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Mendeley readers
Attention Score in Context
| Title |
Development of a text message intervention aimed at reducing alcohol-related harm in patients admitted to hospital as a result of injury
|
|---|---|
| Published in |
BMC Public Health, August 2015
|
| DOI | 10.1186/s12889-015-2130-6 |
| Pubmed ID | |
| Authors |
Sarah Sharpe, Matthew Shepherd, Bridget Kool, Robyn Whittaker, Vili Nosa, Enid Dorey, Susanna Galea, Papaarangi Reid, Shanthi Ameratunga |
| Abstract |
Screening for alcohol misuse and brief interventions (BIs) for harm in trauma care settings are known to reduce alcohol intake and injury recidivism, but are rarely implemented. We created the content for a mobile phone text message BI service to reduce harmful drinking among patients admitted to hospital following an injury who screen positive for hazardous alcohol use. The aim of this study was to pre-test and refine the text message content using a robust contextualisation process ahead of its formal evaluation in a randomised controlled trial. Pre-testing was conducted in two phases. First, in-depth interviews were conducted with 14 trauma inpatients (16-60 years) at Auckland City Hospital and five key informants. Participants were interviewed face-to-face using a semi-structured interview guide. Topics explored included: opinions on text message ideas and wording, which messages did or did not work well and why, interactivity of the intervention, cultural relevance of messages, and tone of the content. In a second phase, consultation was undertaken with Māori (New Zealand's indigenous population) and Pacific groups to explore the relevance and appropriateness of the text message content for Māori and Pacific audiences. Factors identified as important for ensuring the text message content was engaging, relevant, and useful for recipients were: reducing the complexity of message content and structure; increasing the interactive functionality of the text message programme; ensuring an empowering tone to text messages; and optimising the appropriateness and relevance of text messages for Māori and Pacific people. The final version of the intervention (named 'YourCall(™)') had three pathways for people to choose between: 1) text messages in English with Te Reo (Māori language) words of welcome and encouragement, 2) text messages in Te Reo Māori, and 3) text messages in English (with an option to receive a greeting in Samoan, Tongan, Cook Island Māori, Niuean, Tokelauan, Tuvaluan, or Fijian). We have developed a text message intervention underpinned by established BI evidence and behaviour change theory and refined based on feedback and consultation. The next step is evaluation of the intervention in a randomised-controlled trial. |
X Demographics
The data shown below were collected from the profile of 1 X user who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United Kingdom | 1 | 100% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Practitioners (doctors, other healthcare professionals) | 1 | 100% |
Mendeley readers
The data shown below were compiled from readership statistics for 130 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United Kingdom | 1 | <1% |
| Brazil | 1 | <1% |
| Unknown | 128 | 98% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Researcher | 17 | 13% |
| Student > Bachelor | 15 | 12% |
| Student > Ph. D. Student | 14 | 11% |
| Student > Master | 14 | 11% |
| Student > Doctoral Student | 10 | 8% |
| Other | 25 | 19% |
| Unknown | 35 | 27% |
| Readers by discipline | Count | As % |
|---|---|---|
| Medicine and Dentistry | 25 | 19% |
| Psychology | 25 | 19% |
| Nursing and Health Professions | 13 | 10% |
| Social Sciences | 8 | 6% |
| Computer Science | 3 | 2% |
| Other | 17 | 13% |
| Unknown | 39 | 30% |
Attention Score in Context
This research output has an Altmetric Attention Score of 1. 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 23 August 2015.
All research outputs
#18,423,683
of 22,824,164 outputs
Outputs from BMC Public Health
#12,855
of 14,869 outputs
Outputs of similar age
#192,069
of 266,223 outputs
Outputs of similar age from BMC Public Health
#302
of 347 outputs
Altmetric has tracked 22,824,164 research outputs across all sources so far. This one is in the 11th percentile – i.e., 11% of other outputs scored the same or lower than it.
So far Altmetric has tracked 14,869 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 13.9. This one is in the 6th percentile – i.e., 6% of its peers scored the same or lower than it.
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 266,223 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 16th percentile – i.e., 16% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 347 others from the same source and published within six weeks on either side of this one. This one is in the 4th percentile – i.e., 4% of its contemporaries scored the same or lower than it.