Effects of Causal Beliefs About Gout on Public Views About Gout Management: A Randomized Experimental Study

Abstract

Objective

Despite well‐described biologic causes, the public views unhealthy lifestyle choices as the primary cause of gout. This study investigated how causal beliefs about gout influence the public's views about its management.

Methods

In a randomized study, 201 members of the public viewed one of two 2‐minute videos about gout. The videos were identical except for a 45‐second section describing the causes of gout using either a biologic explanation (including genetics, kidney disease, age, sex, and diuretic therapy) or a lifestyle explanation (including diet, alcohol, sugary drinks, and weight). Participants completed a questionnaire about gout and its management. Primary outcome was rating of “How likely is it that long‐term medications would help gout?” on an 11‐point Likert scale.

Results

Participants who viewed the biologic explanation rated hereditary factors and aging as more important causes of gout than those who viewed the lifestyle explanation, and they rated poor diet, alcohol use, and the person's own behavior less highly (P < 0.001 for all). In the biologic group, 13 of 99 (13.1%) gave diet or a specific dietary factor as the most important cause compared with 62 of 102 (60.8%) in the lifestyle group. Those in the biologic group were more likely to believe that long‐term medication would help gout (mean score 7.6 vs 6.5, P = 0.001).

Conclusion

Explaining gout as caused by biologic rather than lifestyle factors affects beliefs about the benefits of long‐term medication. Accurate communication about causes of gout could affect the public's beliefs about treatment strategies and may improve long‐term medication uptake.

INTRODUCTION

Gout is the most common cause of inflammatory arthritis in adults. ¹ It can be treated effectively with long‐term urate‐lowering therapy (ULT) such as allopurinol, which decreases flares, tophi, and disability. ² , ³ Despite this well‐established clinical efficacy, ULT is frequently underprescribed when indicated and is often discontinued by patients after initiation ⁴ , ⁵ , ⁶ ; for example a recent study found that about 63% of people initiating allopurinol did not persist with this therapy for more than a year. ⁷ Previous qualitative research has identified several reasons patients discontinue allopurinol, including experiencing gout flares after starting ULT, receiving conflicting or insufficient information about gout from health care professionals, identifying a dietary trigger for gout, believing they did not have frequent enough flares to warrant medication, and general concerns about taking medication. ⁸

SIGNIFICANCE & INNOVATIONS.

• This is the first randomized study to examine how causal beliefs about gout affect views about its management.

• A brief explanation of either the biologic or lifestyle causes of gout can influence the public's views about gout management, including the necessity of long‐term medication.

• Accurate communication about the causes of gout could affect the public's views about its management and improve uptake of ULT.

Attribution theory describes the origins and consequences of causal beliefs, ⁹ which develop through the acquisition of information from cultural depictions of an illness and personal experiences. ¹⁰ Causal beliefs help to provide an explanation for and a sense of control over events ¹¹ , ¹² and also influence treatment adoption because, depending on the cause of an illness, certain treatments make more sense. The impact of causal beliefs held by members of a community is known to have a significant impact on patients living within that system. Although the impact of this has not been previously explored in gout, it has been investigated in other diseases such as depression. A meta‐analysis that included 43 cultural groups has found that causal beliefs held by a community strongly influenced their preferred treatment options. For example, members of an Indian community who conceptualized it as a physical disease favored medication, and those in a Malayan community who viewed it as caused by emotional stress felt that counseling would be the most effective strategy. ¹³ These beliefs are clinically relevant as they can influence whether patients seek medical care, their treatment decisions, and adjustment to illness. ¹¹ , ¹⁴ , ¹⁵

The pathogenesis of gout involves the development of hyperuricemia leading to the formation of monosodium urate crystals, which deposit in bones, joints, and soft tissue. ¹⁶ Studies have attempted to quantify the contribution of genetic variants and diet to risk of hyperuricemia. A meta‐analysis of data from 16,760 people without gout from the United States found that three dietary scores based on healthy eating guidelines each explained less than 0.3% of the variance in serum urate, whereas 23.9% of variance in serum urate was explained by genome wide single nucleotide variation. ¹⁷ Another study of people with hyperuricemia and gout showed a single genetic variant had substantially larger impact on hyperuricemia than four dietary patterns that were investigated. ¹⁸ Other biologic factors, such as renal impairment, age, and diuretic use, also increase the risk of gout. ¹ , ¹⁹ , ²⁰ , ²¹ , ²² , ²³ Some studies have shown modest reductions in serum urate with the Dietary Approaches to Stop Hypertension (DASH) diet in people with hypertension and hyperuricemia, ²⁴ but studies in patients with gout have not shown a sustained impact of dietary change on serum urate. A crossover study of a DASH‐based diet showed an initial decrease in serum urate in those randomized to a DASH‐based diet compared to patients receiving a usual diet but no difference after the crossover period, ²⁵ and a study of dietary education in patients with gout on ULT found that providing education on diet did not lead to a difference in serum urate after six months. ²⁶

Despite the compelling evidence for biologic causes of gout, it is a common belief in the community that gout is due solely to lifestyle factors. In previous research, when members of the public were asked about the causes of two identical diseases labeled “gout” or “urate crystal arthritis,” participants viewed “gout” as more likely to be caused by diet, alcohol, and the person's own behavior and “urate crystal arthritis” as more likely to be due to the effects of aging. ²⁷ This randomized experimental study aimed to investigate the impact of different causal beliefs about gout on the public's views about gout management, specifically the need for long‐term medication.

MATERIALS AND METHODS

Study design and participants

From June 2023 to April 2024, 201 members of the public were recruited through advertisements on the University of Auckland trials website, posters, and a job search website in Aotearoa/New Zealand. Advertising and participant information was for a study of “video and perceptions of illness” to avoid recruiting a disproportionate number of the public with gout, although participants with gout were not excluded.

Eligible participants were adults aged 18 years or older able to complete a questionnaire in English. Ethical approval was obtained from the University of Auckland Human Participants Ethics Committee (UAHPEC25912), and all participants provided written informed consent. After providing informed consent, participants viewed one of two 2‐minute animated videos about gout and then completed a questionnaire about gout and its management. The study was prospectively registered with the Australian New Zealand Clinical Trials Registry (http://anzctr.org.au; ACTRN12623000455662).

Randomization and masking

A randomization schedule was produced by a biostatistician using a variable block sequence generated in Microsoft Excel (Microsoft Excel for Microsoft 365). Participants were randomized 1:1 to view either the biologic or lifestyle explanation video. The randomization was uploaded to REDCap (Vanderbilt University) by a researcher not involved in the study interviews. As each participant was recruited, their email address was entered into the secure database, and they were emailed either the biologic or lifestyle video automatically by REDCap depending on their randomization.

Procedures

Participants were asked to view the video containing either the biologic or lifestyle description of gout shortly before a 30‐minute Zoom interview with a researcher. The interviewer was blinded to group allocation. The participants were asked not to reveal the contents of the video to the researcher. To confirm that the participant had viewed the video, the interviewer asked the participant what disease the video had been about before the interview. If the participant answered incorrectly, it indicated that they had not viewed the video, so they were excluded from the analysis. Participants were able to view the questions over Zoom as they completed the questionnaire.

The two videos were both two minutes long and had identical beginning and end sections, which answered the questions “What is gout?” and “How is gout treated?”. The middle sections of each video, which described the causes, were both 108 words and 45 seconds in duration. The biologic causes video focused on risk factors such as genetic variants, kidney disease, male sex, age, and diuretic use. The lifestyle causes video described dietary risk factors and being overweight. The full text of each video is shown in Figures 1 and 2, and the links to the videos are available in Supplementary Table 1. Both videos included the same description of gout management, which included reference to medication as well as lifestyle approaches to treatment: “Anti‐inflammatory medications can be used to treat the attacks of arthritis. A balanced diet, regular exercise, and a healthy weight are recommended. A long‐term daily medication can dissolve the crystals and prevent future attacks.”

Figure 1.

Script for biologic causes video. Section of script that differs from lifestyle explanation in bold.

Figure 2.

Script for lifestyle causes video. Section of script that is different from biologic explanation in bold.

Demographic data were collected, and participants were asked whether they had a history of gout or had a close friend or relative with gout. Ethnicity was self‐reported using the standard ethnicity question from the 2018 New Zealand census. ²⁸

Participants were asked, “If you or someone you know was diagnosed with gout, what do you think are the likely causes of this condition?” They were asked to rate nine potential causal factors: stress or worry, hereditary factors, diet or poor eating habits, aging, alcohol use, pollution in the environment, and the person's own behavior. These were rated on a five‐point Likert scale from “strongly disagree” to “strongly agree.” They were also asked separately to provide the three most important causes of gout in rank order, which were recorded as free text.

After the introduction “We are interested in your thoughts about how likely different types of behavior would help your condition if you were diagnosed with gout,” participants were asked to rate a list of seven potential management strategies: managing stress, regular exercise, stopping or restricting alcohol, long‐term medications, changing to a healthier diet, alternative medicine, and losing weight on an 11‐point Likert scale from “would not help at all” to “very likely to help.” This section included the primary outcome, the response to the question, “How likely is it that long‐term medications would help gout?”

Participants were asked to imagine that they had been diagnosed with gout, and their views about medications were further explored with another set of questions, including one that was similar to the primary outcome measure: “How likely is it that you would need long‐term medication prescribed for gout?” They were also asked how concerned they would be to take long‐term medication for gout, how motivated they would be to take long‐term medication for gout, how serious gout is as an illness, and how embarrassed they would be to be diagnosed with gout. Answers were given as a rating on an 11‐point Likert scale.

Illness perceptions were assessed using the Brief Illness Perception Questionnaire. Before completing this questionnaire, participants were asked to imagine they had been diagnosed with gout and to answer the questions based on how they thought the illness would influence their life. The questionnaire assesses eight aspects of perceptions of illness on an 11‐point Likert scale including consequences (how much gout would affect a person's life), duration (how long gout would continue), personal control (how much control the participant feels they would have over gout), treatment control (how much medication would help), identity (severity of symptoms), concern (how concerned the participant would be about having gout), understanding, and emotional impact. ²⁹

As the study advertisements did not specify that the illness being studied was gout, after completing the study interview participants were emailed a debrief sheet that provided further explanation about the study and a link to patient information about gout. ³⁰

Statistical considerations

A sample size calculation was performed based on a previous study of disease labels in gout. ²⁷ The sample size of 200 participants allowed the detection of at least a two‐point difference for a Brief Illness Perception Questionnaire item with a 90% power and an alpha of 0.05. The primary outcome was the response to the question “How likely is it that long‐term medications would help gout?”, measured on an 11‐point Likert scale.

Demographic variables were described using number, percentage, mean, and SD. Between‐group differences were explored using independent sample t‐tests.

Participant responses to the question asking them to provide the three most important causes of gout in rank order were grouped into diet, genetics, alcohol, lifestyle, aging, and “other,” based on groupings used in previous studies. ³¹ , ³² Responses were grouped by a researcher who was blinded to the study allocation.

Data were analyzed using IBM SPSS Statistics version 27 (IBM Corp) and SAS version 9.4 (SAS Institute Inc). Main effects of study allocation were modeled using general linear modeling with normal distribution and identity link function for continuous variables to estimate between‐group mean differences with and without adjustment for personal or family/friend history of gout. Binary distribution and an identity link function were used to estimate absolute percent difference between groups for the adjusted and unadjusted comparisons. Measures of effect are presented with 95% confidence intervals. To preserve an overall 5% significance level within each of the objectives, additional critical alphas are provided in the footnotes to each table corrected for the number of tests performed using the Bonferroni method. Unadjusted P values are provided throughout.

RESULTS

Participants

Between June 30, 2023, and April 11, 2024, 219 participants were recruited. Seventeen participants did not complete the Zoom interview, and one participant's data were excluded because they did not identify the disease in the video as gout. A total of 201 participants correctly identified the disease in the video as gout and completed the interview over Zoom with a researcher, 99 in the biologic causes group and 102 in the lifestyle causes group.

Demographic features are shown in Table 1. Of the 201 participants, 152 (75.6%) were female. There were 47 of 201 (23.4%) participants of Asian ethnicity, 21 of 201 (10.4%) were Māori, 124 of 201 (61.7%) were New Zealand European, and 5 of 201 (2.5%) were Pacific peoples. The average age of participants was 40.3 years, ranging from 19 to 87. There were 3 of 201 participants (1.5%) with a history of gout, and 86 of 201 (42.8%) had a family member or close friend with gout.

Table 1.

Participant characteristics

Demographic variable	All participants, N = 201	Biologic causes, N = 99	Lifestyle causes, N = 102
Gender, n (%)
Female	152 (75.6)	75 (75.8)	77 (75.5)
Male	48 (23.9)	24 (24.2)	24 (23.5)
Other	1 (0.5)	0 (0)	1 (1.0)
Age (mean [SD], range),	40.3 (18.8), 19–87	41.6 (19.2), 20–87	38.9 (18.3), 19–82
Ethnicity, N (%)
Asian	47 (23.4)	18 (18.2)	29 (28.4)
Māori	21 (10.4)	16 (16.2)	5 (4.9)
New Zealand European	124 (61.7)	62 (62.6)	62 (60.8)
Other	4 (2.0)	2 (2.0)	2 (2.0)
Pacific peoples	5 (2.5)	1 (1.0)	4 (3.9)
Experience of gout, N (%)
Personal diagnosis of gout	3 (1.5)	3 (3.0)	0 (0)
Diagnosis of gout in family or close friend	86 (42.8)	46 (46.5)	40 (39.2)

Causal beliefs

Participant ratings of different potential causes of gout are shown in Table 2. Those in the biologic causes group rated hereditary factors as a more important cause of gout than those in the lifestyle causes group, with a mean rating of 4.6 (SD 0.7) in the biologic causes group compared with mean 3.3 (SD 1.2) in the lifestyle causes group, P < 0.001. Those in the lifestyle causes group believed diet or poor eating habits, alcohol, and the person's own behavior were more important causes of gout (all P values < 0.001).

Table 2.

Causes of gout, rated on a 5‐point Likert scale from 1 “strongly disagree” to 5 “strongly agree”^*

Cause	Biologic causes, mean score (SD)	Lifestyle causes, mean score (SD)	Unadjusted mean difference (95% CI)	P	Adjusted mean difference (95% CI)	P
Stress or worry	2.6 (1.1)	2.6 (1.0)	−0.0 (−0.3 to 0.3)	0.83	−0.01 (−0.31 to 0.29)	0.94
Hereditary	4.6 (0.7)	3.3 (1.2)	1.3 (1.0 to 1.6)	<0.001	1.34 (1.07 to 1.60)	<0.001
Diet or poor eating habits	4.0 (0.8)	4.7 (0.5)	−0.7 (−0.9 to −0.5)	<0.001	−0.68 (−0.87 to −0.50)	<0.001
Aging	4.1 (0.8)	3.4 (1.0)	0.6 (0.4 to 0.9)	<0.001	0.65 (0.39 to 0.92)	<0.001
Alcohol use	3.7 (0.9)	4.6 (0.5)	−0.9 (−1.1 to −0.7)	<0.001	−0.93 (−1.13 to −0.72)	<0.001
Pollution	2.3 (0.9)	2.0 (0.9)	0.3 (0.1 to 0.6)	0.009	0.33 (0.08 to 0.58)	0.0095
Chance or bad luck	2.6 (1.2)	2.2 (1.0)	0.3 (0.0 to 0.6)	0.04	0.30 (−0.01 to 0.61)	0.058
A germ or virus	1.9 (1.0)	1.8 (0.9)	0.1 (−0.1 to 0.4)	0.29	0.16 (−0.11 to 0.44)	0.23
The person's own behavior	3.1 (1.2)	3.8 (0.8)	−0.7 (−1.0 to −0.4)	<0.001	−0.70 (−0.99 to −0.41)	<0.001

^*Bolded values signify statistical significance. P value for significance adjusted for multiple comparisons using Bonferroni correction; P value for significance = 0.006; adjustment was for personal history of gout or history of gout in a close friend or relative. CI, confidence interval.

When asked to provide in rank order a list of the three most important causes of gout, 62 of 102 (60.8%) of those in the lifestyle causes group and 13 of 99 (13.1%) of those in the biologic causes group gave either diet in general or a specific dietary factor as the most important cause (P < 0.001). In the biologic causes group, 74 of 99 (74.7%) gave genetics as the most important cause compared with 9 of 102 (8.8%) in the lifestyle causes group, P < 0.001 (Table 3).

Table 3.

Participant listing of most likely cause of gout^*

Grouped cause	Biologic causes group: most important cause of gout, n (%), n = 99	Lifestyle causes group: most important cause of gout, n (%), n = 102	Unadjusted percentage difference (95% CI)	P	Adjusted percentage difference (95% CI)	P
Diet	13 (13.1)	62 (60.8)	−47.7 (−59.2 to −36.1)	<0.001	−48.5 (−60.0 to −37.0)	<0.001
Genetics	74 (74.7)	9 (8.8)	65.9 (55.8 to 76.1)	<0.001	65.9 (55.7 to 75.9)	<0.001
Alcohol	2 (2)	16 (15.7)	−13.7 (−21.3 to −6.1)	<0.001	−12.9 (−20.9 to −4.8)	0.002
Lifestyle	2 (2)	3 (2.9)	−0.9 (−5.2 to 3.4)	0.71	−0.89 (−5.3 to 3.50)	0.69
Aging	3 (3)	2 (2)	1.1 (−3.2 to 5.4)	0.66	1.7 (−5.3 to 8.7)	0.64
Other a	6 (6.1)	10 (9.8)	−3.7 (−1.1 to 3.7)	0.33	−4.6 (−1.2 to 2.9)	0.23

^*Bolded values signify statistical significance. P value for significance adjusted for multiple comparisons using Bonferroni correction; P value for significance = 0.008; adjustment was for personal history of gout or history of gout in a close friend or relative. CI, confidence interval.

^a Other: high cholesterol, liver disease, smoking, stress, kidney disease, weight, urate.

Management strategies

In the biologic causes group, the mean participant rating in response to the question “How likely is it that long‐term medicines would help gout?” (the primary outcome measure) was 8.7 (SD 1.4) compared with 7.9 (SD 1.9) in the lifestyle causes group, P = 0.001 (Table 4). Consistent with this result, when asked the question, “How likely is it that you would need long‐term medication prescribed for gout?”, those in the biologic causes group gave a mean rating of 7.6 (SD 2.2) compared with 6.5 (SD 2.4) in the lifestyle causes group, P = 0.001 (Supplementary Table 2). Changing to a healthier diet, reducing alcohol, and losing weight were all given higher ratings by the lifestyle causes group than the biologic causes group (all P values < 0.001).

Table 4.

Management strategies for gout, scale 0 “wouldn't help it at all” to 10 “very likely to help”^*

Management strategy	Biologic causes, mean score (SD)	Lifestyle causes, mean score (SD)	Unadjusted mean difference (95% CI)	P	Adjusted mean difference (95% CI)	P
Managing stress	5.6 (2.6)	5.8 (2.4)	−0.2 (−0.9 to 0.5)	0.57	−0.17 (−0.87 to 0.53)	0.63
Regular exercise	7.8 (2.1)	8.2 (2.0)	−0.4 (−1.0 to 0.1)	0.14	−0.45 (−1.03 to 0.13)	0.13
Stopping/restricting alcohol	7.8 (2.2)	9.0 (1.3)	−1.2 (−1.7 to −0.7)	<0.001	−1.24 (−1.74 to −0.73)	<0.001
Long‐term medication	8.7 (1.4)	7.9 (1.9)	0.8 (0.3–1.3)	0.001	0.79 (0.31–1.27)	0.001
Changing to a more healthy diet	8.5 (1.8)	9.3 (1.0)	−0.8 (−1.2 to 0.4)	<0.001	−0.85 (−1.26 to −0.44)	<0.001
Alternative medication	4.9 (2.7)	5.0 (2.6)	−0.1 (−0.9 to 0.6)	0.77	−0.06 (−0.81 to 0.69)	0.87
Losing weight	7.5 (2.2)	8.7 (1.4)	−1.3 (−1.8 to −0.8)	<0.001	−1.29 (−1.81 to −0.77)	<0.001

^*Bolded values signify statistical significance. P value for significance adjusted for multiple comparisons using Bonferroni correction; P value for significance = 0.007; adjustment was for personal history of gout or history of gout in a close friend or relative. CI, confidence interval.

Both groups viewed lifestyle changes such as regular exercise, stopping or restricting alcohol, changing diet, and losing weight as likely to be effective, with all these management strategies rated above 7.5 on a 0 to 10 scale by both groups. There was no difference between the two groups in motivation to take long‐term medications or concern about taking long‐term medications or in ratings of how serious gout is as an illness or how embarrassed they would be if they were diagnosed with it.

Illness perceptions

There were no differences between the two groups in ratings of the eight aspects of illness perceptions (Supplementary Table 3).

DISCUSSION

This experimental randomized study has demonstrated that a brief intervention explaining either the biologic or lifestyle causes of gout affects not only the public's views about the causes of gout but also likely its management, including the need for long‐term medication. This was despite there being no difference in the description of treatment options for gout that was provided to the two groups. Therefore, providing accurate information to the public about the causes of gout is a viable strategy for changing illness beliefs and increasing acceptance for the use of long‐term medication in the community.

A key finding of this study was that a brief intervention had an impact on causal beliefs, as demonstrated by the differences between groups in what they believed to be the most important cause of gout. This shows that the intervention was effective in influencing causal beliefs and that it was correctly delivered. The video format, containing both audio and visual material, likely contributed to making the intervention understandable and impactful.

The findings align with prior research investigating the impact of causal beliefs in other illnesses. In patients experiencing a first myocardial infarction, four half‐hour sessions with a psychologist involving a discussion about causal beliefs and the link between the causes of the disease and the treatment plan resulted in a change in causal attributions and a greater intention to attend cardiac rehabilitation. ³³ In another study, members of the public provided with a psychological explanation of a mental illness were more likely to believe the illness to be curable and less likely to believe hospitalization would be essential than those given a biologic explanation. ³⁴ This is the first study to demonstrate the efficacy of an intervention aimed at influencing causal beliefs in gout and has also shown that even a very brief intervention can be effective in changing the public's views about gout management.

A practical application of these findings is that they support calls for improvements in the accuracy of information about gout being accessible to the public. Our results indicate that discussion about the causes of gout could be an effective way of improving acceptance of long‐term ULT. Inaccurate information about the causes of gout is frequently disseminated to the public through newspapers, films, and television. For example, an analysis of newspaper articles about gout found that unhealthy foods and beverages were reported as the cause in 63% of articles whereas biologic causes were included in 40% of articles. ³⁵ Additionally, only 12% of fictional depictions of gout in film and television since 1990 included mention of any biologic cause of gout. ³⁶ A previous randomized study demonstrated that these media depictions affect the public's views about both the causes and management of gout. ³¹ In the current study, both groups gave high ratings for the likely efficacy of lifestyle interventions, reflecting widespread positive views about the benefits of dietary interventions for gout. The findings from this study strengthen calls for accurate public commentary about the causes of gout, as they indicate that causal beliefs impact views on its long‐term management. It highlights the opportunity for public health campaigns that discuss the causes of gout. Our findings also strengthen the justification for development of guidelines for media reporting and depictions of gout, which could be published by nongovernmental organizations or professional groups. Media guidelines exist for reporting on other diseases such as HIV that have historically had inaccurate depictions in film, television, and newspaper. ³⁷ Previous research has shown people with gout frequently experience blame from others as well as inaccurate management advice, which can delay them from receiving effective treatment with ULT. ³⁸ , ³⁹ Therefore, improving the accuracy of information about the causes of gout that is accessible to the public is a strategy that could help people with gout receive better support with their management from their communities.

Strengths of this study include that it was randomized, was blinded, and had a large sample size. Incomplete questionnaires were avoided as participants completed them over Zoom with a researcher. The videos were identical other than a short section discussing potential causes of gout, and both contained text discussing medication and lifestyle management strategies. The questionnaires used in the study to evaluate views on illness perceptions and the causes and management of gout have been used in previous gout‐related research. ²⁷ , ³² , ⁴⁰ , ⁴¹ , ⁴² , ⁴³ Participants were asked about the need for long‐term medication more than once in the questionnaire, and the responses were consistent.

Limitations include the short duration of the study; it is unclear how long the effect of viewing the video lasts, as participants viewed the video shortly before the study interview. No pre‐exposure questionnaire was performed to evaluate whether individual participant answers changed before and after the intervention. As both groups were members of the community recruited in the same way, it was assumed that they had similar baseline knowledge about gout. As depictions of gout emphasizing lifestyle causes are very prevalent, ³⁵ , ³⁶ repeated exposure to explanations about the biologic causes of gout may be required to maintain an awareness of the efficacy of long‐term medication. The study did not include a group examining the effects of a video containing causal information about both biologic and lifestyle factors. This study focused on the views of members of the public; it is unknown whether the intervention would have a similar effect on people with gout themselves and whether beliefs about the benefits of long‐term medication translate into actually taking urate‐lowering medications.

In summary, this study has demonstrated that a brief intervention describing the biologic causes of gout affects views about the likely benefits and necessity of long‐term medication. This confirms the importance of ensuring that accurate information about the biologic causes of gout is accessible to patients and the wider community and demonstrates that even a brief intervention targeting causal beliefs in gout affects views on its management.

AUTHOR CONTRIBUTIONS

All authors contributed to at least one of the following manuscript preparation roles: conceptualization AND/OR methodology, software, investigation, formal analysis, data curation, visualization, and validation AND drafting or reviewing/editing the final draft. As corresponding author, Dr Murdoch confirms that all authors have provided the final approval of the version to be published and takes responsibility for the affirmations regarding article submission (eg, not under consideration by another journal), the integrity of the data presented, and the statements regarding compliance with institutional review board/Declaration of Helsinki requirements.

Supporting information

Disclosure Form:

Supplementary Table 1 Links to view the biological and lifestyle videos

Supplementary Table 2. Views about gout medications (scored on an 11‐point Likert scale)

Supplementary Table 3. Perceptions of gout according to the Brief Illness Perception Questionnaire (BIPQ), scale from 0: ‘no effect at all’ to 10: ‘severely affect my life’