validity of the model.

3. RESULTS

The parameters are assessed in relation to the numbers

of attempts and actual suicide incidents reported be-

tween year 2002 and 2006. The age groups 15–24 and

35–44 yrs have the maximum incidents of attempted

suicides (Figure 2).

The leading conversion of the attempts into actual su i-

cide is demonstrated by the age group 45–54 yrs and

from 2002 year onwards, there is a steady increase in the

rate of suicide and suicide attempts in this age group

(Figure 4). Males in Washington accounted for 79% of

total suicides, though majority of females have at-

tempted suicides with a rate of 62%. There has been a

consistent annual rise in the number of su icidal attempts

as evident from annual health reports (Figure 5). Suicide

comparison ratio among the adult male and female pa-

tient population rate has been measured as 7:2, which is

evident from the finding that during 2003–2005 period.

Among adolescen t and young age group s, approximatel y

25% of attempted suicide by youth male results in death;

whereas three–four percent deaths result in females. 15

to 19 year old males are five times more likely than fe-

males to commit suicides. Caucasian and American In-

dians demonstrate largest proportion of actual number of

suicidal attempts and incidents as 14 every 100,000

resident population each.

Data reflects that in Caucasian and Native Indian

groups, suicide is occurring with 14 per 100,000 rates

each though African-American, Asian and Hispanic

groups demonstrated non-significant rate of eight, eight

and six consecutively. High competition, economic and

social hardship can be observable factors among Cauca-

sian though relationship cannot be established directly;

partially available particulars are only confirmed presently

for family predisposition, abuse, addiction and health

concerns among with Native Americans too [9]. Suicide

rate as observed in relation with academic background

can be described with the ratio of 28:14:9 with 28 with

patients having 12th grade or less education, 14 with

some college level programs and 9 with graduation or

post graduation. Linear regression of suicide rate has

been observed with progression of academics in the sta-

tistical evaluation. Poisoning is identified as the most

common means for attempted suicide cases among

15–24 and 35–54 age group whereas firearms are as the

most common means among the young and adu lt groups

for suicide deaths. Based on the results of statistical

analysis and evaluations, several parameters and their

characteristics have been identified and incorporated for

the development of th e mode l fo r the instrumen t with th e

order as gender, age group, ethnicity, health, education,

environmental condition, and; exposure and access to

perform self-fatality for the Washington region (Fi gure 6).

The construction of the analog utilizes major and re-

curring parameters first and tracks subsequent parame-

ters and their characteristics in the descending order of

evaluation. These Follow-up evaluations with parame-

ters evaluated from various new case studies (a total of

627 case data) rando mly, in dicated results in compliance

with an accuracy of more than 90% of the total cases,

when the parameters are run through the analog model.

4. DISCUSSION

Age groups 15–24 and 35–54 year have demonstrated

the majority of incidents of suicide and su icidal attempts.

Parallel emergence of economic hardship can be pro-

jected as one of the reasons for the growth of suicide rate

among the 45–54 year age group [10].

Higher suicide rate among is recorded among males,

approximately 25% of attempted suicide by youth male

results in death, whereas 3–4 % death results in females,

though higher attempt rate among females is observed

[11]. Health conditions (depression, substance abuse,

Figure 4. Yearly distribution of suicidal incidents in various

age-groups (Number of incidents versus years as x:y coordi-

nates).

Figure 5. Yearly distribution of total number of suicidal inci-

dents (Years versus number of incidents as x:y coordinates).

811 801 823 814 796

2901 3007 3209 3507 3445

500

1000

1500

2000

2500

3000

3500

4000

'02 '03 '04 '05 '06

Suicide Death

Frequency

Suicide Attem pt

Frequency

Linear (Suicide

Attempt Frequency )

716

717

818

840

810

680

641

727

767

742

841

770

817

804

826

490

553

579

626

677

157

162

193

244

0200 400 600 800 1000

'02

'04

'06

75 yrs +

'05 6

5-7

5-6

5-5

5-4

'03 5-3

5-2

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V. Vatsalya et al. / J. Biomedical Science and Engineering 2 (2009) 516-520 519

Figure 6. Analog construction of diagnostic model.

ideation and cond itions like family history, sexual orien-

tation and abuse, disability) show higher probability of

suicidal incidents (Figure 7). Individuals with physical

and sexual abuse have been observed to have four times

higher suicide attempt rate than non-abused. Among

African American communities, some of the major fac-

tors are community segregation, economic hardship and

access to weapon; though cultural encapsulation and

stress is prevalent among other minority groups. From

2002 year onwards, there is a steady increase yearly, in

the number and rate of suicide incidents in the 35–54 age

groups [12]; and the proportion of people living in pov-

erty increased, though data is not sufficient enough to

identify relation to economic hardship [13]. Post-Trau-

matic Stress Disorder, economic hardship, social con-

structs are being studied as an extension of the ongoing

study.

546

600 Male Suicide

539

483

500 459 Frequency

478

Male suide ic

Attempt

400 327

300 294

279

5. CONCLUSIONS

The complexity of suicidal behavior and ideation re-

quires multiple and immediate preventive approach and

application of a predictor model can supplement target-

ing population, requiring adequate health care services to

prevent suicide. Since much published material and

clinical experience demonstrate a number of causative

factors associated with suicide, the early identification

and appropriate treatment of this condition is an impor-

tant strategy for prevention. Improvements may be re-

quired for broadening data collection and investigatory

techniques for possible suicidal attempts, social con-

structs and economic causes; biological and environ-

mental factors and minority groups from both fatal and

Figure 7. Yearly distribution of depression-originated youth

suicidal incidents (Years versus number of incidents as x:y

coordinates).

non-fatal suicide incidents. Utilization of the instrument

at the key regions and community level; significantly

social and community based agencies, academic institu-

tions and care centers can be highly valuable and rec-

ommended. Design, planning and Implementation of

intervention strategies for newly growing suicidal inci-

dents in the 45–54 year age group should be focused

appropriately. A preliminary investigation in various

world regions with above-average suicide rate have

identified points of interests namely Kutznetsk Basin,

former USSR republics (between 1980 and 1995 citing

economic instability); among indigenous peoples in bo th

Australia and Canada in the last 20 years [1]. Depending

upon the various factors and parameters in different

world locations, with specific standardization, an appro-

priate constru ction of the predictor mod el and evalua tion

may be utilized for similar diagnostic procedures and

further research may provide essentials and scope for

development for area specific revisions.

78 82 78 85 99

238 247 Female Suicide

200 Frequency

Female Suicide

100

14 Attemp

0Linear (Male Suicide

Frequency)

2002 2003200420052006 Year

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520

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