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About this Attention Score

  • In the top 25% of all research outputs scored by Altmetric
  • High Attention Score compared to outputs of the same age (81st percentile)
  • Average Attention Score compared to outputs of the same age and source

Mentioned by

policy
1 policy source
twitter
12 X users

Readers on

mendeley
410 Mendeley
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Article details
Title
Translating E-Mental Health Into Practice: What Are the Barriers and Enablers to E-Mental Health Implementation by Aboriginal and Torres Strait Islander Health Professionals?
Published in
Journal of Medical Internet Research, January 2017
DOI 10.2196/jmir.6269
Pubmed ID
Authors
Abstract

With increasing evidence for the effectiveness of e-mental health interventions for enhancing mental health and well-being, a growing challenge is how to translate promising research findings into service delivery contexts. A 2012 e-mental health initiative by the Australian Federal Government (eMHPrac) has sought to address the issue through several strategies, one of which has been to train different health professional workforces in e-mental health (e-MH). The aim of the study was to report on the barriers and enablers of e-MH uptake in a cohort of predominantly Aboriginal and Torres Strait Islander health professionals (21 Indigenous, 5 non-Indigenous) who occupied mainly support or case management roles within their organizations. A 3- or 2-day e-MH training program was followed by up to 5 consultation sessions (mean 2.4 sessions) provided by the 2 trainers. The trainer-consultants provided written reports on each of the 30 consultation sessions for 7 consultation groups. They were also interviewed as part of the study. The written reports and interview data were thematically analyzed by 2 members of the research team. Uptake of e-MH among the consultation group was moderate (22%-30% of participants). There were significant organizational barriers to uptake resulting from procedural and administrative problems, demanding workloads, prohibitive policies, and a lack of fit between the organizational culture and the introduction of new technologies. Personal barriers included participant beliefs about the applicability of e-MH to certain populations, and workers' lack of confidence and skills. However, enthusiastic managers and tech-savvy champions could provide a counter-balance as organizational enablers of e-MH; and the consultation sessions themselves appear to have enhanced skills and confidence, shifted attitudes to new technologies, and seeded a perception that e-MH could be a valuable health education resource. A conclusion from the program was that it was important to match e-MH training and resources to work roles. In the latter stages of the consultation sessions, the Aboriginal and Torres Strait Islander health professionals responded very positively to YouTube video clips and apps with a health education dimension. Therapy-oriented apps and programs may fit less well within the scope of practice of some workforces, including this one. We suggest that researchers broaden their focus and definitions of e-MH and give rather more weight to e-MH's health education possibilities. Developing criteria for evaluating apps and YouTube videos may empower a rather greater section of health workforce to use e-MH with their clients.

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X Demographics

X Demographics

The data shown below were collected from the profiles of 12 X users who shared this research output. Click here to find out more about how the information was compiled.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 410 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Geographical breakdown
Country Count As %
Norway 2 <1%
Netherlands 1 <1%
Denmark 1 <1%
Unknown 406 99%

Demographic breakdown

Readers by professional status
Readers by professional status Count As %
Student > Ph. D. Student 59 14%
Student > Master 47 11%
Researcher 43 10%
Student > Bachelor 30 7%
Student > Doctoral Student 27 7%
Other 71 17%
Unknown 133 32%
Readers by discipline
Readers by discipline Count As %
Social Sciences 48 12%
Computer Science 44 11%
Psychology 38 9%
Business, Management and Accounting 33 8%
Medicine and Dentistry 32 8%
Other 61 15%
Unknown 154 38%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 9. 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 January 2019.
All research outputs
#4,725,328
of 27,787,196 outputs
Outputs from Journal of Medical Internet Research
#3,272
of 8,860 outputs
Outputs of similar age
#77,878
of 427,236 outputs
Outputs of similar age from Journal of Medical Internet Research
#46
of 69 outputs
Altmetric has tracked 27,787,196 research outputs across all sources so far. Compared to these this one has done well and is in the 82nd percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 8,860 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 18.5. This one has gotten more attention than average, scoring higher than 62% 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 427,236 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 81% of its contemporaries.
We're also able to compare this research output to 69 others from the same source and published within six weeks on either side of this one. This one is in the 33rd percentile – i.e., 33% of its contemporaries scored the same or lower than it.