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Affective Forecasting: An Unrecognized Challenge in Making Serious Health Decisions

Overview of attention for article published in Journal of General Internal Medicine, July 2008
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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 (96th percentile)
  • High Attention Score compared to outputs of the same age and source (85th percentile)

Mentioned by

news
1 news outlet
blogs
1 blog
twitter
10 X users
wikipedia
4 Wikipedia pages

Citations

dimensions_citation
153 Dimensions

Readers on

mendeley
166 Mendeley
Title
Affective Forecasting: An Unrecognized Challenge in Making Serious Health Decisions
Published in
Journal of General Internal Medicine, July 2008
DOI 10.1007/s11606-008-0719-5
Pubmed ID
Authors

Jodi Halpern, Robert M. Arnold

Abstract

Patients facing medical decisions that will impact quality of life make assumptions about how they will adjust emotionally to living with health declines and disability. Despite abundant research on decision-making, we have no direct research on how accurately patients envision their future well-being and how this influences their decisions. Outside medicine, psychological research on "affective forecasting" consistently shows that people poorly predict their future ability to adapt to adversity. This finding is important for medicine, since many serious health decisions hinge on quality-of-life judgments. We describe three specific mechanisms for affective forecasting errors that may influence health decisions: focalism, in which people focus more on what will change than on what will stay the same; immune neglect, in which they fail to envision how their own coping skills will lessen their unhappiness; and failure to predict adaptation, in which people fail to envision shifts in what they value. We discuss emotional and social factors that interact with these cognitive biases. We describe how caregivers can recognize these biases in the clinical setting and suggest interventions to help patients recognize and address affective forecasting errors.

X Demographics

X Demographics

The data shown below were collected from the profiles of 10 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 166 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United Kingdom 2 1%
Canada 2 1%
United States 2 1%
Spain 1 <1%
China 1 <1%
Unknown 158 95%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 34 20%
Researcher 25 15%
Student > Master 25 15%
Student > Bachelor 18 11%
Student > Doctoral Student 15 9%
Other 29 17%
Unknown 20 12%
Readers by discipline Count As %
Psychology 59 36%
Medicine and Dentistry 24 14%
Social Sciences 13 8%
Nursing and Health Professions 6 4%
Biochemistry, Genetics and Molecular Biology 6 4%
Other 32 19%
Unknown 26 16%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 26. 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 17 March 2023.
All research outputs
#1,492,345
of 25,389,520 outputs
Outputs from Journal of General Internal Medicine
#1,177
of 8,165 outputs
Outputs of similar age
#3,682
of 100,194 outputs
Outputs of similar age from Journal of General Internal Medicine
#11
of 69 outputs
Altmetric has tracked 25,389,520 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 94th percentile: it's in the top 10% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 8,165 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 22.1. This one has done well, scoring higher than 85% 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 100,194 tracked outputs that were published within six weeks on either side of this one in any source. This one has done particularly well, scoring higher than 96% 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 has done well, scoring higher than 85% of its contemporaries.