This document discusses secondary data analysis in crime science research. It notes that secondary data analysis involves reanalyzing previously collected data for a new purpose. Reliability and validity are critical issues to consider when using secondary data. Reliability refers to whether measurements can be consistently reproduced, while validity examines whether the data accurately measures what it intends to. Secondary data sources like agency records can lack reliability and validity due to discretionary actions influencing data production. Overall, secondary data should be considered a supplemental source and its reliability and validity carefully evaluated for each research purpose.

1. Running head: CRIME SCIENCE RESEARCH 1
Crime Science Research
Secondary data analysis is a form of research that has the data collected and processed in
the previous research are reanalyzed, mostly for a different use by another researcher. In most
cases, it is utilized in the survey data. It is imperative to note that negotiating access to data can
be difficult and can entail accessing this data in a format that is usable (Cockbain & Knutsson,
2014). In collecting the secondary data, it is critical to be aware of matters that relate to
reliability and validity. Just because the data is readily available does not mean that it can be
reliable. Therefore, when one considers using this data, one must be concerned with issues of
reliability and validity. Reliability entails whether a particular measurement technique when it is
applied repeatedly to the same thing would lead to the same results. For instance, when a police
officer is standing the street, guessing car speed as the cars pass by and providing speeding
tickets based on such judgment, is likely to produce unreliable measurement outcomes that one
can easily contest in the court and win (Maxfield & Babbie, 2017). Also, reliability is in most
cases a problem with different indicators used in research related to criminology. For instance,
forensic DNA evidence is currently gaining more popularity in violent crime cases. However,
National Research Council studies have found many errors in procedures used in laboratories
such as evidence contamination, sample mishandling, and analyst bias. Such as are measurement
reliability bias that can result in the unwarranted exclusion of evidence or even lead to the
conviction of an innocent individual.
Reliability problems also arise when a single observer happens to be a source of
information, and there is no way of guarding against the observer’s subjectivity. Therefore, it is
possible to verify if what is reported is true and it is very difficult to find the actual bias in

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reporting. Therefore, the reliability of a measurement in criminal justice research is a
fundamental issue.
The key problem of secondary data results from the recurrent issue of validity. When a
researcher collects data for a certain purpose, one is not sure whether the research outcomes will
be important to the study of interest. In most cases, it is that the original researcher collected data
that is close to the research of interest. In fact, one wishes that the researcher become more
specific with the variables the secondary data researcher is interested in.
Generally, secondary data is not very useful when conducting evaluation studies. This is
because evaluations require answering certain questions regarding certain issues. Secondary data
cannot be entirely relied upon when evaluating a different program due to the reliability of the
outcomes in forming a backbone for evaluation (Mills, Durepos & Wiebe, 2010). In addition,
research that relies on secondary data analysis of the existing records is known to depend on less
on personal interactions with the police representatives, which can make it lose the value of
professional input in the overall outcomes. In addition, sources of secondary data such as agency
records have reliability and validity issues because they entail social production of data. This is
because there are discretionary actions by criminal justice officials among others that affect the
production of these data. Also, agency data is not designed for research since it is for their own
use. Other critical concern is that agency data tracks people and not patterns that in most cases is
the concern of crime science research (Maxfield, 2015).
Therefore, it is apparent that reliability and validity are very critical aspects of concern in
research and cannot be assumed as they relate to use of secondary data in crime science research.
However, it is imperative to note that some of the secondary sources are as reliable as the

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primary sources. However, some sources of secondary data should be used when no other
sources of data are available. Therefore, valid data means that the used data is a representative of
the of the original and it reflects the true findings. To produce results that are highly reliable and
valid, existing data should be considered as supplemental sources of data (Maxfield & Babbie,
2017).
Question 2
Research: Are older customers more vulnerable to cybercrime than other customers?
Hypothesis
This study hypothesizes that the greater the number of years the customers have, the
higher the risk of becoming cybercrime victims. Notably, technological changes are associated
with benefits, but criminals can take advantage of people who are not competent technologically.
Also, the fast pace at which the change is taking place is difficult for many people to maintain
the same pace (Zaeem, Manoharan, & Barber, 2016). Therefore, it is advisable for banks to
ensure that they put “age-friendliness” at the core of the financial, technical and service
propositions (Lock, 2016). There is evidence that indicates that thousands of people aged above
50 years’ experience financial exploitation every day (Bhasin, 2016). In addition to losing money
to fraudsters and falling victims to scams, the loss of trust and dignity can significantly affect
their health (Gilhooly et al., 2016). Another critical consideration is that older people are richer
compared to young adults because of lifetime savings hence increasing the chances of the
fraudsters targeting them. Another reason they are targeted in financial crimes is that they suffer
from cognitive decline hence fraudsters utilize this weakness (More & Nalawade, 2015). Lastly,
the most critical aspect is that the older people are less conversant with the ever-improving

4. CRIME SCIENCE RESEARCH 4
technology. Therefore, older people are likely to find it hard to remember passwords, security
codes or experience challenges with call centers. As such, in most cases, older people become
dependent on carers for assistance in banking hence making increase age a factor that makes one
more vulnerable to cybercrime (Li, Yu, Wong, & Ngan, 2016; Siddiqi, Zdenek, & Gorman,
2015).
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Research Design
This study will adopt a case study research design. A case study in research entails
empirical inquiry to investigate a contemporary phenomenon in a real-life context. As such, it is
pointed that case study is not a method. Instead, it is a strategy that focuses on understanding the
dynamics of a single case (Hagan, 2003). Notably, case studies take a variety of data collection
approaches that include interviews and document analysis; it also includes a technique of data
triangulation for establishing the validity of data. A case study can be undertaken to learn and
understand more about a particular case. This research will embark on a descriptive cases study.
In a descriptive case study, the researcher traces events over time, describes special
characteristics of these events and discovers the key occurrences (David, 2006).
In this study, the researcher will focus on the bank’s available data in which it will be
analyzed using content analysis method. Notably, the content analysis comprises both qualitative
methods and quantitative methods. The researcher will arrange the data in the order of age of the
reporters. The overall aim of content analysis is to demonstrate and understand the vulnerability
of the old people to cybercrime and circumstances under which they fail to comply with the
security protocols required by the bank. Since the main focus is to understand the scale and the

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nature of cybercrime that affects the old people, this research will focus on people data of people
of 50 and above years. It is imperative to note that in this bank’s case, the bank allows access to a
dataset of incidents and a contact list of 500 customers.
First, the researcher will ensure that the participants give informed consent to allow in-
depth case study research. Therefore, among the 500 customers, the research will include data of
participants who will be able to respond to open-ended interviews conducted through the phone
calls. Informed consent forms will be disseminated through email and researcher will try to reach
the old people physically through the address for consent. Interviews will allow the researcher to
seek clarification on the data that the researcher feels needs clarification on the reported incidents
(Mills, Durepos & Wiebe, 2010). Contacting the customer directly is admissible because this
research is an initiative of the bank and the researcher will be a representative of the bank.
In the qualitative methods, the incidences of the participants who meet the inclusion
criteria will be interviewed to identify key themes that emerge. Later, the researcher will ask
relevant questions to the participants depending on the reported incidences through a phone call.
The interview experiences will be recorded and verbatim transcripts made. The transcripts will
be explored to come up with concepts and later categories that describe certain types of
cybercrime and the nature in which the crimes are executed by the cybercriminals. The
qualitative methods will also entail looking into the information provided by the participant in
the reported incidents (s). The data analysis will also entail looking into similarities and
differences in which the cybercrime perpetrators execute money laundering.
In the quantitative form of this research, the researcher will code and count the
occurrence of elements such as the type of cybercrime, i.e. hacking, phishing, social engineering

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fraud among others. The researcher will divide the age of the participants into categories of 10
years. The number of participants will be divided into groups who are between 50-55 years, 56-
60 years, 61-65 years, 66-70 years, 71-75 years, 76-80 years, 81-85 years, 86-90 years and above
90 years. Descriptive statistics will be presented in graphs and tables. The researcher will look
for patterns in the age categories selected as the evidence converges.
Limitations of the study
The first limitation of this study is the validity and reliability of the data reported and
existing in the bank’s database. It is imperative to note that the 5200 reported incidents over the
last ten years are a lot of cases and the bank provides access to only 500 cases. A lot of
technological changes have taken place, and the research might utilize incidents in which the
cybercrime technology that was utilized is now obsolete. The researcher will minimize the
impacts of this limitation by finding whether the technology that is likely to have been used at
the time is obsolete.
Another limitation relates to the time that is available to conduct the study. The bank
reported that there were 5200 incidents in the last ten years. The cases provided are 500. In
addition, the researcher will only address incidents of participants who are alive. This shows time
limitation might lead to missing of important insights since all these cases will not be analyzed
(Wincup, 2017). This limitation will be addressed by looking into the most relevant cases as
informed by recent literature on cybercrime affecting financial industry. This might require an
expert in cybercrime to identify the most relevant incidents for inclusion.
Another issue that is should be recognized as a limitation to this study is the age of the
study participants. It is noted that past the age of 50, people start to suffer from cognitive decline.

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Cognitive decline can affect the quality of evidence provided and might make the participants
fail to provide relevant information. Also, the researcher might encounter challenges convincing
the participants that this is not another plan to steal from them (Bachman & Schutt, 2013). This
study has not embraced a standard test to determine the cognitive ability of the participants, and
the decision for inclusion will be based on the ability of the participants to respond to interview
questions.
Ethical Issues
The first ethical issue entails maintaining confidentiality and privacy as the researcher
goes through the reported incidents (Kimmel, 2007). Some of the old people would like their
financial history to remain confidential and unknown to even relatives. Therefore, during
research, optimal professionalism will be maintained to ensure that after the informed consent,
participants data is handled confidentially. As suggested by Babbie (2015), the researcher will
ensure that the participant is not pestered with questions beyond where they are willing to be
involved. Also, the participants will be identified using pseudonyms and factors such as
geographic location or participant descriptions that can lead to identification will be avoided.
One of the ethical issues relates to a cognitive decline in which some of the participants
might not be in a position to make cognitive decisions of participating in the study and giving
information (Kimmel, 2007). Although they have the autonomy to participate in the study, this
research recognizes that it is dealing with old people who might not be in a position to remember
something that happened five years ago. Therefore, the research will be conducted in the
presence of the carer or relative. At the same time, the research will ensure that this does not
interfere with the privacy of information that the elderly shares with the researcher.

8. CRIME SCIENCE RESEARCH 8
Lastly, the researcher will be dealing with criminal information that can compromise the
security of the participants. In addition, the researcher recognizes the sensitivity of the data that
the bank provides to its future. Therefore, in addition to privacy that relates to the participant,
privacy is required because the information on the dataset provided can be used by competitors
to gain a competitive advantage over the bank (Dantzker, Hunter, & Quinn, 2016). The report
after the research will also be provided to the bank and will not be published without the consent
of the bank.
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Question 3
Mixed Methods
Mixed method are a type of research that the investigator gathers and analyzes data while
integrating the findings and drawing inferences with the utilization of both qualitative and
quantitative methods in a single study (Tashakkori & Creswell, 2007). Therefore, in mixed
method research, the researcher applies both qualitative and quantitative data collection and
analysis in which both methods are used to compare and interpret the data.
One example of mixed methods is the convergent parallel design. This method is
preferred when the aim is to compare different perspectives drawn from qualitative and
quantitative data. Therefore, the focus is to merge two databases to illustrate and show how the
data converges or diverges. Qualitative data for this design can be obtained from interviews,
observations, records, documents, etc. the quantitative data can be in the form of observational
checklists, instrument data, and numeric records. Notably, both qualitative and quantitative data

9. CRIME SCIENCE RESEARCH 9
should be collected using the same parallel constructs, concepts, and variables. Its challenges
relate to the need of expertise in mixed methods that also relate to the need to have to samples
for data collection (Maxfield, 2015).
In an explanatory sequential design, it starts with quantitative data collection and
analysis. This is followed by qualitative research in which there are qualitative data collection
and analysis that then ends with an interpretation of the findings. It is imperative to note that the
qualitative strand is used to explain the quantitative findings and that the study is conducted in
two phases. The findings of the quantitative phase are used to guide the concepts, categories, and
variables considered in the qualitative phase. However, errors that affect the quantitative phase
significantly affects the overall validity of the findings. Therefore, it requires reliable instruments
in data collection in the quantitative phase (Tashakkori & Creswell, 2007).
The third design is the exploratory sequential design that commences with qualitative
methods. These provide background information about the factors or variables of interest that the
researcher uses to progress to the quantitative phase of the study. Therefore, the findings of the
qualitative phase guide the formulation of the quantitative phase. The biggest advantage arises
from its ability to provide sufficient information for development/identification of instrument
that is more reliable for use in the second phase. However, exploratory sequential design can be
time-consuming (Tashakkori & Creswell, 2007).
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10. CRIME SCIENCE RESEARCH 10
References
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Bachman, R., & Schutt, R. K. (2013). The practice of research in criminology and criminal
justice. Sage.
Bhasin, M. L. (2016). Integration of Technology to Combat Bank Frauds: Experience of a
Developing Country. Wulfenia Journal, 23(2), 201-233.
Cockbain, E., & Knutsson, J. (2014). Applied police research (3rd ed.). London: Routledge.
Dantzker, M. L., Hunter, R. D., & Quinn, S. T. (2016). Research methods for criminology and
criminal justice. Jones & Bartlett Learning.
David, M. (2006). Case study research. London: SAGE.
Gilhooly, M. M., Dalley, G., Gilhooly, K. J., Sullivan, M. P., Harries, P., Levi, M., ... & Davies,
M. S. (2016). Financial elder abuse through the lens of the bystander intervention model.
Public Policy & Aging Report, 26(1), 5-11.
Hagan, F. (2003). Research methods in criminal justice and criminology. Boston, MA: Allyn and
Bacon.
Kimmel, A. (2007). Ethical issues in behavioral research. Malden, Mass. [u.a.]: Blackwell.
Li, J. C., Yu, M., Wong, G. T., & Ngan, R. M. (2016). Understanding and preventing financial
fraud against older citizens in Chinese society: Results of a focus group study.

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International journal of offender therapy and comparative criminology, 60(13), 1509-
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