Impact of Age on Online Healthcare Information Search: A Study on Indian Patients

Ms. Jaya Rani¹*, Dr. Ajeya Jha²

Assistant Professor, Sikkim Manipal Institute of Technology, India

Head of Department, Department of Management Studies, Sikkim Manipal Institute of Technology, India

*Corresponding Author E-mail: jayaranim@rediffmail.com; ajeya611@yahoo.co.in

ABSTRACT:

Availability of healthcare information on internet has made it possible for patients or their relatives to search for such information. Considering the delicate nature of such an information as well as its great need felt by the society it is important to know who are these people who actively search for online healthcare information and also those who are unable to do so. This study was undertaken to find answers to one such question – impact of the age factor. The objective of the study is to measure the differences in perception of patients in three exclusive age-groups regarding the impact, merits and demerits of DTC promotion through online-health related websites. In all 754 respondents participated in the survey of which 440 patients were not sufficiently conversant with internet technology and hence were screened out in the first phase. The final survey sample, therefore comprised of 314 patients. One-way ANOVA has been used to measure the difference in perception across three age-groups. The result shows that age is a critical determinant in shaping perceptions of patients regarding the impact, merits and demerits of DTC promotion through online-health related websites. out of 43 select variables the age-based differences are significant in 39 cases; appreciably high in 3 cases and substantially high in 19 cases.

KEY WORDS: Age, Direct to consumer, Healthcare, Indian Patient.

I. INTRODUCTION:

Internet is today the foremost source of uninterrupted and instant information search (Cotten and Gupta, 2004). It is economical and is available widely across the world. In India also, a large majority of people use net regularly and they also search health related information available online.

As in the developed countries the developing countries people too are searching out their health-care related queries by consulting doctors. In recent years Indians have also developed greater awareness for their healthcare. But this is not true all the time. Due to the emergence of internet the health information seeking behavior of the patients has totally altered. Regular online search is becoming common and accepted. Since it is effortless to use, hence very frequently people visit online and search information related to health issues. People search different health related information such as prescription drugs, alternative medicines, nutrition, exercise, medical conditions, current health topics, illegal drugs etc (Baker, Wagner, Singer, and et al., 2003; Escoffery et al., 2005; Fox, 2006; Taha, Sharit, and Czaja, 2009).

Technically direct to consumer promotion is legal in only two of the nations: U.A.S. and New Zealand. There also there are strong voices of protests against such a policy. The Drugs and Magic Remedies (Objectionable Advertisements) Act, 1954 prohibits any kind of promotion of prescription drugs in India.

There is a demand for health related information and due to this Pharmaceutical companies are providing it through health websites. This direct promotional effort of the pharmaceutical companies, for the promotion of pharmaceutical products is known as DTC or direct to consumer marketing. Not only this, health related websites have improved the interactive communication on health related issues. In fact it gives both customers and healthcare professionals to have interactive health information approach. This study has been conducted to understand the impact of age on online health information seeking behavior of Indian patients and their relatives.

From the literature survey we find that most such studies have been under taken in developed region of the world - USA, Europe, UK, Canada and Australia. Other regions of the world have remained untouched in this respect. Also potentially negative impact of DTC on patient behaviour such as ignoring symptoms in favour of brand awareness, developing difficult relationship with physicians, insisting on a particular brand of medicine, prescribing medicines to others, requesting prescription for advertised medicines, seeking use of expensive and unnecessary medicines and failing to understand risk related information on internet has not been studied in a focused manner. It is expected that behavior of patients due to DTC promotion will be different from their counter parts in developed region of the world. In view of this the study was undertaken.

II. SCOPE OF STUDY:

a) The study is applicable in Pharmaceutical industry only.

b) The study is limited to India only.

c) Only the patients taking recourse in allopathy have been surveyed.

d) Only differences in perception of the three age groups have been focused upon

e) Only web-based internet promotion has been studied. Others such as blogs, banner ads, social media driven promotion and mobile based promotion are not a part of this study.

III. METHODOLOGY:

a) Nature of research: The present research is exploratory and empirical in nature with descriptive statistics based on the data on the belief expressed by patients on impact, merits and de-merits of direct-to-consumer promotion of diseases and drugs.

b) Research design: The research-design for the research work is conclusive. To arrive at conclusions descriptive approach has been used

c) Objectives of the study: The objective of the study is to measure the differences in perception of patients in three exclusive age-groups regarding the impact, merits and demerits of DTC promotion through online-health related websites.

d) Hypothesis: Keeping the above objectives in view the following hypothetic framework was proposed:

Ho: No significant differences exist in the perception of patients in different age-groups vis-à-vis impact, merits and demerits of DTC promotion through online-health related websites.

Various indicators for the hypothesis were developed based on an exploratory study whereby patients in different age-groups were interviewed for their opinion on DTC trends. As, apart from its impact, both negative and positive impacts emerged from this exploratory study they were further asked to provide specific reasons for considering it positive or negative. These indicators were included in the present study.

e) Sample: The sample respondents of this research consist of patients taking recourse to allopathy. In all 800 patients were approached for the screen survey. Responses submitted by 44 patients were found to be invalid and hence final sample size comprises of 754 patients. Out of these 440 patients were not sufficiently conversant with internet technology and hence were screened out in the first phase. The final survey sample, therefore comprised of 314 patients. The age and gender matrix of the sample has been given in Table:1.

Table-1: Age-gender matrix of respondents

Count		Gender		Total
		Male	Female	Total
Age	18-30	41	47	88
	31-50	85	48	133
	51 and above	40	53	93

f) Sampling method: Judgment sampling methods were used for the research. List of Patients were also screened on their familiarity and use of with internet and health-based web-sites. Only those patients who declared that they visit health-related web-sites regularly were included in the final survey.

h) Tools: : The tool is developed using Likert scale in a range of 1 to 5 with 1, 2, 3, 4 and 5 corresponding to Strongly Disagree, Disagree, Neither agree Nor Disagree, Agree and Strongly Agree respectively. As stated earlier the statements were developed based on an exploratory study conducted by interviewing patients/their relatives. The respondents were contacted personally by the researcher and after general introduction the tool was handed over to them. The confidentiality of the information obtained from the respondents was assured. The filled questionnaires were collected the same day and on a few occasions after few days. In all respondents were required to respond to 43 statements.

i) Reliability Analysis: Reliability analysis was made by determining the Cronbach's Alpha. As shown in table-2 it was found to be 0.981 which statistically is considered an excellent reliability.

Table-2: Reliability Analysis

Cronbach's Alpha	Cronbach's Alpha Based on Standardized Items	No. of Items
0.979	0.981	43

j) Data Analysis: All analyses were conducted using Statistical Software (SPSS) 16.0 version. The test statistics was checked and found to follow normal distribution (Skewness and kurtosis were within 1 in most cases and within 2 in all cases). For the hypothesis testing the confidence limit is set at 95%. ANOVA was used to determine the significance of variations in the beliefs held by male and female patients. At 95% confidence limit for F-value is more than the tabulated value and corresponding significance (Sign.) less than 0.05.

IV. RESULT AND DISCUSSION:

The results have been provided in the table and the discussion on the same follows.

Sr. No.	Statement	18-30		31-50		51 and more
Sr. No.	Statement	Mean	SD	Mean	SD	Mean	SD	f-Value	Signif.
1	I often seek information from my friends, relatives and internet	4.02	0.83	4.07	0.771	4.08	0.769	0.121	0.886
2	I trust the information that I get through internet	3.99	0.823	4.09	0.743	4	0.766	0.593	0.553
3	The information given on internet is more understandable than the technical language used by the doctor.	4.02	0.83	4.17	0.709	4.34	0.667	4.38	0.013
4	Information on internet is often incomplete.	4.01	0.823	3.56	0.933	4.04	0.765	10.05	0
5	I feel empowered due to information I have collected on internet.	2.84	0.43	3.33	0.935	4.44	0.634	90.2	0
6	My friends have guided me to internet for health related information	2.81	0.843	3.36	0.941	4.38	0.623	91.1	0
7	Internet information helps in following the instructions of the doctor.	4.07	0.823	4.11	0.743	4.27	0.709	3.22	0.041
8	Internet information helps in developing better coordination with doctor	3.68	0.796	3.92	0.794	4.39	0.67	17.82	0
9	Internet information helps in better diagnosis	3.24	0.91	3.17	0.836	3.85	0.807	19.66	0
10	I am more aware regarding the side effects of the drugs.	3.85	0.865	4.13	0.745	4.31	0.706	6.61	0.002
11	Internet information has helped in taking a proactive step.	3.47	0.742	4.04	0.772	4.48	0.634	41.7	0
12	I am healthier due to information I read on internet	3.97	0.831`	4.01	0.776	4.08	0.764	0.568	0.567
13	I feel helpless without the right information available on internet	3.92	0.82	4.02	0.783	4.03	0.773	0.575	0.563
14	Internet has replaced family physician	2.57	0.868	3.1	0.716	2.03	0.633	57.24	0
15	Physicians must assist patients in evaluating health related information obtained through internet.	4.25	0.762	4.17	0.709	4.53	0.601	7.68	0.001
16	Information on internet is often biased .	3.28	0.802	3.41	0.889	3.72	0.826	6.49	0.002
17	Information on internet is often wrong.	2.59	0.814	2.81	0.719	3.68	0.819	57.15	0
18	I serf net at least three times a week.	2.53	0.823	3.45	0.889	3.83	0.789	53	0
19	I surf net at least ten hours a week.	2.61	0.83	3.48	0.93	3.88	0.816	52.2	0
20	If I or anyone fall sick in family I collect information on internet	4	0.743	4.05	0.767	4.27	0.709	3.55	0.03
21	Information provided on internet is highly educative	3.24	1.114	3.19	0.986	3.84	0.888	13.17	0
22	I am able to understand a disease state better with internet information	3.19	0.91	3.13	0.836	3.88	0.807	19.66	0
23	At times I am able to Diagnose a disease state correctly because of online information	3.3	1.075	3.27	0.973	3.98	0.862	13.28	0
24	Internet information helps me in identifying right medicine	2.49	0.994	2.72	1.322	4.27	0.709	76.64	0
25	Internet information Helps me in modifying diet	3.01	0.735	4.08	0.765	4.42	0.714	96.42	0
26	Health related information on internet helps me in identifying non drug related therapy	2.55	0.815	3.44	0.924	4.24	0.728	91.71	0
27	I am able to communicate better with the physician because of the information i have read on internet	3.18	1.056	4.12	0.785	4.01	0.699	33.9	0
28	I understand the instructions of the physicians better if I have gone through the online information.	3.32	1.078	4.07	0.809	3.97	0.731	30.09	0
29	At times I come across sites having wrong information	2.81	0.741	3.38	0.877	3.99	0.78	50.71	0
30	At times I come across heath related Sites having biased information	2.84	0.815	3.43	0.899	4.04	0.806	45.37	0
31	I can distinguish between good and bad health related websites on internet.	3.94	8.35	3.72	8.56	2.87	1.279	30.46	0
32	I share website detail with my friend when they need it	3.16	1.027	3.14	1.053	3.68	1.075	8.25	0
33	I take medicines properly because of my knowledge based on internet information.	3.06	1.143	3.19	1.074	3.76	1.046	8.72	0
34	I follow dietary instructions better because of internet information	3.25	0.974	3.14	1.038	3.69	1.063	7.1	0.001
35	My awareness of side effects and adverse effects of a drug is enhanced because of internet information	3.21	1.06	3.18	1.065	3.63	1.1	6.36	0.002
36	I find information on internet confusing.	2.55	0.815	3.26	0.843	4.04	0.707	75.33	0
37	Information on internet is often biased	2.49	0.84	3.17	0.858	4.2	0.7	99.45	0
38	For any mishappening because of wrong information on internet website owner should be taken to court.	4.02	0.83	4.17	0.709	4.34	0.667	4.37	0.013
39	In case there is a contradiction between what the physician tells me and internet information I trust the physician	4.09	0.928	4.11	0.799	4.22	0.744	2.71	0.087
40	Internet is primary source of health related information.	3.92	0.847	4.03	0.791	4.31	0.713	4.73	0.009
41	I live a healthier life because of internet	3.7	1.233	4.16	0.756	4.39	0.731	13.82	0
42	I find health related information on internet very assuring	3.27	1.003	3.88	0.835	3.28	0.632	33.4	0
43	Internet is useful for collecting information on embarrassing Health state	3.23	0.968	3.79	0.821	4.23	0.61	31.64	0

1. I often seek information from my friends, relatives and internet: From the table we find that the mean value for 3 age-groups namely 18-30, 31 to 50 and above 50 are 4.02, 4.07 and 4.08 respectively. It therefore appears that not much difference exists in the beliefs held by these three age-groups. This is further confirmed by F-value, which is 0.121, much below the tabulated value and the corresponding significance value which is 0.886 much above the required value 0.05.

2. I trust the information that I get through internet: The table reveals that the mean value of the responded of age group 18-30 is 3.99, of age group 31 -50 is 4.09 and age group above 50 is 4. This can be interpreted that people of all age group may have same opinion. This may further be confirmed by F- value which is 0.593 much below the tabulated value. So we accept the null hypothesis and reject the alternative. The level of significance is 0.553 higher than 0.05.

3. The information given on internet is more understandable than the technical language used by the doctor: From the table we find that the mean value of the responses of all age group reveals similarity in belief, The mean value of age group 18-39 is 4.02, age group 31-50 is 4.17 and above 50 is 4.34. The F –value is 4.38 which is more than the tabulated value .So according to decision rule we reject the null hypothesis and accept the alternative hypothesis. It is further confirmed by level of significance which is 0.013 less than 0.05.

4. Information on internet is often incomplete: In the table we can see that the mean value for 3 age-groups namely 18-30, 31 to 50 and above 50 are 4.01, 3.56 and 4.04 respectively. Therefore we can say that in the age group 31-50. The F value is 10.05 much more than tabulated value so the null hypothesis is rejected. It is further confirmed by significant value which is 0.00 less than 0.05.

5. I feel empowered due to information I have collected on internet: The table reveals that the mean value of the responded of age group 18-30 is 2.84, of age group 31 -50 is 3.33 and age group above 50 is 4.44. This can be interpreted that people of all age group have general disagreement on belief. This may further be confirmed by F- value which is 90.2 much higher than the tabulated value. So we reject the null hypothesis and accept the alternative. The level of significance is 0.00 less than 0.05.

6. My friends have guided me to internet for health related information: : From the table we find that the mean value for 3 age-groups namely 18-30, 31 to 50 and above 50 are 2.81, 3.36 and 4.38 respectively. It therefore appears that not much difference exists in the beliefs held by these three age-groups. This is further confirmed by F-value, which is 91.1, much higher than the tabulated value and the corresponding significance value is 0.00 less than the required value 0.05.So we reject the null hypothesis and accept the alternative one.

7. Internet information helps in following the instructions of the doctor: From the table we can see that the mean value of the responses of all age group reveals similarity in belief, The mean value of age group 18-39 is 4.07, age group 31-50 is 4.11 and above 50 is 4.27. The F –value is 3.22, which is more than the tabulated value .So according to decision rule we reject the null hypothesis and accept the alternative hypothesis. It is further confirmed by level of significance which is 0.013 less than 0.05.

8. Internet information helps in developing better coordination with doctor: From the table we find that the mean value of the responses of all age group reveals similarity in belief of age group 18-39 and age group 31-50. The mean value of age group 18-39 is 3.68, age group 31-50 is 3.92 and above 50 is 4.39. The F –value is 17.82, much higher than tabulated value .So according to decision rule we reject the null hypothesis and accept the alternative hypothesis. It is further confirmed by level of significance which is 0.00 less than 0.05.

9. Internet information helps in better diagnosis: The table reveals that the mean value of the responded of age group 18-30 is 3.24, of age group 31 -50 is 3.17 and age group above 50 is 3.85. This can be interpreted that people of all age group have general agreement on the belief.. This may further be confirmed by F- value which is 19.66 muchhigher than the tabulated value. So we reject the null hypothesis and accept the alternative. The level of significance is 0 less than 0.05.

10. I am more aware regarding the side effects of the drugs : The table reveals that the mean value of the responded of age group 18-30 is3.85, of age group 31 -50 is 4.13 and age group above 50 is 4.31. This can be interpreted that people of all age group have general agreement on belief. This may further be confirmed by F- value which is 6.61 higher than the tabulated value. So we reject the null hypothesis and accept the alternative. The level of significance is 0.002 less than 0.05.

11. I am more aware regarding the side effects of the drugs: From the table we find that the mean value of the responses of all age group reveals general agreement in belief. The mean value of age group 18-39 is 3.85, age group 31-50 is 4.13 and above 50 is 4.31. The F –value is 6.61, much higher than tabulated value .So according to decision rule we reject the null hypothesis and accept the alternative hypothesis. It is further confirmed by level of significance which is 0.002 less than 0.05.

12. Internet information has helped in taking a proactive step: From the table we find that the mean value for 3 age-groups namely 18-30, 31 to 50 and above 50 are 3.47, 4.04 and 4.48respectively. It therefore appears that not much difference exists in the beliefs held bythese three age-groups. This is further confirmed by F-value, which is 41.7, much higher than the tabulated value and the corresponding significance value is 0.00 less than the required value 0.05.So we reject the null hypothesis and accept the alternative one.

13. I am healthier due to information I read on internet:

The table reveals that the mean value of the responded of age group 18-30 is 3.97 of age group 31 -50 is 4.01 and age group above 50 is 4.08. This can be interpreted that people of all age group may have similar kind of belief. This may further be confirmed by F- value which is 0.568 much below the tabulated value. So we accept the null hypothesis and reject the alternative. The level of significance is 0.567 higher than 0.05.

14. Internet has replaced family physician: From the table we find that the mean value of the responses of all age group reveals general disagreement in belief. The mean value of age group 18-39 is 2.57, age group 31-50 is 3.1and above 50 is 2.03. The F –value is 57.24, much higher than tabulated value .So according to decision rule we reject the null hypothesis and accept the alternative hypothesis. It is further confirmed by level of significance which is 0.0 less than 0.05.

15. Physicians must assist patients in evaluating health related information obtained through internet:

The table reveals that the mean value of the responded of age group 18-30 is 4.25, of age group 31 -50 is 4.17 and age group above 50 is 4.53. This can be interpreted that people of all age group have general agreement on belief. This may further be confirmed by F- value which is 7.68 higher than the tabulated value. So we reject the null hypothesis and accept the alternative. The level of significance is 0.001 less than 0.05.

16. Information on internet is often biased : : From the table we find that the mean value for 3 age-groups namely 18-30, 31 to 50 and above 50 are 3.28, 3.41 and 3.72 respectively. It therefore appears that not much difference exists in the beliefs held by these three age-groups. This is further confirmed by F-value, which is 6.49, higher than the tabulated value and the corresponding significance value is 0.002 less than the required value 0.05.So we reject the null hypothesis and accept the alternative one.

17. Information on internet is often wrong:

The table reveals that the mean value of the responded of age group 18-30 is 2.59, of age group 31 -50 is 2.81 and age group above 50 is 3.68. This can be interpreted that people of all age group have general disagreement in belief. This may further be confirmed by F- value which is 57.15 much higher than the tabulated value. So we reject the null hypothesis and accept the alternative. The level of significance is 0.00 less than 0.05.

18. I serf net at least three times a week: From the table we find that the mean value for 3 age-groups namely 18-30, 31 to 50 and above 50 are 2.53, 3.45 and 3.83 respectively. It therefore appears that not much difference exists in the beliefs held by these three age-groups. This is further confirmed by F-value, which is 53, much higher than the tabulated value and the corresponding significance value is 0.00 less than the required value 0.05.So we reject the null hypothesis and accept the alternative one.

19. I surf net at least ten hours a week: From the table we can see that the mean value of the responses of all age group reveals similarity in belief, The mean value of age group 18-39 is 2.61, age group 31-50 is 3.48 and above 50 is 3.88. The F –value is 52.2, which is much more than the tabulated value .So according to decision rule we reject the null hypothesis and accept the alternative hypothesis. It is further confirmed by level of significance which is 0.0 less than 0.05.

20. If I or anyone fall sick in family I collect information on internet: The table explains that the mean value of the responded of age group 18-30 is 4, of age group 31 -50 is 4.05 and age group above 50 is 4.27. This can be interpreted that people of all age group have general agreement in belief. Age is not a factor of disagreement. This may further be confirmed by F- value which is 3.55 higher than the tabulated value. So we reject the null hypothesis and accept the alternative. The level of significance is 0.03 less than 0.05.

21. Information provided on internet is highly educative: The table reveals that the mean value of the responded of age group 18-30 is 3.24, of age group 31 -50 is 3.19 and age group above 50 is 3.84. This can be interpreted that people of all age group have general agreement on belief. This may further be confirmed by F- value which is 13.17 higher than the tabulated value. So we reject the null hypothesis and accept the alternative. The level of significance is 0.00 less than 0.05.

22. I am able to understand a disease state better with internet information: From the table we find that the mean value of the responses of all age group reveals similarity in belief, The mean value of age group 18-39 is 3.19, age group 31-50 is 3.13and above 50 is 3.88. The F –value is 19.66 which is much more than the tabulated value .So according to decision rule we reject the null hypothesis and accept the alternative hypothesis. It is further confirmed by level of significance which is 0.0 less than 0.05.

23. At times I am able to Diagnose a disease state correctly because of online information: The table says that the mean value of the responded of age group 18-30 is 3.3, of age group 31 -50 is 3.27 and age group above 50 is 3.98. This can be interpreted that people of all age group have general agreement on belief This may further be confirmed by F- value which is 13.28 higher than the tabulated value. So we reject the null hypothesis and accept the alternative. The level of significance is 0.00 less than 0.05.

24. Internet information helps me in identifying right medicine: The table reveals that the mean value of the responded of age group 18-30 is 2.49 , of age group 31 -50 is 2.72 and age group above 50 is 4.27. This can be interpreted that in age group above 50 there is general agreement on belief. This may further be confirmed by F- value which is 76.64 higher than the tabulated value. So we reject the null hypothesis and accept the alternative. The level of significance is 0.00 less than 0.05.

25. Internet information Helps me in modifying diet: From the table we find that the mean value for 3 age-groups namely 18-30, 31 to 50 and above 50 are 3.01, 4.08 and 4.42respectively. It therefore appears that not much difference exists in the beliefs held by these three age-groups. This is further confirmed by F-value, which is 96.42, much higher than the tabulated value and the corresponding significance value is 0.00 less than the required value 0.05.So we reject the null hypothesis and accept the alternative one.

26. Health related information on internet helps me in identifying non drug related therapy: The table reveals that the mean value of the responded of age group 18-30 is 2.55, of age group 31 -50 is 3.44 and age group above 50 is 4.24. This can be interpreted that people of all age group have general agreement on belief. This may further be confirmed by F- value which is 91.71 much higher than the tabulated value. So we reject the null hypothesis and accept the alternative. The level of significance is 0.00 less than 0.05.

27. I am able to communicate better with the physician because of the information i have read on internet: From the table we find that the mean value for 3 age-groups namely 18-30, 31 to 50 and above 50 are 3.18, 4.12 and 4.01 respectively. It therefore appears that not much difference exists in the beliefs held by these three age-groups. This is further confirmed by F-value, which is 33.9, much higher the tabulated value and the corresponding significance value which is 0.00 lower than the required value 0.05.

28. I understand the instructions of the physicians better if I have gone through the online information: From the table we find that the mean value of the responses of all age group reveals similarity in belief, The mean value of age group 18-39 is 3.32, age group 31-50 is 4.07 and above 50 is 3.97. The F –value is 30.09 which is much more than the tabulated value .So according to decision rule we reject the null hypothesis and accept the alternative hypothesis. It is further confirmed by level of significance which is 0.0 less than 0.05.

29. At times I come across sites having wrong information: In the table it is explains that the mean value of the responded of age group 18-30 is 2.81, of age group 31 -50 is 3.38 and age group above 50 is 3.99. This can be interpreted that people of all age group have general agreement in belief. This may further be confirmed by F- value which is 50.71 much higher than the tabulated value. So we reject the null hypothesis and accept the alternative. The level of significance is 0.00 less than 0.05.

30. At times I come across heath related Sites having biased information: : The table reveals that the mean value of the responded of age group 18-30 is 2.84, of age group 31 -50 is 3.43 and age group above 50 is 4.04. This can be interpreted that people of all age group have general agreement on belief. This may further be confirmed by F- value which is 45.37 much higher than the tabulated value. So we reject the null hypothesis and accept the alternative. The level of significance is 0.00 less than 0.05.

31. I can distinguish between good and bad health related websites on internet: : From the table we find that the mean value for 3 age-groups namely 18-30, 31 to 50 and above 50 are 3.94, 3.72 and 2.87 respectively. It therefore appears that not much difference exists in the beliefs held by these three age-groups. This is further confirmed by F-value, which is 30.46, much higher the tabulated value and the corresponding significance value which is 0.00 lower than the required value 0.05.

32. I share website detail with my friend when they need it: From the table we can see that the mean value of the responses of all age group reveals similarity in belief, The mean value of age group 18-39 is 3.16, age group 31-50 is 3.14 and above 50 is 3.68. The F –value is 8.25, which is much more than the tabulated value .So according to decision rule we reject the null hypothesis and accept the alternative hypothesis. It is further confirmed by level of significance which is 0.0 less than 0.05.

33. I take medicines properly because of my knowledge based on internet information: From the table we find that the mean value of the responses of all age group reveals similarity in belief, The mean value of age group 18-39 is 3.06, age group 31-50 is 3.19 and above 50 is 3.76. The F –value is 8.72 which is higher than the tabulated value .So according to decision rule we reject the null hypothesis and accept the alternative hypothesis. It is further confirmed by level of significance which is 0.0 less than 0.05.

34. I follow dietary instructions better because of internet information: : From the table we find that the mean value for 3 age-groups namely 18-30, 31 to 50 and above 50 are 3.25, 3.14 and 3.69 respectively. It therefore appears that not much difference exists in the beliefs held by these three age-groups. This is further confirmed by F-value, which is 7.1, higher than the tabulated value and the corresponding significance value is 0.001 less than the required value 0.05.So we reject the null hypothesis and accept the alternative one.

35. My awareness of side effects and adverse effects of a drug is enhanced because of internet information: In the table it is explains that the mean value of the responded of age group 18-30 is 3.21, of age group 31 -50 is 3.18 and age group above 50 is 3.63. This can be interpreted that people of all age group have general agreement in belief. This may further be confirmed by F- value which is 6.36 higher than the tabulated value. So we reject the null hypothesis and accept the alternative. It is further confirmed by the level of significance. The level of significance is 0.002 less than 0.05.

36. I find information on internet confusing: : From the table we find that the mean value for 3 age-groups namely 18-30, 31 to 50 and above 50 are 2.55, 3.66 and 4.04 respectively. It therefore appears that not much difference exists in the beliefs held by these three age-groups. This is further confirmed by F-value, which is 75.33, much high than the tabulated value and the corresponding significance value which is 0.00 below than the required value 0.05.

37. Information on internet is often biased: The table reveals that the mean value of the responded of age group 18-30 is 2.49, of age group 31 -50 is 3.17 and age group above 50 is 4.2. This can be interpreted that people of all age group have general agreement on belief. This may further be confirmed by F- value which is 99.45 much higher than the tabulated value. So we reject the null hypothesis and accept the alternative. The level of significance is 0.00 less than 0.05.

38. For any mishappening because of wrong information on internet website owner should be taken to court: From the table we can see that the mean value of the responses of all age group reveals similarity in belief, The mean value of age group 18-39 is 4.02, age group 31-50 is 4.17 and above 50 is 4.34. The F –value is 4.37, which is higher than the tabulated value .So according to decision rule we reject the null hypothesis and accept the alternative hypothesis. It is further confirmed by level of significance which is 0.013 less than 0.05.

39. In case there is a contradiction between what the physician tells me and internet information I trust the physician:

In the table it is explains that the mean value of the responded of age group 18-30 is 4.09, of age group 31 -50 is 4.11 and age group above 50 is 4.22. This can be interpreted that people of all age group have general agreement in belief. This may further be confirmed by F- value which is 2.71 higher than the tabulated value. So we reject the null hypothesis and accept the alternative. It is further confirmed by the level of significance.

40. Internet is primary source of health related information: From the table we find that the mean value of age group 18-39 is 3.92, age group 31-50 is 4.03 and above 50 is 4.73. The F –value is 4.73 which is higher than the tabulated value . So according to decision rule we reject the null hypothesis and accept the alternative hypothesis. It is further confirmed by level of significance which is 0.009 less than 0.05.

41. I live a healthier life because of internet:

The table reveals that the mean value of the responded of age group 18-30 is 3.7, of age group 31 -50 is 4.16 and age group above 50 is 4.39. This can be interpreted that people of all age group have general agreement on belief. This may further be confirmed by F- value which is 13.82 higher than the tabulated value. So we reject the null hypothesis and accept the alternative. The level of significance is 0.00 less than 0.05.

42. I find health related information on internet very assuring: The table reveals that the mean value of the responded of age group 18-30 is 3.27, of age group 31 -50 is 3.88 and age group above 50 is 3.28. This can be interpreted that people of all age group have general agreement on belief. This may further be confirmed by F- value which is 33.4 much higher than the tabulated value. So we reject the null hypothesis and accept the alternative. The level of significance is 0.00 less than 0.05.

43. Internet is useful for collecting information on embarrassing Health state: From the table we find that the mean values for 3 age-groups namely 18-30, 31 to 50 and above 50 are 3.23, 3.79 and 4.23 respectively. It therefore appears that not much difference exists in the beliefs held by these three age-groups. This is further confirmed by F-value, which is 31.64, much high than the tabulated value and the corresponding significance value which is 0.00 below than the required value 0.05.

V. CONCLUSION:

From the result and discussion we find that out of total 43 variables significant differences exist between the expressed beliefs held by patients from different age groups in as many as 39 variables. In 4 variables, therefore, their views did not differ significantly. This reflects the age based differing needs and perceptions of patients. In totality it may be accepted that the null hypothesis (No significant differences exist in the perception of patients in different age-groups vis-à-vis impact, merits and demerits of DTC promotion through online-health related websites) stands rejected.

A meta-analysis shows that the F value is very high (above 30) in as many as 19 cases. This reinforces our view that age plays a large role in determining the perception of patients in vis-à-vis impact, merits and demerits of DTC promotion through online-health related websites. There are still three more variables where the F value is appreciably high (between 15 and 30). It, therefore is obvious that out of 43 select variables the age-based differences are significant in 39 cases; appreciably high in 3 cases and substantially high in 19 cases.

Age-based differences in online search behavior of health-based web-sites are important to understand by the physicians, companies and regulatory authorities. Physicians may adopt age-based counseling of patients to ensure encouragement of positive aspects and discouragement of negative aspects of such promotions. Companies may take up age-based communication style to address the needs, response and vulnerabilities of differing age groups in this respect. Regulatory authorities may also find these results to ensure safe and secure regulatory measures that is sensitive to the age-based requirements and susceptibilities.

VI. REFERENCES:

1. Baker, L., Wagner, T. H., Singer, S., and Bundorf, M. K. (2003). Use of the Internet and e-mail for health care information: results from a national survey. Journal of the American Medical Association, 289 , 2400-2406.

2. Cotten, S. R., and Gupta, S. S. (2004). Characteristics of online and offline health information seekers and factors that discriminate between them. Social Science and Medicine, 59 , 1795-1806.

3. Escoffery, C., Miner, K. R., Adame, D. D., Butler, S., McCormick, L., and Mendell, E. (2005). Internet use for health information among college students. Journal of American College Health, 53(4) , 183-188.

4. Fox, S. (2005). Digital divisions. Pew Internet and American Life Project. Fox, S. (2006). Online health search 2006. Pew Internet and American Life Project.

5. Taha, J., Sharit, J., and Czaja, S. (2009). Use of and Satisfaction With Sources of Health Information Among Older Internet Users and Nonusers. The Gerontologist, 49(5) , 663–673.

Received on 13.11.2014 Modified on 25.11.2014

Asian J. Management 6(1): January–March, 2015 page 17-24

DOI: 10.5958/2321-5763.2015.00004.9