2. Study the effect of introduction
of entertainment (iv) on the
infusion rate (dv) of mobile
healthcare apps especially in
the youngsters(mv) of metro
cities in India.
And allied research on relevant topics
3. The current scenario
• As the above figure shows that by 2013 itself
India had 12 million smartphone users.
• Over 94% of Indian smart phone users access
the internet on their mobile
• But shockingly only 29% of the total
Apps downloaded by adults are health
App which is lowest of all.
This project aims to investigate effectiveness of introduction
Of entertainment to increase the infusion rate of mobile health
care services.
The project will also try to study the perception of Indian
population towards these services
4. Topic description
• Background
• Statement of problem
• Objectives
• Research question
• Research Method
– Approach
– Timeframe
• Questionnaire, Sample size
• Analysis
• Conclusion
5. Background
A health app is categorized by the FDA as mobile software
that diagnoses, tracks or treats disease.
A wellness app is mobile software that enhances or tracks
the overall health of the user.
A recent count of the iTunes app store identified nearly
20,000 health care and wellness apps.
Nearly 70 % of the web-surfing population of rest of the
world have looked up a health topic in the last year.
However the surprisingly Indian population lacks behind in
this as the survey shows only 29% of Indian
smart phone users download health related app.
Though no substantial reasons are found out
As to why the infusion rate India is so low.
6. The Problem
? What is the effect of introduction of
entertainment (iv) on the infusion
rate(dv) of mobile healthcare apps
especially in the youngsters(mv).
? What is the perception of urban and
rural population of India in adopting
the mobile health care services
8. Research Method- timeframe
Research Project
Develop Research hypothesis
and obtain approval
Develop and test questions
Obtain participants
Final collection of data
Research Presentation and Paper
October November December January
9. Project objectives Questionnaire, Sample size
Research Objective:
1) To establish a dependency of entertainment in a mobile
application and its success in the app market.
2) Figure out which markets ( android or apple iTunes) do
Indian youngsters use to download health care apps.
3) Privacy concerns have a big impact on infusion rate of
healthcare mobile apps among Indian youngsters.
4) Figure out relationship between gender and infusion
rate of a mobile health care service.
10. Questionnaire and Sample size
1. After a small study the group decided to opt sample
size as 50.
2. As it was a mobile app service research the group
came to a conclusion that questionnaire needed to be
made available online as it will target the desired
sample population.
Screening questions were added to get the accurate data
To be analyzed.
The sample was targeted from almost all the
metro-cities which gives the research paper
more creditability.
13. As the p (pearsons
chi-square value
0.487 is > than α 0.05
hence accept the
hypothesis.
14.
15.
16. As the p (persons chi-square value
0.153 is > than α 0.05 hence accept
the hypothesis.
17. As the p (persons chi-square value
0.314 is > than α 0.05 hence
accept the hypothesis.
18.
19. µ1 Mobile apps with entertainment in it
µ2 Mobile health apps without entertainment in it
Ho µ1=µ2
H1 µ1>µ2
Entertainment factor in a mobile
app increases is its infusion rate
20. How often you fall ill in a year
Analysis: 76.5% of people fall ill occasionally than 11.8% of the
people who said they fall ill often or not at all.
21.
22. Preference given by gender to the
treatment provided by mobile health
application than doctor treatment
Analysis:
prefernce_over_mobile_healthservices_rather_than_visiting_hospit
gender Frequency Percent Valid Percent
Cumulative
Percent
male Valid agree 2 14.3 14.3 14.3
netural 3 21.4 21.4 35.7
disagree 3 21.4 21.4 57.1
strongly disagree 6 42.9 42.9 100.0
Total 14 100.0 100.0
female Valid strongly agree 2 33.3 33.3 33.3
agree
2 33.3 33.3 66.7
66.7
netural
1 16.7 16.7 83.3
83.3
disagree
1 16.7 16.7 100.0
100.0
Total
6 100.0 100.0
23. Analysis: 42.9% of the men give less preference to the mobile health
care apps than the 33.3% of the women who give more preference to
the Mobile Health care apps
24. Gender give more importance to which health
aspect for the treatment
from mobile Health apps
25. Analysis: 50% of both male and female give more
importance to general health fitness and believes in
treatment to be provided by the Mobile Health care Apps.
26. There is a significant difference between
gender and No. of people who use Health
Care Mobile Apps
27. Value df
Asymp.
Sig. (2-
sided)
Exact
Sig. (2-
sided)
Exact
Sig. (1-
sided)
Pearson Chi-
Square .010(b) 1 .919
Continuity
Correction(a) .000 1 1.000
Likelihood Ratio .011 1 .918
Fisher's Exact
Test 1.000 .664
Linear-by-Linear
Association .010 1 .921
N of Valid Cases 20
Chi-Square Tests
Analysis: p value (91%) > alpha value (5%) that means Null
hypothesis is accepted.
Therefore, there is no significant difference between gender
and no. of people who use Mobile Health Care Apps.
28. Whether the perception of the people
differ based on gender
gender N Mean Std. Deviation
Std. Error
Mean
prefernce_over_mobile_healthser
vices_rather_than_visiting_hospit
male
14 3.9286 1.14114 .30498
female
6 2.1667 1.16905 .47726
Levene's Test
for Equality of
Variances t-test for Equality of Means
F Sig. t df
Sig. (2-
tailed)
Mean
Differen
ce
Std.
Error
Differen
ce
95% Confidence
Interval of the
Difference
Lower Upper
prefernce_over_m
obile_healthservic
es_rather_than_vi
siting_hospit
Equal
variances
assumed
.043 .839 3.143 18 .006 1.76190 .56063 .58406
2.9397
5
Equal
variances
not
assumed
3.111 9.320 .012 1.76190 .56638 .48732
3.0364
9
29. Analysis: Based on the Independent T test analysis :
p value(0.006)< alpha value(.05) that means null hypothesis
is rejected . Therefore, there is significant difference
between the two.
30. 1.The responses got is from limited metro
cities of India.
2.Respondents willingness to share
confidential or private data.
3.Less time span of the survey
