business rescearch
TRANSCRIPT
Mahesh Manikonda Sweety Agrawal,
Namrata Sharma Dinesh Bhujari, Milind Shevde Ameet Phadnis
Rohit Jha
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
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 introductionOf 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
Topic description• Background• Statement of problem• Objectives• Research question• Research Method
– Approach – Timeframe
• Questionnaire, Sample size• Analysis• Conclusion
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.
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
Research Method
Deductive Approach testing theory through observation and data
Exploratory StudyPurposive, self-selection sampling
Research Method- timeframeResearch 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
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.
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 dataTo be analyzed.The sample was targeted from almost all the metro-cities which gives the research papermore creditability.
Used descriptivestats
As the p (pearsons chi-square value 0.487 is > than α 0.05 hence accept the hypothesis.
As the p (persons chi-square value 0.153 is > than α 0.05 hence accept the hypothesis.
As the p (persons chi-square value 0.314 is > than α 0.05 hence accept the hypothesis.
µ1 Mobile apps with entertainment in itµ2 Mobile health apps without entertainment in it
Ho µ1=µ2H1 µ1>µ2
Entertainment factor in a mobile app increases is its infusion rate
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.
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 PercentCumulative
Percentmale 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
agree2 33.3 33.3 66.7
66.7
netural1 16.7 16.7 83.3
83.3
disagree1 16.7 16.7 100.0
100.0
Total6 100.0 100.0
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
Gender give more importance to which health aspect for the treatment from mobile Health apps
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.
There is a significant difference between gender and No. of people who use Health
Care Mobile Apps
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.
Whether the perception of the people differ based on gender
gender N Mean Std. DeviationStd. Error
Meanprefernce_over_mobile_healthservices_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 dfSig. (2-tailed)
Mean Differen
ce
Std. Error
Difference
95% Confidence Interval of the
Difference
Lower Upperprefernce_over_mobile_healthservices_rather_than_visiting_hospit
Equal variances assumed
.043 .839 3.143 18 .006 1.76190 .56063 .584062.9397
5
Equal variances not assumed
3.111 9.320 .012 1.76190 .56638 .487323.0364
9
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.
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