This is an open-access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work, first published in Medicine 2.0, is properly cited. The complete bibliographic information, a link to the original publication on http://www.medicine20.com/, as well as this copyright and license information must be included.
Affordability, acceptability, accommodation, availability, and accessibility are the five most important dimensions of access to health services. Seventy two percent of the Indian population lives in semi-urban and rural areas. The strong mismatched ratio of hospitals to patients, rising costs of health care, rapidly changing demographics, increasing population, and heightened demands in pricing for technological health care usage in emerging economies necessitate a unique health delivery solution model using social media. A greater disease burden lies in the health care delivery in developing country like India. This is due to the lack of health care infrastructure in the majority of semi-urban and rural regions. New techniques need to be introduced in these regions to overcome these issues. In the present scenario, people use social media from business, automobiles, arts, book marking, cooking, entertainment, and general networking. Developed and advanced countries like the United States have developed their communication system for many years now. They have already established social media in a number of domains including health care. Similar practice incidences can be used to provide a new dimension to health care in the semi-urban regions of India.
This paper describes an extended study of a previous empirical study on the expectations of social media users for health care. The paper discusses what the users of social media expect from a health care social media site.
Multiple regression analysis was used to determine the significance of the affect of four factors (privacy, immediacy, usability, and communication) on the usage of health care social media. Privacy, immediacy, usability, and communication were the independent variables and health care social media was the dependant variable.
There were 103 respondents who used the online questionnaire tool to generate their responses. The results from the multiple regression analysis using SPSS 20 showed that the model is acceptable, with
Health care social media requires intelligent implementation in developing economies. It needs to cater to the expectations of the users. The people in India, especially those in urban and semi-urban regions, are very interested in accepting the system.
Social media is now a buzzword in the new generation of digital communications. Social networks are networks that link people and machines [
In developing countries, a number of attempts have been made to reform health care for the underprivileged. However, it is mostly the private sector players [
Moreover, technology has influenced the spread of information and the manner it can be disseminated to the world. Media and its landscape has seen significant transformation in the last decade and social media is increasingly replacing the traditional media [
The developed and advanced countries like the United States have developed their interrelated communication system many years from now. This includes the usage of social media in almost every domain including health care. Manhattan Research Group found long back in 2002 [
The world average of beds per 1000 patients is 2.6 where as in India it is only 0.7 [
Everyone needs similar levels and quality of health care services particularly five dimensions of access to health services as affordability, acceptability, accommodation, availability, and accessibility [
However, these challenges can be relieved for those who might use information technology to an extent by knowing about similar kinds of patients with same disease patterns, share their experiences and many more by the introduction of a one step ahead social media tool for health care. Thus, social media for health care as technology intervention strategy in information technology may exert their influence through both volume and price effects. Technological interventions at every stage in innovation will direct to sustainable health care system especially in the emerging economies context. Research has also confirmed the value addition and trust involved in a continuous online development of the contents for patients [
The augmentation of health care delivery system needs a large reform in the developing economy context. This is directly derived from the poor health care scenario presented in the semi-urban and rural regions. The reform through information and communication tools (ICT), that is, social media might be looked at provided the users are given training. This leads to various research issues. They are: What are the factors that determine the health care social media? Would the people in semi-urban and rural regions of developing countries prefer the intervention to other existing systems? How much information sharing would they be comfortable with? How much would they expect from the health care social media given to them? Hence, this leads to an organized and methodical study of these issues.
This paper makes an attempt to analyze the expectations for health care social media of the already existing users of the social media. The expectations are measured in terms of Privacy, Immediacy, Usability [
It is true to state that these health care reforms are seen mostly in the developed countries. There are few instances of social media usage for health care in the metropolitan areas in India. The world average comparison is just an example of poor infrastructure in India. Amrita et al 2010, [
It has also been observed that the wide prevalence of mobile usage adds to the flexibility of the health care delivery system in India. Recent reports on mobile usage shows that India constitutes 10% of the total mobile usage in the world. The Internet users in India are 11.4% [
The World Health Statistics 2012 [
The motivation of this paper lies in the huge prevalence and acceptance of viral marketing and social media marketing by the people in India. It shows that they are open to new dimensions for comfortable lives. It has already been seen that the drug companies are using social-media to promote their brands. Research has reported positive inclination towards the belief levels for using wiki-based information for health care [
There are a number of health care networks which includes doctors, patients, nurses, pharmacists and who so ever are interested in health care. There are also a number of applications in the Internet including Google health, medicine 2.0 and health 2.0. All of them target to the population who are already using Internet and can understand computer and information technology. It has been seen from the survey of Internet, that there are many social media networks which deal with doctor networks, nurses’ networks, popular disease support forums, health blogs, patients’ voices, and expert answers.
It might also be stated that various efforts have been made to make health care accessible for the rural and semi-urban population. These efforts are more towards the use of mobile and hand held devices for transferring patients’ information to the relevant doctors. Mobile hospitals and similar efforts have also been made in parts of Africa and Brazil.
The growing body of literature on social media and health care is generally concerned with the advertisers to find new customers. However, scarce literatures of social media for effectiveness of health care especially in developing countries have been viewed.
Mobile phones for health care are on the cusp of spurring an information revolution in such regions [
Social media provides an substantial amount of information, having the potential to attract significant audience [
There are a number of health care networks, which includes doctors, patients, nurses, and pharmacists, who are interested in health care. Most of them target to developed and advanced countries. There are not many studies that refer to the developing country perspective. Hence, the objective of the paper is aligned with the aim to understand the social media users in developing country. This might lead us the way to realize how we could proceed further for building any social media tool for developing countries.
Researchers on social media techniques have mentioned seven functional elements [
This study is based on the primary data collected during January 2013 using a survey questionnaire form created in the Google forms in the Internet. This work is based on our previous published paper [
The extensive use of social media has already perturbed the common understanding of the
Hence, learning from the previous work and results, we designed the factors to:
The paper is based on the premise that the health customer is able to choose from where and whom they get treated or prefer some close relatives advices for taking such decisions. The users are free to use and have their views on health information over the Internet or social media.
Since we have targeted the users of the social media as the target group, we did not define any premise of distance and place of stay. The only clause we have used for the respondents is that they should be Indian citizens staying in India. Hence we have relied on the snowball sampling method to spread the online survey link. This also helped us identify the few duplications and quality of information.
Based on our previous experience of the published paper, we designed our questionnaire to remove as well as include the defining constructs for 4 identified factors. Additionally, we designed questions to know the social media presence, preference and health care social media. The distribution of the questions were as such that 42 items were created, 5 each for 4 independent variables and 4, 7, and 11 for social media presence, health care preference, and demography.
The questionnaire was designed as a webpage form using the Google forms available online. The link was shared online through emails, Facebook, Twitter, and interest forums. Sections A to D were designed using 5 point Likert scale. Options ranging from “Strongly Disagree” to “Strongly Agree” for A to C and “Never” to “Always” in the case of D was used. Sections from E to G were majorly multiple choices along with other few to enter themselves as well as select from given choices.
The response of the online Google form automatically got registered in the Excel format. The response rate was good during the first time intimation and dropped after a few days. After 5 to 6 reminders, 103 responses were generated. It is assumed that the sample is random attributing to the wide demography of the respondents. The data points count, that is, n=103 we can say referring to the Central Limit Theorem (n>30) that the sample size is large and normally distributed.
The idea of using online data collection was generated for the reason that our focus was more on the users of the social media and Internet. Moreover, the large audience, reduced cost of travel, quick time to gather responses, easy data management, and less item non-response led to the decision of online data collection.
The demographic profile of the respondents’ show that majority are between the age groups of 19 to 25. Qualification is majorly in graduation and post graduation. Occupation-wise most of them are professionals. Maximum belong to urban and semi-urban regions. The income shows that maximum have the average income between 1819 to 7273 USD but the next income group has more than 14,545 USD. The sample is representative of the social media users keeping in mind the domicile status. Conversely, maximum response is from the age group 25 to 30 years and below. This shows that the online social media users in India are mainly the younger generation.
The four determinants—privacy, immediacy, usability, and communication of health care social media—have been taken as the predictor variables pertaining to multiple regressions. Health care social media has been considered as the dependent (outcome) variable.
Our null hypothesis for determination of the regression has been taken such that the four independent variables (privacy, immediacy, usability, and communication) do not depend on the dependent variable health care social media. Hence, the null hypothesis was designed as health care social media is not dependent on privacy, immediacy, usability, and communication, and are not related. Therefore, the alternative hypothesis is that health care social media is dependent on the variables privacy, immediacy, usability, and communication. Based on the null hypothesis, several propositions are drawn to form the conceptual model (
The data obtained from survey was regressed using the SPSS 20 package for analysis. We present the results of the regression from Model fit statistics in
The significance value in ANOVA (
So it can be said that the independent variables privacy, immediacy, usability, and communication has an influence on the dependent variable, health care social media. Accepting the alternate hypothesis, we proceed to explain the significant influences of the independent variable through the reporting of unstandardized coefficients (
Proposition H1: the predictor variable “privacy” has no influence on health care social media.
Proposition H2: the predictor variable “immediacy” has no influence on health care social media.
Proposition H3: the predictor variable “usability” has no influence on health care social media.
Proposition H4: the predictor variable “communication” has no influence on health care social media.
Reporting of the model summary.a
Model |
|
|
Adjusted |
Standard error of the estimate |
Statistics | .580b | 0.337 | 0.175 | 1.104 |
aDependent variable: Health care social media
bPredictors: (Constant), Communication 5, Communication 4, Privacy 1, Communication 2, Immediacy 1, Privacy 4, Usability 5, Immediacy 3, Usability 2, Immediacy 5, Communication 1, Communication 3, Privacy 5, Privacy 2, Usability 3, Immediacy 2, Usability 4, Privacy 3, Usability 1, Immediacy 4
Reporting of ANOVAa statistics.
Model | Sum of squares | Degrees of freedom | Mean square |
|
Significant difference |
Regression | 50.743 | 20 | 2.537 | 2.082 | .011b |
Residual | 99.936 | 82 | 1.219 | N/A | N/A |
Total | 150.68 | 102 | N/A | N/A | N/A |
aDependent variable: Health care social media
bPredictors: (Constant), Communication 5, Communication 4, Privacy 1, Communication 2, Immediacy 1, Privacy 4, Usability 5, Immediacy 3, Usability 2, Immediacy 5, Communication 1, Communication 3, Privacy 5, Privacy 2, Usability 3, Immediacy 2, Usability 4, Privacy 3, Usability 1, Immediacy 4
Reporting of coefficients.a
Model | Unstandardized coefficients | Standardized coefficients |
|
Significant difference | ||
|
Beta | Standard error | Beta |
|
|
|
Constant | 2.86 | 1.19 |
|
2.404 | 0.018 | |
|
|
|
|
|
|
|
|
1 | -0.009 | 0.1 | -0.011 | -0.093 | 0.926 |
|
2 | 0.001 | 0.114 | 0.001 | 0.005 | 0.996 |
|
3 | -0.182 | 0.158 | -0.14 | -1.152 | 0.253 |
|
4 | 0.044 | 0.145 | 0.039 | 0.308 | 0.759 |
|
5 | -0.222 | 0.126 | -0.19 | -1.76 | 0.082 |
|
|
|
|
|
|
|
|
1 | -0.104 | 0.102 | -0.103 | -1.023 | 0.309 |
|
2 | 0.154 | 0.117 | 0.148 | 1.322 | 0.19 |
|
3 | 0.007 | 0.127 | 0.006 | 0.054 | 0.957 |
|
4 | -0.298 | 0.204 | -0.202 | -1.463 | 0.147 |
|
5 | 0.015 | 0.241 | 0.009 | 0.06 | 0.952 |
|
|
|
|
|
|
|
|
1 | 0.457 | 0.184 | 0.316 | 2.48 | 0.015 |
|
2 | 0.003 | 0.104 | 0.003 | 0.03 | 0.976 |
|
3 | -0.087 | 0.177 | -0.059 | -0.495 | 0.622 |
|
4 | 0.017 | 0.152 | 0.013 | 0.109 | 0.913 |
|
5 | 0.026 | 0.106 | 0.026 | 0.244 | 0.808 |
|
|
|
|
|
|
|
|
1 | 0.116 | 0.132 | 0.094 | 0.883 | 0.38 |
|
2 | -0.16 | 0.103 | -0.153 | -1.55 | 0.125 |
|
3 | 0.075 | 0.117 | 0.067 | 0.646 | 0.52 |
|
4 | 0.354 | 0.095 | 0.405 | 3.732 | 0 |
|
5 | 0.019 | 0.1 | 0.019 | 0.186 | 0.853 |
aDependent variable: Health care social media
Looking at the smaller significance level of the model items in
Now considering the observations based on the good difference between
The implication of usefulness of social media has been well understood through its usage in marketing and other dominant domains. Social media has seen a good influence in the behaviors of the users in developing economies.
This paper is a contribution of how the users expect and understand the health care social media in India as a developing country. The majority of responses from urban and semi-urban domicile population show that they expect that health care becomes more accessible and available. We show how we can refer to the gap of understanding the impact of how the social media can help semi-urban and rural population in health care. The results would help the designers of health care social media to understand the expectations of the semi-urban and urban population in a developing economy. The results show that people would use the social media sites for health. However there is a need of good awareness and training for making it a successful implementation.
The paper has used snowball sampling for online data collection. This method does not report the response rate of the survey. Even though the different online ways were used to distribute the survey link, getting a large population sample remained a problem same as in traditional data collection. Moreover, we do not know the conditions and setting of the respondents at the time of taking the survey.
The bias of the volunteer sample in the earlier work [
The current work shares the similar model of regression as the previous one for measuring the expectations of the users of health care social media. The users in the developing economy are conscious about the openness of the privacy in a public forum. There is a variation from the previous work in which we have tried to understand the communication influences between the users. The negative influence of communication for face-to-face patient-physician interaction shows that people are skeptic towards revealing their identity. This is again confirmed by the negative influence results of controlling identity settings. Both the work shows a positive influence of usability for simple and quick learning health care social media.
The openness of the privacy component was highlighted where it shows negative influence. Users are very skeptic towards keeping their identity and friend’s list open. The less disclosure of health care interests is very prominent. Hence openness of privacy negatively influences the dependant variable. Respondents wish to get advices from experienced people and not only from health experts. Hence immediacy has a positive influence in terms of intermediary communications supported. Usability shows a positive influence where people want to be in directory listings. Communication has a strong positive influence where the users want emergency information over the health care social media.
Questionnaire.
Brazil, South Africa, India, and China
information and communication tools
Indian Space Research Organization
Technology to Health
The authors thank Partha Mukhopadhyay and Rana Basu for their contribution in proof reading the manuscript.
None declared.