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Selfie Aging Index: An Index for the Self-assessment of Healthy and Active Aging

Overview of attention for article published in Frontiers in Medicine, December 2017
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  • Above-average Attention Score compared to outputs of the same age (54th percentile)
  • Good Attention Score compared to outputs of the same age and source (70th percentile)

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6 X users

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Title
Selfie Aging Index: An Index for the Self-assessment of Healthy and Active Aging
Published in
Frontiers in Medicine, December 2017
DOI 10.3389/fmed.2017.00236
Pubmed ID
Authors

Judite Gonçalves, Maria Isabel Gomes, Miguel Fonseca, Tomás Teodoro, Pedro Pita Barros, Maria-Amália Botelho

Abstract

Governments across Europe want to promote healthy and active aging, as a matter of both public health and economic sustainability. Designing policies focused on the most vulnerable groups requires information at the individual level. However, a measure of healthy and active aging at the individual level does not yet exist. This paper develops the Selfie Aging Index (SAI), an individual-level index of healthy and active aging. The SAI is developed thinking about a tool that would allow each person to take a selfie of her aging status. Therefore, it is based entirely on self-assessed indicators. This paper also illustrates how the SAI may look like in practice. The SAI is based on the Biopsychosocial Assessment Model (MAB), a tool for the multidimensional assessment of older adults along three domains: biological, psychological, and social. Indicators are selected and their weights determined based on an ordered probit model that relates the MAB indicators to self-assessed health, which proxies healthy and active aging. The ordered probit model predicts the SAI based on the estimated parameters. Finally, predictions are rescaled to the 0-1 interval. Data for the SAI development come from the Study of the Aging Profiles of the Portuguese Population and the Survey of Health, Aging, and Retirement in Europe. The selected indicators are BMI, having difficulties moving around indoors and performing the activities of daily living, feeling depressed, feeling nervous, lacking energy, time awareness score, marital status, having someone to confide in, education, type of job, exercise, and smoking status. The model also determines their weights. Results shed light on various factors that contribute significantly to healthy and active aging. Two examples are mental health and exercise, which deserve more attention from individuals themselves, health-care professionals, and public health policy. The SAI has the potential to put the individual at the center of the healthy and active aging discussion, contribute to patient empowerment, and promote patient-centered care. It can become a useful instrument to monitor healthy and active aging for different actors, including individuals themselves, health-care professionals, and policy makers.

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X Demographics

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 68 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 68 100%

Demographic breakdown

Readers by professional status Count As %
Researcher 11 16%
Student > Master 8 12%
Student > Ph. D. Student 8 12%
Student > Bachelor 8 12%
Lecturer 3 4%
Other 11 16%
Unknown 19 28%
Readers by discipline Count As %
Medicine and Dentistry 10 15%
Sports and Recreations 7 10%
Psychology 7 10%
Social Sciences 5 7%
Economics, Econometrics and Finance 4 6%
Other 17 25%
Unknown 18 26%
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 19 January 2018.
All research outputs
#7,656,930
of 23,310,485 outputs
Outputs from Frontiers in Medicine
#1,825
of 5,971 outputs
Outputs of similar age
#153,768
of 442,487 outputs
Outputs of similar age from Frontiers in Medicine
#26
of 84 outputs
Altmetric has tracked 23,310,485 research outputs across all sources so far. This one is in the 44th percentile – i.e., 44% of other outputs scored the same or lower than it.
So far Altmetric has tracked 5,971 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 13.5. This one has gotten more attention than average, scoring higher than 68% 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 442,487 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 84 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 70% of its contemporaries.