Strengths and limitations
Unlike most trials in the field of risk communication, this trial studied real-life patients rather than hypothetical scenarios. The study subjects responded to an actual risk to their own health, based on an individual risk profile and treatment effectiveness assessment. The real-life approach is of importance when examining risk communication and the effects of manipulation, that is framing, of information on attitudes, perceptions, and choices. A number of studies and reviews32–34 have shown different effects of framing variations in clinical versus laboratory settings, predominantly due to the influences of contextual factors like stressors, previous personal experiences, and different ways that the risk information may be used or shared, and have called for further studies conducted in real practice.
The definition of the patient population was clear, inclusion and exclusion criteria being well-defined, and the recruitment task in the hands of the GPs straightforward. However, as a consequence of GPs conducting the patient recruitment process, and the prospective inclusion of patients after randomisation of the GPs, there may have been for some selection bias through the recruitment of certain types of patients by the respective GPs, such as those considered particularly suitable for the allocated information format.
The trial used real-life consultations in routine practice. The study does not have information on exactly how the consultations proceeded, nor on whether the effectiveness format was presented as intended. It could have been informative to supplement data collection with audio or video recordings to assess what actually happened in the consultations and the dynamics of the health prevention talk between GPs and their patients. Although approaches such as audio or video recordings might have provided information on intervention fidelity and these dynamics of health prevention talks between GPs and patients, such approaches would require considerable resources.35 Moreover, such monitoring may have affected the dynamics and potentially also influenced patients’ decisions or satisfaction outcomes. In this study, to reduce the risk of intervention infidelity, a detailed protocol was implemented, including a thorough instruction programme for the participating GPs on numerical risk communication and how to use the prognosis and effectiveness information sheets in health prevention consultations with patients concerning CVD risk and effectiveness of cholesterol-lowering medication. It is impossible to know the GPs’ preferred learning styles to which educational methods might be tailored to achieve optimal understanding of risk, effectiveness formats, and skills in communication. This study aimed at pitching the teaching at an appropriate level, in that academic GPs and social scientists in the project group developed the instruction programme based on experiences and knowledge from other trials within the field.11,36–38 Although a degree of performance bias cannot be ruled out, it is the study’s belief that overall intervention fidelity is likely to have been good, as the GPs only had access to the specific information sheets corresponding to their respective allocations. The sheets held information not published elsewhere at the time of the trial, thus GPs could not readily compute the alternative information format from resources available elsewhere. Some selection or attrition bias at the GP level cannot be ruled out: the high dropout rate may have disturbed the randomisation resulting in attrition bias. Furthermore, the GPs choosing to participate in the trial might represent those already well versed in risk communication (selection bias). This might partly explain the relatively high scores on the COMRADE subscales.
Nevertheless, the cluster-randomisation of practices was successful in creating groups of equal sizes, and with an acceptably balanced allocation of patients in the two groups, although the total number of included GPs was modest. Data on characteristics of the participating GPs were sparse, but the study population resembled the background GP population with regard to sex (35% women in the study population and 39% in the background population) and age (mean age of participating GPs 53.9 years, corresponding to the background GP population in 2009 39,40). The study GP population differed slightly from the background GP population with regard to type of practice, in that 22% of the participating practices were single-handed compared with 28% in the background population. Workload may be higher in single-handed than partnership practices, and hence trial participation may have lower priority. Of the 30 practices (56 GPs) initially enrolling for the study, seven practices (22 GPs) did not contribute to recruiting patients. These seven were four POL-allocated practices (14 GPs) and three ARR-allocated practices (eight GPs). The dropouts were characterised by being from partnership practices (86%, n = 19), were equally distributed among male and female GPs, and were not associated with the randomised allocation. Overall, the study feels that the risks of selection and attrition bias were low, but there was some risk of performance bias which is not unusual in an effectiveness study of a skill or competency applied in routine practice.
Corresponding to the study’s hypothesis, the results indicated a greater willingness to redeem statins among ARR patients compared with POL patients, albeit with a broad 95% confidence interval. As a patient’s individual risk (for example, cholesterol level) may likely influence the decision-making, analyses were conducted adjusting for patients’ baseline risk (which included the cholesterol level). This augmented the difference in redemption propensity.
The overall redemption rate regardless of information format was much lower than expected in the power calculation. However, the reliability of the results is supported by the fact that the study had power to detect a statistically significant difference in the primary outcome. While it would not be informative to conduct a post-hoc power analysis, the knowledge gained from the discrepancy between the initial expectations and the experienced redemption rates may be useful in planning future studies in this field.
Lack of statistical power may be a contributing reason for not finding significant results regarding the secondary outcomes, the COMRADE subscales.
Comparison with existing literature
The tendency to reject medication when presented with POL information could be explained by the ease of evaluating the information.41 Most people are used to evaluating numeric differences in time, but not in risks or probability. Consequently, they may find it easier to understand the level of effectiveness when presented with POL, and then find the gain too small to justify redemption of a prescription.
Studies on laypersons and hypothetical scenarios have shown sensitivity to information presented by POL and ability to evaluate POL data.17,18 The hypothesis that patients might require a considerable POL to accept therapy corresponds to findings from Trewby et al,14 where most participants, presented with a hypothetical scenario, required a considerable POL of at least 18 months before being willing to take a hypothetical preventive cholesterol-lowering drug. However, few medical interventions postpone death by more than 1 year.42 Inconsistent sensitivity to levels of effectiveness of a hypothetical cholesterol-lowering drug regardless of effectiveness format used, has been indicated in another Danish study.15 Literature on the impact of these formats on real-life patients’ decision-making is sparse. To the study’s knowledge, no research to date has compared ARR and POL used in real-life risk communication between GPs and their patients.
Implications for research and practice
Although the results of this study revealed a clear difference in redemptions of prescriptions between patients informed by means of ARR and POL, and showed that patients in general seemed confident with their decision and satisfied with the risk communication regardless of format used, it is noteworthy that the redemption of prescriptions was very much lower than expected for both trial groups. This suggests that in the decision-making process about whether to accept a preventive therapy, patients faced with information about their own risk of CVD are indeed sensitive to effectiveness formats. This indicates that with informed decision-making, many patients are not impressed with the reported benefits of proposed therapies, or that the level of effectiveness is not the only determinant of patients’ decision-making concerning therapy. This is consistent with the tension between public health, guidelines, and informed decision-making found in previous studies.37,43–45 It is important that GPs are aware of this tension when talking about health prevention and potential medication with their patients, and that in the decision-making process they handle numerical information on effectiveness with care.
It would be important for future research to assess real-life patients’ perceptions of risk, in general and concerning their own risk when informed about prognosis of disease, and how these perceptions may influence decisions concerning choice of therapy and adherence to chosen therapy. Assessing GPs’ perception of risk would also be important in future research. Knowledge of how patients and their GPs interpret and understand risk information to make decisions to which they adhere, could increase cost-effectiveness of therapies and improve compliance with guideline recommendations.
