FEAR OF FAILURE
Author : Mahak Shrivastava 021331025218
Anushka Mithari 021331025069
Introduction
In today’s competitive academic environment, students often face high expectations regarding performance and success, which can lead to psychological pressure. One common challenge arising from this pressure is fear of failure, defined as anxiety about making mistakes or not meeting expectations. This fear can result in procrastination, avoidance of challenges, low self-confidence, and increased stress, ultimately affecting students’ academic performance and emotional well-being. Understanding the key dimensions of fear of failure is essential for developing effective support strategies. Therefore, this study aims to analyze the underlying factors of fear of failure among students using factor analysis.
Objective
1. To understand hidden variable by Factor Analysis
2. To cluster the respondants by Cluster Analysis
Data Collection
We have framed the following questions
1. I often worry that people will think less of me if I fail.
2. I tend to procrastinate on tasks because I’m afraid I won’t do them perfectly.
3. When I fail, I question my own intelligence or talent.
4. I feel that failing a task is a reflection of my worth as a person.
5. I am afraid that failing will disappoint the people who are important to me.
6. I prefer to stick to things I know I’m good at rather than trying something new.
7. I often feel a physical sense of anxiety (racing heart, sweating) when facing a challenge.
8. I worry that if I fail now, it will negatively impact my entire future.
A likert table is provided with following codes:
Strongly Disagree 1
Disagree 2
Neutral 3
Agree 4
Strongly Agree 5
We approached student of ITM Business School for our primary research.
Data Analysis
Factor Analysis
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KMO and Bartlett’s Test |
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Kaiser-Meyer-Olkin Measure of Sampling Adequacy. |
.830 |
|
|
Bartlett’s Test of Sphericity |
Approx. Chi-Square |
876.037 |
|
df |
28 |
|
|
Sig. |
<.001 |
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Analysis of KMO and Bartlett’s Test
The Kaiser-Meyer-Olkin (KMO) value of 0.830 indicates very good sampling adequacy, suggesting that the data is suitable for factor analysis. Since the value is well above the acceptable limit of 0.50, the variables share sufficient common variance.
Bartlett’s Test of Sphericity < 0.001, indicating that the correlation matrix is not an identity matrix and that meaningful relationships exist among the variables. Therefore, factor analysis is appropriate and justified for this dataset.
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Total Variance Explained |
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|
Component |
Initial Eigenvalues |
Extraction Sums of Squared Loadings |
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||||
|
Total |
% of Variance |
Cumulative % |
Total |
% of Variance |
Cumulative % |
|
|
|
1 |
4.062 |
50.777 |
50.777 |
4.062 |
50.777 |
50.777 |
|
|
2 |
3.137 |
39.210 |
89.987 |
3.137 |
39.210 |
89.987 |
|
|
3 |
.224 |
2.802 |
92.790 |
|
|
|
|
|
4 |
.164 |
2.052 |
94.842 |
|
|
|
|
|
5 |
.133 |
1.659 |
96.501 |
|
|
|
|
|
6 |
.124 |
1.552 |
98.053 |
|
|
|
|
|
7 |
.094 |
1.174 |
99.228 |
|
|
|
|
|
8 |
.062 |
.772 |
100.000 |
|
|
|
|
|
Extraction Method: Principal Component Analysis. |
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Analysis of Total Variance Explained
The results show that two components were extracted based on the eigenvalue criterion (eigenvalue > 1).
- Component 1 has an eigenvalue of 4.062 and explains 50.77% of the total variance.
- Component 2 has an eigenvalue of 3.137 and explains 39.21% of the total variance.
Together, these two components explain 89.98% of the total variance, indicating that they capture the majority of information present in the dataset. The remaining components have eigenvalues less than 1 and contribute minimally, therefore they were not retained.
The extraction of two dominant factors provides a strong and reliable factor structure, making the solution both statistically sound and meaningful for interpretation.
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Component Matrixa |
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|
Component |
|
|
|
1 |
2 |
|
|
|
I often worry that people will think less of me if I fail. |
.799 |
-.540 |
|
|
I tend to procrastinate on tasks because I’m afraid I won’t do them perfectly. |
.699 |
.639 |
|
|
When I fail, I question my own intelligence or talent. |
.766 |
-.566 |
|
|
I feel that failing a task is a reflection of my worth as a person. |
.728 |
-.623 |
|
|
I am afraid that failing will disappoint the people who are important to me. |
.778 |
-.555 |
|
|
I prefer to stick to things I know I’m good at rather than trying something new. |
.593 |
.720 |
|
|
I often feel a physical sense of anxiety (racing heart, sweating) when facing a challenge. |
.623 |
.718 |
|
|
I worry that if I fail now, it will negatively impact my entire future. |
.689 |
.621 |
|
|
Extraction Method: Principal Component Analysis. |
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a. 2 components extracted. |
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Due to the presence of high cross-loadings, factor rotation (Varimax method) was applied to obtain a clear, interpretable, and meaningful factor structure.
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Rotated Component Matrix |
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|
Component |
||
|
1 |
2 |
||
|
I often worry that people will think less of me if I fail. |
.959 |
.104 |
|
|
I tend to procrastinate on tasks because I’m afraid I won’t do them perfectly. |
.121 |
.940 |
|
|
When I fail, I question my own intelligence or talent. |
.950 |
.064 |
|
|
I feel that failing a task is a reflection of my worth as a person. |
.958 |
-.004 |
|
|
I am afraid that failing will disappoint the people who are important to me. |
.952 |
.079 |
|
|
I prefer to stick to things I know I’m good at rather than trying something new. |
-.013 |
.933 |
|
|
I often feel a physical sense of anxiety (racing heart, sweating) when facing a challenge. |
.011 |
.951 |
|
|
I worry that if I fail now, it will negatively impact my entire future. |
.124 |
.919 |
|
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Extraction Method: Principal Component Analysis. |
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a. Rotation converged in 3 iterations. |
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Analysis of Rotated Component Matrix
After applying Varimax rotation, a clear two-factor structure emerged with high and distinct factor loadings, making interpretation meaningful. Each variable loads strongly on only one component, indicating minimal cross-loading and strong factor separation.
Component 1 – Social & Self-Worth Fear
High loadings were observed for:
- Worry about others thinking less after failure (.959)
- Questioning intelligence after failure (.950)
- Viewing failure as a reflection of self-worth (.958)
- Fear of disappointing important people (.952)
This component reflects fear related to social evaluation, self-esteem, and emotional impact of failure.
Component 2 – Performance Anxiety & Avoidance
High loadings were observed for:
- Procrastination due to fear of imperfection (.940)
- Preference for familiar tasks (.933)
- Physical anxiety during challenges (.951)
- Fear of negative future consequences (.919)
This component represents performance anxiety, perfectionism, stress reactions, and avoidance behavior.
The rotated solution provides a clear, reliable, and interpretable two-factor structure, confirming that fear of failure among students consists of two major dimensions: social–emotional fear and performance-related anxiety.
Cluster Analysis
The method we are using for cluster analysis is K Mean Cluster
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Final Cluster Centers |
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|
Cluster |
|
|
|
1 |
2 |
|
|
|
I often worry that people will think less of me if I fail. |
2 |
4 |
|
|
I tend to procrastinate on tasks because I’m afraid I won’t do them perfectly. |
5 |
3 |
|
|
When I fail, I question my own intelligence or talent. |
2 |
4 |
|
|
I feel that failing a task is a reflection of my worth as a person. |
2 |
4 |
|
|
I am afraid that failing will disappoint the people who are important to me. |
2 |
4 |
|
|
I prefer to stick to things I know I’m good at rather than trying something new. |
5 |
3 |
|
|
I often feel a physical sense of anxiety (racing heart, sweating) when facing a challenge. |
5 |
3 |
|
|
I worry that if I fail now, it will negatively impact my entire future. |
5 |
3 |
|
|
Number of Cases in each Cluster |
|||
|
Cluster |
1 |
20.000 |
|
|
2 |
72.000 |
|
|
|
Valid |
92.000 |
|
|
|
Missing |
.000 |
|
|
|
|
|
|
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Analysis of Final Cluster Centers
The final cluster centers represent the average scores of variables after convergence, showing two clearly distinct student groups based on fear of failure dimensions.
Cluster 1 – High Performance Anxiety & Avoidance Group
This cluster shows high scores (5) on:
· Procrastination due to fear of imperfection
· Preference for familiar tasks
· Physical anxiety when facing challenges
· Worry about future consequences
And low scores (2) on:
· Fear of social judgment
· Self-worth concerns
· Fear of disappointing others
This indicates students who experience strong performance anxiety, stress reactions, and avoidance behavior, but relatively lower social evaluation fear.
Cluster 2 – High Social & Emotional Fear Group
This cluster shows high scores (4) on:
· Fear of negative social judgment
· Questioning intelligence after failure
· Viewing failure as self-worth reflection
· Fear of disappointing important people
And moderate scores (3) on:
· Procrastination, anxiety, and future worries
This reflects students mainly driven by social pressure, emotional sensitivity, and self-esteem concerns.
Table of Members
|
Cluster Membership |
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|
Case Number |
Cluster |
Distance |
|
1 |
2 |
2.552 |
|
2 |
2 |
3.071 |
|
3 |
2 |
2.899 |
|
4 |
2 |
3.071 |
|
5 |
2 |
2.372 |
|
6 |
2 |
2.751 |
|
7 |
2 |
2.932 |
|
8 |
2 |
2.541 |
|
9 |
2 |
3.344 |
|
10 |
2 |
2.208 |
|
11 |
2 |
2.378 |
|
12 |
2 |
3.306 |
|
13 |
2 |
2.480 |
|
14 |
2 |
2.475 |
|
15 |
2 |
3.255 |
|
16 |
2 |
2.208 |
|
17 |
2 |
2.884 |
|
18 |
2 |
2.875 |
|
19 |
2 |
2.811 |
|
20 |
2 |
2.865 |
|
21 |
1 |
1.139 |
|
22 |
1 |
1.482 |
|
23 |
1 |
1.448 |
|
24 |
1 |
1.264 |
|
25 |
1 |
1.377 |
|
26 |
1 |
1.448 |
|
27 |
1 |
1.264 |
|
28 |
1 |
1.377 |
|
29 |
1 |
1.548 |
|
30 |
1 |
1.139 |
|
31 |
1 |
1.377 |
|
32 |
1 |
1.548 |
|
33 |
1 |
1.139 |
|
34 |
1 |
1.377 |
|
35 |
1 |
1.548 |
|
36 |
1 |
1.139 |
|
37 |
1 |
1.377 |
|
38 |
1 |
1.548 |
|
39 |
1 |
1.139 |
|
40 |
1 |
1.377 |
|
41 |
2 |
3.918 |
|
42 |
2 |
4.094 |
|
43 |
2 |
3.974 |
|
44 |
2 |
3.885 |
|
45 |
2 |
3.537 |
|
46 |
2 |
4.101 |
|
47 |
2 |
3.910 |
|
48 |
2 |
3.510 |
|
49 |
2 |
4.309 |
|
50 |
2 |
3.264 |
|
51 |
2 |
4.118 |
|
52 |
2 |
3.732 |
|
53 |
2 |
3.699 |
|
54 |
2 |
4.101 |
|
55 |
2 |
3.522 |
|
56 |
2 |
3.900 |
|
57 |
2 |
3.960 |
|
58 |
2 |
3.454 |
|
59 |
2 |
4.309 |
|
60 |
2 |
3.264 |
|
61 |
2 |
4.118 |
|
62 |
2 |
3.732 |
|
63 |
2 |
3.699 |
|
64 |
2 |
4.101 |
|
65 |
2 |
3.522 |
|
66 |
2 |
5.849 |
|
67 |
2 |
5.057 |
|
68 |
2 |
6.109 |
|
69 |
2 |
4.739 |
|
70 |
2 |
6.109 |
|
71 |
2 |
5.149 |
|
72 |
2 |
5.767 |
|
73 |
2 |
5.443 |
|
74 |
2 |
5.491 |
|
75 |
2 |
5.443 |
|
76 |
2 |
5.849 |
|
77 |
2 |
5.057 |
|
78 |
2 |
6.109 |
|
79 |
2 |
4.739 |
|
80 |
2 |
6.109 |
|
81 |
2 |
1.359 |
|
82 |
2 |
1.933 |
|
83 |
2 |
1.637 |
|
84 |
2 |
1.874 |
|
85 |
2 |
1.550 |
|
86 |
2 |
2.024 |
|
87 |
2 |
1.514 |
|
88 |
2 |
2.045 |
|
89 |
2 |
1.264 |
|
90 |
2 |
1.253 |
|
91 |
2 |
1.954 |
|
92 |
2 |
1.208 |
Analysis of Cluster Membership
The cluster membership results show that all 92 respondents have been successfully classified into two distinct clusters based on similarity in their fear of failure responses.
· Cluster 1: 20 respondents
· Cluster 2: 72 respondent
The distance values indicate how close each case is to its assigned cluster center. Lower distance values represent better fit and stronger similarity with the cluster profile. Most respondents show acceptable distance values, confirming good cluster stability and reliability.
Conclusion
The study successfully examined the underlying dimensions of fear of failure among students of ITM Business School using Factor Analysis and Cluster Analysis.
The KMO value (0.830) and significant Bartlett’s Test (p < 0.001) confirmed that the data was suitable for factor analysis. The results revealed a strong two-factor structure explaining approximately 89.98% of the total variance, indicating a highly reliable and meaningful model.
The two major dimensions identified were:
1. Social & Self-Worth Fear – This dimension reflects fear of negative social judgment, disappointment of important people, and linking failure to self-worth and intelligence.
2. Performance Anxiety & Avoidance – This dimension represents procrastination, preference for familiar tasks, physical anxiety symptoms, and fear of future consequences.
Further, K-Means Cluster Analysis classified students into two distinct groups:
· Cluster 1 (20 students): High performance anxiety and avoidance behavior but lower social evaluation fear.
· Cluster 2 (72 students): High social and emotional fear with moderate performance anxiety.
Overall, the findings indicate that fear of failure among students is multidimensional and primarily driven by social–emotional concerns and performance-related anxiety. Understanding these distinct patterns can help educational institutions design targeted psychological support programs, counseling interventions, and skill-development workshops to reduce fear of failure and improve students’ academic confidence and well-being.