The potential of the Internet for health communication: The use of an interactive on-line tool for diabetes risk prediction

Holmberg, Christine; Harttig, Ulrich; Schulze, Matthias B.

doi:10.1016/j.pec.2010.04.021

Cited by 14 publications

(15 citation statements)

References 39 publications

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“…For example, one study of an online diabetes risk calculator showed that higher diabetes risk was associated with a greater number of risk recalculations. 14 One possible interpretation of this effect is that high-risk participants were looking for a better number, or were trying to determine whether the factors that led to their risk estimate felt legitimate. In another study, many participants reported the same perceived diabetes risk before and after receiving their personalized risk estimate, even when the risk calculator provided an estimate that was different from their own estimate.…”

Section: Introductionmentioning

confidence: 99%

Belief in numbers: When and why women disbelieve tailored breast cancer risk statistics

Scherer

Ubel

McClure

et al. 2013

Patient Education and Counseling

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Objective To examine when and why women disbelieve tailored information about their risk of developing breast cancer. Methods 690 women participated in an online program to learn about medications that can reduce the risk of breast cancer. The program presented tailored information about each woman’s personal breast cancer risk. Half of women were told how their risk numbers were calculated, whereas the rest were not. Later, they were asked whether they believed that the program was personalized, and whether they believed their risk numbers. If a woman did not believe her risk numbers, she was asked to explain why. Results Beliefs that the program was personalized were enhanced by explaining the risk calculation methods in more detail. Nonetheless, nearly 20% of women did not believe their personalized risk numbers. The most common reason for rejecting the risk estimate was a belief that it did not fully account for personal and family history. Conclusions The benefits of tailored risk statistics may be attenuated by a tendency for people to be skeptical that these risk estimates apply to them personally. Practice Implications Decision aids may provide risk information that is not accepted by patients, but addressing the patients’ personal circumstances may lead to greater acceptance.

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Section: Introductionmentioning

confidence: 99%

Belief in numbers: When and why women disbelieve tailored breast cancer risk statistics

Scherer

Ubel

McClure

et al. 2013

Patient Education and Counseling

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“…An important example is online risk assessments that identify people at risk of diseases (Fanaian et al, 2010;Heikes, Eddy, Arondekar, & Schlessinger, 2008;Nielen et al, 2010;Sheridan, Pignone, & Mulrow, 2003;Witteman, Zikmund-Fisher, Waters, Gavaruzzi, & Fagerlin, 2011). Although the aim of such assessments is not always formally described as facilitating health decisions, most experts involved agree that this is important, besides the more general aim of creating risk awareness (Holmberg, Harttig, Schulze, & Boeing, 2011;Ruiz et al, 2013;Sheridan et al, 2010), or specific aims focused on health behaviour, for example motivating people to adopt preventive behaviour (Holmberg et al, 2011;Koelewijn-van Loon et al, 2009;Sheridan et al, 2010), and improving population health (Colkesen et al, 2011;Holmberg et al, 2011;Jacobson, Gutkin, & Harper, 2006;Ruiz et al, 2013). In the Netherlands, the 'Prevention Consultation for Cardio-metabolic risk' has been introduced in GP and occupational health care (Dekker et al, 2011;Van der Meer et al, 2013).…”

Section: What Does This Study Add?mentioning

confidence: 99%

Barriers in using cardiometabolic risk information among consumers with low health literacy

Damman

Bogaerts

Dongen

et al. 2015

British J Health Psychol

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What is already known on this subject? Online disease risk assessments have become widely available internationally. People with low SES and health literacy tend to participate less in health screening. Risk information is difficult to understand, yet little research has been carried out among people with low health literacy. What does this study add? People with low health literacy do not optimally use risk information in an online cardiometabolic risk assessment. The texts provided in the cardiometabolic risk assessment do not suit to their existing knowledge. The typical risk communication (numbers, bar graph, verbal label) seems to provoke undervaluation of risk.

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“…Anyone with Internet access, a Web browser, some interest in their future health, and five minutes to spare can enter a few pieces of information about themselves and receive an assessment of their risk of human immunodeficiency virus infection [1], breast cancer [2], heart attack [3,4], diabetes [5,6], prostate cancer recurrence [7,8], or one of multiple options from a broad array of common conditions [9]. Online risk calculators have been heralded as a means to disseminate individualized risk prediction scores with an aim toward increased understanding of personal risk, improved health behavior, higher-quality decision making, and, ultimately, better population health [10]. …”

Section: Introductionmentioning

confidence: 99%

Risk Estimates From an Online Risk Calculator Are More Believable and Recalled Better When Expressed as Integers

Witteman¹,

Zikmund‐Fisher²,

Waters³

et al. 2011

J Med Internet Res

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BackgroundOnline risk calculators offer different levels of precision in their risk estimates. People interpret numbers in varying ways depending on how they are presented, and we do not know how the number of decimal places displayed might influence perceptions of risk estimates.ObjectiveThe objective of our study was to determine whether precision (ie, number of decimals) in risk estimates offered by an online risk calculator influences users’ ratings of (1) how believable the estimate is, (2) risk magnitude (ie, how large or small the risk feels to them), and (3) how well they can recall the risk estimate after a brief delay.MethodsWe developed two mock risk calculator websites that offered hypothetical percentage estimates of participants’ lifetime risk of kidney cancer. Participants were randomly assigned to a condition where the risk estimate value rose with increasing precision (2, 2.1, 2.13, 2.133) or the risk estimate value fell with increasing precision (2, 1.9, 1.87, 1.867). Within each group, participants were randomly assigned one of the four numbers as their first risk estimate, and later received one of the remaining three as a comparison.ResultsParticipants who completed the experiment (N = 3422) were a demographically diverse online sample, approximately representative of the US adult population on age, gender, and race. Participants whose risk estimates had no decimal places gave the highest ratings of believability (F 3,3384 = 2.94, P = .03) and the lowest ratings of risk magnitude (F 3,3384 = 4.70, P = .003). Compared to estimates with decimal places, integer estimates were judged as highly believable by 7%–10% more participants (χ2 3 =17.8, P < .001). When comparing two risk estimates with different levels of precision, large majorities of participants reported that the numbers seemed equivalent across all measures. Both exact and approximate recall were highest for estimates with zero decimals. Odds ratios (OR) for correct approximate recall (defined as being within 50% of the original estimate) were, for one decimal place, OR = 0.65 (95% CI 0.49–0.86), for two decimal places, OR = 0.70 (95% CI 0.53–0.94), and for three decimal places, 0.61 (95% CI 0.45–0.81). Exact recall showed a similar pattern, with larger effects.ConclusionsThere are subtle but measurable differences in how people interpret risk estimates of varying precision. Adding decimal places in risk calculators offers little to no benefit and some cost. Rounding to the nearest integer is likely preferable for communicating risk estimates via risk calculators so that they might be remembered correctly and judged as believable.

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The potential of the Internet for health communication: The use of an interactive on-line tool for diabetes risk prediction

Cited by 14 publications

References 39 publications

Belief in numbers: When and why women disbelieve tailored breast cancer risk statistics

Belief in numbers: When and why women disbelieve tailored breast cancer risk statistics

Barriers in using cardiometabolic risk information among consumers with low health literacy

Risk Estimates From an Online Risk Calculator Are More Believable and Recalled Better When Expressed as Integers

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