MID TERM (SPRING 2020)

Subject:
Advanced Research Methods
(Qualitative)

Submitted by:
Ayesha Ali

Roll No. 13771

MS Clinical Psychology Semester II

Question no.1
Describe Ethical issues in Research in detail?
Answer: Introduction:
Definition of research ethics:
“Research ethics are the set of ethics that govern how scientific and other research is
performed at research institutions such as universities, and how it is disseminated”.

Ethics are broadly the set of rules, written and unwritten, that governs our expectations of
our own and others’ behaviour. Effectively, they set out how we expect others to behave, and
why. While there is broad agreement on some ethical values (for example, that murder is bad),
there is also wide variation on how exactly these values should be interpreted in practice.

Research ethics are important for a number of reasons.

 They promote the aims of research, such as expanding knowledge.

 They support the values required for collaborative work, such as mutual respect and
fairness. This is essential because scientific research depends on collaboration between
researchers and groups.
 They mean that researchers can be held accountable for their actions. Many researchers
are supported by public money, and regulations on conflicts of interest, misconduct, and
research involving humans or animals are necessary to ensure that money is spent
appropriately.
 They ensure that the public can trust research. For people to support and fund research,
they have to be confident in it.
Codes of Ethics

Governments agencies who fund or commission research often publish codes of conduct
for researchers, or codes of ethics.

Major ethical issues in conducting research

1. Informed consent

Informed consent is the major ethical issue in conducting research. According to

Armiger: "it means that a person knowingly, voluntarily and intelligently, and in a clear and
manifest way, gives his consent".

Informed consent is one of the means by which a patient's right to autonomy is protected.
Beauchamp and Childress define autonomy as the ability for self determination in action
according to a personal plan. Informed consent seeks to incorporate the rights of autonomous
individuals through self- determination. It also seeks to prevent assaults on the integrity of the
patient and protect personal liberty and veracity. Of course individuals can make informed
decisions in order to participate in research voluntarily only if they have information on the
possible risks and benefits of the research. Free and informed consent needs to incorporate an
introduction to the study and its purpose as well as an explanation about the selection of the
research subjects and the procedures that will be followed. It is essential to describe any physical
harm or discomfort, any invasion of privacy and any threat to dignity as well as how the subjects
will be compensated in that case. In addition the subjects need to know any expected benefits
either to the subject or to science by gaining new knowledge.
 Another major ethical issue is obtaining an informed consent from groups with
diminished autonomy which will be further discussed later. From what has been discussed, it
becomes clear that disclosure, comprehension, competency and voluntariness are the four
essential parts of a consent.

2. Beneficence- Do not harm

The ethical principle of beneficence refers to the Hippocratic "be of benefit, do not
harm". Beauchamp and Childress, suggest that

"The principle of beneficence includes the professional mandate to do effective and significant
research so as to better serve and promote the welfare of our constituents".

Beneficence is sometimes difficult to predict when creating a hypothesis especially in

qualitative research. Carr says that if the research findings prove that it was not beneficial as it s
expected, this can raise immense ethical considerations especially for nurses. Ford and Reutter
say that "beneficence relates to the benefits of the research, while non-malificence relates to the
potential risks of participation". Non-malificence requires a high level of sensitivity from the
researcher about what constitutes "harm". According to Burns and Grove "discomfort and harm
can be physiological, emotional, social and economic in nature".

When a researcher tries to learn intimate details of the participants lives he has to deal
with opening old wounds. Non-munificence dictates both preventing intentional harm and
minimizing potential harm. A researcher must consider all possible consequences of the research
and balance the risks with proportionate benefit. The type, degree, and number of potential risks
must be assessed as well as the patient’s value system which ranks various harms. The risk
benefit ratio can only be achieved by identifying these factors. If the risks outweigh the benefits,
the study should be revised. 

3. Respect for anonymity and confidentiality

The issue of confidentiality and anonymity is closely connected with the rights of
beneficence, respect for the dignity and fidelity.ANA suggests anonymity is protected when the
subject's identity cannot be linked with personal responses. If the researcher is not able to
promise anonymity he has to address confidentiality, which is the management of private
information by the researcher in order to protect the subject's identity. Levine advocates that
confidentiality means that individuals are free to give and withhold as much information as they
wish to the person they choose. The researcher is responsible to "maintain confidentiality that
goes beyond ordinary loyalty". Clarke addresses the ethical dilemma of the researcher when
confidentiality must be broken because of the moral duty to protect society.

According to the utilitarian theory, which focuses on the best interest of all involved, the
happiness of society is of greater importance. On the other hand, the deontological theory which
ignores the result implies that the moral duty is what really matters. If a researcher, though, acts
deontological he may feel that he has not protected society. Another issue is that the researcher
may have to report confidential information to courts which can also cause moral dilemmas. In
those cases, it can be argued that the moral duty and personal ethos can be stronger than legal
requirements. Even if there are no duty conflicts, the researcher faces several problems with
respect to maintaining confidentiality especially in qualitative research where conduct is
personal, the sample is smaller and the reports display quotations of interviews. Ford and Reutter
suggest using pseudonyms and distorting identifying details of interviews when transcribing the
tapes used.
Vulnerable groups of people

Nowadays, there is an increased concern about vulnerable groups and whether it is ethical
or not for them to be used as research subjects." Fisher classifies vulnerability as one
characteristic of people unable to protect their own rights and welfare”. So, vulnerable groups
include captive populations (prisoners, institutionalized, students etc), mentally ill persons, aged
people, children, critically ill or dying, poor, with learning disabilities, sedated or unconscious.

The different opinions about their participation in research can be attributed to their
inability to give an informed consent and also to their need for further protection and sensitivity
from the researcher as they are in a greater risk of being deceived, threatened or forced to
participate. Many are in favor of the use of such subjects in research whilst others would argue
strongly against it. Most condition their responses according to the seriousness of the research,
the level of potential risk and the availability of alternatives. According to Burns and Grove
vulnerability increases the need for justification for the use of such subjects. An intense analysis
of potential risks and benefits should be the first step of starting such a research and careful
approach should exist both in acquiring consent and during the research procedure itself. Persons
with diminished autonomy are also more vulnerable to invasion of privacy, since their right to
privacy is limited in contrast to other's right to know. 

Even when clear ethical standards and principles exist, there will be times when the need
to do accurate research runs up against the rights of potential participants. No set of standards
can possibly anticipate every ethical circumstance. Furthermore, there needs to be a procedure
that assures that researchers will consider all relevant ethical issues in formulating research
plans. To address such needs most institutions and organizations have formulated an Institutional
Review Board (IRB), a panel of persons who reviews grant proposals with respect to ethical
implications and decides whether additional actions need to be taken to assure the safety and
rights of participants. By reviewing proposals for research, IRBs also help to protect both the
organization and the researcher against potential legal implications of neglecting to address
important ethical issues of participants.

Question no.2
What are data collection techniques in qualitative research method? Elaborate indepth
interview , Focus group discussion, Narrative records , Observation methods and Archival
data.
Answere:-

Qualitative research method:

 Qualitative research is a type of social science research that collects and works with non-
numerical data and that seeks to interpret meaning from these data that help understand social
life through the study of targeted populations or places.

“Qualitative research is defined as a market research method that focuses on obtaining data
through open-ended and conversational communication”.

This method is not only about “what” people think but also “why” they think so. For
example, consider a convenience store looking to improve its patronage. A systematic
observation concludes that the number of men visiting this store are more. One good method to
determine why women were not visiting the store is to conduct an in-depth interview of potential
customers in the category.

Definition of data collection:

Data collection is the process of gathering and measuring information on targeted variables
in an established system, which then enables one to answer relevant questions and evaluate
outcomes. There are two approaches to collecting and analyzing data:
● Quantitative research :
Quantitative research deals with numbers and statistics,

● Qualitative research. :
While qualitative research deals with words and meanings
Qualitative data:
Qualitative data is non-statistical and is typically unstructured or semi-structured in nature.
This data isn’t necessarily measured using hard numbers used to develop graphs and charts.
Instead, it is categorized based on properties, attributes, labels, and other identifiers.
Qualitative data can be generated through:
● Texts and documents
● Audio and video recordings
● Images and symbols
● Interview transcripts and focus groups
● Observations and notes

Techniques of data collection for qualitative research methods:

1. Focus groups
 Focus groups share many common features with less structured interviews, but there is
more to them than merely collecting similar data from many participants at once. A focus group
is a group discussion on a particular topic organised for research purposes. This discussion is
guided, monitored and recorded by a researcher (sometimes called a moderator or facilitator)

Focus groups were first used as a research method in market research, originating in the
1940s in the work of the Bureau of Applied Social Research at Columbia University. Eventually
the success of focus groups as a marketing tool in the private sector resulted in its use in public
sector marketing, such as the assessment of the impact of health education campaigns. However,
focus group techniques, as used in public and private sectors, have diverged over time.
Therefore, in this paper, we seek to describe focus groups as they are used in academic research.

When focus groups are used

Focus groups are used for generating information on collective views, and the meanings
that lie behind those views. They are also useful in generating a rich understanding of
participants' experiences and beliefs. Suggested criteria for using focus groups include.

 As a standalone method, for research relating to group norms, meanings and processes
 In a multi-method design, to explore a topic or collect group language or narratives to be
used in later stages
 To clarify, extend, qualify or challenge data collected through other methods
 To feedback results to research participants.
 Morgan suggests that focus groups should be avoided according to the following criteria:
 If listening to participants' views generates expectations for the outcome of the research
that can not be fulfilled
 If participants are uneasy with each other, and will therefore not discuss their feelings and
opinions openly
 If the topic of interest to the researcher is not a topic the participants can or wish to
discuss
 If statistical data is required. Focus groups give depth and insight, but cannot produce
useful numerical results.

Conducting focus groups: group composition and size

The composition of a focus group needs great care to get the best quality of discussion.
There is no 'best' solution to group composition, and group mix will always impact on the data,
according to things such as the mix of ages, sexes and social professional statuses of the
participants. What is important is that the researcher gives due consideration to the impact of
group mix (eg, how the group may interact with each other) before the focus group proceeds.

Interaction is key to a successful focus group. Sometimes this means a pre-existing group
interacts best for research purposes, and sometimes stranger groups. Pre-existing groups may be
easier to recruit, have shared experiences and enjoy a comfort and familiarity which facilitates
discussion or the ability to challenge each other comfortably. In health settings, pre-existing
groups can overcome issues relating to disclosure of potentially stigmatising status which people
may find uncomfortable in stranger groups (conversely there may be situations where disclosure
is more comfortable in stranger groups). In other research projects it may be decided that
stranger groups will be able to speak more freely without fear of repercussion, and challenges to
other participants may be more challenging and probing, leading to richer data.

Group size is an important consideration in focus group research. Stewart and

Shamdasani suggest that it is better to slightly over-recruit for a focus group and potentially
manage a slightly larger group, than under-recruit and risk having to cancel the session or having
an unsatisfactory discussion. They advise that each group will probably have two non-attenders.
The optimum size for a focus group is six to eight participants (excluding researchers), but focus
groups can work successfully with as few as three and as many as 14 participants. Small groups
risk limited discussion occurring, while large groups can be chaotic, hard to manage for the
moderator and frustrating for participants who feel they get insufficient opportunities to speak.

Preparing an interview schedule

Like research interviews, the interview schedule for focus groups is often no more
structured than a loose schedule of topics to be discussed. However, in preparing an interview
schedule for focus groups, Stewart and Shamdasani suggest two general principles:

1. Questions should move from general to more specific questions

2. Question order should be relative to importance of issues in the research agenda.
 There can, however, be some conflict between these two principles, and trade offs are often
needed, although often discussions will take on a life of their own, which will influence or
determine the order in which issues are covered. Usually, less than a dozen predetermined
questions are needed and, as with research interviews, the researcher will also probe and expand
on issues according to the discussion.

Moderating

Moderating a focus group looks easy when done well, but requires a complex set of
skills, which are related to the following principles.

 Participants have valuable views and the ability to respond actively, positively and
respectfully. Such an approach is not simply a courtesy, but will encourage fruitful
discussions
 Moderating without participating: a moderator must guide a discussion rather than join in
with it. Expressing one's own views tends to give participants cues as to what to say
(introducing bias), rather than the confidence to be open and honest about their own
views
 Be prepared for views that may be unpalatably critical of a topic which may be important
to you

In-depth interview:

An in-depth interview is defined as a qualitative research technique where intensive

individual interviews are conducted. In such interviews, there are smaller numbers of
respondents so that on a particular program, idea, or subject the respondent’s perspectives are
explored. An in-depth interview can also be mentioned as a loosely structured interview that
permits freedom for both the interviewer and interviewee in case of changing directions and also
exploring additional points when required. In-depth interviews are varied from survey interviews
where they are less structured. When survey interviews are considered they have a rigid
structure where questions are formulated and asked in sequential order and the same old
answers are defined. When in-depth qualitative interviews are considered, it is continuous and
flexible. Such kinds of interviews are not prepared well in advance and are also not a usual one.
Types of in-depth Interviews:
As per the definition of an in-depth interview, it is a quality-based research approach that
is used to interview a candidate intensively where the number of responders are few and the
research is concentrated mainly upon a single topic, idea or program. It is a good way of
gathering qualitative data or information.
Usually, the in-depth interviews differ from formal conversations to informal conversations.
Based on this process, in-depth interviews are characterized into 3 types, they are
● Structured
● Semi-structured
● Unstructured
Roles of In-Depth Interviews:
● Able to obtain the context of any problem.
● Able to evaluate potential solutions.
● Helps in determining the knowledge insights

Steps Involved in In-Depth Interview:

There are very few steps involved in conducting an in-depth interview.
● The first step involved in conducting an in-depth interview is by developing a sampling
strategy.
 ● The second step would be writing down an in depth interview guide which involves the
questions that are associated with the interview.
● The next step would be conducting an in-depth interview and finally would be analyzing
the data obtained.
In-depth interviews are appropriate and beneficial when a detailed report of any individual’s
thoughts or behaviors are required. Instead of focus groups, in-depth interviews can be
conducted when individuals are not interested in discussing openly in a group.
Observations: 

Observation is one of the traditional qualitative data collection method used by

researchers to gather descriptive text data by watching or observing the people and their behavior
at events or in their natural settings. In this method, the researcher is completely immersed in
watching or observing people by taking a participatory stance to take down notes. Aside from
taking notes, these days, different methods such as videos, photographs, audio recordings,
tangible items like artifacts, mementos are also be used. 

There are two main types of observation,

Covert:

 In this method, the observer is concealed without letting anyone know that they are being
observed. For example, a researcher studying the rituals of a wedding in nomadic tribes must
join them as a guest and quietly observe everything that goes around him. 

Overt:

 In this method, everyone is aware that they are being observed. For example, A
researcher or an observer wants to study wedding rituals of a nomadic tribe. To proceed with the
research, the observer or researcher can reveal why he is attending the marriage and even use a
video camera to shoot everything that goes on around him. 

Observation is one of the useful qualitative data collection methods, especially when you
want to study the ongoing process, situation, or reactions on a specific issue related to the people
being observed. Even when you want to understand people’s behavior or their way of interaction
in a particular community or demographic, you can rely on data generated through observation.
Remember, if you fail to get quality data through surveys, interviews, or group discussions, rely
on observation. It is the best and trusted qualitative data collection method to generate qualitative
data as it requires equal to no efforts from the participants. 
Narrative Records:-

“Narrative observations are a written sequential account of what is perceived. This

method of observation allows the educator to record the child’s actions in detail.”

Narratives can be helpful in observing and recording:

 Gross motor skills

 Fine motor skills
 Social interactions
 Spontaneous language
 Play patterns

Types of Narrative Records:

Anecdotal Record:

An anecdotal record requires that the observer, write a brief account of a selected incident
or behaviour soon after it occurs. These records are frequently used because they can be written
up at the end of the day and are an appropriate method of recording developmental stages. They
require some expertise on the part of the recorder in choosing significant sequences of behaviour.

Running Record:

A running record is a written description of the child’s behaviour. The observer records
exactly what a child says and does in sequence as he/she watches. This method of observation
enables educators to record more detail, to describe more accurately, to avoid assumptions, be
aware of personal biases, and also to make better use of the data that is collected.

Archival Records:

Materials created or received by a person, family, or organization, public or private, in

the conduct of their affairs that are preserved because of the enduring value contained in the
information they contain or as evidence of the functions and responsibilities of their creator.

Conclusion 
Qualitative research is one of the best methods for identifying the behavior and patterns
governing social conditions, issues, or topics. It spans a step ahead of quantitative data as it fails
to explain the reasons and rationale behind a phenomenon, but qualitative data quickly does. 

Question:3

Explain techniques of Data analysis : Successive Approximation, Content Analysis,

Semiotic &Analysis, Interpretative Phenomenoligical Analysis, Presenting Qualitative
Research Results and Report writing.?

Answer:

Data analysis:

Data analysis is defined as a process of cleaning, transforming, and modeling data to

discover useful information for business decision-making. The purpose of Data Analysis is to
extract useful information from data and taking the decision based upon the data analysis.

Whenever we take any decision in our day-to-day life is by thinking about what happened
last time or what will happen by choosing that particular decision. This is nothing but analyzing
our past or future and making decisions based on it. For that, we gather memories of our past or
dreams of our future. So that is nothing but data analysis. Now same thing analyst does for
business purposes, is called Data Analysis. Data Analysis consists of the following phases:

 Data Requirement Gathering

 Data Collection
 Data Cleaning
 Data Analysis
 Data Interpretation
 Data Visualization
Data Analysis Tools

Data analysis tools make it easier for users to process and manipulate data, analyze the
relationships and correlations between data sets, and it also helps to identify patterns and trends
for interpretation.
Types of Data Analysis: Techniques and Methods

There are several types of data analysis techniques that exist based on business and
technology. The major types of data analysis are:

1. Text Analysis
2. Statistical Analysis
3. Diagnostic Analysis
4. Predictive Analysis
5. Prescriptive Analysis

Text Analysis

Text Analysis is also referred to as Data Mining. It is a method to discover a pattern in

large data sets using databases or data mining tools. It used to transform raw data into business
information. Business Intelligence tools are present in the market which is used to take strategic
business decisions. Overall it offers a way to extract and examine data and deriving patterns and
finally interpretation of the data.

Statistical Analysis

Statistical Analysis shows "What happen?" by using past data in the form of dashboards.
Statistical Analysis includes collection, Analysis, interpretation, presentation, and modeling of
data. It analyses a set of data or a sample of data. There are two categories of this type of
Analysis - Descriptive Analysis and Inferential Analysis.
Descriptive Analysis

Analyses complete data or a sample of summarized numerical data. It shows mean and
deviation for continuous data whereas percentage and frequency for categorical data.

Inferential Analysis

Analyses sample from complete data. In this type of Analysis, you can find different
conclusions from the same data by selecting different samples.

Diagnostic Analysis

Diagnostic Analysis shows "Why did it happen?" by finding the cause from the insight
found in Statistical Analysis. This Analysis is useful to identify behavior patterns of data. If a
new problem arrives in your business process, then you can look into this Analysis to find
similar patterns of that problem. And it may have chances to use similar prescriptions for the
new problems.

Predictive Analysis

Predictive Analysis shows "what is likely to happen" by using previous data. The
simplest example is like if last year I bought two dresses based on my savings and if this year my
salary is increasing double then I can buy four dresses. But of course it's not easy like this
because you have to think about other circumstances like chances of prices of clothes is
increased this year or maybe instead of dresses you want to buy a new bike, or you need to buy a
house!

Prescriptive Analysis

Prescriptive Analysis combines the insight from all previous Analysis to determine which
action to take in a current problem or decision. Most data-driven companies are utilizing
Prescriptive Analysis because predictive and descriptive Analysis are not enough to improve data
performance. Based on current situations and problems, they analyze the data and make
decisions.

2. Successive Approximation:

Definition:

“A successive approximation ADC is a type of analog-to-digital converter that converts a

continuous analog waveform into a discrete digital representation via a binary search through all
possible quantization levels before finally converging upon a digital output for each conversion.”

Successive Approximation is occasionally called ‘shaping’. The methods of successive

approximation were introduced and tested by B.F. Skinner who used the technique to train
pigeons, dogs, dolphins, and people over the course of his career. In successive approximation,
each successive step towards the desired behavior is identified and rewarded. The series of
rewards for different steps of the behavior increases the likelihood that the steps will be taken
again and that they will lead to the desired end result being fulfilled.

Successive Approximation and Complex Behavior Changes

If you are considering using successive approximation to change human behavior there
are many examples of how it has worked. Successive approximation has been used to curb
childhood obesity by helping families identify and take subsequent steps towards healthy eating
habits that improve weight to height rations. It has also been used in addiction counseling to
break cocaine habits by providing positive reinforcement to gradual behavioral changes and
increasing the likelihood those behaviors will be turned into an overall better habit.

In this way, successive approximation helps what could be a huge change in behavior or
behavior desire outside of the norm become a more accessible behavior by building up to it. Few
people succeed by going “cold turkey” and animals are highly unlikely to perform complex tasks
on their own. Rather than looking at the final outcome as a major hurdle or difficulty, these
examples show us that breaking down the final desired behavior into smaller steps can increase
the likelihood that the behavior will change. It is a method used primarily in operant conditioning
whereby behaviours which are desired are reinforced. Initially, approximate behaviours are
reinforced, however, later into the study, only precise behaviours are reinforced.
 Operant conditioning is a type of learning that forms associations between behaviors and
the resulting events or consequences. Shaping is a type of operant conditioning that uses
reinforcers to guide behavior closer towards a desired behavior. Shaping occurs through
successive approximations that guide the target through incremental steps, ultimately leading to
the desired goal. Shaping and the technique of successive approximations have played a vital
role in research.

CONTENT ANALYSIS:

Definition:

“It  is a research technique used to make replicable and valid inferences by interpreting
and coding textual material. By systematically evaluating texts (e.g., documents, oral
communication, and graphics), qualitative data can be converted into quantitative data”.

Or,

“Any technique for making inferences by systematically and objectively identifying special
characteristics of messages.” (from Holsti, 1968)

Content analysis is a research tool used to determine the presence of certain words,
themes, or concepts within some given qualitative data (i.e. text). Using content analysis,
researchers can quantify and analyze the presence, meanings and relationships of such certain
words, themes, or concepts. Researchers can then make inferences about the messages within the
texts, the writer(s), the audience, and even the culture and time of surrounding the text.

Uses of Content Analysis

 Identify the intentions, focus or communication trends of an individual, group or

institution
  Describe attitudinal and behavioral responses to communications
 Determine psychological or emotional state of persons or groups
 Reveal international differences in communication content
 Reveal patterns in communication content
 Pre-test and improve an intervention or survey prior to launch
 Analyze focus group interviews and open-ended questions to complement quantitative
data.

Types of Content Analysis

There are two general types of content analysis: conceptual analysis and relational
analysis. Conceptual analysis determines the existence and frequency of concepts in a text.
Relational analysis develops the conceptual analysis further by examining the relationships
among concepts in a text. Each type of analysis may lead to different results, conclusions,
interpretations and meanings.

 Conceptual Analysis

Typically people think of conceptual analysis when they think of content analysis. In
conceptual analysis, a concept is chosen for examination and the analysis involves quantifying
and counting its presence. The main goal is to examine the occurrence of selected terms in the
data. Terms may be explicit or implicit. Explicit terms are easy to identify. Coding of implicit
terms is more complicated: you need to decide the level of implication and base judgments on
subjectivity (issue for reliability and validity). Therefore, coding of implicit terms involves using
a dictionary or contextual translation rules or both.
General steps for conducting a conceptual content analysis:

1. Decide the level of analysis: word, word sense, phrase, sentence, themes.

2. Decide how many concepts to code for: develop pre-defined or interactive set of
categories or concepts. Decide either: A. to allow flexibility to add categories through the
coding process, or B. to stick with the pre-defined set of categories.

 Option A allows for the introduction and analysis of new and important material that
could have significant implications to one’s research question.
 Option B allows the researcher to stay focused and examine the data for specific
concepts.
3. Decide whether to code for existence or frequency of a concept. The decision changes the
coding process.
 When coding for the existence of a concept, the researcher would count a concept
only once if it appeared at least once in the data and no matter how many times it
appeared.
 When coding for the frequency of a concept, the researcher would count the number
of times a concept appears in a text.
4. Decide on how you will distinguish among concepts:
 Should text be coded exactly as they appear or coded as the same when they appear in
different forms? For example, “dangerous” vs. “dangerousness”. The point here is to
create coding rules so that these word segments are transparently categorized in a
logical fashion. The rules could make all of these word segments fall into the same
category, or perhaps the rules can be formulated so that the researcher can distinguish
these word segments into separate codes.
 What level of implication is to be allowed? Words that imply the concept or words
that explicitly state the concept? For example, “dangerous” vs. “the person is scary”
vs. “that person could cause harm to me”. These word segments may not merit
separate categories, due the implicit meaning of “dangerous”.
5. Develop rules for coding your texts. After decisions of steps 1-4 are complete, a
researcher can begin developing rules for translation of text into codes. This will keep the
coding process organized and consistent. The researcher can code for exactly what he/she
wants to code. Validity of the coding process is ensured when the researcher is consistent
and coherent in their codes, meaning that they follow their translation rules. In content
analysis, obeying by the translation rules is equivalent to validity.
6. Decide what to do with irrelevant information: should this be ignored (e.g. common
English words like “the” and “and”), or used to reexamine the coding scheme in the case
that it would add to the outcome of coding?
7. Code the text: This can be done by hand or by using software. By using software,
researchers can input categories and have coding done automatically, quickly and
efficiently, by the software program. When coding is done by hand, a researcher can
recognize error far more easily (e.g. typos, misspelling). If using computer coding, text
could be cleaned of errors to include all available data. This decision of hand vs.
computer coding is most relevant for implicit information where category preparation is
essential for accurate coding.
 8. Analyze your results: Draw conclusions and generalizations where possible. Determine
what to do with irrelevant, unwanted or unused text: reexamine, ignore, or reassess the
coding scheme. Interpret results carefully as conceptual content analysis can only
quantify the information. Typically, general trends and patterns can be identified.

Relational Analysis

Relational analysis begins like conceptual analysis, where a concept is chosen for
examination. However, the analysis involves exploring the relationships between concepts.
Individual concepts are viewed as having no inherent meaning and rather the meaning is a
product of the relationships among concepts.

There are three subcategories of relational analysis to choose from prior to going on to the
general steps.

1. Affect extraction: an emotional evaluation of concepts explicit in a text. A challenge to

this method is that emotions can vary across time, populations, and space. However, it
could be effective at capturing the emotional and psychological state of the speaker or
writer of the text.
2. Proximity analysis: an evaluation of the co-occurrence of explicit concepts in the text.
Text is defined as a string of words called a “window” that is scanned for the co-
occurrence of concepts. The result is the creation of a “concept matrix”, or a group of
interrelated co-occurring concepts that would suggest an overall meaning.
3. Cognitive mapping: a visualization technique for either affect extraction or proximity
analysis. Cognitive mapping attempts to create a model of the overall meaning of the text
such as a graphic map that represents the relationships between concepts.

Reliability and Validity

Reliability:

 Because of the human nature of researchers, coding errors can never be eliminated but only
minimized. Generally, 80% is an acceptable margin for reliability. Three criteria comprise the
reliability of a content analysis:

1. Stability: the tendency for coders to consistently re-code the same data in the same way
over a period of time.
2. Reproducibility: tendency for a group of coders to classify categories membership in the
same way.
3. Accuracy: extent to which the classification of text corresponds to a standard or norm
statistically.
Validity:

Three criteria comprise the validity of a content analysis:

 1. Closeness of categories: this can be achieved by utilizing multiple classifiers to arrive at
an agreed upon definition of each specific category. 
2. Conclusions: What level of implication is allowable? Do conclusions correctly follow
the data? Are results explainable by other phenomena? This becomes especially
problematic when using computer software for analysis and distinguishing between
synonyms.
3. Generalizability of the results to a theory: dependent on the clear definitions of
concept categories, how they are determined and how reliable they are at measuring the
idea one is seeking to measure. 

SEMIOTIC ANALYSIS:

Definition: 

“It views the sign and use of signs as a part of a sign system. A sign system directs the
use of the sign and thus, the system always has an effect on the contents of individual signs. A
sign is never independent of the meanings and use of other signs”.

What is semiotics?

Semiotics is the study of signs and symbols and their use of interpretation. Usually,
semiotic analysis studies the roles of signs and the part they play on a social and cultural scale.

What is a sign/signifier?

A sign is the smallest unit of meaning. In order to create or define a sign, you will need
two pieces:

 The signifier (any material or physical form of the sign – the object that exists)
 The signified (a cultural or social concept that a signifier refers to – what it means)
The diagrams above are examples of the “Sausserean” models (named after Ferdinand de
Saussure, who helped create the model).
 The tree represents the concept of what we think about when we hear the word “tree.”
(the signified)
 The sound of the word “tree” - or reading the word in print – brings up the mental image
of an actual tree. (the signifier)
 The line between the signified and signifier represents the link the mind triggers
whenever the two are placed together. The arrows represent that constant interaction
between concept and sound/visual.

Another Semiotic Terms to Know

 Denotation :
The most basic literal meaning of a sign. Denotative interpretations help associate the
signifier (the physical/material) with the actual definition of the signified (concept).Example: a
rose is a sign for a type of flower in a garden.
 Connotation:
The secondary, cultural meaning of a sign. Connotative interpretations help associate the
signifier (the physical/material) with emotions, feelings, or cultural“stories” of the signified
(concept). Example: a rose is a sign for passion or true love (think Romeo and Juliet or the
enchanted rose in Beauty and the Beast)
 Ideology :
A set of ideas that create a culture's expectations, goals, and actions; in semiotics, this relates
usually to social or political issues.
 Paradigm:
A set of associated signifieds (concepts) or signifiers (the physical/material) which belong to
the same category; Example: when working with film and television, a paradigm may include
ways of transitioning, or moving, from a shot/camera angle (dissolve, cut, fade, etc.)
 Syntagm :
A sequential chain that combines interacting signifiers (the physical/material) and forms a
meaningful whole within a semiotic text Example: courses to different meals – each meal
(breakfast, lunch, and dinner) holds a separate meaning, so the sequential chain would dictate
what courses to serve.
 Mythology :
The combination of paradigms and syntagms that make up a well-told story with regards to
cultural association Example: the American cowboy mythology/the Wild West mythology)
  Semiotic situation :
A moment when we try to make sense of our surroundings and interpret one aspect based on
the signs of our situation.

INTERPRETATIVE PHENOMENOLIGICAL ANALYSIS:

Introduction:

Interpretative Phenomenological Analysis (IPA) has become a dominant qualitative

research methodology in many academic disciplines. Its emphasis on convergence and
divergence of experiences, as well as its mission in examining detailed and nuanced analysis of
the lived experience of small number participants , is particularly appealing to many researchers.
IPA is an integrative hermeneutic phenomenology first proposed by Jonathan Smith in a paper
that argued for an experiential approach in psychology that could equally dialogue with
mainstream psychology. But its structured approach and qualitative orientation seems to appeal
to other disciplines in human, social and health care research. IPA has two primary aims: to look
in detail at how someone makes sense of life experience, and to give detailed interpretation of
the account to understand the experience. The desire to know more about this qualitative
research methodology has intensified.

The aim of this paper is to provide an overview and limitations of IPA which has risen in
popularity in many academic disciplines due to its useful methodology in studying existential
experience. This study provides insights into this growing area of qualitative research approach.
The paper begins with a brief overview and rationale for qualitative research approach. It will
then go on to introduce the philosophical foundations of phenomenology. Then followed by the
theoretical underpinnings and criticisms of IPA. The paper concludes by bringing together some
thoughts for future researchers who might use IPA as their preferred research methodology.
Qualitative Research Approach

IPA is a qualitative research approach. Qualitative research explores and understands the
meanings people assign to their experiences. Qualitative inquiries seek to shed light on meanings
that are less perceptible. They also seek to investigate complexities of our social world. They are
inductive and share similarities in exploring ‘what’ ‘why’ and ‘how’ questions, as opposed to
‘how much’ and ‘how many’ preferred by quantitative studies. What’s more, qualitative research
is designed to study people’s life experiences and deliberately shuns quantitative preoccupation
with measuring, counting and prediction in favor of describing, exploring, understanding and
interpreting how a phenomenon.

Introducing Phenomenology:

Phenomenology is an approach began by Edmund Husserl and later developed by Martin

Heidegger that seeks to study the lived human experiences and the way things are perceived and
appear to the consciousness . Phenomenology has evolved into a relatively mature qualitative
research methodology during the last decades of the twentieth century largely due to a seismic
shift from mainly deductive quantitative research to inductive research. Phenomenology has
attracted growing interest in everyday experience in the domain of public and professional
practice including nursing, education, psychology, and social work. Though such interest has
also contributed to the proliferation of the approach with little consensus of what constitutes the
methodology. Heated debates have ensued about the appropriate ways to undertake
phenomenological research. However, two broad categories can be identified: descriptive and
hermeneutic. These follow the broad philosophical traditions of Husserl and Heidegger,
respectively.

The general focus of the descriptive phenomenological approach is to examine the

essence or structure of experiences in the way it occurs to our conscious. Thus, descriptions of
the experiences are anchored rigorously to the data without the influence of any external theory.
This approach is based on the philosophy of Husserl’s phenomenology which involves the
principles of epoché, intentional analysis and eidetic reduction. Put simply, the researcher is
required to adopt a phenomenological attitude and bracket or put aside past knowledge or
presuppositions.

Introducing IPA

As seen from the above, various phenomenological inspired research approaches use
different approaches ranging from pure description to interpretation. However, a modern way of
conducting a phenomenological research is IPA. IPA is particularly attractive because of its
commitment to explore, describe, interpret, and situate the participants’ sense making of their
experiences. The main theoretical underpinnings of IPA: phenomenology, hermeneutics,
idiography is next discussed.
PA and Phenomenology

IPA seeks to understand the lived experience by integrating the works of four major
phenomenological philosophers: Husserl, Heidegger, Merleau-Ponty, and Sartre to illuminate
phenomenology as a singular and pluralist endeavour existing in a continuum. One of the
striking features of IPA is a detailed and systematic analysis of consciousness. Like Husserl,
researchers primarily seek to capture the participants’ experiences of a phenomenon by
bracketing their fore-knowledge . To identify core structures and features of human experience,
Husserl encouraged the questioning of natural attitude through phenomenological reflection and
dissuaded things being taken for granted. Husserl believed that this could be achieved by
consciously setting aside our previous knowledge and to detach ourselves from prejudices, prior
understandings and our own history . Therefore, given that the basis of IPA is the examination of
the thing itself; thoughtful focus and the careful examination of experience in the way it occurs
to the participants proposed by Husserl is essential.

Husserl’s thesis on phenomenology has been criticized by many for being too
philosophical, conceptual and difficult to decipher. Moreover, the notion that the ultimate human
experience can be examined by setting aside pre-conceived knowledge has been dismissed as
simplistic and unattainable. Furthermore, pure experience advocated by Husserl is elusive and
inaccessible because experience is usually witnessed after the event has already happened

IPA and Hermeneutics

The next major theoretical underpinning of IPA is hermeneutics, which is the art and
science of interpretation or meaning. Meaning in this context is deemed as something fluid that is
continuously open to new insight, revision, interpretation, and reinterpretation. IPA employs four
influential philosophers: Heidegger, Schleiermacher, Ricoeur and Gadamer to advance the thesis
of hermeneutic phenomenology.

Ricoeur linked phenomenology and hermeneutics by explaining that experience and

meaning are closely intertwined. Thus, meaning in his view is indispensable to experience.
Hence, for both Ricoeur and hermeneutics experience and language is co-emergent. Language is
not only used for descriptive purposes, but as an expressive force of experience. Experience
reveals itself only when it is expressed in poetic, figurative and rhythmic language. Thus,
through interactive and textual interpretation, hermeneutic theorists utilize their subjective
expressions to reconstruct original meanings during textual interpretation. Hermeneutic
phenomenology therefore embraces the literary and poetic aesthetic application of language that
emanates from the process and product of research. 

Idiography

IPA is also said to be fundamentally idiographic, in that it is committed to the detailed

analysis of a phenomenon under investigation. It takes great care of each case, offering detailed
and nuanced analysis, valuing each case in its own merits before moving to the general cross-
case analysis for convergence and divergence between cases. Researchers are required to
carefully follow this idiographic approach throughout the analytic process for a meticulous
detailed examination of the convergence and divergence between the participants’ experiences.

In view of all that has been discussed so far, one may understand that IPA is indeed a
forward-looking research methodology that has the potential in understanding and interpreting
the experiences of people, because it offers practical and accessible guidelines in conducting
phenomenological research. However, it has methodological limitations and need to be
considered.
Criticisms of IPA

IPA has been criticized for being riddled with ambiguities as well as lacking
standardization. Others also point out that it is mostly descriptive and not sufficiently
interpretative. But the increasingly large quantity of publications that outline the theoretical,
methodological and philosophical underpinnings of IPA has been pointed out to the critics.

The most vigorous criticism of IPA is that the methodology suffers from four major
conceptual and practical limitations. Firstly, IPA like many phenomenological studies gives
unsatisfactory recognition to the integral role of language . But in their rebuttal of this criticism,
they accept that meaning making takes place in the context of narratives, discourse, metaphors
etc., and whilst the primary purposes of IPA are to gain insight into experience, it is always
intertwined with language 

Secondly, questions have been raised whether IPA can accurately capture the experiences
and meanings of experiences rather than opinions of it. Whilst phenomenology as philosophy is
associated with introspection allowing the philosopher to explore his or her experiences through
‘phenomenological meditation’, phenomenology as a research approach relies on the accounts of
participants and the experiences of researchers.

Presenting Qualitative Research Result

The Results :
Introduction:-
The results section is where you report the findings of your study based upon the
methodology [or methodologies] you applied to gather information. The results section should
state the findings of the research arranged in a logical sequence without bias or interpretation. A
section describing results is particularly necessary if your paper includes data generated from
your own research.
Structure and Writing Style:-
1. Organization and Approach

● For most research papers in the social and behavioral sciences, there are two
possible ways of organizing the results. Both approaches are appropriate in how you
report your findings, but use only one format.
 ● Present a synopsis of the results followed by an explanation of key findings. This
approach can be used to highlight important findings.
For example, you may have noticed an unusual correlation between two variables
during the analysis of your findings. It is appropriate to point this out in the results
section. However, speculating as to why this correlation exists, and offering a hypothesis
about what may be happening, belongs in the discussion section of your paper.
● Present a result and then explain it, before presenting the next result then
explaining it, and so on, then end with an overall synopsis.
This is the preferred approach if you have multiple results of equal significance. It
is more common in longer papers because it helps the reader to better understand each
finding. In this model, it is helpful to provide a brief conclusion that ties each of the
findings together and provides a narrative bridge to the discussion section of the your
paper.

Content:
In general, the content of your results section should include thefollowing:
● Introductory context for understanding the results by restating the research
problem underpinning your study.
 This is useful in re-orientating the reader's focus back to the research problem
after reading the literature review and your explanation of the methods of data gathering
and analysis.
● Inclusion of non-textual elements, such as, figures, charts, photos, maps, tables, etc.
to further illustrate key findings, if appropriate.
Rather than relying entirely on descriptive text, consider how your findings can
be presented visually. This is a helpful way of condensing a lot of data into one place that
can then be referred to in the text. Consider referring to appendices if there is a lot of
non-textual elements.
● A systematic description of your results, highlighting for the reader observations
that are most relevant to the topic under investigation.
Not all results that emerge from the methodology used to gather information may
be related to answering the "So What?" question. Do not confuse observations with
interpretations; observations in this context refers to highlighting important findings you
discovered through a process of reviewing prior literature and gathering data.
● The page length of your results section is guided by the amount and types of data to
be reported.
However, focus on findings that are important and related to addressing the
research problem. It is not uncommon to have unanticipated results that are not relevant
to answering the research question. This is not to say that you don't acknowledge
tangential findings and, in fact, can be referred to as areas for further research in the
conclusion of your paper. However, spending time in the results section describing
tangential findings clutters your overall results section.
● A short paragraph that concludes the results section by synthesizing the key
findings of the study.
Highlight the most important findings you want readers to remember as they
transition into the discussion section. This is particularly important if, for example, there
are many results to report, the findings are complicated or unanticipated, or they are
impactful or actionable in some way [i.e., able to be pursued in a feasible way applied to
practice].
Problems to Avoid
When writing the results section, avoid doing the following:
● Discussing or interpreting your results. Save this for the next section of your paper,
although where appropriate, you should compare or contrast specific results to those
found in other studies [e.g., "Similar to the work of Smith [1990], one of the findings of
this study is the strong correlation between motivation and academic achievement...."].
● Reporting background information or attempting to explain your findings.
This should have been done in your introduction section, but don't panic! Often
the results of a study point to the need for additional background information or to
explain the topic further, so don't think you did something wrong. Revise your
introduction as needed.
● Ignoring negative results.
A negative result generally refers to a finding that does not support the underlying
assumptions of your study. Do not ignore them. Document them and then state in your
discussion section why you believe a negative result emerged from your study. Note that
negative results, and how you handle them, offer you the opportunity to write a more
engaging discussion section, therefore, don't be hesitant to highlight them.
● Including raw data or intermediate calculations.
Ask your professor if you need to include any raw data generated by your study,
such as transcripts from interviews or data files. If raw data is to be included, place it in
an appendix or set of appendices that are referred to in the text.
● Be as factual and concise as possible in reporting your findings.
Do not use phrases that are vague or non-specific, such as, "appeared to be
greater than other variables..." or "demonstrates promising trends that...." Subjective
modifiers should be explained in the discussion section of the paper [i.e., why did one
variable appear greater? Or, how does the finding demonstrate a promising trend?].
● Presenting the same data or repeating the same information more than once.
If it is important to highlight a particular finding, you will have an opportunity to
emphasize its significance in the discussion section. Do not repeat it in your results
section.
● Confusing figures with tables.
 Be sure to properly label any non-textual elements in your paper. Don't call a
chart an illustration or a figure a table. If you are not sure, go here.

Report writing of Qualitative Research

In this section, we look at how to write an APA-style empirical research report, an
article that presents the results of one or more new studies. Recall that the standard
sections of an empirical research report provide a kind of outline. Here we consider each
of these sections in detail, including what information it contains, how that information is
formatted and organized, and tips for writing each section. At the end of this section is a
sample APA-style research report that illustrates many of these principles.

Sections of a Research Report

Title Page and Abstract
An APA-style research report begins with a title page. The title is centred in the upper half of
the page, with each important word capitalized. The title should clearly and concisely (in
about 12 words or fewer) communicate the primary variables and research questions.
This sometimes requires a main title followed by a subtitle that elaborates on the main
title, in which case the main title and subtitle are separated by a colon. Here are some
titles from recent issues of professional journals published by the American
Psychological Association.
● Sex Differences in Coping Styles and Implications for Depressed Mood
● Effects of Aging and Divided Attention on Memory for Items and Their Contexts
 ● Computer-Assisted Cognitive Behavioural Therapy for Child Anxiety: Results of
Randomized Clinical Trial
● Virtual Driving and Risk Taking: Do Racing Games Increase Risk-Taking Cognitions,
Affect, and Behaviour?
Below the title are the authors’ names and, on the next line, their institutional affiliation—the
university or other institution where the authors worked when they conducted the
research. As we have already seen, the authors are listed in an order that reflects their
contribution to the research. When multiple authors have made equal contributions to the
research, they often list their names alphabetically or in a randomly determined order.
 For articles that are being submitted for publication, the title page also includes an author
note that lists the authors’ full institutional affiliations, any acknowledgments the authors
wish to make to agencies that funded the research or to colleagues who commented on it,
and contact information for the authors. For student papers that are not being submitted
for publication, including theses author notes are generally not necessary.

The abstract
 The abstract is a summary of the study. It is the second page of the manuscript and is
headed with the word Abstract. The first line is not indented. The abstract presents the
research question, a summary of the method, the basic results, and the most important
 conclusions. Because the abstract is usually limited to about 200 words, it can be a
challenge to write a good one.
Ch#1 : Introduction
 The introduction begins on the third page of the manuscript. The heading at the top of
this page is the full title of the manuscript, with each important word capitalized as on the
title page. The introduction includes three distinct subsections, although these are
typically not identified by separate headings. The opening introduces the research
question and explains why it is interesting, the literature review discusses relevant
previous research, and the closing restates the research question and comments on the
method used to answer it.
The Opening
 The opening, which is usually a paragraph or two in length, introduces the research
question and explains why it is interesting. To capture the reader’s attention, researcher
Daryl Bem recommends starting with general observations about the topic under study,
expressed in ordinary language (not technical jargon)observations that are about people
and their behaviour (not about researchers or their research; (Bem, 2003).
 After capturing the reader’s attention, the opening should go on to introduce the research
question and explain why it is interesting. Will the answer fill a gap in the literature? Will
it provide a test of an important theory? Does it have practical implications? Giving
readers a clear sense of what the research is about and why they should care about it will
motivate them to continue reading the literature review—and will help them make sense
of it.
Ch#2 The Literature Review
 Immediately after the opening comes the literature review, which describes relevant
previous research on the topic and can be anywhere from several paragraphs to several
pages in length. However, the literature review is not simply a list of past studies. Instead,
it constitutes a kind of argument for why the research question is worth addressing. By
the end of the literature review, readers should be convinced that the research question
makes sense and that the present study is a logical next step in the ongoing research
process.
  Like any effective argument, the literature review must have some kind of structure. For
example, it might begin by describing a phenomenon in a general way along with several
studies that demonstrate it, then describing two or more competing theories of the
phenomenon, and finally presenting a hypothesis to test one or more of the theories. Or it
might describe one phenomenon, then describe another phenomenon that seems
inconsistent with the first one, then propose a theory that resolves the inconsistency, and
finally present a hypothesis to test that theory. In applied research, it might describe a
phenomenon or theory, then describe how that phenomenon or theory applies to some
important real-world situation, and finally suggest a way to test whether it does, in fact,
apply to that situation.
 Looking at the literature review in this way emphasizes a few things. First, it is extremely
important to start with an outline of the main points that you want to make, organized in
the order that you want to make them. The basic structure of your argument, then, should
be apparent from the outline itself. Second, it is important to emphasize the structure of
your argument in your writing. One way to do this is to begin the literature review by
summarizing your argument even before you begin to make it. “In this article, I will
describe two apparently contradictory phenomena, present a new theory that has the
potential to resolve the apparent contradiction, and finally present a novel hypothesis to
test the theory.” Another way is to open each paragraph with a sentence that summarizes
the main point of the paragraph and links it to the preceding points. These opening
sentences provide the “transitions” that many beginning researchers have difficulty with.
Instead of beginning a paragraph by launching into a description of a previous study,
such as “Williams (2004) found that…,” it is better to start by indicating something about
why you are describing this particular study.
Here are some simple examples:
Another example of this phenomenon comes from the work of Williams (2004).
● Williams (2004) offers one explanation of this phenomenon.
● An alternative perspective has been provided by Williams (2004).
● We used a method based on the one used by Williams (2004).
Finally, remember that your goal is to construct an argument for why your research question is
interesting and worth addressing—not necessarily why your favourite answer to it is
 correct. In other words, your literature review must be balanced. If you want to
emphasize the generality of a phenomenon, then of course you should discuss various
studies that have demonstrated it. However, if there are other studies that have failed to
demonstrate it, you should discuss them too. Or if you are proposing a new theory, then
of course you should discuss findings that are consistent with that theory. However, if
there are other findings that are inconsistent with it, again, you should discuss them too. It
is acceptable to argue that the balance of the research supports the existence of a
phenomenon or is consistent with a theory (and that is usually the best that researchers in
psychology can hope for), but it is not acceptable to ignore contradictory evidence.
Besides, a large part of what makes a research question interesting is uncertainty about its
answer.
The Closing
 The closing of the introduction—typically the final paragraph or two—usually includes
two important elements. The first is a clear statement of the main research question or
hypothesis. This statement tends to be more formal and precise than in the opening and is
often expressed in terms of operational definitions of the key variables. The second is a
brief overview of the method and some comment on its appropriateness.
 Thus the introduction leads smoothly into the next major section of the article—the
method section.
Ch#3 Method
 The method section is where you describe how you conducted your study. An important
principle for writing a method section is that it should be clear and detailed enough that
other researchers could replicate the study by following your “recipe.” This means that it
must describe all the important elements of the study—basic demographic characteristics
of the participants, how they were recruited, whether they were randomly assigned, how
the variables were manipulated or measured, how counterbalancing was accomplished,
and so on. At the same time, it should avoid irrelevant details such as the fact that the
study was conducted in Classroom 37B of the Industrial Technology Building or that the
questionnaire was double-sided and completed using pencils.
 The method section begins immediately after the introduction ends with the heading
“Method” (not “Methods”) centred on the page. Immediately after this is the subheading
“Participants,” left justified and in italics. The participants subsection indicates how
many participants there were, the number of women and men, some indication of their
age, other demographics that may be relevant to the study, and how they were recruited,
including any incentives given for participation.