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Searching for success: Development of a combined patient-reported-outcome (“PRO”) criterion for operationalizing success in multi-modal pain therapy

Overview of attention for article published in BMC Health Services Research, July 2015
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1 X user
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2 Wikipedia pages

Citations

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11 Dimensions

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37 Mendeley
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Title
Searching for success: Development of a combined patient-reported-outcome (“PRO”) criterion for operationalizing success in multi-modal pain therapy
Published in
BMC Health Services Research, July 2015
DOI 10.1186/s12913-015-0939-4
Pubmed ID
Authors

Carolin Donath, Lisa Dorscht, Elmar Graessel, Reinhard Sittl, Christoph Schoen

Abstract

There is a need for a way to measure success in multi-modal pain therapy that researchers and clinicians can agree upon. According to developments in health services research, operationalizing success should take patient-reported outcomes into account. We will present a success criterion for pain therapy that combines different patient-reported variables and includes validity measures. The usable criterion should be part of a statistically significant and satisfactory model identifying predictors of successful pain therapy. Routine data from 375 patients treated with multi-modal pain therapy from 2008 to 2013 were used. The change scores of five constructs were used for the combined success criterion: pain severity, disability due to pain, depressiveness, and physical- and mental-health-related quality of life. According to the literature, an improvement of at least ½ standard deviation was required on at least four of the five constructs to count as successful. A three-step analytical approach including multiple binary logistic regression analysis was chosen to identify the predictors of therapy success with the success criterion as the dependent variable. A total of 58.1 % of the patients were classified as successful. Convergent and predictive validity data show significant correlations between the criterion and established instruments, while discriminative validity could also be shown. A multiple binary logistic regression analysis confirmed the feasibility; a significant model (Chi(2) (8) = 52.585; p < .001) that explained 17.6 % of the variance identified the following predictors of therapy success: highest pain severity in the last 4 weeks, disability due to pain, and number of physician visits in the last 6 months. It is possible to develop a feasible success criterion that combines several variables and includes patient-reported outcomes ("PROs") with routine data that can be used in a predictor analysis in multi-modal pain therapy. The criterion was based on basic constructs used in pain therapy and used widespread validated self-rating instruments. Thus, it should be easy to transfer this criterion to other institutions.

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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.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 37 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United Kingdom 2 5%
Spain 1 3%
Unknown 34 92%

Demographic breakdown

Readers by professional status Count As %
Student > Master 7 19%
Student > Bachelor 5 14%
Student > Doctoral Student 4 11%
Professor 3 8%
Researcher 3 8%
Other 7 19%
Unknown 8 22%
Readers by discipline Count As %
Medicine and Dentistry 9 24%
Psychology 9 24%
Nursing and Health Professions 4 11%
Social Sciences 3 8%
Unspecified 1 3%
Other 3 8%
Unknown 8 22%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 4. 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 06 March 2018.
All research outputs
#7,225,652
of 22,840,638 outputs
Outputs from BMC Health Services Research
#3,570
of 7,639 outputs
Outputs of similar age
#76,359
of 234,762 outputs
Outputs of similar age from BMC Health Services Research
#58
of 113 outputs
Altmetric has tracked 22,840,638 research outputs across all sources so far. This one has received more attention than most of these and is in the 67th percentile.
So far Altmetric has tracked 7,639 research outputs from this source. They typically receive more attention than average, with a mean Attention Score of 7.7. This one has gotten more attention than average, scoring higher than 52% 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 234,762 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 66% of its contemporaries.
We're also able to compare this research output to 113 others from the same source and published within six weeks on either side of this one. This one is in the 46th percentile – i.e., 46% of its contemporaries scored the same or lower than it.