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Perceived Health Risks of 3G Cell Phones: Do Users Care?


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Remember the still-unresolved debates concerning eye strain, fatigue due to posture, and mental stress induced by working extensively at desktop or laptop computers? The introduction of innovative information and communication technology is often associated with questions about potential health risks. While some of these hazards might be valid, others may be only hype.

A recent health controversy is associated with possible health hazards arising from high levels of radiation potentially affecting users of cell phones. Due to unprecedented growth of cell phone use and the obvious importance of this issue, numerous studies have attempted to answer the question "Does the use of cell phones pose a threat to health?," without providing a definite answer thus far.

A different but related issue concerns the perception of possible health risks associated with cell phone use. This is important, as perceptions regarding the hazard, and not the actual hazard, affect user behavior. Studies investigating the influence of perceived risk on intention to use particular IT have mostly considered the influence of a general perceived risk, or examined risk facets that did not include a health component [3]. As such, studies targeting perceived health hazards associated with the use of innovative IT have been rare.

A substantive body of consumer behavior research acknowledges that, to reduce the effects of perceived risk, studies must recognize and measure the effects of various facets of risk perceptions [5]: financial (or economic), performance, social, physical (or health), psychological, and time. This line of research has consistently found that physical risk was the least important determinant of intention to acquire a product or service. Little health risk is usually involved when using most consumer products or services, the probable cause for the absence of the perceived health risk factor in IT studies. Risk perceptions, however, may be important with regard to new technologies that might impose life-threatening hazards. A relevant research question is: How important is the influence of a perceived health hazard on intention to use cell phones?

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Research Approach

In order to understand user perceptions of health risk (HR) and the relationships with perceived usefulness (PU) of a technology and user behavioral intention (BI) to adopt this technology, we conducted a cross-sectional study based on empirical data gathered through an online survey targeting the business and academic communities in Canada. The introductory page of the survey manipulated the health hazard perceptions of individuals, by presenting contrasting information from a credible sourcethe British Broadcasting Corporation Web siteon possible health issues associated with the use of third-generation (3G) cell phones. These cell phones were chosen as the IT innovation, not because they might produce different levels of radiation from previous generations of cell phones (even though they may) but because their newness increases uncertainty and, possibly, risk perception associated with their use.

Our research used a randomizing procedure in which successive participants were presented information from the BBC Web site supporting the idea that cell phones are dangerous for health, alternating with other information from the same Web site supporting the opposite idea. After completing the survey, all participants were shown that the BBC Web site actually presented a balanced view and there was no clear evidence to date for either of the two arguments.

Of the 206 valid responses to the online survey, 107 participants were women (51.94%) and 99 were men (48.06%). Over 48% of the users were less than 26 years old. Participants had an average of 6.76 years of cell phone use experience, with a median of 10 years (range from 0, meaning non-users, to 20), and an average of 7.51 cell phone calls made and received per day, with a median of 30 (range from 0 for non-users to 60).

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Research Findings

The health hazard manipulation had the expected effects: individuals presented the "safe" information reported lower risk perceptions (mean = 2.67) than individuals in the "unsafe" condition (mean = 3.61) on a 1 to 7 Likert scale (significant at the 0.0001 level). This also proved that perceptions are strongly influenced by information received, and this information overshadows existing views.

The structural model of the research, path coefficients, their significance (or p) values, and the variances explained by the constructs in the model are presented in the figure here. The model links the perceived health risk borrowed from the consumer behavior research to the perceived usefulness and behavioral intention to use a technology of the widely popular Technology Acceptance Model (TAM) introduced by Davis [2]. The research model estimates were based on Partial Least Squares (PLS) techniques.

Perceived health hazard has a small negative indirect influence on the intention to use cell phones. This influence is important only in conjunction with the PU, which fully mediates the HR effect. The mediation proposition was tested by running a separate direct-effect model for each outcome of HR. A HRBI model revealed somewhat strong relationships (strength of -0.17, p<0.05) and a HRPU model showed that HR predicts PU (strength of -0.14, p<0.01). However, once the mediator PU was considered in the partially mediated model (see the figure here) the direct effect of HR on BI became small (strength of -0.09) and not significant. Thus, when expressing their intention to use 3G cell phones, people acknowledge some health risk but this is overshadowed by the utility they associate with this technology.

Perceived health hazard diminishes perceived usefulness. The main conclusion drawn from the analysis is that HR perceptions affect the PU of 3G cell phones, which in turn, influences user BI to use these phones, the strength of the relationships being -0.13 and 0.56, respectively (see the figure here). The very low level of PU variance accounted for by HR (0.02) implies that HR has an almost negligible explanatory value for the PU of 3G cell phones. We conclude that, when judging the usefulness of cell phones, users care very little about possible health hazards and other factors may be more important (for example, perceived ease of use as in TAM).

Mature people have stronger health risk perceptions than younger people. Some studies show that, as people grow older, they tend to perceive less risk in various activities because of a diminished emotional responsiveness or psychological immunization. Other research shows that young people fail to understand the associated risk arising from cumulative effects.


Although health concerns have some negative impact on intention to use cell phones, perceived usefulness remains the dominant factor.


To investigate the moderating role of age, we split the sample by gender into two age quartiles (below 26, average age of 22, and above 31 years, average age of 44) and estimated the model with each sample. Focusing only on significant coefficients, we concluded the effect of HR on PU is stronger for mature people. PU, in turn, has a stronger effect on BI in this context. Thus, the indirect effect of HR on BI (HRPUBI) is stronger for more mature people than for younger ones. Overall, younger individuals (less than 26) are less concerned with possible health risks when evaluating the usefulness of 3G cell phones and in deciding to adopt this technology. This concurs with studies showing that younger people care less than more mature individuals about perceived consequences of possible health hazards such as smoking.

Males perceive stronger effects than females. The analysis also revealed that gender moderates all the model's relationships. The effect of HR on PU and the effect of PU on BI are stronger for males than for females, indicating the overall indirect effect of health risk perceptions on behavioral intentions is stronger for males than for females. Previous research regarding gender influence usually suggests that women perceive more threats from potential hazards and thus manifest more insecurity than men [4], but our study did not find similar effects.

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Conclusion

The purpose of this study was to investigate the effects of perceived health risks associated with potentially hazardous IT innovations on intention to adopt. We found that perceived health risk has a small indirect negative influence on the intention to use 3G cell phones. This is consistent with consumer behavior research [1]. Similarly to other IT studies, we found that perceived health risk of 3G cell phones negatively affects their perceived usefulness. Perceived usefulness, in turn, positively influences intention to use 3G cell phones. Therefore, although health concerns have some negative impact on intention to use cell phones, perceived usefulness remains the dominant factor and its influence eclipses the insignificant direct relationship between perceived health risk and intention to use.

The results described in this column translate into practical implications. As perceived health risk has some indirect effect on user intentions to utilize 3G cell phones, marketers of new IT innovations should be aware of such perceptions and try to mitigate them. Research proving scientifically that an IT innovation is risk-free is desirable, but an alternative approach is to follow the example of more mature technologies. For instance, computer manufacturers have offered devices to alleviate computer-associated health hazards: including special pads, armrests, and screen shields.

Marketers should also conduct studies to identify health-risk concerns in market segments and adopt better ways to address them. For example, we found that mature males seem to care more about possible health risks from 3G cell phones.

This study was a first attempt to integrate the concept of perceived health risk into technology adoption research. Further investigation is desirable into the influence of other factors and contexts (such as using a cell phone while driving a car) that intervene in relationships between perceived health hazards of innovative IT and intention to use the IT.

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References

1. Brooker, G. An assessment of an expanded measure of perceived risk. Advances in Consumer Research 11, (1984), 439441.

2. Davis, F. Perceived usefulness, perceived ease of use, and user acceptance of information technology. MIS Quarterly 13, 3 (Sept. 1989), 319340.

3. Featherman, M. and Pavlou, P. Predicting e-services adoption: A perceived risk facets perspective. International Journal of Human Computer Studies 59, 1 (2003), 451474.

4. Finucane, M.L., Slovic, P., Mertz, C.K., Flynn, J., and Satterfield, T.A. Gender, race, and perceived risk: The `white male' effect. Health, Risk, and Society 2, 2 (2000), 159172.

5. Lim, N. Consumers' perceived risk: Sources versus consequences. Electronic Commerce Research and Applications 2, 3 (2003), 216228.

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Authors

Mihail Cocosila (cocosim@mcmaster.ca) is a Ph.D. candidate in the DeGroote School of Business at McMaster University in Hamilton, Ontario, Canada.

Ofir Turel (turelo@mcmaster.ca) is a Ph.D. candidate in the DeGroote School of Business at McMaster University in Hamilton, Ontario, Canada.

Norm Archer (archer@mcmaster.ca) is a professor emeritus in the DeGroote School of Business at McMaster University in Hamilton, Ontario, Canada.

Yufei Yuan (yuanyuf@mcmaster.ca) is a professor in the DeGroote School of Business at McMaster University in Hamilton, Ontario, Canada.

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Figures

UF1Figure. The structural model.

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©2007 ACM  0001-0782/07/0600  $5.00

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Article Contents:
  • Introduction
  • Research Approach
  • Research Findings
  • Conclusion
  • References
  • Authors
  • Figures