The effect of different cardiovascular risk presentation formats on intentions, understanding and emotional affect: a randomised controlled trial using a web-based risk formatter (protocol)

Does a multi-component intervention including pictorial risk communication about subclinical atherosclerosis improve perceptions of cardiovascular disease risk without deteriorating efficacy beliefs?

BACKGROUND

Pictorial communication about subclinical atherosclerosis can improve cardiovascular disease (CVD) risk, but whether it leads to long-term shifts in self-rated CVD risk (risk perception) and beliefs about possibility to influence personal risk (efficacy beliefs) is unknown.

PURPOSE

To study the impact of personalized color-coded and age-related risk communication about atherosclerosis and motivational conversation, compared to traditional risk factor-based communication, on risk perception and efficacy beliefs. Also, whether risk perception increases with message severity.

METHOD

The effect of the pragmatic RCT Visualization of Asymptomatic Atherosclerotic Disease for Optimum Cardiovascular Prevention (VIPVIZA) was analyzed using a linear mixed effects model with risk perception and efficacy believes at 1-year and 3-year follow up as dependent variables. Participants' (n = 3532) CVD risk perception and efficacy beliefs were assessed with visual analog scales (0-10). Fixed effects were group (intervention vs control), time point (1 year or 3 years) and interaction between group and time point. Further, the models were adjusted for corresponding baseline measurement of the dependent variable and a baseline × time point interaction. Effect of pictorial color-coded risk in the intervention group was investigated using a corresponding mixed effects model, but with pictorial risk group (message severity) as exposure instead of intervention group.

RESULTS

After one year, the intervention group rated their CVD risk as higher (m = 0.46, 95% CI 0.32-0.59), with an effect also after 3 years (m = 0.57, 95% CI 0.43-0.70). The effect was consistent in stratified analyses by sex and education. Overall, no effect on efficacy beliefs was observed. In the intervention group, differences in CVD risk perception were found between participants with different color-coded risk messages on atherosclerosis status.

CONCLUSION

Personalized, color-coded and age-related risk communication about atherosclerosis had an effect on risk perception with an effect also after 3 years, whereas overall, no effect on efficacy beliefs was observed.

Risk scoring for the primary prevention of cardiovascular disease

BACKGROUND

The current paradigm for cardiovascular disease (CVD) emphasises absolute risk assessment to guide treatment decisions in primary prevention. Although the derivation and validation of multivariable risk assessment tools, or CVD risk scores, have attracted considerable attention, their effect on clinical outcomes is uncertain.

OBJECTIVES

To assess the effects of evaluating and providing CVD risk scores in adults without prevalent CVD on cardiovascular outcomes, risk factor levels, preventive medication prescribing, and health behaviours.

SEARCH METHODS

We searched the Cochrane Central Register of Controlled Trials (CENTRAL) in the Cochrane Library (2016, Issue 2), MEDLINE Ovid (1946 to March week 1 2016), Embase (embase.com) (1974 to 15 March 2016), and Conference Proceedings Citation Index-Science (CPCI-S) (1990 to 15 March 2016). We imposed no language restrictions. We searched clinical trial registers in March 2016 and handsearched reference lists of primary studies to identify additional reports.

SELECTION CRITERIA

We included randomised and quasi-randomised trials comparing the systematic provision of CVD risk scores by a clinician, healthcare professional, or healthcare system compared with usual care (i.e. no systematic provision of CVD risk scores) in adults without CVD.

DATA COLLECTION AND ANALYSIS

Three review authors independently selected studies, extracted data, and evaluated study quality. We used the Cochrane 'Risk of bias' tool to assess study limitations. The primary outcomes were: CVD events, change in CVD risk factor levels (total cholesterol, systolic blood pressure, and multivariable CVD risk), and adverse events. Secondary outcomes included: lipid-lowering and antihypertensive medication prescribing in higher-risk people. We calculated risk ratios (RR) for dichotomous data and mean differences (MD) or standardised mean differences (SMD) for continuous data using 95% confidence intervals. We used a fixed-effects model when heterogeneity (I²) was at least 50% and a random-effects model for substantial heterogeneity (I² > 50%). We evaluated the quality of evidence using the GRADE framework.

MAIN RESULTS

We identified 41 randomised controlled trials (RCTs) involving 194,035 participants from 6422 reports. We assessed studies as having high or unclear risk of bias across multiple domains. Low-quality evidence evidence suggests that providing CVD risk scores may have little or no effect on CVD events compared with usual care (5.4% versus 5.3%; RR 1.01, 95% confidence interval (CI) 0.95 to 1.08; I² = 25%; 3 trials, N = 99,070). Providing CVD risk scores may reduce CVD risk factor levels by a small amount compared with usual care. Providing CVD risk scores reduced total cholesterol (MD -0.10 mmol/L, 95% CI -0.20 to 0.00; I² = 94%; 12 trials, N = 20,437, low-quality evidence), systolic blood pressure (MD -2.77 mmHg, 95% CI -4.16 to -1.38; I² = 93%; 16 trials, N = 32,954, low-quality evidence), and multivariable CVD risk (SMD -0.21, 95% CI -0.39 to -0.02; I² = 94%; 9 trials, N = 9549, low-quality evidence). Providing CVD risk scores may reduce adverse events compared with usual care, but results were imprecise (1.9% versus 2.7%; RR 0.72, 95% CI 0.49 to 1.04; I² = 0%; 4 trials, N = 4630, low-quality evidence). Compared with usual care, providing CVD risk scores may increase new or intensified lipid-lowering medications (15.7% versus 10.7%; RR 1.47, 95% CI 1.15 to 1.87; I² = 40%; 11 trials, N = 14,175, low-quality evidence) and increase new or increased antihypertensive medications (17.2% versus 11.4%; RR 1.51, 95% CI 1.08 to 2.11; I² = 53%; 8 trials, N = 13,255, low-quality evidence).

AUTHORS' CONCLUSIONS

There is uncertainty whether current strategies for providing CVD risk scores affect CVD events. Providing CVD risk scores may slightly reduce CVD risk factor levels and may increase preventive medication prescribing in higher-risk people without evidence of harm. There were multiple study limitations in the identified studies and substantial heterogeneity in the interventions, outcomes, and analyses, so readers should interpret results with caution. New models for implementing and evaluating CVD risk scores in adequately powered studies are needed to define the role of applying CVD risk scores in primary CVD prevention.

Doctor-patient differences in risk and time preferences: A field experiment

We conduct a framed field experiment among patients and doctors to test whether the two groups have similar risk and time preferences. We elicit risk and time preferences using multiple price list tests and their adaptations to the healthcare context. Risk and time preferences are compared in terms of switching points in the tests and the structurally estimated behavioural parameters. We find that doctors and patients significantly differ in their time preferences: doctors discount future outcomes less heavily than patients. We find no evidence that doctors and patients systematically differ in their risk preferences in the healthcare domain.

Internet-based interventions for the secondary prevention of coronary heart disease

BACKGROUND

The Internet could provide a means of delivering secondary prevention programmes to people with coronary heart disease (CHD).

OBJECTIVES

To determine the effectiveness of Internet-based interventions targeting lifestyle changes and medicines management for the secondary prevention of CHD.

SEARCH METHODS

We searched the Cochrane Central Register of Controlled Trials (CENTRAL), MEDLINE, EMBASE, in December 2014. We also searched six other databases in October 2014, and three trials registers in January 2015 together with reference checking and handsearching to identify additional studies.

SELECTION CRITERIA

Randomised controlled trials (RCTs) evaluating Internet-delivered secondary prevention interventions aimed at people with CHD.

DATA COLLECTION AND ANALYSIS

Two review authors independently assessed risk of bias and extracted data according to the Cochrane Handbook for Systematic Reviews of Interventions. We assessed evidence quality using the GRADE approach and presented this in a 'Summary of findings' table.

MAIN RESULTS

Eighteen trials met our inclusion criteria. Eleven studies are complete (1392 participants), and seven are ongoing. Of the completed studies, seven interventions are broad, targeting the lifestyle management of CHD, and four focused on physical activity promotion. The comparison group in trials was usual care (n = 6), minimal intervention (n = 3), or traditional cardiac rehabilitation (n = 2).We found no effects of Internet-based interventions for all-cause mortality (odds ratio (OR) 0.27, 95% confidence interval (CI) 0.04 to 1.63; participants = 895; studies = 6; low-quality evidence). There was only one case of cardiovascular mortality in a control group (participants = 895; studies = 6). No incidences of non-fatal re-infarction were reported across any of the studies. We found no effects for revascularisation (OR 0.69, 95% CI 0.37 to 1.27; participants = 895; studies = 6; low-quality evidence).We found no effects for total cholesterol (mean difference (MD) 0.00, 95% CI -0.27 to 0.28; participants = 439; studies = 4; low-quality evidence), high-density lipoprotein (HDL) cholesterol (MD 0.01, 95% CI -0.06 to 0.07; participants = 437; studies = 4; low-quality evidence), or triglycerides (MD 0.01, 95% CI -0.17 to 0.19; participants = 439; studies = 4; low-quality evidence). We did not pool the data for low-density lipoprotein (LDL) cholesterol due to considerable heterogeneity. Two out of six trials measuring LDL cholesterol detected favourable intervention effects, and four trials reported no effects. Seven studies measured systolic and diastolic blood pressure; we did not pool the data due to substantial heterogeneity. For systolic blood pressure, two studies showed a reduction with the intervention, but the remaining studies showed no effect. For diastolic blood pressure, two studies showed a reduction with the intervention, one study showed an increase with the intervention, and the remaining four studies showed no effect.Five trials measured health-related quality of life (HRQOL). We could draw no conclusions from one study due to incomplete reporting; one trial reported no effect; two studies reported a short- and medium-term effect respectively; and one study reported both short- and medium-term effects.Five trials assessed dietary outcomes: two reported favourable effects, and three reported no effects. Eight studies assessed physical activity: five of these trials reported no physical activity effects, and three reported effectiveness. Trials are yet to measure the impact of these interventions on compliance with medication.Two studies measured healthcare utilisation: one reported no effects, and the other reported increased usage of healthcare services compared to a control group in the intervention group at nine months' follow-up. Two trials collected cost data: both reported that Internet-delivered interventions are likely to be cost-effective.In terms of the risk of bias, the majority of studies reported appropriate randomisation and appropriate concealment of randomisation processes. A lack of blinding resulted in a risk of performance bias in seven studies, and a risk of detection bias in five trials. Two trials were at risk of attrition bias, and five were at risk for reporting bias.

AUTHORS' CONCLUSIONS

In general, evidence was of low quality due to lack of blinding, loss to follow-up, and uncertainty around the effect size. Few studies measured clinical events, and of those that did, a very small number of events were reported, and therefore no firm conclusions can be made. Similarly, there was no clear evidence of effect for cardiovascular risk factors, although again the number of studies reporting these was small. There was some evidence for beneficial effects on HRQOL, dietary outcomes, and physical activity, although firm conclusions cannot yet be made. The effects on healthcare utilisation and cost-effectiveness are also inconclusive, and trials are yet to measure the impact of Internet interventions on compliance with medication. The comparison groups differed across trials, and there were insufficient studies with usable data for subgroup analyses. We intend to study the intensity of comparison groups in future updates of this review when more evidence is available. The completion of the ongoing trials will add to the evidence base.

Transparent Reporting of a multivariable prediction model for Individual Prognosis or Diagnosis (TRIPOD): explanation and elaboration

The TRIPOD (Transparent Reporting of a multivariable prediction model for Individual Prognosis Or Diagnosis) Statement includes a 22-item checklist, which aims to improve the reporting of studies developing, validating, or updating a prediction model, whether for diagnostic or prognostic purposes. The TRIPOD Statement aims to improve the transparency of the reporting of a prediction model study regardless of the study methods used. This explanation and elaboration document describes the rationale; clarifies the meaning of each item; and discusses why transparent reporting is important, with a view to assessing risk of bias and clinical usefulness of the prediction model. Each checklist item of the TRIPOD Statement is explained in detail and accompanied by published examples of good reporting. The document also provides a valuable reference of issues to consider when designing, conducting, and analyzing prediction model studies. To aid the editorial process and help peer reviewers and, ultimately, readers and systematic reviewers of prediction model studies, it is recommended that authors include a completed checklist in their submission. The TRIPOD checklist can also be downloaded from www.tripod-statement.org.

Improving bone mineral density reporting to patients with an illustration of personal fracture risk

Background

To determine patients’ preferences for, and understanding of, FRAX® fracture risk conveyed through illustrations.

Methods

Drawing on examples from published studies, four illustrations of fracture risk were designed and tested for patient preference, ease of understanding, and perceived risk. We enrolled a convenience sample of adults aged 50 and older at two medical clinics located in the Midwestern and Southern United States. In-person structured interviews were conducted to elicit patient ranking of preference, ease of understanding, and perceived risk for each illustration.

Results

Most subjects (n = 142) were female (64%), Caucasian (76%) and college educated (78%). Of the four risk depictions, a plurality of participants (37%) listed a bar graph as most preferred. Subjects felt this illustration used the stoplight color system to display risk levels well and was the most “clear,” “clean,” and “easy to read”. The majority of subjects (52%) rated the pictogram as the most difficult to understand as this format does not allow people to quickly ascertain their individual risk category.

Conclusions

Communicating risk to patients with illustrations can be done effectively with clearly designed illustrations responsive to patient preference.

Trial Registration

ClinicalTrials.gov Identifier: NCT01507662