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1. TO EXPLORE THE CORRELATION
BETWEEN SELECTED COGNITIVE
BIASES AND RELATIONSHIP
SATISFACTION

A Dissertation Submitted to
Indira Gandhi National Open University
in partial fulfilment of the requirement
for the degree of
M.Sc. Counselling and Family Therapy (MSCCFT)

Name of the Researcher:
Enrolment No:
Contact Details:

Regional Centre: RC - Delhi 1 (07)
Submitted as part of MCFTP002 in
Dissertation Guide: (IHE, 0787)
Indira Gandhi National Open University
Maidangarhi, New Delhi – 110068.

5. Dissertation Synopsis (MCFTP002)




TABLE OF CONTENTS

Title 3
Introduction
Statement of the Problem
Justification/Rationale of the Study
Objectives
Hypothesis
Variables
3
3
3
5
6
6
Review of Literature 7
Methodology
Research Design
Sample Details
Tools and Techniques of Data Collection
Method of Data Analysis - Statistics to be used
9
9
9
10
11
List of References 12
Appendix
I. Certificate of assigning an approved guide for dissertation
II. Certificate of approval of research proposal
III. Draft data collection questionnaire
13
14
15
16

6. Dissertation Synopsis (MCFTP002)




TITLE
A study to explore the correlation between selected cognitive biases (as measured by
DACOBS) and relationship satisfaction (as measured by RDAS).
INTRODUCTION
Romantic relationships between human beings are influenced by a myriad of factors. Some of
these factors such as personality, attachment styles, values and beliefs and life goals and
aspirations are characteristics of the individuals that form the particular dyad.
These individual-specific factors also include rational thinking, including the extent to which
the actions of those forming the dyad are impacted by their cognitive heuristics and biases.
This research effort is an endeavour to explore correlations between Cognitive Biases and
Relationship Satisfaction as elaborated further in this proposal.
STATEMENT OF THE PROBLEM
Is there a correlation between the level of cognitive biases viz. Jumping to Conclusions bias,
Belief Inflexibility bias, Attention for Threat bias, and External Attribution bias as measured
using DACOBS and Relationship Satisfaction as measured by RDAS?
JUSTIFICATION/RATIONALE OF THE STUDY
HEURISTICS, BIASES AND DECISION MAKING
The practitioners in the human JDM area focus on one fundamental question related to
human cognition: Why humans do what they do? i.e., everything else remaining the same,
why did they choose one particular path over the other alternatives available. The
understanding of the answer, and its application drives the field forward.

7. Dissertation Synopsis (MCFTP002)




In 2002, Daniel Kahneman won the Nobel Prize in Economics for the work that he did in this
space in collaboration with Amos Tversky. They showed that people are “…incapable of
fully analysing complex decision situations when the future consequences are uncertain.
Under such circumstances, they rely instead on heuristic shortcuts or rules of thumb.” (The
Sveriges Riksbank Prize in Economic Sciences in Memory of Alfred Nobel 2002: Popular
information, 2002). Simply, while humans have the ability to think rationally using ‘System
2’, they often do not, and often when it matters the most (high-stake decisions). Instead, they
rely on their ‘gut feeling’ or ‘emotions’ – effectively using the automated heuristics of
‘System 1’. And, this is true of all humans irrespective of their background, level of
education and any other differences.
While heuristics have played a critical role in human survival and development, and continue
to be not only useful but necessary in several contexts, in other contexts they may lead to
cognitive biases resulting in judgment and decision-making errors with significant adverse
consequences. These often remain invisible to the observers but have a tremendous impact on
the life of the concerned individuals.
IMPACT ON RELATIONSHIPS
Cognitive Biases are omnipresent – they impact human lives in contexts ranging from
financial decisions to romantic relationships, from day-to-day choices to life-changing
decisions. These impacts can be positive and negative.
Positive Impacts include improved efficiency and decision-making which derives from the
fact that cognitive biases are rooted in heuristics – and, heuristics play a great evolutionary
role - they help us quickly assess situations and make decisions, streamlining interactions and
promoting efficiency. Positive self-image and Improved relationships could be some of the
other results of cognitive biases.

8. Dissertation Synopsis (MCFTP002)




Negative Impacts include misunderstandings and conflict due to misinterpretation of
information and actions of others. Communication breakdowns and unrealistic expectations
could be some of the other results amongst many others.
Even though Cognitive Biases have significant impact on human relationships, there has been
limited research in the area. JDM in itself is a nascent field, which is still developing. At this
time, the focus however, seems to be in its industrial and clinical applications along with
improving the assessments and tools for better results and more efficient implementation.
Therefore, in this dissertation I propose to explore this nascent area and contribute to research
in this field. The significance of any research study can be evaluated across some key
dimensions: importance within context of study, relevance to the subjects of study, general
applicability, and extension of existing knowledge/filling gaps in existing knowledge.
From the discussion above, it is clear that this project is significant in many ways – it is
important in the context in which it is being conducted and it is of critical relevance to the
subjects of the study – those in relationships. Additionally, the findings of the study should be
extremely useful for the society in general – by creating a path for improvement of
relationship stability. Also, this study would fill a critical gap that exists in the current
knowledge about the relation between one aspect of rational thinking and relationships.
OBJECTIVES
To assess the presence or absence of a significant correlation between the level of each of the
Cognitive Biases measured by DACOBS viz Jumping to Conclusions bias, Belief
Inflexibility bias, Attention for Threat bias and External Attribution bias; and, Relationship
Satisfaction as measured by RDAS.

9. Dissertation Synopsis (MCFTP002)




HYPOTHESES
H0,1: There is no significant relationship between the Jumping to Conclusions bias and
Relationship Satisfaction.
H0,2: There is no significant relationship between the Belief Inflexibility bias and
Relationship Satisfaction.
H0,3: There is no significant relationship between the Attention for Threat bias and
Relationship Satisfaction.
H0,4: There is no significant relationship between the External Attribution bias and
Relationship Satisfaction.
VARIABLES
In this research two different groups of variables will be dealt with. Considering this project
is an ex-post facto research the option of modifying/controlling the variables is not available.
By observation of and understanding of the relationships amongst the variables the
understanding of the subject of the study will be enhanced. The two groups of variables are:
1. Variables pertaining to Cognitive Biases: This set would comprise of scores for the
level of four different Cognitive Biases – Jumping to Conclusions bias, Belief
Inflexibility bias, Attention for Threat bias and External Attribution bias. Thus, a set
of four variables.
2. Variables pertaining to Relationship Satisfaction: This includes an Overall
Relationship Satisfaction Score. In addition, we will be measuring three subscales in
RDAS - Cohesion, Consensus and Satisfaction.

10. Dissertation Synopsis (MCFTP002)




REVIEW OF LITERATURE
Cognitive bias refers to a systematic (that is, non-random and, thus, predictable) deviation
from rationality in judgment or decision-making. A growing body of experimental knowledge
suggests that people’s judgments and decisions are often far from rational: they are affected
by seemingly irrelevant factors or fail to take into account important information. Moreover,
these departures from the rational norm are usually systematic: people fail consistently in the
same type of problem, making the same mistake. That is, people seem to be irrational in a
predictable way. (Blanco, 2017)
Typically, the consequence of cognitive bias is a form of irrational behaviour that is
predictable (because it is systematic). Cognitive biases have been proposed to underlie many
beliefs and behaviours that are dangerous or problematic to individuals: superstitions,
pseudoscience, prejudice, poor consumer choices, etc. (Blanco, 2017)
These negative consequences of biases are also, logically, expected to have a serious impact
on human relationships. The popular (pop-psychology) media is full of numerous articles,
videos, etc. on this topic. However, there is very limited real scientific research in the space.
In this context, there lies an opportunity to produce work that will de facto be seminal if it
proves its worth through its findings and relevance.
RESEARCH STUDIES
Heuristics and Cognitive Biases is an area drawing lot of attention from practitioners of
different fields. While some are working to explore these more, others are focusing on the
‘application’, for example, the works of Thaler et al on ‘Nudge’. The importance of the field
has been highlighted by the Nobel Prizes awarded to Daniel Kahneman and Richard Thaler.

11. Dissertation Synopsis (MCFTP002)



Some of the numerous important publications related to this area are:
• Judgment under Uncertainty: Heuristics and Biases (Kahneman & Tversky, 1974)
was the seminal paper that introduced various cognitive biases and heuristics that
influence decision making, including anchoring, availability, and representativeness
biases. It laid the foundation for much of the subsequent research in this field.
• This groundbreaking study Prospect Theory: An Analysis of Decision under Risk
(Kahneman & Tversky, 2013) proposed prospect theory, which revolutionized the
understanding of how individuals make decisions under uncertainty. It introduced
concepts such as loss aversion and framing effects, significantly impacting economics
and psychology.
• Study titled The Framing of Decisions and the Psychology of Choice (Kahneman &
Tversky, 1981) examined how the framing of options influences decision making. It
demonstrates that people's choices can be swayed by the way options are presented,
even when the options are objectively equivalent.
• Article titled The Comprehensive Assessment of Rational Thinking (Stanovich, 2016)
details the work currently undergoing to develop the tools for understanding and
assessing ‘Rationality Quotient’ to measure the level of Rational Thinking.
In addition to the above, the books Thinking, Fast and Slow by Nobel laureate Daniel
Kahneman, Predictably Irrational: The Hidden Forces That Shape Our Decisions by Dan
Ariely and Nudge by Nobel laureate Richard Thaler have significantly advanced the
understanding of cognitive biases, heuristics, and human judgment and decision making,
shaping research and applications in psychology, economics, and beyond. However, no
meaningful research establishing a corelation between cognitive biases and relationship
satisfaction could be found online or in-library.

12. Dissertation Synopsis (MCFTP002)




METHODOLOGY
RESEARCH DESIGN
The project will be a Quantitative Non-Interventional Research. Using purposive sampling,
respondents would be identified and requested to fill the inventory of questions, which will
thereafter be quantitatively analysed.
The research design would be Ex-post facto - co-relational, wherein two sets of observations
would be made for each subject – first, regarding Cognitive Biases using DACOBS and
second, regarding Relationship Satisfaction using RDAS. These observations will yield us
two groups of variables as discussed earlier.
Once data is received, it will be collated, organised, tabulated, summarized and subsequently
analysed. For the purpose of analyses correlation techniques would be used to identify the
relationship amongst the variables.
SAMPLE DETAILS
Sample: The questionnaire would be administered to adults above 18 years of age who are
currently in or have been in the past in a romantic relationship. An attempt would be made to
collect data from a demographically diverse set to enable assessment of differences based on
demographic variation.
Inclusion Criteria: The participants and their partners should be healthy, not suffering any
serious medical situation or disability or an otherwise severe life stressor such as job loss.
The abnormalities, if such cases were included, may serve as extraneous variables. This is
because they may impact relationship satisfaction.
Sample size: 50

13. Dissertation Synopsis (MCFTP002)




Sampling Type: Purposive Sampling
Place: The questionnaire would primarily be administered online.
TOOLS AND TECHNIQUES OF DATA COLLECTION
Data collection would be performed using the Questionnaire method. For this purpose, a
questionnaire has been developed (see Appendix III) which comprises of three parts:
1. General Information covering Demographic Details.
2. Davos Assessment of the Cognitive Biases Scale (DACOBS) (Gaag, et al., 2013) to
measure Cognitive Biases:
a. The DACOBS is a self-report scale having 42 Likert’ scale items for assessing
Cognitive Biases, Cognitive Limitations and Safety Behaviours.
b. The items allow respondent to choose an answer on a 7-point scale ranging
from Strongly Agree to Strongly Disagree.
c. For this research the 24 items pertinent to Cognitive Biases will be used.
These include 6 items each for four independent cognitive bias subscales:
Jumping to Conclusions bias, Belief Inflexibility bias, Attention for Threat
bias and External Attribution bias
d. The DACOBS scale, with its seven independent subscales, was found to be
reliable and valid for use in clinical practice and research. (Gaag, et al., 2013)
3. Revised Dyadic Adjustment Scale (RDAS) (Busby, Christensen, Crane, & Larson,
1995) to measure Overall Relationship Satisfaction and its components.
a. In the field of couple and family psychology, the Dyadic Adjustment Scale is a
widely used measure of marital adjustment. D. M. Busby et al. (1995)
published a revised version of the scale (RDAS)
b. RDAS includes 14 items made using Likerts’ scale method.

14. Dissertation Synopsis (MCFTP002)




c. Three components of marital adjustment are operationalized: consensus,
satisfaction and cohesion.
d. The construct validity, criterion validity, internal consistency and split-half
reliability for the RDAS were found to be acceptable. (Busby, Christensen,
Crane, & Larson, 1995)
No modification has been made to the items from DACOBS or RDAS, as any changes may
hamper the reliability and validity of the instruments.
METHOD OF DATA ANALYSIS - STATISTICS TO BE USED
Simple correlation analysis will be performed amongst the various variables to assess the
existence or absence of relationships amongst them. More specifically, given sufficient data
is available Pearson’s r will be used as a measure of correlation. In the unexpected case of the
conditions pertaining to usage of the specified tool are not met, a non-parametric equivalent
of the test will be used. While Kendall’s Tau would be an option, the use of Chi Square
method may also be considered as Bivariate relation analysis is being done.
Over here, it is important to highlight that the intent is not to check for multi-variate
correlation. In the project Bivariate correlations amongst the various variables (as defined
earlier) will be analysed.
Considering the complexity of the analyses, computerised tools such as Microsoft Excel,
Microsoft Access, SASS, SPSS etc. may have to be used. It is also possible to make use of a
cloud-based solution ex: Google Sheets. The tool will be selected based on availability at the
time of analysis and details and rationale thereof will be laid out in the Dissertation.

15. Dissertation Synopsis (MCFTP002)




REFERENCES
Blanco, F. (2017). Encyclopedia of Animal Cognition and Behavior. (J. Vonk, & T.
Shackelford, Eds.) Cham: Springer.
Busby, D. M., Christensen, C., Crane, D. R., & Larson, J. H. (1995). A revision of the dyadic
adjustment scale for use with distressed and nondistressed couples: Construct
hierarchy and multidimensional scales. Journal of Marital and Family Therapy, 21,
29-308.
Gaag, M. v., Schütz, C., Napel, A. t., Landa, Y., Delespaul, P., Bak, M., . . . Hert, M. d.
(2013). Development of the Davos Assessment of Cognitive Biases Scale
(DACOBS). Schizophrenia Research, 144, 63-71.
Garrett, H. E. (1966). Statistics in Psychology and Education. New York: David Mckay
Company, Inc. and Longman Group Ltd.
Kahneman, D., & Tversky, A. (1974). Judgment under Uncertainty: Heuristics and Biases.
Science, 184(4157), 1124-1131.
Kahneman, D., & Tversky, A. (1981). The framing of decisions and the psychology of
choice. Science, 211(4481), 453-458.
Kahneman, D., & Tversky, A. (2013). Prospect theory: An analysis of decision under risk. In
Handbook of the fundamentals of financial decision making: Part I (pp. 99-127).
World Scientific.
Singh, A. K. (2013). Tests, Measurements and Research Methods in Behavioral Sciences.
Patna: Bharati Bhawan.
Stanovich, K. E. (2016). The Comprehensive Assessment of Rational Thinking. Educational
Psychologist, 51(1), 23-34.
The Sveriges Riksbank Prize in Economic Sciences in Memory of Alfred Nobel 2002: Popular
information. (2002). Retrieved from The Nobel Prize:
https://www.nobelprize.org/prizes/economic-sciences/2002/popular-information/

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ACKNOWLEDGEMENTS
The successful completion of this dissertation has been made possible by the contributions of
several people. I acknowledge their contributions and would like to thank them for their help.
GUIDANCE
Even the most renowned travellers need navigators to show them the way to successfully
complete their journey. This dissertation has been no less than a journey. And its success has
been made possible by the support and help of my navigator , Assistant
Professor, Institute of Home Economics, Delhi University, who agreed to be my project
guide. I am greatly indebted to her for the valuable guidance provided during the project. I
would like to express my gratitude and extend my sincere thanks to her for the constant
motivation and supervision.
I would also like to thank , Assistant Coordinator for IGNOU programmes
in IHE for taking out the time from her very busy schedule to discuss my area of interest in
detail, and for allocation of the appropriate guide.
PERMISSION TO USE THE TOOLS
This research endeavour makes use of two tools – the DACOBS and the RDAS. I’m thankful
to the authors of both the tools, especially Dr. Mark van der Gaag (DACOBS) and Dr. Dean
Busby (RDAS) for promptly responding to my emails and confirming that I can make use of
their tools for research.

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PARTICIPATION AND SUPPORT WITH DATA COLLECTION
The findings of any dissertation based on primary research can only be as good as the
quantity and quality of data they are based on. To ensure both can be a challenging task for
the researcher. I’m, therefore, thankful to all the subjects who participated in the data
collection exercise by filling the forms and sharing their personal details.
I’m also thankful to all my classmates, colleagues and friends who helped in the data
collection exercise by identifying the subjects and helping get the forms filled. This helped in
ensuring that the I could collect much more data than initially planned.

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TABLE OF CONTENTS
Annexure 1: Certificate of Assigning an Approved Guide ........................................................ 2
Annexure 2: Certificate of Approval of Research Proposal ...................................................... 3
Approved Synopsis .................................................................................................................... 4
Annexure 3: Certificate of Authenticity .................................................................................. 16
Acknowledgements .................................................................................................................. 17
Table of Contents ..................................................................................................................... 19
List of Tables ........................................................................................................................... 22
List of Figures .......................................................................................................................... 23
Abbreviations Used .................................................................................................................. 26
Abstract .................................................................................................................................... 27
Chapter I: Introduction ............................................................................................................. 28
1. Background And Rationale of the Study ......................................................................... 28
2. Statement of the Problem ................................................................................................. 32
3. Research Questions .......................................................................................................... 32

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Chapter IV: Results and Discussion ........................................................................................ 53
1. Data Analysis ................................................................................................................... 53
2. Results of the Analysis..................................................................................................... 56
3. Discussion ...................................................................................................................... 101
Chapter V: Summary, Conclusions and Recommendations .................................................. 103
1. Brief restatement of the problem, objectives, hypotheses, delimitations, methodology of
the study ............................................................................................................................. 103
2. Major findings of the study ............................................................................................ 105
3. Implications and conclusions of the study ..................................................................... 107
4. Strengths and limitations of the study ............................................................................ 108
5. Suggestions for further research .................................................................................... 110
Chapter VI: References ......................................................................................................... 113
Research Questionnaire ......................................................................................................... 118
Permission to use DACOBS .................................................................................................. 125
Permission to use RDAS ........................................................................................................ 126

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LIST OF TABLES
Table 1: Scoring for Cognitive Biases (DACOBS) ................................................................. 44
Table 2: Scoring Key for RDAS .............................................................................................. 46
Table 3: Correlation amongst research variables (calculated using SPSS) ............................. 55

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LIST OF FIGURES
Figure 1: Correlation between Jumping to Conclusions Bias (DACOBS) and Overall Relationship
Satisfaction (RDAS) ............................................................................................................................. 57
Figure 2: Correlation between Jumping to Conclusions Bias (DACOBS) and Consensus (RDAS) .... 58
Figure 3: Correlation between Jumping to Conclusions Bias (DACOBS) and Decision Making
(RDAS) ................................................................................................................................................. 59
Figure 4: Correlation between Jumping to Conclusions Bias (DACOBS) and Values (RDAS) .......... 60
Figure 5: Correlation between Jumping to Conclusions Bias (DACOBS) and Affection (RDAS) ...... 61
Figure 6: Correlation between Jumping to Conclusions Bias (DACOBS) and Satisfaction (RDAS) .. 62
Figure 7: Correlation between Jumping to Conclusions Bias (DACOBS) and Stability (RDAS)........ 63
Figure 8: Correlation between Jumping to Conclusions Bias (DACOBS) and Conflict (RDAS) ........ 64
Figure 9: Correlation between Jumping to Conclusions Bias (DACOBS) and Cohesion (RDAS) ...... 65
Figure 10: Correlation between Jumping to Conclusions Bias (DACOBS) and Activities (RDAS) .... 66
Figure 11: Correlation between Jumping to Conclusions Bias (DACOBS) and Discussion (RDAS).. 66
Figure 12: Correlation between Belief Inflexibility Bias (DACOBS) and Overall Relationship
Satisfaction (RDAS) ............................................................................................................................. 68
Figure 13: Correlation between Belief Inflexibility Bias (DACOBS) and Consensus (RDAS) ........... 69
Figure 14: Correlation between Belief Inflexibility Bias (DACOBS) and Decision Making (RDAS) 70
Figure 15: Correlation between Belief Inflexibility Bias (DACOBS) and Values (RDAS) ................. 71
Figure 16: Correlation between Belief Inflexibility Bias (DACOBS) and Affection (RDAS)............. 72

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Figure 17: Correlation between Belief Inflexibility Bias (DACOBS) and Satisfaction (RDAS) ......... 73
Figure 18: Correlation between Belief Inflexibility Bias (DACOBS) and Stability (RDAS) .............. 74
Figure 19: Correlation between Belief Inflexibility Bias (DACOBS) and Conflict (RDAS) ............... 75
Figure 20: Correlation between Belief Inflexibility Bias (DACOBS) and Cohesion (RDAS) ............. 76
Figure 21: Correlation between Belief Inflexibility Bias (DACOBS) and Activities (RDAS) ............ 77
Figure 22: Correlation between Belief Inflexibility Bias (DACOBS) and Discussion (RDAS) .......... 77
Figure 23: Correlation between Attention for Threat Bias (DACOBS) and Overall Relationship
Satisfaction (RDAS) ............................................................................................................................. 79
Figure 24: Correlation between Attention for Threat Bias (DACOBS) and Consensus (RDAS) ........ 80
Figure 25: Correlation between Attention for Threat Bias (DACOBS) and Decision Making (RDAS)
.............................................................................................................................................................. 81
Figure 26: Correlation between Attention for Threat Bias (DACOBS) and Values (RDAS) .............. 82
Figure 27: Correlation between Attention for Threat Bias (DACOBS) and Affection (RDAS) .......... 83
Figure 28: Correlation between Attention for Threat Bias (DACOBS) and Satisfaction (RDAS) ....... 84
Figure 29: Correlation between Attention for Threat Bias (DACOBS) and Stability (RDAS) ............ 85
Figure 30: Correlation between Attention for Threat Bias (DACOBS) and Conflict (RDAS) ............ 86
Figure 31: Correlation between Attention for Threat Bias (DACOBS) and Cohesion (RDAS) .......... 87
Figure 32: Correlation between Attention for Threat Bias (DACOBS) and Activities (RDAS) .......... 88
Figure 33: Correlation between Attention for Threat Bias (DACOBS) and Discussion (RDAS) ........ 88
Figure 34: Correlation between External Attribution Bias (DACOBS) and Overall Relationship
Satisfaction (RDAS) ............................................................................................................................. 90
Figure 35: Correlation between External Attribution Bias (DACOBS) and Consensus (RDAS) ........ 91

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Figure 36: Correlation between External Attribution Bias (DACOBS) and Decision Making (RDAS)
.............................................................................................................................................................. 92
Figure 37: Correlation between External Attribution Bias (DACOBS) and Values (RDAS) .............. 93
Figure 38: Correlation between External Attribution Bias (DACOBS) and Affection (RDAS) .......... 94
Figure 39: Correlation between External Attribution Bias (DACOBS) and Satisfaction (RDAS)....... 95
Figure 40: Correlation between External Attribution Bias (DACOBS) and Stability (RDAS) ............ 96
Figure 41: Correlation between External Attribution Bias (DACOBS) and Conflict (RDAS) ............ 97
Figure 42: Correlation between External Attribution Bias (DACOBS) and Cohesion (RDAS) .......... 98
Figure 43: Correlation between External Attribution Bias (DACOBS) and Activities (RDAS) .......... 99
Figure 44: Correlation between External Attribution Bias (DACOBS) and Discussion (RDAS) ........ 99

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ABBREVIATIONS USED
A: Affection
Ac: Activities
A4T: Attention for Threat
BI: Belief Inflexibility
C: Conflict
Coh: Cohesion
Con: Consensus
D: Discussion
DACOBS: Davos Assessment of the Cognitive Biases Scale
DM: Decision Making
EA: External Attribution
JDM: Judgment and Decision Making
J2C: Jumping to Conclusions
ORS: Overall Relationship Satisfaction
RDAS: Revised Dyadic Adjustment Scale
S: Stability
Sat: Satisfaction
SES: Socio-Economic Status
V: Values

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ABSTRACT
The objective of the study was to assess the presence or absence of a significant correlation
between the level of each of the Cognitive Biases measured by DACOBS viz Jumping to
Conclusions bias, Belief Inflexibility bias, Attention for Threat bias and External Attribution
bias; and, Relationship Satisfaction as measured by RDAS.
This was a Quantitative Non-Interventional Research. Using purposive sampling,
respondents were identified and requested to fill the inventory of questions, which was
thereafter quantitatively analysed. The research form was filled by a total of 209 respondents,
out of which 143 satisfied the criteria to be included in the analyses.
The research design was ex-post facto - co-relational, wherein two sets of observations were
made for each subject – first, regarding Cognitive Biases using DACOBS and second,
regarding Relationship Satisfaction using RDAS. These observations yielded two groups of
variables – pertaining to Cognitive Biases and Relationships, respectively.
Relationship between the four cognitive biases - Jumping to Conclusions, Belief Inflexibility,
Attention for Threat, and External Attribution - and Relationship Satisfaction was tested and
the null Hypothesis was accepted for all cases indicating that statistically significant
correlation was not found between any of these cognitive biases and relationship satisfaction.
However, additional analyses were performed to assess the correlations between these four
cognitive biases and the various scales and sub-scales of RDAS. A statistically significant
relationship was found at α=0.05 between External Attribution bias and Satisfaction.

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CHAPTER I: INTRODUCTION
1. BACKGROUND AND RATIONALE OF THE STUDY
Romantic relationships between human beings are influenced by a myriad of factors. Some of
these factors such as personality, attachment styles, values and beliefs and life goals and
aspirations are characteristics of the individuals that form the particular dyad.
These individual-specific factors also include rational thinking, including the extent to which
the actions of those forming the dyad are impacted by their cognitive heuristics and biases.
This research effort is an endeavour to explore correlations between Cognitive Biases and
Relationship Satisfaction as elaborated further in this proposal.
HEURISTICS, BIASES AND DECISION MAKING
The practitioners in the human JDM area focus on one fundamental question related to
human cognition: Why humans do what they do? i.e., everything else remaining the same,
why did they choose one particular path over the other alternatives available. The
understanding of the answer, and its application drives the field forward.
In 2002, Daniel Kahneman won the Nobel Prize in Economics for the work that he did in this
space in collaboration with Amos Tversky. They showed that people are “…incapable of
fully analyzing complex decision situations when the future consequences are uncertain.
Under such circumstances, they rely instead on heuristic shortcuts or rules of thumb.” (The
Sveriges Riksbank Prize in Economic Sciences in Memory of Alfred Nobel 2002: Popular
information, 2002). Simply, while humans have the ability to think rationally using ‘System

30. Dissertation (MCFTP002)


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2’, they often do not, and often when it matters the most (high-stake decisions). Instead, they
rely on their ‘gut feeling’ or ‘emotions’ – effectively using the automated heuristics of
‘System 1’. And, this is true of all humans irrespective of their background, level of
education and any other differences.
While heuristics have played a critical role in human survival and development, and continue
to be not only useful but necessary in several contexts, in other contexts they may lead to
cognitive biases resulting in judgment and decision-making errors with significant adverse
consequences. These often remain invisible to the observers but have a tremendous impact on
the life of the concerned individuals.
IMPACT ON RELATIONSHIPS
Cognitive Biases are omnipresent – they impact human lives in contexts ranging from
financial decisions to romantic relationships, from day-to-day choices to life-changing
decisions. These impacts can be positive and negative.
Positive Impacts include improved efficiency and decision-making which derives from the
fact that cognitive biases are rooted in heuristics – and, heuristics play a great evolutionary
role - they help us quickly assess situations and make decisions, streamlining interactions and
promoting efficiency. Positive self-image and Improved relationships could be some of the
other results of cognitive biases.
Negative Impacts include misunderstandings and conflict due to misinterpretation of
information and actions of others. Communication breakdowns and unrealistic expectations
could be some of the other results amongst many others.

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Even though Cognitive Biases are expected to have significant impact on human
relationships, there has been limited research in the area. JDM in itself is a nascent field,
which is still developing. At this time, the focus however, seems to be in its industrial and
clinical applications along with improving the assessments and tools for better results and
more efficient implementation.
Therefore, in this dissertation I propose to explore this nascent area and contribute to research
in this field.
SIGNIFICANCE OF THE STUDY
From the discussion above, it is clear that this project is significant in many ways. However,
to assess the significance of any research study it is best to take a methodical approach. As
such we can evaluated the significance of this study across some key dimensions:
1. Importance within context of study: The context of this study is factors affecting
human relationships. Specifically, the impact of cognitive processes on romantic
relationships. Therefore, in a critical way the future of the relationship.
Considering the study is directly tackling a matter of critical importance to the context
– that is the impact of this very influence, it qualifies as significant on the dimension
of relevance to context.
2. Relevance to the subjects of study: It is inarguable that healthy relationships are a
necessity for every individual who is in a relationship – the very people who form the
subjects of this research.
Considering this study deals with this very topic, it is relevant to not only the subjects
of the study, but also to their partners and spouses.

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3. General applicability: The results of this study are applicable to every normal
household in the country where there is a married/romantic relationship or would be
in the future.
Therefore, the findings of the study are extremely useful for the society in general –
by exploring a path for improvement of relationship stability.
4. Extension of existing knowledge/filling gaps in existing knowledge: The process of
reviewing the literature led to the realization that the subject under study is of critical
importance and general relevance. However, sufficient research is not available in the
Indian context. This research project is an attempt at filling this critical gap that exists
in the current knowledge about the relation between one aspect of rational thinking
and relationships.
Here, I would like to additionally state that this is just a humble beginning. Human
relationships play a crucial role in the progress of the human race. It is one of the
crucial determinants of what the society would become. Extensive research is required
on the various dimensions of the relationship. Through this dissertation, the process
has started with some of the dimensions. Hopefully, this shall be continued in the
future.
From the discussion above, it is clear that this research endeavour is significant in many ways
– it is important in the context in which it is being conducted and it is of critical relevance to
the subjects of the study – those in romantic relationships. Additionally, the findings of the
study are extremely useful for the society in generally – both in clinical and normal scenarios.
Also, as discussed earlier, this study fills a critical gap that exists in the current knowledge
about human relationships and their relation to cognitive processes.

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2. STATEMENT OF THE PROBLEM
Research is happening regarding applications and implications of cognitive biases in various
areas. However, there hasn’t been much focus on understanding the correlation between the
level of cognitive biases and Relationship Satisfaction. This is the problem intended to be
addressed in this research endeavour.
3. RESEARCH QUESTIONS
Is there a correlation between the level of cognitive biases viz. Jumping to Conclusions bias,
Belief Inflexibility bias, Attention for Threat bias, and External Attribution bias as measured
using DACOBS and Relationship Satisfaction as measured by RDAS?
4. OBJECTIVES OF THE STUDY
To assess the presence or absence of a significant correlation between the level of each of the
Cognitive Biases measured by DACOBS viz Jumping to Conclusions bias, Belief
Inflexibility bias, Attention for Threat bias and External Attribution bias; and, Relationship
Satisfaction as measured by RDAS.
5. HYPOTHESES OF THE STUDY
H0,1: There is no significant relationship between the Jumping to Conclusions bias and
Relationship Satisfaction.
H0,2: There is no significant relationship between the Belief Inflexibility bias and
Relationship Satisfaction.

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H0,3: There is no significant relationship between the Attention for Threat bias and
Relationship Satisfaction.
H0,4: There is no significant relationship between the External Attribution bias and
Relationship Satisfaction.
6. OPERATIONAL DEFINITIONS OF THE TERMS
Cognitive Biases: Cognitive biases can generally be described as systematic and universally
occurring tendencies, inclinations, or dispositions that skew or distort information processes
in ways that make their outcome inaccurate, suboptimal or simply wrong. They are
systematic cognitive dispositions or inclinations in human thinking and reasoning that often
do not comply with the tenets of logic, probability reasoning, and plausibility. These intuitive
and subconscious tendencies are at the basis of human judgment, decision making, and the
resulting behavior. (Toet & Korteling, 2022)
Jumping to Conclusions bias: It is a reasoning bias, also known as the data gathering bias
(Gaag, et al., 2013). It describes an individuals' tendency to make hasty decisions based on
insufficient information. (Dudley, Taylor, Wickham, & Hutton, 2016)
Belief Inflexibility bias: It is a bias against disconfirming evidence that prevents the
reappraisal of situations and locks an individual in… (Gaag, et al., 2013) [to their existing
beliefs and convictions.]
Attention for Threat bias: It is an attention bias where an individual develops a tendency to
prioritize the processing of threats over benign or neutral stimuli (Azriel & Bar-Haim, 2020)
i.e., there is a selective attention for threat. (Gaag, et al., 2013)

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External Attribution bias: It is also known as Source Monitoring Bias, and is marked by a
tendency to attribute own thoughts and utterances to an external origin after a short while and
also involves blaming others (Gaag, et al., 2013).
Romantic Relationship: A dyadic relationship where two individuals identify as being
romantically involved or married. Throughout this report when the term relationship is used,
it refers to a romantic relationship unless specified otherwise.
Relationship Satisfaction: For the purpose of this research, relationship satisfaction simply
refers to the satisfaction from the relationship and is determined by three factors – Consensus,
Satisfaction and Cohesion, as explained below.
Consensus: Consensus on matters of importance to [relationship] functioning (Busby,
Christensen, Crane, & Larson, 1995) viz. decision making, values and affection.
Satisfaction: Satisfaction in the romantic relationship with respect to having a sense of
stability in the relationship and the level of conflict in the relationship.
Cohesion: Cohesion in the romantic relationship as observed through activities and
discussions.
7. VARIABLES
In this research two different groups of variables were dealt with. Considering this was an ex-
post facto research the option of modifying/controlling the variables was not available. By
observation of and understanding of the relationships amongst the variables the
understanding of the subject of the study was enhanced. The two groups of variables are:

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VARIABLES PERTAINING TO COGNITIVE BIASES
This is a set of four variables comprising of scores for the level of four different Cognitive
Biases:
1. Jumping to Conclusions bias
2. Belief Inflexibility bias
3. Attention for Threat bias
4. External Attribution bias. a set of four variables.
VARIABLES PERTAINING TO RELATIONSHIP SATISFACTION
This includes an Overall Relationship Satisfaction Score. In addition, there are three scales
and seven subscales in RDAS:
1. Consensus:
a. Decision Making
b. Values
c. Affection
2. Satisfaction
a. Stability
b. Conflict
3. Cohesion:
a. Activities
b. Discussion
Though not originally planned, and out of the originally defined scope of the research, the
correlation of the various biases was also assessed against the various subscales.

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8. DELIMITATIONS OF THE STUDY
Following are the major delimitations of this study:
1. Geographically, the analyses have been limited to responses from Indians only. This
has been done because sufficient responses could not be obtained from international
respondents to enable statistically meaningful analyses.
2. By age, the analyses have been limited to those above the age of 18. Even though the
tools do not place any age restriction, it was decided to restrict the respondents to
legal age people. Otherwise, consent would have to be obtained from the parents/
guardians of such respondents, and they might not even be comfortable sharing about
their relationships with their parents/guardians.
3. Timeframe of data collection was limited to till mid-April (about 3 months) to be able
to meet the deadline for submission of the dissertation to the study centre, and as per
the guidance in the dissertation manual.
4. An obvious delimitation was to those who have been or were in a relationship.
5. Evaluation of responses on the norms of the tools to assess the level of marital distress
or the level of bias has been kept out of scope of this research.
EXCLUSION CRITERIA
Two strict exclusion criteria have been followed:
1. The respondent or partner having a medical condition were excluded.
2. The respondent or partner undergoing any other severe life stressor were excluded.
The analyses have been limited to those who did not have the above stressors as they would
serve as extraneous variables impacting the findings.

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CHAPTER II: REVIEW OF LITERATURE
1. THEORETICAL BACKGROUND
Cognitive bias refers to a systematic (that is, non-random and, thus, predictable) deviation
from rationality in judgment or decision-making. A growing body of experimental knowledge
suggests that people’s judgments and decisions are often far from rational: they are affected
by seemingly irrelevant factors or fail to take into account important information.
Moreover, these departures from the rational norm are usually systematic: people fail
consistently in the same type of problem, making the same mistake. That is, people seem to
be irrational in a predictable way. (Blanco, 2017)
Typically, the consequence of cognitive bias is a form of irrational behaviour that is
predictable (because it is systematic). Cognitive biases have been proposed to underlie many
beliefs and behaviours that are dangerous or problematic to individuals: superstitions,
pseudoscience, prejudice, poor consumer choices, etc. (Blanco, 2017)
These negative consequences of biases are also, logically, expected to have a serious impact
on human relationships. The popular (pop-psychology) media is full of numerous articles,
videos, etc. on this topic. However, there is very limited real scientific research in the space.
In this context, there’s an opportunity to produce work that is de facto seminal, if it proves its
worth through its findings and relevance.

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2. RESEARCH STUDIES AND OTHER PUBLISHED MATERIAL
Heuristics and Cognitive Biases is an area drawing lot of attention from practitioners of
different fields. While some are working to explore these more, others are focusing on the
‘application’, for example, the works of Thaler et al on ‘Nudge’. The importance of the field
has been highlighted by the Nobel Prizes awarded to Daniel Kahneman and Richard Thaler.
However, a rigorous search over numerous months did not yield any studies of a nature
similar to this. It is possible that there is some research which is yet unpublished, or
something that this researcher has failed to successfully locate. In any case, we must move
forward, and focus on the literature that is available.
Some of the numerous important publications related to the area of Judgment and Decision
Making (JDM) are:
• Judgment under Uncertainty: Heuristics and Biases (Kahneman & Tversky, 1974)
was the seminal paper that introduced various cognitive biases and heuristics that
influence decision making, including anchoring, availability, and representativeness
biases. It laid the foundation for much of the subsequent research in this field.
• This groundbreaking study Prospect Theory: An Analysis of Decision under Risk
(Kahneman & Tversky, 2013) proposed prospect theory, which revolutionized the
understanding of how individuals make decisions under uncertainty. It introduced
concepts such as loss aversion and framing effects, significantly impacting economics
and psychology.
• Study titled The Framing of Decisions and the Psychology of Choice (Kahneman &
Tversky, 1981) examined how the framing of options influences decision making. It

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demonstrates that people's choices can be swayed by the way options are presented,
even when the options are objectively equivalent.
• Article titled The Comprehensive Assessment of Rational Thinking (Stanovich, 2016)
details the work currently undergoing to develop the tools for understanding and
assessing ‘Rationality Quotient’ to measure the level of Rational Thinking.
In addition to the above, the books Thinking, Fast and Slow by Nobel laureate Daniel
Kahneman, Predictably Irrational: The Hidden Forces That Shape Our Decisions by Dan
Ariely and Nudge by Nobel laureate Richard Thaler have significantly advanced the
understanding of cognitive biases, heuristics, and human judgment and decision making,
shaping research and applications in psychology, economics, and beyond.
Considering, no meaningful research establishing a corelation between cognitive biases and
relationship satisfaction could be found online or in-library, it was decided to explore other
relevant research pertaining to impact of cognitive phenomenon on romantic relations:
1. In the study titled A brief intervention to promote conflict reappraisal preserves
marital quality over time (Finkel, Slotter, Luchies, Walton, & Gross, 2013) the
authors found that decline in marital quality was eliminated among couples in the
reappraisal condition. This effect of the reappraisal intervention on marital quality
over time was mediated through reductions in conflict-related distress over time. This
study illustrates the potential of brief, theory-based, social-psychological interventions
to preserve the quality of intimate relationships over time.
2. In the study titled Mindfulness-Based Relationship Enhancement (Carson, Carson,
Gil, & Baucom, 2004) the authors evaluated the effects of a novel intervention,
mindfulness-based relationship enhancement, designed to enrich the relationships of
relatively happy, non-distressed couples. Results suggested the intervention was

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efficacious in, amongst other things, favourably impacting couples' levels of
relationship satisfaction, autonomy, relatedness, closeness, acceptance of one another,
and relationship distress.
3. In the study titled Why am I unsatisfied? Adult attachment style, gendered irrational
relationship beliefs, and young adult romantic relationship satisfaction (Stackert &
Bursik, 2003) the results indicated that insecure individuals (anxious-ambivalent or
avoidant) endorsed significantly more relationship-specific irrational beliefs than
those with a secure adult attachment style. Further, both an insecure adult attachment
style and stronger adherence to relationship-specific irrational beliefs were related to
diminished relationship satisfaction.
4. In the study titled Effect of four aspects of rational statements on expected satisfaction
with a close relationship (Cramer, 2005) the author found that four aspects of rational
thinking: tendency not to exaggerate negative effects, not to demand that one's wishes
should always be met, not to globally rate individuals or relationships, and not to
over-generalise that these experiences always have happened or will happen,
combined together significantly decreased the expected relationship dissatisfaction.
Together they also significantly decreased the irrational tendency to agree that
disagreements are destructive.
Thus, as discussed above, even though there is limited research in the specific area chosen for
this study. The studies that have been conducted to assess the impact of cognitive
phenomenon on relationships, in general, point to a connection between them. This is also
what one would expect logically. And, thus, we hoped that this research endeavour would
help discover some statistically significant connection that has been left undiscovered so far.

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CHAPTER III: METHODOLOGY
1. INTRODUCTION
The aim of this research is to identify whether a correlation exists between the level of
cognitive biases viz. Jumping to Conclusions bias, Belief Inflexibility bias, Attention for
Threat bias, and External Attribution bias as measured using DACOBS and Relationship
Satisfaction as measured by RDAS. Using purposive sampling, respondents were identified
and requested to fill the data collection questionnaire. The research form was filled by a total
of 209 respondents, out of which 143 were deemed suitable for the final analyses.
The data collection questionnaire consisted of three parts – first, general information, second,
the DACOBS, to assess the level of presence of the four cognitive biases, and third, the
RDAS, to assess the level of relationship satisfaction.
Once the forms were filled, the data was collated, organised, tabulated, summarized and
subsequently analysed. For the purpose of analyses Pearson’s correlation technique was used
to identify the relationship amongst the various sub-scales of the two tests.
The methodology is explained in detail below.
2. RESEARCH DESIGN
This was a Quantitative Non-Interventional Research. Using purposive sampling,
respondents were identified and requested to fill the inventory of questions, which was
thereafter quantitatively analysed.

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The research design was ex-post facto - co-relational, wherein two sets of observations were
made for each subject – first, regarding Cognitive Biases using DACOBS and second,
regarding Relationship Satisfaction using RDAS. These observations yielded two groups of
variables – pertaining to Cognitive Biases and Relationships, respectively.
3. POPULATION OF THE STUDY
The questionnaire was administered to adults above 18 years of age who are currently in or
have been in the past in a romantic relationship. An attempt was made to collect data from a
demographically diverse set to enable assessment of differences based on demographic
variation, if required.
4. SAMPLE OF THE STUDY
Sample size: Total data collected: 209 against originally proposed 50; 143 responses were
available for analyses after applying the various inclusion and exclusion criteria.
Sampling Type: Purposive Sampling
Inclusion Criteria: The respondents whose responses whose responses were finally included
in the analysis, and their partners, were healthy, not suffering any serious medical situation or
disability or an otherwise severe life stressor such as job loss. The abnormalities, if such
cases were included, were expected to serve as extraneous variables as they can be expected
to impact relationship satisfaction.
5. TOOLS AND TECHNIQUES USED FOR DATA COLLECTION
Data collection was performed using the Questionnaire method. For this purpose, a
questionnaire was developed (see Appendix I) which comprised of three parts as explained

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below. No modification was made to the items from DACOBS or RDAS, as any changes
could have hampered the reliability and validity of the instruments.
1. GENERAL INFORMATION
The general information comprised of two parts:
1. General Information including demographic details about the respondent
2. General Information including demographic details about the partner
3. Information about the relationship
While 1 was collected in the beginning of the questionnaire, questions for 2 and 3 were
placed in the RDAS section, just before the questions of the tool.
2. DACOBS
Davos Assessment of the Cognitive Biases Scale (DACOBS) (Gaag, et al., 2013) was used to
measure Cognitive Biases. Permission was obtained over email to use the tool (see
appendices.)
Structure
The DACOBS is a self-report scale having 42 Likert’ scale items for assessing Cognitive
Biases, Cognitive Limitations and Safety Behaviours. The items allow respondent to choose
an answer on a 7-point scale ranging from Strongly Agree to Strongly Disagree.
For this research the 24 items pertinent to Cognitive Biases were used. These include 6 items
each for four independent cognitive bias subscales: Jumping to Conclusions bias, Belief
Inflexibility bias, Attention for Threat bias and External Attribution bias

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Reliability and Validity
The DACOBS scale, with its seven independent subscales, was found to be reliable and valid
for use in clinical practice and research. (Gaag, et al., 2013)
Reliability was considered to be ‘good’:
- The Cronbach alphas were calculated as a measure of internal consistency and range
from .64 to .90
- The split half-reliability ranges from .70 to .92
- For test-retest reliability a correlation between both assessments was calculated and
ranges from .72 to .92
Validity was affirmed for five of seven subscales (the five subscales include all four cognitive
bias scales which are being used in this research). They showed significant associations with
the validation measures ranging from .360 to .627. And, DACOBS could even be used to
discriminate between schizophrenia spectrum patients and normal control subjects.
Scoring
Scoring for the DACOBS involves calculating a sum of the scores for the items belonging to
the respective bias as outlined below after each item has been scored on a range from 1 to 7.
The subscale scores for the Cognitive Biases are calculated as follows:
Table 1: Scoring for Cognitive Biases (DACOBS)
Bias Calculation (Item Numbers)
Jumping to conclusions bias 3 + 8 + 16 + 18 + 25 + 30
Belief Inflexibility bias 13 + 15 + 26 + 34 + 38 + 41
Attention for Threat bias 1 + 2 + 6 + 10 + 20 + 37

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External Attribution bias 7 + 12 + 17 + 22 + 24 + 29

3. RDAS
Revised Dyadic Adjustment Scale (RDAS) (Busby, Christensen, Crane, & Larson, 1995) was
used to measure Overall Relationship Satisfaction and its components. Permission was
obtained over email to use the tool (see appendices.)
Structure
RDAS is a self-report questionnaire that assesses seven dimensions of couple relationships
within three overarching categories including Consensus in decision making, values and
affection, Satisfaction in the relationship with respect to stability and conflict regulation, and
Cohesion as seen through activities and discussion.
RDAS includes only 14 items, each of which asks the respondents to rate certain aspects of
her/his relationship on a 5- or 6-point scale.
Reliability and Validity
The construct validity, criterion validity, internal consistency and split-half reliability for the
RDAS were found to be acceptable. (Busby, Christensen, Crane, & Larson, 1995)
Reliability: RDAS has been found to have a Cronbach’s alpha (reliability) of .90.
Validity:
- Construct validity for the RDAS is supported by its high correlation with a similar
measure, the Locke-Wallace Marital Adjustment Test (MAT). The correlation
between the RDAS and the MAT was .68 (p < .01).

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- In addition, the correlation between the RDAS and the original Dyadic Adjustment
Scale (DAS) was .97 (p < .01).
- In terms of discriminant validity, the RDAS has been found to successfully
differentiate between 81% of distressed and non-distressed cases.
Scoring
Scores on the RDAS range from 0 to 69 with higher scores indicating greater relationship
satisfaction and lower scores indicating greater relationship distress. The cut-off score for the
RDAS is 48 such that scores of 48 and above indicate non-distress and scores of 47 and
below indicate marital/relationship distress. (Crane, Middleton, & Bean, 2000)
Scoring for the RDAS is a simple process of calculating a sum of the scores for the 14 items.
This gives an overall score which can be interpreted using the above noted cut-off score. The
subscale scores can be interpreted using the table below:
Table 2: Scoring Key for RDAS

Scores Range from:
Higher scores on any
of these subscales
indicate greater
stability and
satisfaction in the
relationship. Lower
scores indicate greater
distress.
Consensus 0 to 30
Decision Making: Items 3 and 6. 0 to 10
Values: Items 1 and 5 0 to 10
Affection: Items 2 and 4 0 to 10
Satisfaction 0 to 20
Stability: Items 7 and 9 0 to 10
Conflict: Items 8 and 10 0 to 10
Cohesion 0 to 19
Activities: Items 11 and 13 0 to 9
Discussion: Items 12 and 14 0 to 10

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6. PROCEDURE OF DATA COLLECTION
Data collection was done using a questionnaire, based on the tools mentioned above, created
specifically for the purpose. The form was shared directly with individuals who fulfilled the
necessary criteria, as well as on various fora where the sample population was available.
The respondents were identified using purposive sampling.
Considering the research area was new, it was ensured that the total number of responses
obtained was much more than the original target. This also helped ensure that more than
sufficient responses were available for inclusion based on the criteria defined earlier.
7. PROCEDURE OF DATA ANALYSIS
TABULATION AND ENCODING OF DATA
The data obtained from the respondents was converted into tables in spreadsheet format by
using the cloud-based tool Google Sheets.
The columns of the data were encoded according to the section names:
1. General Information questions were encoded by the field name such as Gender, DOB,
and so on.
2. DACOBS questions were encoded as D_1, D_2, and so on according to their order in
the original questionnaire, to avoid any confusion. The numbers pertaining to the
unused sub-scales were not used.
3. In the RDAS section:
a. General Questions were encoded g_1, g_2 and so on.
b. RDAS Standardised Tool questions were encoded R_1, R_2 and so on.

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CLEANING OF DATA
The following steps were undertaken for cleaning of data:
1. Dummy responses for testing the form’s completeness, legibility, etc. were removed.
2. Responses were checked to identify if there were any insincere responses – all options
as always agree, all the time… and clearly wrong info – such as date of birth. One
such response was found and removed from the analysis.
3. Responses from people who are not natives of India – people from Canada, UK, USA,
South Africa, Tanzania, Mexico and Malawi – were removed. Their data was
collected with the intention of attempting an inter-country comparison of results.
However, with just 1-2 responses for each of these countries enough data was not
available to be able to perform statistically significant analyses using parametric tools.
And, even with parametric tools there was a high probability of sampling bias. Thus,
they were removed.
4. The date of births seemed to be entered wrong in some of the forms, these were
reverified manually, and corrected where required.
ANONYMISATION
The anonymisation of responses was carried out by creating a respondent ID with values r1,
r2… for respondent 1, 2… and so on. The email IDs, which are the only way to identify and
get in touch with the respondents, were thereafter obfuscated from all places except the
original form filled and this unique ID created for every respondent became the ‘primary key’
for all purposes.

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SCORING
Once the data was prepared and cleaned, scoring was done by creating a separate spreadsheet
for scoring of each of the tools:
1. The “scoreD” sheet was created for scoring of responses to DACOBS questions.
a. The individual responses were assigned a numerical value as per the scoring
key given in the tool. Responses to the individual questions were encoded as
sD_1, sD_2 and so on.
b. After this, the scoring key of the tool (presented earlier) was used to calculate
the aggregate scores for each individual for each of the four cognitive biases.
These were encoded as J2C, BI, A4T and EA. The titles of these columns
were encoded in blue colour for easy identification.
2. The “scoreR” sheet was created for scoring of responses to RDAS questions.
a. The individual responses were assigned a numerical value as per the scoring
key given in the tool. Responses to the individual questions were encoded as
sR_1, sR_2 and so on.
b. After this the scoring key of the tool was used to calculate the aggregate scores
for each individual for each of the seven sub-scales. These were encoded as
Decision Making, Values, Affection, Stability, Conflict, Activities, and
Discussion. The titles of these columns were encoded in purple colour for easy
identification.
c. After this the scoring key of the tool was used to calculate the aggregate scores
for each individual for each of the three scales. These were encoded as
Consensus, Satisfaction, and Cohesion. The titles of these columns were
encoded in blue colour for easy identification.

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d. After this the overall relationship satisfaction scores for each individual were
calculated. The title of this column was encoded in green colour for easy
identification.
After scoring, the data was now ready for statistical analyses. It was, hence, exported to MS
Excel format which could be directly imported into SPSS for further processing.
STATISTICAL ANALYSES
Once the score data was ready for interpretation and further analysis, bivariate correlation
analysis was performed amongst the various variables to assess the existence or absence of
relationships amongst them. More specifically, considering sufficient data was available
(n=143) Pearson’s r was used as a measure of correlation, there was no requirement to use a
non-parametric equivalent of the test.
To check the level of significance, a two-tailed test was used considering our interest is
limited to assessing the presence of a relationship and not whether it is positive or negative.
The level of significance was checked at both α=0.01 and α=0.05. The hypotheses were
accepted at α=0.05 itself.
Over here, it is important to highlight that the intent is not to check for multi-variate
correlation. In the research bivariate correlations amongst the various variables (as defined
earlier) were analysed.
In addition, scatter plot charts depicting correlation have been created to enable the reader to
visually evaluate the results. This is the only place in the research report where data-points
have been shown on an individual basis, however, no further information is revealed.

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TOOLS USED FOR ANALYSES
Considering the complexity of the analyses, computerised tools were used. An attempt was
made to use the cloud-based Looker Studio by Google, but it was deemed too advanced for
the current scope. So, I reverted to the originally proposed tools:
- The cloud-based Google Sheets was used for the preparation of the data – which
involved collating, organising and tabulating the data to prepare it for scoring, and
carrying out the scoring.
- This was downloaded in MS Excel format for further analyses. Correlation scatter
plot charts which have been presented in the next section were built in MS Excel.
Additionally, the input for statistical analyses was generated from MS Excel.
- SPSS (evaluation version) was used for the statistical analyses required to test the
hypotheses. Fortunately, an evaluation version of ‘SPSS 15.0 for Windows’ was
present with the user which allows ~15 days long free access to the tool. The open-
source alternative PSPP was also tried, and deemed to perform satisfactorily, in case
any analyses are to be performed in the future after the expiry of SPSS’ free trial
period.
8. ETHICAL CONCERNS
As a researcher it is my obligation to conduct the research in an ethical and conscientious
manner. This research endeavour involved collecting data which was quite personal and
sensitive – information about the relationship of the person filling the form with his/her
spouse and about their own cognitive functioning.

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Here are some of the key guidelines from the Ethical Principles of Psychologists and Codes
of Conduct (American Psychological Association, 2010) relevant to research:
“4.04(a) Psychologists include in written and oral reports and consultations, only
information germane to the purpose for which the communication is made.
“4.06 ...(1) psychologists do not disclose confidential information that reasonably
could lead to the identification of a client/patient, research participant, or other
person or organisation...
“4.07 Psychologists do not disclose in their writings, lectures, or other public media,
confidential, personally identifiable information concerning their clients/patients,
students, research participants, organizational clients, or other recipients of their
services that they obtained during the course of their work...”
Keeping the guidelines in mind and considering the sensitivity of the data, the subjects were
assured that the data would be kept confidential. To maintain confidentiality the minimum
necessary personally identifiable information was collection, and even so the individual
responses have not been shared in this report. All data is shared in a statistically aggregated
manner or in the form of visuals, and all interpretations were also drawn at this level.

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CHAPTER IV: RESULTS AND DISCUSSION
In this chapter, we look at the data analysis, the results of the analysis and a discussion of the
findings and their interpretation in context of existing research.
1. DATA ANALYSIS
To summarise the earlier discussion, the data for this research was collected from 209
individuals above 18 years of age who were either married or in a romantic relationship. It
was thereafter tabulated, with data for the two sets of questionnaires DACOBS and RDAS
tabulated separately. The tabulated data was then scored using the scoring key reproduced in
the previous section. The scored data was thus ready for interpretation and further analyses.
Bivariate correlation analysis was performed amongst the various variables to assess the
existence or absence of relationships amongst them. More specifically, considering sufficient
data was available (n=143) Pearson’s r was used as a measure of correlation. The results of
this correlation are represented in Table 3: Correlation amongst research variables (calculated
using SPSS).
As highlighted earlier, while the two sets of variables being assessed comprise of multiple
variables, the intent was never to assess multi-variate correlation. Bivariate correlations
amongst the various variables have been analysed in this report. Keeping this in mind the
results of testing the hypotheses with each pair of variables have been discussed here.
Before getting into the results, however, it would help to take a quick look at Table 3:
Correlation amongst research variables (calculated using SPSS) and understand how to use it.

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- The first row of this table has the scales of RDAS – Consensus, Satisfaction, and
Cohesion.
- The second row of the tables has the seven sub-scales of RDAS – Decision Making,
Values, Affection, Conflict, Stability, Activities and Discussion.
- The last column in the first and second rows pertains to overall relationship
satisfaction (the aggregate RDAS score.)
- The first column of this table has the cognitive bias variables from DACOBS –
Jumping to Conclusions Bias, Belief Inflexibility Bias, Attention for Threat bias and
External Attribution bias.
- The second column of this table shows what the numbers are. You may observe the
pattern – there are three rows pertaining to each variable from DACOBS. The first
row shows the values of the Pearson coefficient, second row shows the levels of
significance for the two tailed test and the third one shows the sample size for each
question.
- From the third column and thirds row onwards, the intersection of each column
(RDAS variable) and row (DACOBS variable) tells us about the correlation between
the two variables.
- The cells highlighted in gray/numbers marked with ‘*’ are the statistically significant
at α = 0.05.

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2. RESULTS OF THE ANALYSIS
In this section the results of the analysis performed on the data after scoring have been and
the interpretation of these results have been discussed.
The section has been structured by the pairs of variables under evaluation - the correlation of
each variable from DACOBS with each of the variables from the RDAS is discussed one by
one. So, for example: first, the Jumping to Conclusions Bias is taken. Its correlation is
assessed first with the overall Relationship Satisfaction to test the Hypothesis. After that its
correlation with the Consensus scale is discussed. This is followed by a discussion of its
correlation with the various subscales of Consensus such as Decision Making. Then the
process is repeated for the remaining scales and sub-scales of RDAS, till the correlation of
this Bias with all the 11 variables of RDAS has been discussed. This process has been
followed for all the four cognitive biases.
It is also important to highlight that the variables from DACOBS form the x-axis, which is
used to depict the dependent variable. But it should be noted that the analysis done in this
research is purely correlational. Attempt has been made to explore the correlations between
the variables as proposed. No attempt at establishing the causality has been made anywhere
in this report, even where correlation was found.
It must also be noted that, in this research the norms of the two scales are not being used for
interpretation of the level of bias or level of relationship distress as that is not the objective of
this research. The focus has been delimited to assessing correlations between variables for
hypotheses testing.

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Table 3: Correlation amongst research variables (calculated using SPSS) indicates a
correlation of +0.0461 between these two variables. This finding is indicated by the line of
best fit being near parallel to x axis in Figure 11: Correlation between Jumping to
Conclusions Bias (DACOBS) and Discussion (RDAS).
This correlation is small and insignificant for the given sample size at both α=0.01 and
α=0.05. Therefore, we can conclude that an increase or decrease in Jumping to Conclusions
bias may or may not be accompanied by a change in the level of Discussion (Cohesion).

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Table 3: Correlation amongst research variables (calculated using SPSS) indicates a
correlation of +0.0216 between these two variables. This finding is indicated by the line of
best fit being near parallel to x axis in Figure 33: Correlation between Attention for Threat
Bias (DACOBS) and Discussion (RDAS).
This correlation is small and insignificant for the given sample size at both α=0.01 and
α=0.05. Therefore, we can conclude that an increase or decrease in Attention for Threat bias
may or may not be accompanied by a change in the level of Discussion (Cohesion).

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Table 3: Correlation amongst research variables (calculated using SPSS) indicates a
correlation of -0.0785 between these two variables. This finding is indicated by the line of
best fit being near parallel to x axis in Figure 44: Correlation between External Attribution
Bias (DACOBS) and Discussion (RDAS).
This correlation is small and insignificant for the given sample size at both α=0.01 and
α=0.05. Therefore, we can conclude that an increase or decrease in External Attribution bias
may or may not be accompanied by a change in the level of Discussion (Cohesion).

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3. DISCUSSION
The objective of this research was to assess the presence or absence of a significant
correlation between the level of each of the Cognitive Biases measured by DACOBS viz
Jumping to Conclusions bias, Belief Inflexibility bias, Attention for Threat bias and External
Attribution bias; and, Relationship Satisfaction as measured by RDAS.
Based on the literature review some expectations were set on what the results of this research
would be like, even though there was no certainty due to the lack of research on the topic.
This expectation was that significant correlation would be found between the various
cognitive biases and relationship satisfaction.
However, the results, in general, turned out to be counter-intuitive. All the null hypotheses
were rejected. Statistically significant correlation wasn’t found between any of the four
cognitive biases and relationship satisfaction. The correlation between the various sets of
variables turned out to be small and insignificant.
Considering this, it was decided to go beyond the originally defined scope and also explore
the existence of correlations between the cognitive biases and the various scales and sub-
scales of the RDAS. Accordingly, first correlations were calculated between the various
cognitive biases and the three scales of RDAS viz. Consensus, Satisfaction and Cohesion.
And, then correlations were calculated between the various cognitive biases and the seven
sub-scales of RDAS viz. Decision Making, Values, Affection, Stability, Conflict, Activities
and Discussion.
However, again, statistically significant correlation was not found to exist between the
cognitive biases and any of the RDAS variables, with one exception.

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This research managed to successfully uncover the correlation between a cognitive bias and
one aspect of relationship satisfaction. The cognitive bias is External Attribution bias. The
specific RDAS scale is Satisfaction.
There is a correlation of -0.1796 between these two variables. This correlation is significant
for the given sample size at α=0.05. The negative sign indicates that the correlation is
negative. Therefore, it can be concluded that an increase in External Attribution bias is
accompanied by a decrease in the level of Satisfaction. Even though the correlation may not
be very high, it is statistically significant – which is a major finding!
To summarize, while the null hypothesis was accepted for all four pairs from the four pairs of
variables analysed, and no correlation was found between the selected cognitive biases and
relationship satisfaction, this research managed to successfully discover a statistically
significant correlation between External Attribution Bias and Satisfaction.

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CHAPTER V: SUMMARY, CONCLUSION S AND
RECOMMENDATIONS
1. BRIEF RESTATEMENT OF THE PROBLEM, OBJECTIVES, HYPOTHESES,
DELIMITATIONS, METHODOLOGY OF THE STUDY
Research is happening regarding applications and implications of cognitive biases in various
areas. However, there hasn’t been much focus on understanding the correlation between the
level of cognitive biases and Relationship Satisfaction. This was the problem addressed in
this research endeavour.
The objective of the study was to assess the presence or absence of a significant correlation
between the level of each of the Cognitive Biases measured by DACOBS viz Jumping to
Conclusions bias, Belief Inflexibility bias, Attention for Threat bias and External Attribution
bias; and, Relationship Satisfaction as measured by RDAS.
There were four null Hypotheses that were tested in the study:
1. No significant relationship between the Jumping to Conclusions bias and Relationship
Satisfaction.
2. No significant relationship between the Belief Inflexibility bias and Relationship
Satisfaction.
3. No significant relationship between the Attention for Threat bias and Relationship
Satisfaction.
4. No significant relationship between the External Attribution bias and Relationship
Satisfaction.

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The major delimitations of this study were: only respondents belonging to India, above the
age of 18 who were or have been in a relationship were included. Respondents having
stressors such as medical condition, job loss etc. were kept out of scope of this analyses. The
cut-off date to fill the form was April 13
th
, 2024. Evaluation of responses based on the norms
of the tools to assess the level of marital distress or the level of biases has been kept out of the
scope of this research.
This was a Quantitative Non-Interventional Research. Using purposive sampling,
respondents were identified and requested to fill the inventory of questions, which was
thereafter quantitatively analysed.
The research design was ex-post facto - co-relational, wherein two sets of observations were
made for each subject – first, regarding Cognitive Biases using DACOBS and second,
regarding Relationship Satisfaction using RDAS. These observations yielded two groups of
variables – pertaining to Cognitive Biases and Relationships, respectively.
The research form was filled by a total of 209 respondents (against the proposed 50), out of
which 143 were deemed suitable for the final analyses.
The data collection questionnaire consisted of three parts – first, General Information,
second, the DACOBS, to assess the level of presence of the four cognitive biases, and third,
the RDAS, to assess the level of relationship satisfaction.
Once the forms were filled, the data was collated, organised, tabulated, summarized and
subsequently analysed. For the purpose of analyses Pearson’s correlation technique was used
to identify the relationship amongst the various sub-scales of the two tests.

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2. MAJOR FINDINGS OF THE STUDY
From the discussion in the previous section, it is clear that no significant correlation was
found between relationship satisfaction and any of the four cognitive biases in scope of this
research. As a consequence, all the null hypotheses were accepted.
Broadly, through this research effort it was found that:
LEVEL 1: CORRELATION BETWEEN COGNITIVE BIASES AND RELATIONSHIP SATISFACTION
1. No significant relationship exists between the Jumping to Conclusions bias and
Relationship Satisfaction.
2. No significant relationship exists between the Belief Inflexibility bias and Relationship
Satisfaction.
3. No significant relationship exists between the Attention for Threat bias and Relationship
Satisfaction.
4. No significant relationship exists between the External Attribution bias and Relationship
Satisfaction.
LEVEL 2: CORRELATION BETWEEN COGNITIVE BIASES AND CONSENSUS, SATISFACTION AND
COHESION
1. No significant relationship between the Jumping to Conclusions bias and any of the three
Consensus, Satisfaction and Cohesion.
2. No significant relationship between the Belief Inflexibility bias and any of the three
Consensus, Satisfaction and Cohesion.
3. No significant relationship between the Attention for Threat bias and any of the three
Consensus, Satisfaction and Cohesion.

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4. No significant relationship between the External Attribution bias and Consensus or
Cohesion. However, a statistically significant relationship was found at α=0.05
between External Attribution bias and Satisfaction.
LEVEL 3: CORRELATION BETWEEN COGNITIVE BIASES AND THE RDAS SUB-SCALES (DECISION
MAKING, VALUES, AFFECTION, STABILITY, CONFLICT, ACTIVITIES AND DISCUSSION)
1. No significant relationship exists between the Jumping to Conclusions bias and the RDAS
Sub-Scales (Decision Making, Values, Affection, Stability, Conflict, Activities and
Discussion).
2. No significant relationship exists between the Belief Inflexibility bias and the RDAS Sub-
Scales (Decision Making, Values, Affection, Stability, Conflict, Activities and
Discussion).
3. No significant relationship exists between the Attention for Threat bias and the RDAS
Sub-Scales (Decision Making, Values, Affection, Stability, Conflict, Activities and
Discussion).
4. No significant relationship exists between the External Attribution bias and the RDAS
Sub-Scales (Decision Making, Values, Affection, Stability, Conflict, Activities and
Discussion).
Thus, the two major findings of this study are: the absence of correlation between the four
cognitive biases and relationship satisfaction (and other RDAS variables), and the presence of
a statistically significant correlation between the External Attribution bias and the
Satisfaction dimension of RDAS.

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3. IMPLICATIONS AND CONCLUSIONS OF THE STUDY
The study delved into exploring the correlation between cognitive biases and relationship
satisfaction, a topic less explored in previous research. Through a quantitative non-
interventional approach, it aimed to examine the relationship between four specific cognitive
biases (Jumping to Conclusions, Belief Inflexibility, Attention for Threat, and External
Attribution) and relationship satisfaction. The null hypotheses were tested, and the study
revealed several insights.
Firstly, the study found no significant correlation between any of the four cognitive biases
and relationship satisfaction. This implies that individuals' tendencies towards these
cognitive biases do not significantly impact their overall satisfaction within romantic
relationships. This outcome suggests that factors beyond theses cognitive biases might play a
more influential role in determining relationship satisfaction.
Secondly, the study examined the correlation between cognitive biases and consensus,
satisfaction, and cohesion within relationships. Again, no significant relationships were found
between the cognitive biases and these aspects, except for External Attribution bias, which
showed a statistically significant relationship with satisfaction. This suggests that while most
cognitive biases do not directly influence consensus, satisfaction, and cohesion within
relationships, External Attribution bias may have a specific impact on satisfaction levels.
Lastly, the study investigated the correlation between cognitive biases and various sub-scales
of the Relationship Assessment Scale (RDAS), including decision making, values, affection,
stability, conflict, activities, and discussion. Like the previous findings, no significant
relationships were found between the cognitive biases and these RDAS sub-scales. This

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indicates that the cognitive biases examined in the study do not significantly affect specific
aspects of relationship dynamics as measured by the RDAS.
In summary, the study's major implications and conclusions are twofold:
Firstly, it highlights the lack of a significant correlation between the examined cognitive
biases and overall relationship satisfaction, as well as other aspects of relationship dynamics
measured by the RDAS. This suggests that while these cognitive biases may influence
individual thought processes, they may not be strong determinants of relationship satisfaction
or specific relationship dynamics.
Secondly, the study also reveals a nuanced finding regarding External Attribution bias, which
showed a significant correlation with satisfaction.
4. STRENGTHS AND LIMITATIONS OF THE STUDY
In this section, we look at the various strengths and limitations of the research conducted.
These must be kept in mind while interpreting this report. This is also accompanied by
suggestions for someone who wants to further this research – how to possibly overcome some
of the limitations that are highlighted.
1. Related to Sample:
a. Sample size is one of the big strengths of this endeavour. By collecting the data
for over 200 people there was scope of being strict while following the inclusion
and exclusion criteria.
b. Improving representativeness: There are several aspects related to demographics
and other features which were probably not covered well by the sample ex: socio-
economic status, level of education or schooling, etc. as the present sample is
majorly focused on middle income group families.

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2. Related to Research Area: Another major strength of this effort is the area of research.
The intersection of cognitive biases and relationship satisfaction is a nascent area with
limited work and any research in this space, if done properly, has the potential to make a
meaningful contribution.
3. Related to Potential for Replication: The study has been performed very systematically
using standardised tools and approaches making it very easy for anyone in any part of the
world to replicate it without any major issue.
4. Related to Filling Questionnaire:
a. Due to time and other constraints, it wasn’t possible for the researcher to monitor
the conditions and mental state under which the respondents filled the form with
strictness. Anyone using the results should keep this in mind.
b. Some respondents filled DOB with data that was obviously wrong. While it could
be figured out and the respondents were approached to get the correct information.
However, there may be other, not so obvious, errors from the respondents’ end
which might have gone unnoticed or could not possibly be noticed.
5. Related to Availability of Standardised Tools
a. While there was no dearth of tools for assessing relationship satisfaction, the story
for cognitive biases was completely different. While work in the field is ongoing
and possibly over a hundred cognitive biases have been identified already, there
are very limited tools available to assess them in individuals.
b. Most tools are currently under development, or testing, or some other stage – and
are not ready for use in research.
c. Out of those tools which are available for use, some tools are activity type and
require one on one administration which was not feasible.

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d. Some other tools are too time-taking, or can be administered only to students of a
higher-grade level due to the use of complex language/sentence construction.
e. The researcher was fortunate to have found DACOBS, just about the time the
synopsis was being prepared.
6. Related to Scope: Due to the paucity of tools, as discussed above, this study focused on
only four of the cognitive biases – which was one of the biggest limitations. Even some of
the major well-known biases such as Anchoring Bias could not be explored. There were
alternatives available but either they were too time consuming or not reliable and valid
enough, making them unusable for the purpose of this research.
Apart from these, the other limitations that are faced by a researcher using a questionnaire,
and that too with limited number of open-ended questions were faced in this research too. For
example, there was no opportunity to clarify in case any responses were on unexpected lines.
However, the researcher believes that even with these limitations, this research is an
important work in this area, not only in India but globally, and will help those who work
further in the area by acting as a source of reference and a starting point.
5. SUGGESTIONS FOR FURTHER RESEARCH
Overall, these findings contribute to the understanding of cognitive biases in the context of
romantic relationships, emphasizing the complexity of factors that contribute to relationship
satisfaction and dynamics. Further research could:
1. Explore the impact of other cognitive biases on the same variables (RDAS) related to
relationships.

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8. International Differences: An attempt was made in this study to collect data from
other countries across the world to do a cross-comparison. Even though responses
were obtained from many countries around the world, sufficient responses could not
be obtained to enable an analysis. Perhaps, someone else could try the same again, or
may be researchers from different countries may join hands to replicate and continue
this work.
Therefore, as is obvious from the above, there is plenty of scope to take this work of research
further or do related researches. The researcher would be happy to collaborate or support any
one willing to expend energies on making a difference in this very critical yet under-
researched area.

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CHAPTER VI: REFERENCES
American Psychological Association. (2010). Ethical Principles of Psychologists and Code of
Conduct. Washington DC: American Psychological Association.
Azriel, O., & Bar-Haim, Y. (2020). Attention bias. In J. S. Abramowitz, & S. M. Blakey
(Eds.), Clinical handbook of fear and anxiety: Maintenance processes and treatment
mechanisms (pp. 203-218). American Psychological Association.
Blanco, F. (2017). Encyclopedia of Animal Cognition and Behavior. (J. Vonk, & T.
Shackelford, Eds.) Cham: Springer.
Busby, D. M., Christensen, C., Crane, D. R., & Larson, J. H. (1995). A revision of the dyadic
adjustment scale for use with distressed and nondistressed couples: Construct
hierarchy and multidimensional scales. Journal of Marital and Family Therapy, 21,
29-308.
Carson, J. W., Carson, K., Gil, K. M., & Baucom, D. H. (2004). Mindfulness-Based
Relationship Enhancement. Behavior Therapy, 471-494.
Cramer, D. (2005). Effect of four aspects of rational statements on expected satisfaction with
a close relationship. British Journal of Guidance & Counselling, 227-238.
Crane, D. R., Middleton, K. C., & Bean, R. A. (2000). Establishing criterion scores for the
Kansas Marital Satisfaction Scale (KMSS) and the Revised Dyadic Adjustment Scale
(RDAS). American Journal of Family Therapy, 53-60.

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Dudley, R., Taylor, P., Wickham, S., & Hutton, P. (2016). Psychosis, Delusions and the
“Jumping to Conclusions” Reasoning Bias: A Systematic Review and Meta-analysis.
Schizophrenia Bulletin, 652-655.
Finkel, E. J., Slotter, E. B., Luchies, L. B., Walton, G. M., & Gross, J. J. (2013). A brief
intervention to promote conflict reappraisal preserves marital quality over time.
Psychological Science, 1595-601.
Gaag, M. v., Schütz, C., Napel, A. t., Landa, Y., Delespaul, P., Bak, M., . . . Hert, M. d.
(2013). Development of the Davos Assessment of Cognitive Biases Scale
(DACOBS). Schizophrenia Research, 144, 63-71.
Garrett, H. E. (1966). Statistics in Psychology and Education. New York: David Mckay
Company, Inc. and Longman Group Ltd.
Kahneman, D., & Tversky, A. (1974). Judgment under Uncertainty: Heuristics and Biases.
Science, 184(4157), 1124-1131.
Kahneman, D., & Tversky, A. (1981). The framing of decisions and the psychology of
choice. Science, 211(4481), 453-458.
Kahneman, D., & Tversky, A. (2013). Prospect theory: An analysis of decision under risk. In
Handbook of the fundamentals of financial decision making: Part I (pp. 99-127).
World Scientific.
Singh, A. K. (2013). Tests, Measurements and Research Methods in Behavioral Sciences.
Patna: Bharati Bhawan.

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Stackert, R. A., & Bursik, K. (2003). Why am I unsatisfied? Adult attachment style, gendered
irrational relationship beliefs, and young adult romantic relationship satisfaction.
Personality and Individual Differences, 1419-1429.
Stanovich, K. E. (2016). The Comprehensive Assessment of Rational Thinking. Educational
Psychologist, 51(1), 23-34.
The Sveriges Riksbank Prize in Economic Sciences in Memory of Alfred Nobel 2002: Popular
information. (2002). Retrieved from The Nobel Prize:
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Toet, A., & Korteling, J. E. (2022). Cognitive Biases. In Encyclopedia of Behavioral
Neuroscience, 2nd edition (Second Edition) (pp. 610-619). Academic Press.

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APPENDICES

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APPENDIX I
DATA COLLECTION QUESTIONNAIRE

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GENERAL INFORMATION
About You
Email ID: ______________
Age: ______________ years
Nature of work:  Job  Business  Professional  Daily wage  Other
Maximum Educational qualification:
 Less than 10+2  10+2/High School  Graduate  Post Graduate or Higher
Country: ______________

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PART II: RDAS
About the Relationship
Please answer the remaining questions in this survey keeping in mind any one of your
relationships - preferably, the current relationship.
Will you answer following questions based on:  Current Relationship  Past Relationship
Nature of Relationship:  Marriage  Dating
Length of relationship (including courting period in case of marriage): _________
years/months
Do you and your partner/spouse have differing religious beliefs or cultural background:
 Yes  No.
Are you or your partner/spouse suffering from any medical problem(s):  Yes  No.
Are you or your partner/spouse currently facing any other life situation (such as job loss) due
to which you are under severe stress:  Yes  No.
About Your Partner/Spouse
Age: ______________ years
Nature of work:  Job  Business  Professional  Daily wage  Other
Maximum Educational qualification:
 Less than 10+2  10+2/High School  Graduate  Post Graduate or Higher
Country: ______________

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Instructions: Most persons have disagreements in their relationships. Please indicate below
the approximate extent of agreement or disagreement between you and your partner for each
item on the following list.

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APPENDIX II
PERMISSION TO USE TOOLS