Exploring Differences in Privacy Concerns and Tagging Behavior Among Older and Younger Adults

Written by escholar | Published 2024/02/13
Tech Story Tags: online-privacy | dark-patterns | privacy-decision-making | dark-pattern-design | digital-manipulation | behavioral-research | facebook-experiment-results | data-disclosure-behavior

TLDRThis section presents the results of a comprehensive analysis of privacy decisions using experimental data from a Facebook application study. It highlights the impact of framing, defaults, and justification messages on tagging decisions, along with insights into age-related differences in privacy concerns and tagging behavior. Discover how age group moderates the effects of different variables on privacy behavior, providing valuable insights into online privacy dynamics.via the TL;DR App

Authors:

(1) Reza Ghaiumy Anaraky, New York University;

(2) Byron Lowens;

(3) Yao Li;

(4) Kaileigh A. Byrne;

(5) Marten Risius;

(6) Xinru Page;

(7) Pamela Wisniewski;

(8) Masoumeh Soleimani;

(9) Morteza Soltani;

(10) Bart Knijnenburg.

Table of Links

Abstract & Introduction

Background

Research Framework

Methods

Results

Discussion

Limitations and Future Work

Conclusion & References

Appendix

5 Results

5.1 Sample Characteristics

Across the older adult participants, there were 15 females and 29 males. Their average age was 68.8 years (min = 65, max = 77, sd = 3.23). The young adult sample had 87 males, 71 females, and 4 individuals who did not self-identify as female or male. Their average age was 20.30 (min = 18, max = 25, sd = 2.18). The dataset also measured participants’ Facebook usage frequency on a 9-point scale from “Never” coded as 0 to “Almost constantly” coded as 9 and the time they spend on Facebook in each session on a 5-point scale from “A few minutes” coded as 1 to “Several hours” coded as 6. On average, older adults used the Facebook platform more frequently (mean = 5.708, sd = 1.519) compared to younger adults (mean = 5.402, sd = 2.055). However, both age groups spent an average time of 30 minutes on Facebook ( older adults: mean = 2.054, sd = 1,194 and young adults: mean = 2.119, sd = 1.275). In the following, we present our analyses with regards to our hypotheses. Table 2 summarizes the hypothesis tests.

5.2 Effects on Tagging Decision

In contrast to H1 and in line with the privacy paradox, we did not find any significant relationship between privacy concerns and disclosure decision (p>.05). Therefore, H1 is rejected. However, we found support for H2 and H3 suggesting both framing and default significantly influence tagging decisions. Users who see the positively framed option of “Tag me in the photos” were 31.9% more likely [2] to use the tagging feature compared to those who see the negatively framed option of “Do not tag me in the photos” (p < .001). Furthermore, those users who were being tagged by default were 19.4% more likely to use the tagging feature (p<.01). In addition, in contrast to H4, the various justifications did not influence tagging decision differently (χ2 (4) = 0.823, p > 0.05). Finally, in line with what we hypothesized in H9, older adults were 19.8% more likely to use the tagging feature compared to young adults (p<.05).

5.3 Effects on Privacy Concerns

In contrast to H5 and H6, we did not find any significant effects of framing and default manipulations on privacy concerns (p > .05). However, we did find a significant main effect of justifications on privacy concerns (χ2 (4) = 9.827, p < 0.05). Subsequent planned contrast tests revealed a significant effect of justification valence (p < 0.05), supporting H7 and suggesting that negative justification messages lower users’ privacy concerns compared to positive justifications by 0.132 standard deviations. However, this effect was negated by a marginal interaction between justification type and valence, meaning that the difference between positive and negative justifications mostly hold for normative justifications (see Figure 5). Finally, in contrast to H8, older and younger adults did not have significant differences in terms of their overall level of privacy concerns (p > 0.05).

Our results show that in contrast to our H8, older and younger adults have the same levels of privacy concerns. Furthermore, while having the same levels of concern, older adults are more open to disclosure. We further unpack the effects of age by studying moderation effects of age and dark pattern designs. We therefore run a saturated path model and report it below. Fig- ure 6 and Table A1 summarize our results..

5.4 Moderating Effects of Age Group on Tagging Decision

We found age group to moderate the effect of framing on tagging decision; the effect of framing was stronger for older adults than for young adults: older adults who were exposed to a positively framed option were 53.1% more likely to use the tagging feature while young adults who were exposed to a positively framed option were only 33.1% more likely to use the tagging feature (p < .05). Figure 7 depicts this effect. We found a similar moderation effect for defaults suggesting that older adults were more likely to keep the default option and use the tagging feature compared to young adults. However, this effect did not reach significance (p = .062).

Similarly, age did not moderate the effect of justifications on the tagging decision (χ2 (4) = 4.822, p > 0.05). Lastly, while the effect of privacy concerns on the tagging decision was stronger for older adults than for young adults, this effect was not significant (p>.05).

5.5 Moderating Effects of Age Group on Privacy Concern

The effect of defaults on privacy concerns were moderated by age group: an opt-out default increased older adults privacy concerns by 0.255 times standard deviation compared to a negative default, while an opt-out default increased young adults’ privacy concerns by only

0.066 times standard deviation compared to a negative default (p < 0.01). Figure 8 depicts this effect and suggests that an opt-out default only significantly increases the privacy concerns for older adults. Age group did not moderate the effects of any other variable on privacy concerns(p > 0.05).


[2] To present the results in a comprehensive manner, we convert the log odds-ratio to percentages. For example, the effect of framing on disclosure is 0.277 (table A1), which is a log odds-ratio. Therefore, disclosure in the positive framing group is e0 .277 = 1.319 times higher than in the negative framing group, i.e., a 31.9% difference in the odds of disclosure

This paper is available on arxiv under CC BY-NC-SA 4.0 DEED license.


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