Impact of Real-Life Television Shows on Viewers: An Investigation for Launch of a New Real-Life TV Series

This study investigates the impact of real-life television shows on viewers and the necessity of introducing a new real-life TV series. It explores the genuineness of the television live programs, consequences of the live programs on society, and presents a conceptual model. The study also includes quantitative exploration with sample analysis and hypotheses testing.

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Impact of Real-Life Television Shows on Viewers:
An Investigation for Launch of a New Real-Life TV Series

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Table of Contents
1.0 Introduction.....................................................................................................................................3
2.0 Qualitative Exploration..........................................................................................................................3
2.1 Genuineness of the television live programs.....................................................................................3
2.2 Consequences of the live programs on the society...........................................................................4
2.3 Conceptual Model.............................................................................................................................5
3.0 Quantitative Exploration........................................................................................................................6
3.1 Sample Analysis.................................................................................................................................6
3.2 Hypotheses Testing............................................................................................................................8
A. First Hypothesis...........................................................................................................................8
B. Second Hypothesis.......................................................................................................................9
C. Third Hypothesis..........................................................................................................................9
D. Fourth Hypothesis......................................................................................................................10
E. Fifth Hypothesis.........................................................................................................................10
F. Sixth Hypothesis........................................................................................................................11
4.0 Discussion............................................................................................................................................12
5.0 Conclusion and Recommendation.......................................................................................................13
6.0 References...........................................................................................................................................14
7.0 Appendices..........................................................................................................................................15
7.1 Appendix: H1...................................................................................................................................15
7.2 Appendix: H2...................................................................................................................................17
7.3 Appendix: H3...................................................................................................................................19
7.4 Appendix: H4...................................................................................................................................20
7.5 Appendix: H5...................................................................................................................................21
7.6 Appendix: H6...................................................................................................................................23

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1.0 Introduction
Effect of excessive and tortuous television viewing has always been associated with
adverse impact on behavior and health of the viewer. Negative impact on education and
psychological attributes amplifies the need of parental guidance based program viewing for the
teenagers. Long lasting adverse effect of continuous television viewing has long been discussed
by many researchers. The current study was to facilitate the NBN Corporation with the research
on the necessity of introduction of their real-life TV show.
2.0 Qualitative Exploration
2.1 Genuineness of the television live programs
Real-life TV programs have manifested its’ advantages of providing information
attainment for viewers but parallel controversies have also been created as well. The profile of
the participants includes good looking human beings who can entertain the audiences. Hence,
specific brand of acting performance becomes inevitable for these wisely selected candidates.
Impulsive decision making, impossible looking ventures, and enthusiasm are the elements of a
fascinating real life TV program. These physiognomies keep the viewers glued to the programs,
trying to predict the sequence of the show. These real life shows entirely follow the course of
set-up activities from the commencement day. Unfortunately, the focus of the programs slowly
shifts away from the real-life and the participants concentrate on the publicity from the show
markedly for a negative reason. The entertaining significance gets replaced by filthy
psychological hindrance, and the audience sometimes gets petrified due to their involvement
with the actions in the show. This particular strategy articulates to retain the viewers of the
program and influences to stay tuned to the shows. Alacritous participation reveals unpleasant
part of the participants, where they were familiar with the dreadful reality of the programs. The
characters of these shows possibly enter in some kind of monetary agreement with the producers,
and the influence of the characters of the shows captivates the viewer’s imagination. Invade into
their private life that way, unless they are moved with some lucrative rewards. Audiences gets
affected and confused by the ugly sides of television instead of watching real life experiences,

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which in turn affects the overall perspective of life. But, if the outcome does have any
implication on an individual and only the entertainment value is appreciated, then the affect
fizzes out. Viewers want TV shows drafted with skills & techniques, where the idea is to make it
interesting and close to the real life (Allen & Mendick, 2013).
2.2 Consequences of the live programs on the society
The authenticity of the shows does not matter too much if only the entertainment value is
apprehended. The negative impact of the shows becomes the primary objective instead of
focusing on the meaningful real-life constituent. The participants reveal impression about their
acknowledgement of the negative influence factors of the real-life TV shows. The confusion
between the reality and so-called realities should not be utilized by the TV stations. The
producers should bear in mind about the social responsibility issue and should not make the
power of mass media as a cliché. Every so often the audience gets involved with the episodes of
the shows which go far beyond the entertaining value. The emotions go with the development of
the reality show and the probability of staying till the end becomes very high. It is even very
hazardous for kids who can’t differentiate between fiction and reality (An & Lee, 2010).
Eventually they get too engaged in these shows and take them seriously. Guidance and control
over the demographics of the viewers, turns out to be difficult (Swinburn & Shelly, 2009).
Therefore, mentally immature people take the shows seriously and at some point of time in life,
they experience trouble differentiating fiction from reality. These viewers get emotionally
affected at the end of the show as they probably dedicate their time completely in the programs.
Sometimes, people try to make contacts with the real life show participants, causing gross
violation against privacy of the actors. Few real-life programs such as game shows or
educational talk provide entertainment and leisure to viewers. These programs should be
encouraged instead of the usual theatrical serials, which will promote moral ideologies for the
pleasure of entertainment. The controversial shows should be treated indifferently despite their
filthiness and should not take them too seriously.

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2.3 Conceptual Model
Figure 1: Impact of Real life TV shows from multiple viewpoints
TVShowsImpactViewersPersonalityPessimisticvaluesAttitudeSensitivityTrustIssusesPerceptionArtificialParticipantsLossofprivacyPublicity

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3.0 Quantitative Exploration
3.1 Sample Analysis
The scholar was able to collect research data, in form of the responses regarding the
impact of TV shows from 300 respondents from the University campus. The one to one
interviews were conducted in a time span of three days with permission from the ethical
committee of the University. The demographic analysis revealed that there were 89 males
(29.7%) and 211 females (70.3%) in the sample of respondents. Age scrutiny discovered that
most of the participants (N = 115, 38.3%) were in the age group of 18 years to 25 years, whereas
N = 88 (29.3%) participants were in the 26 years to 35 years of age bracket. The lowest number
(N = 33, 11.0%) of participants were in the 36 years and more age group, and there were N = 64
(21.3%) teenagers among the respondents. From the answers of the respondents, the most
popular show was found out as “Survivor” with N =127 (42.3%) viewers. “Big Brother” was
second most popular show with N =103 (34.3%) viewers, followed by “Jerry Springer” with N=
70 (23.3%) audience among the sample. Popularity of the unfamiliar set-up shows was evident
with N = 198 (66.0%) viewers. The staged show comparatively had less numbers of listeners (N
= 102, 34.0%).
Figure 2: Gender distribution of the sample

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Figure 3: Age distribution of the sample
Figure 4: Popularity of the TV shows
Figure 5: Choice of show category of viewers

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3.2 Hypotheses Testing
In the current analysis six hypotheses were tested using appropriate statistical measures
and statistics. The SPSS software environment was used for the statistical evaluation and the
calculated raw data has been provided in the appendices section of the present work.
A. First Hypothesis
The nature of the data of the responses of the participants was ordinal in nature, as the
responses were collected trough a likert scale format. The two fields respectively “relate to
participants on reality TV” (SW = 0.9, P < 0.05) and “enjoy watching reality TV shows” (SW =
0.91, p < 0.05) were not normal according to Shapiro-Wilk test. However, normality check of
ordinal data was considered of no use, and hence Kruskal’s Gamma was used for inspecting the
correlation between the two variables (Döring et al., 2017). The value of the correlation
(Gamma = 0.028, p = 0.671) signified statistically insignificant correlation between the two
factors. Confirmatory test was done using Spearman’s correlation (R = 0.025, p = 0.663) and the
result was equally insignificant. From the evidences the null hypothesis failed to get rejected, and
no correlation was found between “relate to participants on reality TV” and “enjoy watching
reality TV shows”.

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B. Second Hypothesis
The gender disparity in enjoyment while watching TV shows was compared using non
parametric test (Corder & Foreman, 2014). The data for enjoyment of TV shows was ordinal in
nature, and the difference for two levels of the nominal variable, gender was evaluated using
Mann-Whitney U test. Mann- Whitney U test (Stat = 3420.00, p < 0.05) and a parallel Wilcoxon
W test (Stat = 7425.00, p < 0.05) confirmed statistically significant difference in enjoyment of
watching TV shows for the two genders. The results were confirmed using two sample
Kolmogorov- Smirnov Z test (Stat = 4.14, p < 0.05) (Drezner & Turel, 2011). Based on the test
results, it was evident that females with mean ranks (MR) of 178.79 were enjoying the TV shows
more than the men (MR = 83.43). Hence, the null hypothesis was rejected against the alternate
hypothesis at 5% level of significance.
C. Third Hypothesis
The reality show preference of respondents was a nominal variable in nature and age was
a continuous variable. Hence, to test the association, non parametric Chi-Square test was used
along with cross tabulation. The Pearson Chi-Square ( χ2=219 .57 , p<0 . 05 ) and the likelihood
ratio test (LR = 236.52, p < 0.05) confirmed statistically significant relation of age with choice
of TV shows. It was also noticed that age of 59.67% (N = 179) of the respondents were below
25 years. Therefore, based on the support results the null hypothesis was rejected at 5%
significance level. There was a statistically significant relation between age and selection of the
TV show among the respondents.

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D. Fourth Hypothesis
Both the factors of the testing were ordinal in nature; hence, non-parametric test was
opted for establishing correlation between the variables (Mayers, 2013). The correlation was
measured by Kendall’s tau-b (Value = 0.016, p = 0.744), and Kruskal’s Gamma (Value = 0.022,
p = 0.744). Spearman correlation (R = 0.019, p = 0.912) also confirmed the results of the above
correlations. A very weak positive correlation was observed between the two ordinal factors, and
statistically the correlation was not significant at 5% level of significance. Hence, based on the
results, null hypothesis failed to get rejected. There was no significant correlation between
enjoyment of the TV shows and delineation of real life in a reality TV show.
E. Fifth Hypothesis
Testing of the above hypothesis at 5% level of significance was done using non-
parametric Wilcoxon Signed Ranks test for the two ordinal factors. Three test conditions were
evaluated for average ranks. The mean negative ranks between “Depicting real life behaviors on
reality TV” and “Having attractive participants on reality TV is important” was 89.45 (N = 92),
whereas the mean for positive ranks was 132.87 (N = 138). The Wilcox Signed Rank test
statistics (Z = -5.106, p < 0.05) established the alternate hypothesis. The null hypothesis was
rejected at 5% level of significance, and a statistically significant difference was observed
between the variables.

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F. Sixth Hypothesis
The testing of hypothesis was conducted keeping the ordinal nature of both the factors in
mind. Non-parametric test was utilized for hypothesis testing at 5% level of significance.
Kruskal- Wallis test revealed that mean rank for under 18 respondents was 230.48 (N = 64),
between 18 years to 25 years was 196.52 (N = 115), between 26 years to 35 years was 69.53 (N
= 88) and for 36 years and above was 50.94 (N = 33). The test statistic ( χ2=215 .91 , P<0 . 05 )
was statistically significant to reject the null hypothesis. A confirmatory Median test (
χ2=180 . 45 , P<0 . 05 ) supported the test results of Kruskal- Wallis test (McKight & Najab,
2010). Hence, the null alternate hypothesis was accepted, and significant difference was
established between having attractive participant between different age groups.
Figure 6: Age group wise attractiveness in reality TV shows

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4.0 Discussion
The qualitative and quantitative data analysis was in line with each other. The qualitative
analysis revealed that the respondents were disturbed about the genuineness of the content of the
shows. The “attitude” towards the “authenticity” of the reality shows was addressed based on the
transcript description of the respondents. The consequences of the real life TV programs were
addressed in the second half of the qualitative analysis, where the respondents’ views on
negative impact of the shows on the society, especially on the children got reflected. The general
awareness about the ways and programs of entertainment in television was eminent from the
discussion in the transcript.
The quantitative analysis sustained the outcome of the qualitative scrutiny. Hypothesis
wise elaboration revealed that, significant relation was missing between enjoyments of TV
viewing and relating participants of the TV shows (H1). Significant gender difference was
observed in enjoyment from TV programs (H2), whereas, no relation was found between
delineation of real life in a reality show and enjoyment of the TV programs (H4). The
noteworthy relation between age groups and reality TV show preference (H3) critically
acclaimed the transcript discussions of the respondents. Age group was an important factor in
importance of attractive participant (H6), and relation of importance of attractive participant with
enjoyment of reality TV shows (H5) was equally important (Lundy, Ruth & Park, 2008).

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5.0 Conclusion and Recommendation
The major difference in the two mode of analysis got reflected in attitude analysis of the
respondents towards the authenticity of the shows. Quantitative analysis revealed that a certain
percentage of participants were interested in the entertainment from the TV shows, while the
qualitative mode suggested such measures only. On the contrary to the qualitative analysis,
respondents did not exhibited association between attractive participation and portrayal of real
behavior neither relation between enjoyment from the shows and depiction of real life
surrounded by the theme of the TV show was established. The negative influence of the shows
was nonetheless supported by the quantitative investigation in the first and the fourth hypotheses.
The NBN Company was advised to sponsor a real-life program with educational or health
oriented values (Heinonen, 2011). The authenticity of the aired real-life TV shows were in
question, although, effect of those shows was not significantly enough to affect the outlook about
the TV shows. People were still enjoying purely for the purpose of entertainment. But, concern
of the negative impact, especially on adolescence of the teenagers was imperative from the study.

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6.0 References
Allen, K., & Mendick, H. (2013). Keeping it real? Social class, young people and
‘authenticity’in reality TV. Sociology, 47(3), 460-476.
An, S. K., & Lee, D. (2010). An integrated model of parental mediation: the effect of family
communication on children's perception of television reality and negative viewing
effects. Asian Journal of Communication, 20(4), 389-403.
Corder, G. W., & Foreman, D. I. (2014). Nonparametric statistics: A step-by-step approach.
John Wiley & Sons.
Döring, D., Haberland, B. E., Bauer, A., Dobenecker, B., Hack, R., Schmidt, J., & Erhard, M. H.
(2017). Consistency in behavior: Evaluation of behavior tests in laboratory
beagles. Journal of Veterinary Behavior: Clinical Applications and Research, 21, 59-63.
Drezner, Z., & Turel, O. (2011). Normalizing variables with too-frequent values using a
Kolmogorov–Smirnov test: A practical approach. Computers & Industrial
Engineering, 61(4), 1240-1244.
Heinonen, K. (2011). Consumer activity in social media: Managerial approaches to consumers'
social media behavior. Journal of Consumer Behaviour, 10(6), 356-364.
Lundy, L. K., Ruth, A. M., & Park, T. D. (2008). Simply irresistible: Reality TV consumption
patterns. Communication Quarterly, 56(2), 208-225.
Mayers, A. (2013). Introduction to Statistics and SPSS in Psychology. Pearson Higher Ed.
McKight, P. E., & Najab, J. (2010). Kruskal‐Wallis Test. The corsini encyclopedia of
psychology, 1-1.
Swinburn, B., & Shelly, A. (2009). Effects of TV time and other sedentary
pursuits. International journal of obesity, 32(S7), S132.

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7.0 Appendices
7.1 Appendix: H1
Case Processing Summary
Cases
Valid Missing Total
N Percent N Percent N Percent
I relate to participants on
Reality TV shows 300 100.0% 0 0.0% 300 100.0%
I enjoy watching Reality TV
shows 300 100.0% 0 0.0% 300 100.0%
Tests of Normality
Kolmogorov-Smirnova Shapiro-Wilk
Statistic df Sig. Statistic df Sig.
I relate to participants on
Reality TV shows .211 300 .000 .900 300 .000
I enjoy watching Reality TV
shows .161 300 .000 .906 300 .000
a. Lilliefors Significance Correction

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Crosstabs H1
Case Processing Summary
Cases
Valid Missing Total
N Percent N Percent N Percent
I relate to participants on
Reality TV shows * I enjoy
watching Reality TV shows
300 100.0% 0 0.0% 300 100.0%
Symmetric Measures
Value Asymp. Std.
Errora
Approx. Tb Approx. Sig.
Ordinal by Ordinal
Gamma .028 .065 .425 .671
Spearman Correlation .025 .059 .436 .663c
Interval by Interval Pearson's R .021 .060 .357 .721c
N of Valid Cases 300
a. Not assuming the null hypothesis.
b. Using the asymptotic standard error assuming the null hypothesis.
c. Based on normal approximation.

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7.2 Appendix: H2
Mann-Whitney Test
Ranks
Are you Male or Female? N Mean Rank Sum of Ranks
I enjoy watching Reality TV
shows
Male 89 83.43 7425.00
Female 211 178.79 37725.00
Total 300
Test Statisticsa
I enjoy watching
Reality TV
shows
Mann-Whitney U 3420.000
Wilcoxon W 7425.000
Z -8.934
Asymp. Sig. (2-tailed) .000
a. Grouping Variable: Are you Male or
Female?

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Two-Sample Kolmogorov-Smirnov Test
Frequencies
Are you Male or Female? N
I enjoy watching Reality TV
shows
Male 89
Female 211
Total 300
Test Statisticsa
I enjoy watching
Reality TV
shows
Most Extreme Differences
Absolute .524
Positive .000
Negative -.524
Kolmogorov-Smirnov Z 4.144
Asymp. Sig. (2-tailed) .000
a. Grouping Variable: Are you Male or Female?

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7.3 Appendix: H3
Crosstabs H3
Case Processing Summary
Cases
Valid Missing Total
N Percent N Percent N Percent
What is your age? * Which
Reality TV show do you
prefer?
300 100.0% 0 0.0% 300 100.0%
Chi-Square Tests
Value df Asymp. Sig. (2-
sided)
Pearson Chi-Square 219.573a 6 .000
Likelihood Ratio 236.523 6 .000
Linear-by-Linear Association 164.818 1 .000
N of Valid Cases 300
a. 0 cells (.0%) have expected count less than 5. The minimum expected
count is 7.70.

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7.4 Appendix: H4
Crosstabs H4
Case Processing Summary
Cases
Valid Missing Total
N Percent N Percent N Percent
I enjoy watching Reality TV
shows * Depicting real life
behaviors on Reality TV is
important
300 100.0% 0 0.0% 300 100.0%
Symmetric Measures
Value Asymp. Std.
Errora
Approx. Tb Approx. Sig.
Ordinal by Ordinal
Kendall's tau-b .016 .050 .327 .744
Gamma .022 .068 .327 .744
Spearman Correlation .019 .060 .334 .739c
Interval by Interval Pearson's R .006 .062 .111 .912c
N of Valid Cases 300
a. Not assuming the null hypothesis.
b. Using the asymptotic standard error assuming the null hypothesis.
c. Based on normal approximation.

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7.5 Appendix: H5
Wilcoxon Signed Ranks Test
Ranks
N Mean Rank Sum of Ranks
Depicting real life behaviors
on Reality TV is important -
Having attractive participants
on Reality TV is important
Negative Ranks 92a 89.45 8229.50
Positive Ranks 138b 132.87 18335.50
Ties 70c
Total 300
a. Depicting real life behaviors on Reality TV is important < Having attractive participants on
Reality TV is important
b. Depicting real life behaviors on Reality TV is important > Having attractive participants on
Reality TV is important
c. Depicting real life behaviors on Reality TV is important = Having attractive participants on
Reality TV is important
Test Statisticsa
Depicting real life
behaviors on
Reality TV is
important -
Having attractive
participants on
Reality TV is
important
Z -5.106b
Asymp. Sig. (2-tailed) .000
a. Wilcoxon Signed Ranks Test
b. Based on negative ranks.

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Sign Test
Frequencies
N
Depicting real life behaviors
on Reality TV is important -
Having attractive participants
on Reality TV is important
Negative Differencesa 92
Positive Differencesb 138
Tiesc 70
Total 300
a. Depicting real life behaviors on Reality TV is important < Having
attractive participants on Reality TV is important
b. Depicting real life behaviors on Reality TV is important > Having
attractive participants on Reality TV is important
c. Depicting real life behaviors on Reality TV is important = Having
attractive participants on Reality TV is important
Test Statisticsa
Depicting real life
behaviors on
Reality TV is
important -
Having attractive
participants on
Reality TV is
important
Z -2.967
Asymp. Sig. (2-tailed) .003
a. Sign Test

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7.6 Appendix: H6
Kruskal-Wallis Test
Ranks
What is your age? N Mean Rank
Having attractive participants
on Reality TV is important
Under 18 64 230.48
18-25 115 196.52
26-35 88 69.53
36+ 33 50.94
Total 300
Test Statisticsa,b
Having attractive
participants on
Reality TV is
important
Chi-Square 215.913
df 3
Asymp. Sig. .000
a. Kruskal Wallis Test
b. Grouping Variable: What is
your age?

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Median Test
Frequencies
What is your age?
Under 18 18-25 26-35 36+
Having attractive participants
on Reality TV is important
> Median 63 65 0 0
<= Median 1 50 88 33
Test Statisticsa
Having attractive
participants on
Reality TV is
important
N 300
Median 3.0000
Chi-Square 180.447b
df 3
Asymp. Sig. .000
a. Grouping Variable: What is
your age?
b. 0 cells (.0%) have expected
frequencies less than 5. The
minimum expected cell frequency
is 14.1.