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Tailoring interventions to implement recommendations for the treatment of elderly patients with depression: a qualitative study

Overview of attention for article published in International Journal of Mental Health Systems, September 2015
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  • Above-average Attention Score compared to outputs of the same age (54th percentile)
  • Above-average Attention Score compared to outputs of the same age and source (57th percentile)

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Title
Tailoring interventions to implement recommendations for the treatment of elderly patients with depression: a qualitative study
Published in
International Journal of Mental Health Systems, September 2015
DOI 10.1186/s13033-015-0027-5
Pubmed ID
Authors

Eivind Aakhus, Ingeborg Granlund, Andrew D. Oxman, Signe A. Flottorp

Abstract

To improve adherence to evidence-based recommendations, it is logical to identify determinants of practice and tailor interventions to address these. We have previously prioritised six recommendations to improve treatment of elderly patients with depression, and identified determinants of adherence to these recommendations. The aim of this article is to describe how we tailored interventions to address the determinants for the implementation of the recommendations. We drafted an intervention plan, based on the determinants we had identified in a previous study. We conducted six group interviews with representatives of health professionals (GPs and nurses), implementation researchers, quality improvement officers, professional and voluntary organisations and relatives of elderly patients with depression. We informed about the gap between evidence and practice for elderly patients with depression and presented the prioritised determinants that applied to each recommendation. Participants brainstormed individually and then in groups, suggesting interventions to address the determinants. We then presented evidence on the effectiveness of strategies for implementing depression guidelines. We asked the groups to prioritise the suggested interventions considering the perceived impact of determinants and of interventions, the research evidence underlying the interventions, feasibility and cost. We audiotaped and transcribed the interviews and applied a five step framework for our analysis. We created a logic model with links between the determinants, the interventions, and the targeted improvements in adherence. Six groups with 29 individuals provided 379 suggestions for interventions. Most suggestions could be fit within the drafted plan, but the groups provided important amendments or additions. We sorted the interventions into six categories: resources for municipalities to develop a collaborative care plan, resources for health professionals, resources for patients and their relatives, outreach visits, educational and web-based tools. Some interventions addressed one determinant, while other interventions addressed several determinants. It was feasible and helpful to use group interviews and combine open and structured approaches to identify interventions that addressed prioritised determinants to adherence to the recommendations. This approach generated a large number of suggested interventions. We had to prioritise to tailor the interventions strategies.

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 73 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 73 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 12 16%
Student > Master 11 15%
Researcher 10 14%
Student > Doctoral Student 9 12%
Student > Bachelor 5 7%
Other 7 10%
Unknown 19 26%
Readers by discipline Count As %
Psychology 13 18%
Nursing and Health Professions 12 16%
Medicine and Dentistry 10 14%
Social Sciences 5 7%
Biochemistry, Genetics and Molecular Biology 2 3%
Other 9 12%
Unknown 22 30%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 3. 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 18 May 2016.
All research outputs
#12,935,224
of 22,828,180 outputs
Outputs from International Journal of Mental Health Systems
#445
of 718 outputs
Outputs of similar age
#118,684
of 267,845 outputs
Outputs of similar age from International Journal of Mental Health Systems
#3
of 7 outputs
Altmetric has tracked 22,828,180 research outputs across all sources so far. This one is in the 42nd percentile – i.e., 42% of other outputs scored the same or lower than it.
So far Altmetric has tracked 718 research outputs from this source. They typically receive more attention than average, with a mean Attention Score of 8.3. This one is in the 37th percentile – i.e., 37% 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 267,845 tracked outputs that were published within six weeks on either side of this one in any source. This one has gotten more attention than average, scoring higher than 54% of its contemporaries.
We're also able to compare this research output to 7 others from the same source and published within six weeks on either side of this one. This one has scored higher than 4 of them.