Does Animation Have Bad Effects On People
J Med Cyberspace Res. 2012 Jul-Aug; 14(four): e106.
Blithe Graphics for Comparing Two Risks: A Cautionary Tale
Monitoring Editor: Gunther Eysenbach
Brian J Zikmund-Fisher, PhD, 
1 2, three, 4 Holly O Witteman, PhD,3 Andrea Fuhrel-Forbis, MA,3 Nicole 50 Exe, MPH,3 Valerie C Kahn, MPH,three and Mark Dickson, MA3
oneDepartment of Health Behavior and Health Didactics, School of Public Health, University of Michigan, Ann Arbor, MI, United States
2Department of Internal Medicine, University of Michigan, Ann Arbor, MI, U.s.
3Center for Bioethics and Social Sciences in Medicine, Academy of Michigan, Ann Arbor, MI, U.s.
ivChance Science Center, School of Public Wellness, University of Michigan, Ann Arbor, MI, The states
Brian J Zikmund-Fisher, Department of Wellness Behavior and Health Education, Schoolhouse of Public Health, University of Michigan, 1415 Washington Heights, Ann Arbor, MI, 48109-2029, The states, Phone: 1 734 936 9179, Fax: 1 734 763 7379, Email: ude.hcimu@dnumkizb.
Brian J Zikmund-Fisher
iSection of Wellness Behavior and Health Teaching, School of Public Wellness, University of Michigan, Ann Arbor, MI, United states of america
2Department of Internal Medicine, University of Michigan, Ann Arbor, MI, United States
3Centre for Bioethics and Social Sciences in Medicine, Academy of Michigan, Ann Arbor, MI, United States
ivRisk Science Center, School of Public Health, University of Michigan, Ann Arbor, MI, U.s.
Holly O Witteman
3Heart for Bioethics and Social Sciences in Medicine, University of Michigan, Ann Arbor, MI, Us
Andrea Fuhrel-Forbis
iiiCenter for Bioethics and Social Sciences in Medicine, Academy of Michigan, Ann Arbor, MI, U.s.
Nicole L Exe
iiiMiddle for Bioethics and Social Sciences in Medicine, University of Michigan, Ann Arbor, MI, United States
Valerie C Kahn
3Center for Bioethics and Social Sciences in Medicine, University of Michigan, Ann Arbor, MI, United States
Mark Dickson
threeCenter for Bioethics and Social Sciences in Medicine, University of Michigan, Ann Arbor, MI, Usa
Received 2011 December 20; Revisions requested 2012 Jan 17; Revised 2012 Mar ii; Accustomed 2012 May 24.
Abstract
Background
The increasing employ of computer-administered risk communications affords the potential to supervene upon static adventure graphics with animations that use motion cues to reinforce fundamental risk messages. Research on the employ of animated graphics, however, has yielded mixed findings, and trivial enquiry exists to identify the specific animations that might improve risk cognition and patients' decision making.
Objective
To test whether viewing animated forms of standard pictograph (icon array) take chances graphics displaying risks of side effects would improve people'due south power to select the treatment with the everyman risk profile, as compared with viewing static images of the same risks.
Methods
A total of 4198 members of a demographically diverse Internet console read a scenario near two hypothetical treatments for thyroid cancer. Each treatment was described every bit as effective but varied in side furnishings (with one option slightly better than the other). Participants were randomly assigned to receive all risk information in 1 of 10 pictograph formats in a quasi-factorial blueprint. We compared a control condition of static grouped icons with a static scattered icon display and with 8 Flash-based blithe versions that incorporated different combinations of (i) building the risk 1 icon at a fourth dimension, (2) having scattered hazard icons settle into a group, or (3) having scattered take a chance icons shuffle themselves (either automatically or by user command). Nosotros assessed participants' ability to choose the better treatment (selection accuracy), their gist knowledge of side effects (knowledge accuracy), and their graph evaluation ratings, controlling for subjective numeracy and need for cognition.
Results
When compared against static grouped-icon arrays, no animations significantly improved any outcomes, and most showed meaning performance degradations. Even so, participants who received animations of grouped icons in which at-take a chance icons appeared i at a fourth dimension performed as well on all outcomes as the static grouped-icon command grouping. Displays with scattered icons (static or animated) performed particularly poorly unless they included the settle animation that allowed users to view outcome icons grouped.
Conclusions
Many combinations of animation, especially those with scattered icons that shuffle randomly, announced to inhibit noesis accuracy in this context. Static pictographs that grouping chance icons, even so, perform very well on measures of knowledge and option accurateness. These findings parallel recent prove in other data advice contexts that less tin can exist more—that is, that simpler, more than focused information presentation tin effect in improved agreement. Determination aid designers and health educators should proceed with caution when considering the use of blithe gamble graphics to compare two risks, given that show-based, static risk graphics announced optimal.
Keywords: Run a risk, patient education every bit topic, patient-provider communication, decision aids, visual aids
Introduction
The most basic mode to communicate hazard to patients is to provide them with a chance number. All numerical formats are not equivalent, nonetheless, and considerable research has compared, for instance, the pros and cons of using frequency formats instead of percentages [1-4] and the potential pitfalls of specific formats such as 1-in-X [5,6] and number needed to care for [7]. In improver, research on affective influences on risk perceptions arrive clear that the aforementioned risk number can atomic number 82 to very different feelings about that risk based on different circumstances, presentations, or contexts [eight,9].
In an effort to brand risk statistics more than intuitive, both researchers and wellness educators have increasingly turned to visual displays of risk. While this literature is evolving, comparative studies have shown that icon-based displays (often called pictographs or icon arrays) appear to have pregnant advantages over other displays such as bar graphs and pie charts [10-fourteen]. In particular, displays that visually represent the part-whole relationships (ie, the number of take a chance events in comparing with the unabridged at-gamble population) appear to exist better understood [14,xv] and may be of particular help to people with lower numeracy skills [xvi].
Animated Risk Displays
While almost numerical and visual formats for communicating risk are easily implementable in traditional paper-and-pencil materials, the last decade has seen an enormous increase in the utilise of electronic applications designed to communicate adventure to patients. Today, we regularly see computers in clinical consultation rooms, patients tin can become to innumerable websites that volition guess their health risks, and a growing suite of mobile device applications are available that purport to support salubrious living in various ways.
Such technologies open the door to using multimedia techniques such equally animation for communicating risk. Blitheness is ordinarily used in online applications to call users' attention to a detail area of the screen [17] or portion of the content [18]. This type of signaling may help people make sense of verbal information [19], may help them better larn how a complex system such equally a turbofan jet engine works [20], and may assist somewhat in the acquisition of complex cognitive skills such as doing experimental research or designing a house [21].
Motion Cues
Animation of risk graphics could be particularly useful because it allows motion cues to depict attention to specific elements of the visual display. For instance, instead of only showing the proportion of area or icons afflicted by a risk, animation could exist used to sequentially describe the viewer's heart to each new chance event, thereby calculation a time cue (how speedily the set of events occurs) to reinforce the smallness or largeness of the take chances. Such cues may be particularly useful when comparing multiple risks.
Transformations
When people are at risk for a health outcome, they volition either experience the outcome or not. The randomness of this occurrence or nonoccurrence is one of the conceptual challenges of risk communication. By research has noted that icon array displays that besprinkle effect icons randomly convey this sense of randomness but make information technology hard to grasp exactly how large the take a chance is [3,22], whereas displays that group event icons are easy to count (allowing for faster interpretation) [eleven]. Animation could exist used to transform i arrangement into another (for example, a scattered display into a grouped display, or 1 type of scatter into another), which might enable viewers to have the best of both worlds.
Potential Concerns
While animated displays may have potential advantages, there are also several reasons for circumspection and further research regarding their use in risk communication applications. Many types of animation exist, each of which may reinforce different types of gist messages. In the absence of research clarifying what types of animation are taken to imply different types of conceptual understanding, employ of animated graphics has the potential to cause unintended negative effects. Reviews of other types of animated graphics have institute decidedly mixed results [23], providing reason to question whether animated graphics will back up improved understanding over static graphs. It may be the case that their utility depends on user characteristics. For example, animated graphs have previously been demonstrated to help people who had performed well on a short mathematics examination administered prior to an experiment that tested ability to transform graphs of mathematical functions, while hindering those who had performed more poorly on the mathematics test [24]. The benefits or drawbacks of adding animation cues may likewise depend on the complexity of the visual stimulus, since human factors inquiry has shown that excessively complicated displays can reduce people'southward ability to attend to particular cues [18].
Existing Research
Very piddling work has been done to appraise whether animation of risk graphics can amend people'due south understanding of their wellness risk, or which types of animation might ameliorate or inhibit accurateness of risk knowledge and risk perceptions. One notable exception is the written report of Han et al, which showed that a dynamic scattered display increased subjective dubiousness about a run a risk, making participants less certain nigh their interpretations of hazard information [25]. Other researchers have examined using interactive take a chance displays to engage people in learning about chance [26-28], but these studies have focused on the result of different types of participant tasks (eg, manually graphing a provided risk number or playing within a game-like surroundings) rather than the visual cues potentially provided by animation.
To begin to explore whether viewing specific types of motility cues and visual transformations in blithe risk graphics could improve people's knowledge accuracy, decision making or choice accuracy, and graph evaluation ratings as compared with viewing static images, we conducted a randomized survey experiment comparing various animated and static displays in the context of a hypothetical medical treatment scenario. Our main research question was whether animated displays with dissimilar types of motion would increment or decrease participants' power to identify which of two handling options had lower side effect risks (choice accuracy). A secondary research question involved determining, via graph evaluation ratings, whether people like or dislike these types of animation for receiving medical risk data.
Methods
Recruitment
Nosotros selected a stratified random sample of United states of america adults historic period 21 years and older from a panel of Net users administered by Survey Sampling International (Shelton, CT, U.s.), which recruits panel members through a variety of opt-in methods. To ensure demographic multifariousness (though not necessarily representativeness) and offset large expected variations in response rates, we drew distinct subsamples by both age and race (thereby roughly approximating the distributions of these characteristics in the U.s.a. population), and dynamically adapted the number of email invitations in each demographic subsample until all quotas were achieved. Selected panel members received an electronic mail invitation with a personalized link to complete the online survey with one reminder email for nonresponders. Survey Sampling International tracked participation via unique identification numbers to prevent duplicate uses of the same link to participate. Nosotros recruited for a 3-week period in fall 2010. On completion, participants were entered into both an instant-win contest and a monthly drawing administered by Survey Sampling International for modest prizes.
Pattern of the Study
Respondents read a revised version of a curt vignette previously used in a report of interactive graphics [28] in which they imagined being given a diagnosis of thyroid cancer and discussing 2 types of hypothetical external beam radiation treatments with their doctor. The two treatments, called focal beam therapy and crossed beam therapy, were each briefly described and and then presented as existence equally effective in treating the patient'due south type of thyroid cancer. Each therapy likewise had the same risk (11%) of causing one side issue: fatigue. However, the treatments were described as differentially likely to cause a second side effect, mouth and pharynx problems: one therapy caused mouth and pharynx problems in 16% of patients, whereas the other therapy caused mouth and throat bug in only 14% of patients. We randomly assigned which therapy had the college risk to prevent our scenario descriptions from biasing our results. The scenario referred to a less common disease (thyroid cancer, instead of breast or prostate cancer) and included hypothetical types of radiation axle therapy in order to minimize respondent preconceptions about handling options or their associated risks.
Our primary inquiry question was to determine whether different graphical formats would increase respondents' power to recognize which treatment choice was less risky (choice accuracy). To do and so, we implemented a quasi-factorial design to experimentally vary the type of hazard graphic used to nowadays each of the two side effects in a side-by-side presentation. Participants were randomly assigned to ane of 10 experimental conditions summarized in Table 1.
Tabular array 1
Experimental conditions.
| Version | Animated? | Initial organization | Animation type | |||
| Congenital? | Settle into grouping? | Shuffle? | ||||
| V1 | Static grouped | No | Grouped | NAa | NA | NA |
| V2 | Static scattered | No | Scattered | NA | NA | NA |
| V3 | Scatter, settles | Yes | Scattered | No | Yes | No |
| V4 | Grouped, congenital | Yes | Grouped | Yep | NA | No |
| V5 | Scatter, built | Yeah | Scattered | Yep | No | No |
| V6 | Scatter, built, settles | Yep | Scattered | Aye | Yes | No |
| V7 | Besprinkle, machine shuffles | Yep | Scattered | No | No | Automatic |
| V8 | Scatter, automobile shuffles, settles | Yes | Scattered | No | Yep | Automatic |
| V9 | Scatter, user shuffles | Yes | Scattered | No | No | User controlled |
| V10 | Scatter, user shuffles, settles | Yes | Scattered | No | Yep | User controlled |
Approximately 20% of participants in full were assigned to 1 of 2 static display weather. Participants in the baseline status (V1: static grouped) saw side-by-side static icon arrays (a x × x matrix of blocks) in which all of the colored blocks used to represent event occurrence (ie, experience of fatigue, or mouth or pharynx problems) were grouped at the lesser of the display (Figure 1). A second group of participants (V2: static scattered) viewed a scattered static display in which the outcome icons were randomly distributed within the matrix to help convey the underlying random distribution of events. Previous research has suggested that this type of scattered brandish does, in fact, assistance convey randomness, but at the expense of a sense of the magnitude of the take a chance [3,xi,22,25]. We included this design factor to explore whether nosotros might achieve the best of both worlds past displaying randomness without sacrificing a sense of quantity.
Icon arrays (version V1: static grouped) displaying the risk of mouth and throat problems for both hypothetical treatments.
The remaining fourscore% of participants viewed 1 of 8 blithe displays that included 1 or more than animations based on the unlike types of potentially useful motion cues discussed above. Some groups (V4, V5, and V6) viewed congenital displays that were either grouped or scattered according to the above description. In these versions, participants initially viewed an empty assortment (ie, all icons were grayness) merely then saw colored icons representing risk events appear sequentially (1 every 450 milliseconds) in each of the 2 graphs until the concluding level of risk was reached. Note that due to different levels of gamble betwixt the ii handling options, this animation meant that, for the display of oral cavity and pharynx trouble risks, colored blocks finished actualization in 1 of the 2 arrays before the other one, creating a motion cue to reinforce which handling had a larger risk.
Participants in the scattered graphs conditions (built or not) were further subdivided based on whether they saw two other animations. Get-go, some participants in scattered conditions saw the scattered hazard elements remain still (V2 and V5); others (V7 and V8) saw these colored blocks shuffle (redisplay themselves repeatedly in new randomly generated positions) in a manner similar to the dynamic random visual used by Han et al [25] to promote subjective uncertainty; and others (V9 and V10) were required to press a button that acquired the blocks to shuffle a few times before they could proceed. We included this last condition to test whether having user control of the random scattering procedure would impact participants' perceptions of the take chances. 2nd, while some participants saw but the pictographs with the risk scattered (V2, V5, V7, and V9), others initially saw a scattered display that then showed the colored units settling down toward the bottom of the array and then arranging themselves into the aforementioned grouping seen by the grouped weather condition. In other words, we used blitheness in these settle weather condition (V3, V6, V8, and V10) to enable participants to detect both an initial scattered visual (which may promote agreement of randomness) and an ending grouped visual (to facilitate assessment of risk magnitude).
All survey versions were pretested by study squad members for functionality and to estimate time to complete prior to survey launch. Nosotros also randomly varied which handling was shown on the left as well as what color was used to refer to each treatment to forestall lodge effects. Example movies of V4 (grouped, congenital), V6 (scatter, built, settles), and V9 (besprinkle, user shuffles), which collectively demonstrate all of the animation types, are available as multimedia appendices (see Multimedia Appendix i, Multimedia Appendix 2, and Multimedia Appendix 3).
On entering our survey, participants were given an introduction page that explained the purpose of the study, the bearding nature of the research, and the expected time to take the survey. The survey consisted of 57 total questions over 20 webpages (betwixt 0 and 9 questions per folio). Participants as well completed betwixt iii and 8 webpages of survey materials for unrelated studies (cantankerous-randomized across all 10 arms of this study) after completing the master and secondary measures for this written report merely earlier completing individual divergence measures (eg, numeracy) and demographics. This design received institutional review board exempt status approval as bearding survey inquiry.
Measures and Covariates
Our main event measure was the preferred treatment pick (focal beam or crossed beam). Nosotros also asked respondents two gist cognition questions in which they were to betoken which therapy had a higher risk of fatigue (both equal), or mouth or throat problems (which varied based on randomization).
We asked iii graph evaluation items to evaluate user preferences about the different gamble graphics. These questions asked respondents to use a ten-point Likert-blazon scale to rate how well the graphs described the take a chance of different side effects, how helpful the graphs were, and whether the respondent would like to see chance information in this type of graph. Our a priori intention was to combine these ratings into a 3-item calibration.
Because aplenty evidence exists that fifty-fifty highly educated adults can have poor numeracy skills (ie, facility and comfort with quantitative wellness data such as risk statistics) [29-31], all study participants also completed the Subjective Numeracy Scale (SNS) [32], a validated measure out of quantitative ability and preference for receiving information in numerical form. The SNS has previously been shown to correlate with the power to recall and cover both textual and graphical risk communications [33,34]. A participant's SNS score is calculated equally his or her mean rating beyond the 8 SNS questions and ranges from 1 (least numerate) to 6 (most numerate).
We also assessed participants' demand for cognition using a shortened version (7 of xviii questions) of the Need for Noesis Calibration [35] due to concerns about survey duration. Responses were averaged to create a unmarried scale.
Statistical Analyses
Since our master goal for this written report was to explore the upshot of different types of animation on treatment choices, primary analyses focused on the percentage of accurate choices (ie, percentage choosing the handling with the everyman risk profile), knowledge accuracy, and graph evaluation ratings. To calculate the significance of the observed variations, nosotros used logistic regression models (linear regressions for graph ratings) that included graph version (with V1: static grouped as reference), also as SNS score and Demand for Cognition Scale score as covariates. We also analyzed subsets for the effect of numeracy by splitting at the median, grouping participants into lower-numeracy and higher-numeracy subgroups, and rerunning the logistic regression analyses for each numeracy subgroup (while nonetheless controlling for demand for cognition). All analyses were performed using Stata version 11 [36], and all tests of significance were 2-sided and used alpha = .05.
Results
Sample Description
In total, 6240 people historic period 21 years and older reached the survey website and viewed the commencement content folio. Of these, 38 reported having a diagnosis of thyroid cancer and were excluded equally having preexisting knowledge of related treatment options, leaving 6202 possible participants.
Overall, 4198 (67.vii%) of participants completed the entire survey (range across the x survey versions: 64%–71%), including questions on demographics, which came toward the end of the survey instrument. Nosotros restricted our analyses to this subsample. Characteristics of those participants who answered each demographic question are reported in Table 2. We observed a wide range of educational achievement, with 1540 participants (36.7%) having a bachelor's or college college degree but also 809 (19.three%) having completed high school or less education. The SNS numeracy measure showed high reliability (Cronbach'south alpha = .86), as did the shortened need for cognition measure (Cronbach alpha = .83). Mean SNS score was four.30, with substantial variation (range 1.five–vi.0; SD ane.03). Considering questions virtually participants' demographics came at the terminate of the survey, we practice not know whether the demographics of those who dropped out differed from those who completed the survey.
Table 2
Participant demographic characteristics (n = 4198)a.
| Characteristic | Category | Frequency (%) | Mean (SD) |
| Age (years) | 21–29 | 698 (16.seven%) | 49.1 (16.1) |
| 30–39 | 663 (15.8%) | ||
| 40–49 | 588 (14.0%) | ||
| l–59 | 848 (20.ii%) | ||
| 60–69 | 1035 (24.vii%) | ||
| 70+ | 359 (8.6%) | ||
| Gender | Male | 1936 (46.2% | |
| Female | 2255 (53.viii%) | ||
| Ethnicity | Hispanic (any race) | 485 (11.7%) | |
| Raceb | White | 3267 (78.0%) | |
| African American | 592 (14.1%) | ||
| All other | 384 (9.ii%) | ||
| Education | < High school | 86 (ii.1%) | |
| Loftier school only | 723 (17.3%) | ||
| Some higher/trade | 1832 (43.8%) | ||
| Available'due south caste | 1017 (24.3%) | ||
| Master'due south/doctorate | 523 (12.5%) | ||
| Subjective Numeracy Scale score | 1.00–one.99 | 102 (2.4%) | four.thirty (1.03) |
| 2.00–2.99 | 337 (8.1%) | ||
| 3.00–3.99 | 970 (23.3%) | ||
| iv.00–four.99 | 1491 (35.eight%) | ||
| 5.00–5.99 | 1179 (28.iii%) | ||
| 6.00 | 91 (ii.ii%) |
Treatment Choice Accuracy
Tabular array three reports the percentage of participants who correctly chose the ascendant treatment choice (ie, the therapy with the lower risk of oral cavity and throat problems), stratified by numeracy level. Lower-numeracy participants selected the all-time treatment option about 75% of the fourth dimension, and varying the graphic used to brandish the side effect risks did non result in whatever significant differences in treatment choices based on the logistic regression analysis. At that place was much more variation, notwithstanding, among higher-numeracy participants. While participants in the baseline V1 group (static grouped) fabricated the correct treatment choice about 85% of the time, participants in most of the other experimental conditions were less likely to pick the best treatment choice. In the logistic regression assay, nosotros observed significantly different option rates for participants in all of the scattered merely not settled groups (V2, V5, V7, and V9) as well equally V10 (scatter, user shuffles, settles). Nearly of the remaining experimental groups as well were less likely than the V1 control group to cull the best treatment, although the differences were not statistically significant. The only group that was more likely (albeit not statistically significant) than the static grouped condition to cull optimally was V4 (built, grouped).
Tabular array 3
Percentage choosing best treatment choice, by graph version and respondent numeracy.
| Version | Lower numeracy | Higher numeracy | |||||
| % | ORa (95% CIb) | P value | % | OR (95% CI) | P value | ||
| V1 | Static grouped | 74.3 | Reference | – | 84.8 | Reference | – |
| V2 | Static scattered | 72.two | 0.90 (0.59–i.36) | .62 | 76.vi | 0.58 (0.34–1.00) | .05 |
| V3 | Besprinkle, settles | 75.v | one.04 (0.68–1.59) | .85 | 80.0 | 0.72 (0.42–1.24) | .23 |
| V4 | Grouped, built | 75.2 | 1.02 (0.67–one.55) | .93 | 86.3 | 1.xiv (0.64–2.04) | .66 |
| V5 | Scatter, congenital | 68.3 | 0.73 (0.48–one.11) | .fourteen | 74.4 | 0.53 (0.31–0.ninety) | .02 |
| V6 | Besprinkle, congenital, settles | 77.three | i.14 (0.74–1.77) | .55 | 81.0 | 0.77 (0.44–one.34) | .35 |
| V7 | Scatter, auto shuffles | 72.3 | 0.87 (0.56–i.34) | .52 | 74.2 | 0.52 (0.31–0.89) | .02 |
| V8 | Scatter, motorcar shuffles, settles | 76.4 | 1.08 (0.70–1.67) | .72 | 82.9 | 0.87 (0.50–1.50) | .61 |
| V9 | Scatter, user shuffles | 72.9 | 0.92 (0.sixty–i.40) | .69 | 67.vi | 0.37 (0.22–0.63) | <.001 |
| V10 | Scatter, user shuffles, settles | 73.3 | 0.94 (0.62–1.43) | .77 | 75.8 | 0.56 (0.33–0.96) | .03 |
Gist Noesis Accurateness
Tabular array iv reports the percent of participants (by graph version and numeracy level) who accurately identified that both treatments had equal risks of fatigue. Here, the design of results is quite similar for both lower- and higher-numeracy respondents. In both numeracy groups, the baseline group (V1) that saw static grouped graphs had either the highest or next-highest level of noesis. Knowledge was similar to the baseline in V4 (grouped, congenital) for lower-numeracy participants, and in V8 (scatter, shuffles, settles) for all participants. Participants in the remaining groups all showed lower cognition rates, with statistically significant differences observed in the logistic regression analyses for V2, V5 (college numeracy only), V7 (lower numeracy only), V9 and V10 (college numeracy simply).
Table iv
Percent correctly identifying that both treatments had an equal risk of fatigue, past graph version and respondent numeracy.
| Version | Lower numeracy | Higher numeracy | |||||
| % | ORa (95% CIb) | P value | % | OR (95% CI) | P value | ||
| V1 | Static grouped | 78.viii | Reference | – | 86.3 | Reference | – |
| V2 | Static scattered | 68.8 | 0.59 (0.38–0.91) | .02 | 73.three | 0.44 (0.26–0.75) | .003 |
| V3 | Scatter, settles | 71.vi | 0.67 (0.43–1.03) | .07 | 81.ii | 0.69 (0.39–1.22) | .21 |
| V4 | Grouped, built | 79.3 | ane.01 (0.64–1.60) | .97 | 82.1 | 0.74 (0.42–1.32) | .31 |
| V5 | Scatter, congenital | 74.0 | 0.75 (0.48–1.eighteen) | .21 | 75.0 | 0.49 (0.28–0.84) | .01 |
| V6 | Scatter, congenital, settles | 75.3 | 0.80 (0.51–i.26) | .34 | 83.i | 0.79 (0.44–i.43) | .44 |
| V7 | Scatter, machine shuffles | 70.9 | 0.64 (0.forty–one.00) | .05 | 84.1 | 0.85 (0.47–1.54) | .lx |
| V8 | Besprinkle, machine shuffles, settles | 78.ii | 0.94 (0.59–i.49) | .79 | 86.2 | 0.99 (0.55–ane.79) | .98 |
| V9 | Besprinkle, user shuffles | 66.1 | 0.52 (0.34–0.80) | .003 | 70.two | 0.38 (0.22–0.64) | <.001 |
| V10 | Scatter, user shuffles, settles | 75.3 | 0.81 (0.52–i.27) | .36 | 77.7 | 0.56 (0.32–0.98) | .04 |
The blueprint of results was quite similar for accurately identifying the treatment with the college rates of mouth and pharynx bug (Table 5), with lower noesis rates observed for versions V2, V5, V7, and V9 in particular. However, people who saw the V4 (grouped, built) risk graphic had somewhat college knowledge than those who saw the baseline V1 (static grouped) version, although this difference was non significant for either lower- or higher-numeracy participants.
Table 5
Percentage correctly identifying the treatment with the college risk of mouth and throat problems, by graph version and respondent numeracy.
| Version | Lower numeracy | Higher numeracy | |||||
| % | ORa (95% CIb) | P value | % | OR (95% CI) | P value | ||
| V1 | Static grouped | 46.nine | Reference | – | 65.one | Reference | – |
| V2 | Static scattered | 44.9 | 0.92 (0.64–ane.34) | .68 | 55.7 | 0.68 (0.44–1.04) | .07 |
| V3 | Scatter, settles | 45.5 | 0.93 (0.64–1.33) | .68 | 62.3 | 0.89 (0.58–1.36) | .59 |
| V4 | Grouped, built | 54.ix | 1.35 (0.94–1.95) | .11 | 69.8 | 1.25 (0.81–1.95) | .31 |
| V5 | Scatter, congenital | 42.4 | 0.81 (0.55–1.19) | .29 | 55.0 | 0.67 (0.43–ane.02) | .06 |
| V6 | Scatter, congenital, settles | 50.9 | 1.15 (0.79–1.67) | .46 | 62.9 | 0.92 (0.59–one.42) | .70 |
| V7 | Scatter, auto shuffles | 39.4 | 0.71 (0.48–i.05) | .09 | 52.six | 0.lx (0.39–0.93 | .02 |
| V8 | Scatter, machine shuffles, settles | 53.0 | ane.24 (0.85–1.lxxx | .26 | 64.9 | 0.99 (0.65–1.52) | .96 |
| V9 | Scatter, user shuffles | 34.6 | 0.59 (0.41–0.87) | .007 | 48.6 | 0.51 (0.33–0.78) | .002 |
| V10 | Besprinkle, user shuffles, settles | 42.9 | 0.84 (0.58–i.22) | .36 | 54.viii | 0.76 (0.50–1.16) | .21 |
Graph Evaluation Ratings
As planned, nosotros combined our three graph evaluation rating questions into a three-particular scale based on the average rating, which had high reliability (Cronbach's alpha = .93). Table 6 reports the hateful graph evaluation ratings for each graph type. Here, a clear pattern emerges: consistent with the previous results for cognition accuracy and treatment selection accurateness, participants in 2 conditions, V1 (static grouped) and V4 (grouped, built), reported the highest evaluation ratings for both lower- and higher-numeracy participants. Participants in the V3 (besprinkle, settles) and V6 (scatter, built, settles) groups had slightly lower ratings, though the differences were not statistically significant. The remaining 6 graph types received significantly lower graph evaluation ratings in the linear regression models, with all differences highly significant (all P < .001) versus the baseline static grouped status.
Tabular array 6
Graph evaluation ratingsa, by graph version and respondent numeracy.
| Version | Lower numeracy | College numeracy | |||||
| Mean | Coefficientb (95% CI)c | P value | Mean | Coefficient (95% CI) | P value | ||
| V1 | Static grouped | v.99 | Reference | – | vii.24 | Reference | – |
| V2 | Static scattered | iv.68 | –i.30 (–1.75 to –0.86) | <.001 | 5.07 | –2.17 (–2.68 to –1.65) | <.001 |
| V3 | Besprinkle, settles | 5.72 | –0.29 (–0.73 to 0.15) | .19 | 6.72 | –0.51 (–1.03 to 0.00) | .05 |
| V4 | Grouped, congenital | half-dozen.31 | 0.thirty (–0.14 to 0.75) | .19 | half-dozen.98 | –0.25 (–0.77 to 0.26) | .33 |
| V5 | Scatter, built | iv.89 | –1.12 (–1.59 to –0.66) | <.001 | 5.60 | –1.64 (–2.15 to –1.12) | <.001 |
| V6 | Besprinkle, built, settles | five.90 | –0.12 (–0.57 to 0.34) | .62 | 6.81 | –0.43 (–0.95 to 0.09) | .11 |
| V7 | Scatter, auto shuffles | 4.02 | –2.01 (2.48 to –i.55) | <.001 | 4.60 | –2.64 (–3.xvi to –2.12) | <.001 |
| V8 | Besprinkle, machine shuffles, settles | 5.27 | –0.75 (–1.20 to –0.29) | <.001 | 6.08 | –ane.sixteen (–1.66 to –0.65) | <.001 |
| V9 | Scatter, user shuffles | 4.09 | –ane.91 (–2.36 to –1.46) | <.001 | 4.77 | –2.47 (–2.98 to –ane.95) | <.001 |
| V10 | Scatter, user shuffles, settles | four.88 | –1.12 (–1.57 to –0.67) | <.001 | 5.34 | –one.90 (–two.41 to –1.39) | <.001 |
Word
Chief Results
In this study, we evaluated 8 different animated icon array take a chance graphics that incorporated different combinations of 3 basic animations: building risk 1 unit at a fourth dimension, settling scattered risk into a grouping to ease assessment of magnitude, and shuffling scattered risk to reinforce randomness. When compared against the type of static, grouped icon pictographs that take been previously shown to support high levels of risk knowledge [ten], the animated graphics consistently fell short. No animated display resulted in significantly improved knowledge or evaluation ratings versus the static grouped control display, and significant deficits were observed for most of the animated versions. Just the building animation that presented the colored icons representing risk events 1 at a fourth dimension (eg, V4: grouped, built) showed even the slightest promise of improving understanding, and this was not consistent across result measures.
Consistent with some prior research [22], scattered hazard displays mostly resulted in poorer knowledge and graph evaluation ratings. Shuffling the outcome icons oftentimes made things worse and dramatically lowered evaluation ratings. Calculation an animation to allow a scattered hazard to settle into a grouping did help, though such animations did not convey whatever advantages over displays that started in a grouped orientation to begin with. However, a parallel report from our enquiry group (personal communication with HO Witteman, et al, December 8, 2011) suggested that animated displays of scattered icons that include both the building and settling animations may increase sensitivity to differences in risk magnitude. In add-on, Han et al found that a dynamic scattered icon assortment resulted in increased subjective doubt near cancer risks [25]. If and then, a scatter-plus-settle animation may have practical value even if information technology does not confer intrinsic improvements in risk knowledge or preference.
Limitations
Our study has several key limitations. First, nosotros recruited participants from an online survey console and gave them a hypothetical medical treatment scenario. As a event, participants may well have been less motivated to learn nigh the risk levels and more than hands distracted by the animations. This account is consistent with our findings that increased complication of animations (eg, shuffling) particularly decreased participant noesis accuracy. It is certainly possible that patients facing bodily medical treatment decisions would exist better focused on the risk knowledge and, equally a result, take smaller deficits or perhaps improvements in understanding over static graphs. Nosotros notation, however, we plant our strongest variations not in knowledge, but in our participants' graph evaluation ratings. Additionally, it is possible that patients facing actual medical handling decisions would be more than susceptible to distraction due to the complexity of animations considering of increased cerebral burden or stress brought about by their affliction. Although it is plausible that more complicated, "cooler" animations might yield higher evaluation ratings, especially amongst participants who were only taking a survey and non making real medical decisions, in fact nosotros observed the opposite design: the most complex graphics were least preferred past our study participants.
2d, the task used in our experiment required comparing two risks. Animated graphs were presented side-past-side, making it possible that it was the dual presentation of animation, rather than the animation per se, that hampered the chatty effectiveness of the graphics. We selected a comparison task because many risk evaluation and decision processes require balancing competing risks and benefits, making this a plausible application for such graphics. It may be that, although the animation was harmful in this context, it might withal hold value in the context of a single risk, or when presenting i risk at a time.
3rd, our analyses focused here on differences between higher-numeracy and lower-numeracy participants. All the same, recent research has shown that interpretation of hazard graphics is likewise mediated past graphical literacy skills, which are only moderately correlated with numeracy [37,38]. Information technology is possible that some of the effects we aspect to numeracy are in fact graphical literacy effects. While we did non collect graphical literacy measures here (considering these data were nerveless prior to publication of the scale), we intend to mensurate both numeracy and graphical literacy in follow-upwards inquiry.
Comparison With Prior Piece of work
Our study is placed in the context of previous piece of work, most notably Tversky et al'due south 2002 all-encompassing review of animated graphics [23]. Using their delineation, the job of specifying a dominant option in our study is made more challenging by the fact that wellness risks are not inherently visuospatial concepts. In their review, the authors noted mixed furnishings of animated graphics, and suggested that fair comparisons between animated graphics and static graphics require information content that can exist adequately conveyed in the static course. This was the case in our context, and this may explain the lack of benefit demonstrated, similar to previous studies where static graphics were able to finer convey information (eg, [39]). Tversky et al [23] also reviewed other experimental studies, based on which they argued, reasonably, that the benefits of some animated graphics may exist owing to the additional information content that could be conveyed via the blithe movement. Therefore, potential benefits of animation may exist, merely are concentrated in contexts in which static graphics cannot communicate all the information of the blithe versions. The near equivalence of some of our blithe versions in performance measures suggests that further inquiry is needed to investigate their potential for conveying additional information that is hard to convey in static graphics alone, for example, the random nature of events in health risks.
It is also of import to notation that our task in this study involved the comparison of two risks. This is a mutual effect in assessing health risks and making decisions appropriately. However, this may have introduced problems by dividing participants' attending between ii areas of the screen, both of which were moving simultaneously. This may reflect the fact that people find focusing on competing animations difficult [17].
Previous piece of work suggests an interaction between domain knowledge and the effects of animation. For case, animation helped more than avant-garde students acquire to transform graphs of simple mathematical functions into more complex functions but hindered novice students [24]. Our study, on the other hand, suggests that the functioning of people with lower numeracy, who might be expected to accept more trouble with blitheness, did non differ beyond conditions, whereas those with higher numeracy showed a decline in operation with the addition of animation (while nonetheless maintaining higher overall rates of accuracy and knowledge). Nosotros speculate that this outcome depends on whether the blitheness builds on prior cognition (as may, for example, exist the case with animated displays of physics bug) or distracts from people's ability to perform required tasks. Contempo work has shown that more numerate people tend to count icons in displays such as ours and derive their sense of risk magnitude from that process [40]. In our experiments, the attention-grabbing nature of the animation may have prevented higher-numeracy participants from applying this learning strategy, thereby degrading their performance.
It is also worth clarifying the distinction between the animated risk graphics tested hither and interactive graphing tasks in which the bulletin recipient has to alter the visual display to evidence or uncover risk data. Researchers have tested the impact of having people adapt bar graphs [26] or pictographs [28] to display provided risk statistics. However, these studies take had decidedly mixed effects, with the pictograph study finding that the interactive task significantly decreased people's power to identify a dominant treatment selection [28]. Another recent study used an exploratory chore in which participants clicked in a matrix until they uncovered a hazard event. This task elicited more emotional responses than static graphics, increasing qualitative statements of business organization nigh large risks or relief about pocket-size ones. However, a subsequent experimental study found no overall effect of interactive versus static graphic type on take a chance estimates or risk feelings, though it did reduce disparities attributable to differences in numeracy [27]. Such mixed findings are mirrored in enquiry on other forms of interactivity in health education such equally video games [41] and immersive 3-dimensional environments [42].
There are likewise considerable parallels between our findings regarding the potentially distracting effects of animation and recent evidence in other data communication contexts that less can exist more—that is, that simpler, more focused data presentations can result in improved agreement. For example, people are better able to identify preferred hospitals out of a set when tabular presentations of information excluded determination-irrelevant information [43]. Similarly, agreement of cancer recurrence risks and decisions about adjuvant therapies can be improved by removing information about irrelevant options [12], excluding redundant bloodshed statistics [44], and presenting relevant information one piece at a time [34]. Both these studies and our present investigation serve equally reminders that people'due south ability to process multiple things at once is quite limited, and thus risk communications need to ensure that the user'due south attention is drawn narrowly and specifically to the near of import piece of data or visual cue. In terms of animation, both our study and Tversky and colleagues' [23] review imply that static graphics may be preferable to animated versions as long as the static displays fully present the most decision-relevant information.
Conclusions
If the goal of a health adventure communication is to ensure that patients understand the magnitude of risk and are able to make appropriate comparisons between ii risks, our work suggests that the use of blitheness to provide motion cues in computer-administered run a risk graphics is fraught with peril. Nosotros tested 8 combinations of 3 cadre animations that we believed might back up amend understanding or satisfaction, but our results showed that these animations were at best unhelpful and often significantly detrimental. Static pictographs that grouped event icons at the lesser of the array consistently resulted in optimal treatment choices, higher knowledge accurateness, and better graph evaluation ratings. This finding adds to the growing literature supporting their use as best exercise in many patient instruction contexts.
Computer-based communications are likely to be the fashion of selection for many futurity efforts to educate patients about health risks that require preventive action and medical handling decisions. Such technologies offer many new types of visual (and auditory) cues that could be used to reinforce risk data, and in that location are oftentimes pressures to utilise the latest "bells and whistles" in such applications. Our research, however, sounds a cautionary annotation.
Ultimately, effective patient decision making requires specific types of agreement. At a minimum, patients need to realize that a risk could occur and exist able to identify which actions are more or less probable to lead to preferred outcomes. While we remain hopeful that certain types of animation might be useful in specific take chances communication contexts (eg, by using building animations to show accumulation of risk over time), our nowadays efforts did non back up quality decision making. More research is clearly needed to evaluate different types of move cues and to identify which animations lead to ameliorate results versus the features of those that do not. In the meantime, nosotros reiterate the finding from our previous work in interactive graphics [28]: decision assistance designers should proceed with caution when considering the use of flashy run a risk graphics.
Acknowledgments
This inquiry was supported past a grant from the Foundation for Informed Medical Decision Making (IIG 0126-1). Dr Zikmund-Fisher is supported by a career development award from the American Cancer Social club (MRSG-06-130-01-CPPB). The funding agreements ensured the authors' independence in designing the study, interpreting the information, and publishing the report. The authors give thanks Mark Swanson for programming the Wink-based animations for this report.
Abbreviations
| SNS | Subjective Numeracy Calibration |
Multimedia Appendix 1
MP4 flick showing the V4 (Grouped, Built) blitheness of the gamble of mouth and throat problems.
Multimedia Appendix ii
MP4 picture showing the V6 (Besprinkle, Built, Settles) animation of the risk of rima oris and pharynx problems.
Multimedia Appendix 3
MP4 film showing the V9 (Besprinkle, User Shuffles) animation of the risk of rima oris and throat problems.
Footnotes
Conflicts of Interest:
None declared.
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Articles from Journal of Medical Internet Inquiry are provided here courtesy of Gunther Eysenbach
Source: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3409597/
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