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X Demographics
Mendeley readers
Attention Score in Context
| Title |
Competing with big business: a randomised experiment testing the effects of messages to promote alcohol and sugary drink control policy
|
|---|---|
| Published in |
BMC Public Health, December 2017
|
| DOI | 10.1186/s12889-017-4972-6 |
| Pubmed ID | |
| Authors |
Maree Scully, Emily Brennan, Sarah Durkin, Helen Dixon, Melanie Wakefield, Colleen L. Barry, Jeff Niederdeppe |
| Abstract |
Evidence-based policies encouraging healthy behaviours are often strongly opposed by well-funded industry groups. As public support is crucial for policy change, public health advocates need to be equipped with strategies to offset the impact of anti-policy messages. In this study, we aimed to investigate the effectiveness of theory-based public health advocacy messages in generating public support for sugary drink/alcohol policies (increased taxes; sport sponsorship bans) and improving resistance to subsequent anti-policy messages typical of the sugary drink/alcohol industry. We conducted a two-wave randomised online experiment assigning Australian adults to one of four health policies (sugary drink tax; sugary drink industry sports sponsorship ban; alcohol tax; alcohol industry sports sponsorship ban). Within each health policy, we randomised participants to one of five message conditions: (i) non-advocacy based message about the size and seriousness of the relevant health issue (control); (ii) standard pro-policy arguments alone; (iii) standard pro-policy arguments combined with an inoculation message (forewarning and directly refuting anti-policy arguments from the opposition); (iv) standard pro-policy arguments combined with a narrative message (a short, personal story about an individual's experience of the health issue); or (v) standard pro-policy arguments combined with a composite inoculation and narrative message. At time 1, we exposed participants (n = 6000) to their randomly assigned message. Around two weeks later, we re-contacted participants (n = 3285) and exposed them to an anti-policy message described as being from a representative of the sugary drink/alcohol industry. Generalised linear models tested for differences between conditions in policy support and anti-industry beliefs at both time points. Only the standard argument plus narrative message increased policy support relative to control at time 1. The standard argument plus narrative and standard argument plus inoculation messages were effective at increasing resistance to the persuasive impact of anti-policy messages relative to control at time 2. Dissemination of advocacy messages using inoculation or narrative components can help strengthen public resistance to subsequent anti-policy messages from industry groups. |
X Demographics
The data shown below were collected from the profiles of 3 X users who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Ireland | 2 | 67% |
| United States | 1 | 33% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Scientists | 2 | 67% |
| Members of the public | 1 | 33% |
Mendeley readers
The data shown below were compiled from readership statistics for 98 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 98 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Master | 17 | 17% |
| Researcher | 11 | 11% |
| Student > Ph. D. Student | 9 | 9% |
| Student > Bachelor | 6 | 6% |
| Student > Doctoral Student | 4 | 4% |
| Other | 14 | 14% |
| Unknown | 37 | 38% |
| Readers by discipline | Count | As % |
|---|---|---|
| Social Sciences | 13 | 13% |
| Nursing and Health Professions | 10 | 10% |
| Medicine and Dentistry | 8 | 8% |
| Psychology | 5 | 5% |
| Economics, Econometrics and Finance | 5 | 5% |
| Other | 16 | 16% |
| Unknown | 41 | 42% |
Attention Score in Context
This research output has an Altmetric Attention Score of 14. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 29 August 2019.
All research outputs
#2,415,621
of 23,870,803 outputs
Outputs from BMC Public Health
#2,770
of 15,453 outputs
Outputs of similar age
#56,218
of 446,477 outputs
Outputs of similar age from BMC Public Health
#65
of 216 outputs
Altmetric has tracked 23,870,803 research outputs across all sources so far. Compared to these this one has done well and is in the 89th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 15,453 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 14.3. This one has done well, scoring higher than 82% of its peers.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 446,477 tracked outputs that were published within six weeks on either side of this one in any source. This one has done well, scoring higher than 87% of its contemporaries.
We're also able to compare this research output to 216 others from the same source and published within six weeks on either side of this one. This one has gotten more attention than average, scoring higher than 70% of its contemporaries.