FACTORS AFFECTING RESILIENCY AMONG DISASTER VICTIMS
A Research Presented to be
Submitted to the Graduate School of Arts and Science
Psychology Department
Holy Angel University
In Partial Fulfilment of the Requirements
in the subject
ADVANCED PSYCHOLOGICAL STATISTICS
2nd Trimester, A.Y 2019-2020
Submitted By:
RUTH C. BARROGA
MARY JOY R. FACUN
ROXANNE P. STA. INES
Submitted To:
DR. JOSEPH FRANCISCO
| Lecturer |
Table of Contents
Abstract
Chapter 1: THE PROBLEM AND ITS BACKGROUND
Introduction
Statement of the Problem
Hypotheses
Scope and Delimitation of the Study
Chapter 2: METHODOLOGY
Data Procedures
Data Instruments
Research Design
Respondents
Data Presentation and Statistical Analysis
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3
4
5
5
6
6
7
8
9
9
Chapter 3: RESULTS AND DISCUSSION
Discussion of Results
Participants according Demographic Profile
Measures of Resilience, Hope and Optimism
Relationship between Resiliency and Hope
Relationship between Resiliency and Optimism
Optimism and Hope Predicts Resilience
Conclusions
Recommendation s
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11
12
13
13
14
15
15
References
16
Appendices
18
Appendix I: Consent
Appendix II: Brief Survey Scale
Appendix III: Short Grit Scale
Appendix IV: The Trait Hope Scale
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21
22
25
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Chapter 1
THE PROBLEM AND ITS BACKGROUND
Introduction
Every year, millions of people are affected by both human-caused and natural disaster; it
can be in forms of explosions, earthquakes, floods, tornadoes, or fires. Disaster typically strikes
quickly and cause great harm. Thus, being a victim of such is not only a single phase in life.
Instead, it is an on-going process that lasts for months or years even after the adversity. It not
only leaves traces of property destruction and financial difficulties, but also abandon the victims
with damaged sense of balance.
The far-reaching impact of disasters can engender a range of psychological consequences
(Raphael & Maguire, 2009). The big questions, though, are how bad can these consequences be,
and for whom. Is it possible for people to survive a disaster without suffering lasting
psychological damage, and if so, how many people are likely to be able to do so? And what
could be the possible factors that enable them to surpass tragic experiences?
Human beings hold the ability to resist an adverse situation and this unique characteristic
is one of the basic instincts to survive. Physical capacity fails oftentimes, but drive and
conviction to survive in difficult situations persist and remain as a source of strength. In the
language of understanding, it is referred to an internal capacity to fight, and some refer to this as
“resilience”. Masten et al (1990) define resilience as “the process of, capacity for, or outcome of
successful adaptation despite challenging or threatening circumstances”. Resilience in response
to disaster therefore is the ability to bounce back and return to normalcy despite the plight and
3
destruction as an aftermath of disaster, it involves doing well against the odds, coping, and
recovering (Rutter, 1985; Stein, 2005).
Discussions of resilience concerning victims of disasters are typically framed with
reference to risk, vulnerability and protective factors. It is the complex interplay of these factors
over time that determines the victim’s outcome. Some of the resilience factors are the contrary of
a risk factor, such as having a sense of hope, as well as optimism. Some may be amenable to
change, and others not. Hence the importance of resilience factors for outcomes lies not only in
their impact on protecting the victim, but also on enabling growth and future development,
despite adverse circumstances. Hence the current emphasis is on understanding resilience as a
process rather than a particular character trait (Luthar et al, 2003).
In this research entitled “Factors Affecting Resiliency among Disaster Victims”, the
researcher aims to identify the factors and relationship affecting the resilience among the victims
of a disaster. The research will also seek to assess and understand how these factors may lead to
positive outcomes and what mechanisms are involved.
Statement of the Problem
This study aims to explore the factors affecting the resiliency among disaster victims.
Specifically, it sought to answer the following questions:
1. What is the respondents profile as to:
1.1 Age
1.2 Gender
1.3 Educational Attainment
1.4 Province
4
2. What type of disaster that the respondents
3. How may the respondents profile be described as to:
3.1 Level of resiliency
3.2 Level of hope
3.3 Level of optimism
4. What is the significant relationship between the following:
4.1 Resiliency and optimism
4.2 Resiliency and hope
Hypothesis
H1: There is a significant relationship between resilience and hope
H2: There is a significant relationship between resilience and optimism
H3: Optimism and hope predicts resiliency
Scope and Delimitation
The study focused on the factors affecting resiliency among the victims, particularly of
the respondents who have been a victim of natural and human-caused disaster in Region III.
However, the researchers identified only three provinces, particularly Bataan, Tarlac and
Pampanga which had recent major catastrophic experiences cause by natural and human-made
disasters, such as fire, typhoon, floods and earthquake. The study comprised 50 participants who
had an experience or a victim of either natural or human-caused disaster. The study specifically
dealt with the (a) respondents level of resiliency, hope, and optimism (b) the relationship
between resiliency, hope, and optimism, and (c) hope and optimism as predictor of resiliency.
5
Chapter 2
METHODOLOGY
This chapter presents the methods for investigation and selection of respondents used in
conducting the study. It also describes the research instrument that the researcher administered
for collecting data and the statistical devises with which to treat data.
Data Gathering Procedure
The needed data was obtained by means of survey. The Survey Method allows the
collection of a large amount of data from a large population. Survey method is employed to
identify the factors affecting the resiliency of the respondents, it allows for standardization of
data which allows easy comparisons. In addition, since this method is easily understood by the
respondents, it is perceived as authoritative. Furthermore, the survey method gives more control
over the research process. The principle instrument is a scale, on which each respondent is asked
to respond to the same set of scales in a predetermined order.
After selecting and finalizing the tools for data collection, a set of finalised copy of the
instruments was distributed to the respondents. The researcher started the data gathering
procedure by stating the purpose and importance and requesting permission and consent to
conduct the survey. The researcher briefly explained the purpose and importance of the study
and assured the confidentiality of the data collected. The survey instruments were distributed to
all the respondents after collecting informed consent from them (see Appendix I). Some of the
survey was conducted on site by the researcher, and most are distributed and collected online.
The environment and procedure for all the respondents were kept uniform to the maximum
possible.
6
There was no risk for the subjects involved in this study because no respondent identifiers
were recorded. All data was recorded in a SPSS file located on this researcher’s laptop which
was password protected and never out of the researcher’s possession.
Research Instrument
This research employed 3 instruments. The first instrument used was the resilience scale.
The resilience scale (RS) (see Appendix II), measures the capacity to withstand life stressors, and
to thrive and make meaning from challenges consists of a 6-item "Brief Resilience Scale (BRS)"
constructed by Smith, B. W., Dalen, J., Wiggins, K., Tooley, E., Christopher, P., & Bernard, J.
(2008). The possible score range on the BRS is from 1 (low resilience) to 5 (high resilience).
According to the authors of the BRS, scores can be interpreted as low resilience with score of
1.00-2.99, normal resilience with score of 3.00-4.30 and high resilience with score of 4.31-5.00.
The scores of the 6 Likert items (half reverse coded) are summed.
The second instrument used was The Short Grit Scale by Duckworth & Quinn, (2009)
(see Appendix III); it is a self-report inventory to measure perseverance and passion for longterm goals. Participants responded to eight statements evaluated on a 5-point Likert-type scale
ranging from very much like me (5) to not at all like me (1). A sample response item includes,
“Setbacks don’t discourage me.”
The third instrument was The Hope Scale (Snyder et al., 1991) (see Appendix IV) which
is a self-report inventory to measure participants’ attitudes toward goals and objectives. The
Hope Scale is divided into two subscales: agency and pathways. Participants responded to eight
statements evaluated on an 8-point Likert-type scale ranging from definitely true (8) to definitely
false (1). A sample response item includes, “I can think of many ways to get the things in life
that are important to me.”
7
All instruments were yielded for the purpose of generating responses that are as detailed
as possible and thereby made the research endeavour productive.
Research Design
The main purpose of this research is to investigate whether there is any correlation
between hope, optimism, and resiliency among disaster affected. Thus, the research undertaking
applied quantitative approach and descriptive-correlation design. Quantitative approach was
employed since this research will define the research questions based on the trends in the field of
research site, and the need to explain why something occurs. Based on the research question that
will mainly investigate the correlation between the variables, this research is also classified as
descriptive-correlation in nature.
The research is descriptive because it involves gathering data that described events and
them organizes, tabulates, illustrates, and describes the data collection. It utilized by the
researcher to obtain information concerning the current status of the phenomena and describes
the data with respect to variables or conditions in a situation. Likewise, it is correlation in the
sense that the researcher will investigate the degree of association between two or more
variables. As such, survey method was also employed. It is defined as the act of examining a
process or questioning a selected sample of individuals to obtain data from a targeted group of
people about their opinions, behaviour and knowledge. The researcher used face-to-face survey
to collect data for the study. It was applied to understand and validate the respondent’s
perspective on their experience, and the factors affecting their resiliency.
8
Respondents
The study was carried out in Region III particularly in the province of Bataan, Tarlac and
Pampanga. The researcher took 50 respondents particularly of ages not younger than 18 years
old prior to the study.
The identification of respondents for the study was identified through the so called
purposive sampling technique. It is a form of non-probability sampling that is popular in
qualitative research, wherein decisions concerning the individuals to be included were taken by
the researcher; this simply means that the subjects are selected because of some characteristics or
criteria. For this reason, the individuals who qualified as respondents are those who were: (a)
victims of natural or human-caused disaster not longer than two years from its occurrence, (b) at
least 18 years old, and (c) residents of Bataan, Tarlac and Pampanga.
Data Presentation And Statistical Analysis
Statistical Treatment
For the purpose of arriving at more meaningful results, numerical data was analysed and
interpreted of resorting to such statistical tools as regression analysis and correlation.
Regression analysis is a statistical technique in social and behavioural sciences as well as
in physical sciences which involves identifying and evaluating the relationship between a
dependent variable and one or more independent variables. It is particularly useful for assess and
adjusting for confounding. Model of the relationship is hypothesized and estimates of the
parameter values are used to develop an estimated regression equation. Various tests are then
employed to determine if the model is satisfactory. If the model is deemed satisfactory, the
9
estimated regression equation can be used to predict the value of the dependent variable given
values for the independent variables.
Correlation is a statistical measure that indicates the extent to which two or more
variables fluctuate together, it quantifies the degree and direction to which two variables are
related. To quantify the strength of the relationship, we can calculate the correlation coefficient
(r). Its numerical value ranges from –1.0. to +1.0 r > 0 indicates positive linear relationship, r < 0
indicates negative linear relationship while r = 0 indicates no linear relationship. In this study,
the researcher used the correlation technique to classify the relationship between the variables of
hope, optimism, and resilience among the victims of natural and human-caused disaster.
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Chapter 3
DISCUSSION AND RECOMMENDATION
This chapter presents the summary of results, conclusion, and recommendation of the
study to the problems presented based on the data gathered from the respondents.
Discussion of Result
Fifty victims of natural and/or human-caused disaster in Region III and Metro Manila
were chosen as respondents to the study through purposive sampling technique. Survey
Instruments were used to collect relevant data. The analysis of data yielded the following sets of
findings based in the information gathered from the respondents. The obtained quantitative data
were analysed by means of descriptive statistics, Pearson’s r, and linear regression using
computer software SPSS 21.
Participants according Demographic Profile
The study surveyed participants with a total population of 50 from the center of Bataan,
Tarlac and Pampanga.
As shown in Table 1, largest population which comprised 68% (N=34) are in the age
group of 30-49 years old. While 14% (N=7) of the population belong to the age group of 18-29
years old. In terms of gender distribution, 56% (N=28) of the population are female and 44%
(N=22) of the population are male. Comprising 60% (N=30) of the population are residents of
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Tarlac.
The table also shows that 50% (N=25) of the population had an experience of flood
which majority are residents of Tarlac.
Table : Distribution of participants according Demographic Profile
Frequency
7
34
9
50
Percent
14.0
68.0
18.0
100.0
Age Group
18-29 years old
30-49 years old
50 years old & above
Total
Gender
Male
Female
Total
22
28
50
44.0
56.0
100.0
Type of
Disaster
Typhoon/Flood
Fire
Earthquake
Total
25
15
10
50
50.0
30.0
20.0
100.0
Province
Tarlac
Pampanga
Bataan
Total
30
10
10
50
60.0
20.0
20.0
100.0
Measures of Resilience, Hope and Optimism
As shown in Table 1, the respondents showed moderate level of resiliency (M = 4.04, SD
= .58). In terms of hope, results revealed that the level of their hope is also moderate (M = 39.80,
SD = 11.48), and their level of optimism indicates moderate to high (M = 4.04, SD = .533). All
of the result shows moderate to high levels of resiliency, hope, and optimism among the
respondents.
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Table 2 Measures of Resilience, Hope and Optimism
N
Valid
Missing
Mean
Std. Deviation
Resilience
50
0
4.0450
Hope
50
0
39.80
Optimism
50
0
4.0420
.57630
11.480
.53339
Relationship between Resiliency and Hope
In Table 2, it is reported that resilience is significantly correlated with hope among
disaster victims. Since the computed value of r which is 0.258 is greater than the tabular value of
0.2428at .05 level of significance of 45 degrees of freedom, the null hypothesis is disconfirmed
in favour of the research hypothesis. It means that an increase in level of hope will result in an
increase of resiliency. Furthermore, resilience and optimism are found to have a positive
correlated relationship. This also expresses that when optimism is increasing, the resilience will
also increase. Resilience, was then positively associated with hope and optimism.
Table 3Relationship between Resiliency and Hope
Descriptive Statistics
Resilience
Hope
Mean
4.0450
47.04
Std. Deviation
.57630
8.468
N
50
50
Relationship between Resiliency and Optimism
Furthermore, resilience and optimism are found to have a positive correlated relationship.
Since the computed value of r which is 0.293 is greater than the tabular value of 0.2428at .05
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level of significance of 45 degrees of freedom, the null hypothesis is disconfirmed in favour of
the research hypothesis. This also expresses that when optimism is increasing, the resilience will
also increase. Resilience, was then positively associated with hope and optimism.
Table 3: Relationship between Resiliency and Optimism
Resiliencescore
Gritscore
Descriptive Statistics
Mean
Std. Deviation
4.0450
.57630
4.0420
.53339
N
50
50
Optimism and Hope Predicts Resilience
Linear regression was employed to determine if hope and optimism is a significant
predictor of resiliency. As shown in Table 4, the analysis indicates a significant result and
accepts the hypothesis that optimism and hope predicts resilience. These findings suggested that
higher level of hope and level of optimism is associated with the ability of an individual to
bounce back from adversity. Results revealed that both optimism and hope significantly predicts
the respondents’ resilience. (R2 = .380, F = 3.955, p < .000).
Table 4: Optimism and Hope Predicts Resilience
Coefficientsa
Unstandardized
Standardized
Coefficients
Coefficients
Model
B
Std. Error
Beta
1
(Constant)
3.235
.650
Hope
-.012
.007
-.241
Grit
.320
.146
.296
a. Dependent Variable: Resilience
t
4.976
-1.786
2.192
Sig.
.000
.081
.033
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CONCLUSION
The outcomes from this study showed that, optimism and hope has a significant positive
relationship with resilience. Therefore, hypothesis 1 regarding the significant relationship
between resilience and hope is accepted. In addition, hypothesis 2 regarding the significant
relationship between resilience and optimism is also accepted. Results showed that both
optimism and hope is positively correlated to resiliency.
The current study indicated that the relationship between optimism, hope and resilience
found to be positively significant. It means that people with high resilience scored high on
optimism and hope. Thus, hypothesis 3 stating that optimism and hope is a predictor of resilience
among disaster affected respondent is accepted and proved here. Resilience, hope, and optimism
are positive aspects of healthy life. Similar finding has also been observed in another study. So
the present study conclude that optimism and hope is a good predictor of the victim’s capacity to
recover quickly from difficulties, and allows them to come back at least as strong as before after
a devastating incident that knocks them down.
RECOMMENDATIONS
Researchers who wish to pursue the same study, or add to it, researcher suggests to
consider a larger number of participants for more representation of the population and to limit
the influence of the outliers. Likewise, the participants should also be selected properly in terms
of their experiences, necessary information, as well as their location.
Furthermore, future investigators should focus on studying the adversity of natural
disaster on the lives of natural disaster victims and to also consider other possible variables
affecting their level of resiliency.
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REFERENCES
Mustafa Nadeem Kirman (2015, July) Hope, Resilience and Subjective Well-being among
college going Adolescent Girls. Volume-II, Issue-I, Page No. 262-270.
Panchal, Sandeep (2016, June). Optimism in Relation to Well-being, Resilience, and Perceive
Stress.
Reyes, Marc Eric S. et al. (2019, September). Self-Esteem and Optimism as Predictors of
Resilience among Selected Filipino Active Duty Military Personnel in Military Camps.
Journal of Positive Psychology & Wellbeing. Vol. x, No. x, 1 –11.
F. Walsh and M. Mcgoldrick (2004). Facilitating family and community resilience in response to
major disaster.
Markovitz, S. E., Schrooten, W., Arntz, A., & Peters, M. L. (2015). Resilience as a predictor for
emotional response to the diagnosis and surgery in breast cancer patients. Psycho‐
oncology, 24(12), 1639-1645.
Coutu, D. L. (2002). How resilience works. Harvard business review, 80(5), 46-56.
Liberta, Taylor et al. (2016, October). The Impact of Hope and Resilience on Multiple Factors in
Neurosurgical Patients.
Michael Philip Hand. (2004). Psychological resilience: The influence of positive and negative
life events upon optimism, hope, and perceived locus of control.
Antonovsky, A. Health, stress and coping. San Francisco: Jossey-Bass.
Chemtob, C. M. (2002, November) A public health approach to trauma recovery.
Bonanno et al. Weighing the Costs of Disaster: Consequences, Risks, and Resilience in
Individuals, Families, and Communities
Figley, C. R., & McCubbin, H. I. (Eds.) (1983). Stress and the family, Volume II: Coping with
catastrophe. New York: Brunner/Mazel.
Ford, B., & Searing, V. (2000, April). Community approaches: Mayan survivors in Guatemala.
De Sousa and Shrivastava. Resilience among people who face natural disaster
Danieli, Y. (1981). Differing adaptational styles in families of survivors of the Nazi Holocaust:
Some implications for treatment. Children Today, 10(5).
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Duckworth, A.L, & Quinn, P.D. (2009). Development and validation of the Short Grit Scale
(GritS). Journal of Personality Assessment, 91, 166-174.
http://www.sas.upenn.edu/~duckwort/images/Duckworth%20and%20Quinn.pdf
Duckworth, A.L.,
Heidie Losoi. Psychometric Properties of the Finnish Version of the Resilience Scale and its
Short Version
One of the best and highly recommended (Windle et al., 2011) resilience scales is the Brief
Resilience Scale by Smith and colleagues, 2008.
Padhy, Meera et al. (2015, April). Optimism and Psychological Well-Being of Police Officers
with Different Work Experiences
Peterson, C., Matthews, M.D., & Kelly, D.R. (2007). Grit: Perseverance and passion for longterm goals. Journal of Personality and Social Psychology, 9, 1087-1101.
Snyder, C. R., Harris, C., Anderson, J. R., Holleran, S. A., Irving, L. M., Sigmon, S. T., et
al.(1991). The will and the ways: Development and validation of an individualdifferences measure of hope. Journal of Personality and Social Psychology, 60, 570-585.
Snyder, C. R. (1994). The psychology of hope: You can get there from here. New York: Free
Press.
Snyder, C. R. (2002). Hope theory: Rainbows in the mind. Psychological Inquiry, 13, 249-275.
Wagnild, G. M. (2010). Special report on the 25-Item Resilience Scale. Worden, MT: The
Resilience Center.
Wagnild,G.M.,&Young,H.M.(1993).Development and psychometric evaluation of the Resilience
Scale.
https://www.psytoolkit.org/survey-library/resilience-brs.html
http://www.sas.upenn.edu/~duckwort/images/Grit%20JPSP.pdf
https://www.rand.org/education-and-labor/projects/assessments/tool/2007/grit-scale.html
https://ppc.sas.upenn.edu/resources/questionnaires-researchers/adult-hope-scale
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APPENDICES
18
Appendex I: INFORMED CONSENT FORM
Title of the Research Study: FACTORS AFFECTING RESILIENCY AMONG DISASTER
VICTIMS
Researchers: Ruth C. Barrogga, Mary R. Joy Facun, Roxanne P. Sts. Ines
Graduate School
Holy Angel University
Angeles, Pampanga
Purpose of the Study
We are currently conducting a research as part of our subject Advanced Psychological Statistics
requirements. In line with this, you are invited to participate in a research study exploring the factors
affecting resiliency among disaster victims in Region III. The survey will take approximately 10 minutes
of your time to complete and contains basic questions about level of hope, optimism/grit that may
influence resiliency. If you have any questions about the study, feel free to ask the researcher; questions
about the rights of research participants and other research related concerns.
Participation and Withdrawal
Your decision to participate is completely voluntary and you have the right to withdraw your participation
from this study at any time before the survey is submitted. Declining to participate in this study will not
affect your relation to the researchers.
Confidentiality
Your participation in this research will be completely anonymous and data will be kept confidential as
possible. All gathered data will be given codes and stored separately from any names or other direct
identification of participants. These files will not be identifiable in anyway. Only the researcher and her
subject lecturer will have access to individual survey data.
Benefits of Participation
There will be no direct benefit to you from participating in this research study. However, the study may
contribute in providing an overview about the importance of resiliency in experiencing disasters and how
hope and optimism could be significant predictors of resiliency.
Consent
If you agree to participate in this research study after fully reading and understanding the statements
above, please sign below to indicate your acceptance to participate. If you wish to have a copy of this
informed consent form for your future reference, you may cut the above segment of this form or ask for a
copy.
____________________________________
Signature of Participant
____________________________________
Signature of Researcher
_____________________________
Date
_____________________________
Date
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SURVEY QUESTIONNAIRE
Name (Optional):
Q1: What is your gender?
 Male
 Female
Q2: What is your age group?




18-29
30-39
40-49
50 and over
Q3: What is your highest academic qualification?






Bachelor Degree (Please specify) ____________________________________________
High School Graduate
Elementary Graduate
Completed Vocational course (Please specify) __________________________________
Alternative Learning System
None of the above
Q4: In which province do you live?
 Bataan
 Pampanga
 Tarlac
Note: Resilience (Katatagan) refers to the he capacity to recover quickly from difficulties; the
quality that allows some people to be knocked down by life and come back at least as strong as
before.
Optimism/Grit (Pagiging positibo sa buhay), an attitude that can positively affect a person’s
mental and physical health
Hope (Pag-asa), a feeling of expectation, desire, and grounds for believing that something good
may happen.
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Appendix II: Brief Resilience Scale
21
Appendix III: Short Grit Scale
Directions for taking the Grit Scale: Please respond to the following 8 items. Be honest –
there are no right or wrong answers!
1. New ideas and projects sometimes distract me from previous ones.*
2. Setbacks don’t discourage me.
3. I have been obsessed with a certain idea or project for a short time but later lost
interest.*
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4. I am a hard worker.
e
5. I often set a goal but later choose to pursue a different one.*
6. I have difficulty maintaining my focus on projects that take more than a few months
to
complete.*
7. I finish whatever I begin.
23
t much like me
8. I am diligent.
Scoring:
1. For questions 2, 4, 7 and 8 assign the following points: 5 = Very much like me 4 =
Mostly like me 3 = Somewhat like me 2 = Not much like me 1 = Not like me at all
2. For questions 1, 3, 5 and 6 assign the following points: 1 = Very much like me 2 =
Mostly like me 3 = Somewhat like me 4 = Not much like me 5 = Not like me at all
Add up all the points and divide by 8. The maximum score on this scale is 5 (extremely
gritty), and the lowest score on this scale is 1 (not at all gritty).
Grit Scale citation
Duckworth, A.L, & Quinn, P.D. (2009). Development and validation of the Short Grit
Scale
(GritS).
Journal
of
Personality
Assessment,
91,
166-174.
http://www.sas.upenn.edu/~duckwort/images/Duckworth%20and%20Quinn.pdf
Duckworth, A.L., Peterson, C., Matthews, M.D., & Kelly, D.R. (2007). Grit:
Perseverance and passion for long-term goals. Journal of Personality and Social Psychology, 9,
1087-1101. http://www.sas.upenn.edu/~duckwort/images/Grit%20JPSP.pdf
24
Appendix IV: The Trait Hope Scale
25