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Measuring patient activation in Italy: Translation, adaptation and validation of the Italian version of the patient activation measure 13 (PAM13-I)

Overview of attention for article published in BMC Medical Informatics and Decision Making, December 2015
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  • Good Attention Score compared to outputs of the same age (66th percentile)
  • Above-average Attention Score compared to outputs of the same age and source (54th percentile)

Mentioned by

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4 tweeters

Citations

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34 Dimensions

Readers on

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32 Mendeley
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Title
Measuring patient activation in Italy: Translation, adaptation and validation of the Italian version of the patient activation measure 13 (PAM13-I)
Published in
BMC Medical Informatics and Decision Making, December 2015
DOI 10.1186/s12911-015-0232-9
Pubmed ID
Authors

Guendalina Graffigna, Serena Barello, Andrea Bonanomi, Edoardo Lozza, Judith Hibbard

Abstract

The Patient Activation Measure (PAM13) is an instrument that assesses patient knowledge, skills, and confidence for disease self-management. This cross-sectional study was aimed to validate a culturally-adapted Italian Patient Activation Measure (PAM13-I) for patients with chronic conditions. 519 chronic patients were involved in the Italian validation study and responded to PAM13-I. The PAM 13 was translated into Italian by a standardized forward-backward translation. Data quality was assessed by mean, median, item response, missing values, floor and ceiling effects, internal consistency (Cronbach's alpha and average inter-item correlation), item-rest correlations. Rasch Model and differential item functioning assessed scale properties. Mean PAM13-I score was 66.2. Rasch analysis showed that the PAM13-I is a good measure of patient activation. The level of internal consistency was good (α = 0.88). For all items, the distribution of answers was left-skewed, with a small floor effect (range 1.7-4.5 %) and a moderate ceiling effect (range 27.6-55.0 %). The Italian version formed a unidimensional, probabilistic Guttman-like scale explaining 41 % of the variance. The PAM13-I has been demonstrated to be a valid and reliable measure of patient activation and the present study suggests its applicability to the Italian-speaking chronic patient population. The measure has good psychometric properties and appears to be consistent with the developmental nature of the patient activation phenomenon, although it presents a different ranking order of the items comparing to the American version. PAM13-I can be a useful assessment tool to evaluate interventions aimed at improving patient engagement in healthcare and to train doctors in attuning their communication to the level of patients' activation. Future research could be conducted to further confirm the validity of the PAM13-I.

Twitter Demographics

The data shown below were collected from the profiles of 4 tweeters who shared this research output. Click here to find out more about how the information was compiled.

Mendeley readers

The data shown below were compiled from readership statistics for 32 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 32 100%

Demographic breakdown

Readers by professional status Count As %
Researcher 5 16%
Student > Doctoral Student 5 16%
Student > Ph. D. Student 4 13%
Student > Bachelor 4 13%
Professor 3 9%
Other 5 16%
Unknown 6 19%
Readers by discipline Count As %
Medicine and Dentistry 9 28%
Psychology 6 19%
Nursing and Health Professions 5 16%
Social Sciences 2 6%
Linguistics 1 3%
Other 0 0%
Unknown 9 28%

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 21 January 2016.
All research outputs
#6,307,891
of 12,437,358 outputs
Outputs from BMC Medical Informatics and Decision Making
#485
of 1,125 outputs
Outputs of similar age
#112,873
of 343,651 outputs
Outputs of similar age from BMC Medical Informatics and Decision Making
#66
of 151 outputs
Altmetric has tracked 12,437,358 research outputs across all sources so far. This one is in the 48th percentile – i.e., 48% of other outputs scored the same or lower than it.
So far Altmetric has tracked 1,125 research outputs from this source. They receive a mean Attention Score of 4.9. This one has gotten more attention than average, scoring higher than 55% 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 343,651 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 151 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 54% of its contemporaries.