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•  Purpose: To investigate the level of implicit anti-fat
bias of physical therapy students in two Kansas
Doctor of Physical Therapy (DPT) Programs.
•  Research Methods and Procedures: Paper and
pencil version of the Implicit Association Test (IAT) for
one private and one public DPT program. The IAT
was used to assess implicit weight bias utilizing the
target categories of “fat people” and “thin people”
paired with one attitude attribute category of “good”
vs. “bad”, and two stereotype attribute categories of
“lazy” vs. “motivated” and “stupid” vs. “smart.
•  Results: Both programs exhibited significant implicit
anti-fat bias. The public university exhibited a greater
implicit anti-fat bias for only one IAT pairing compared
to the private university. There was no difference
between males and females.
•  Discussion: Physical therapy students show a
strong anti-fat bias. Identification of implicit anti-fat
bias is important to allow for implementation of
educational strategies to eliminate such bias.
Abstract
•  Two-thirds of Americans are overweight or obese.1
•  Obesity is a rising global epidemic.2
•  Research has consistently documented weight bias
in various healthcare professionals including
physicians, nurses, medical students, dietitians and
psychologists.3,4,5,6-9
•  Physical Therapy students are taught the
importance of exercise and nutrition, but the
increasing normalcy of inactivity and obesity could
have a complacent and negative impact on the
treatment of this ever-rising disease.
•  Implicit biases are unconscious biases that occur
automatically and are usually measured by
response-latency techniques, such as the Implicit
Association Test (IAT). These tests measure the
strength of association between target categories
and attribute categories.12,13,14
•  Explicit biases are conscious and intentional and
they are measured through self-reports (i.e. Likert
Scale).3,6-9,12
•  Bringing forward an implicit bias is more difficult
because the individual is not aware of how their
subconscious feelings could possibly affect patient
care.
•  The development and use of the IAT has been
widely accepted because of the challenges
presented with measuring implicit attitudes.
Introduction
Methods
•  This study used the paper and pencil version of the
IAT.
•  Subjects were given two trial IAT. In the first trial,
the categories are paired with two on one side
(flowers and good) and two on the other side
(insects and bad). To classify the word, the subject
place checkmark on either the right or left side of
the word that corresponds to the correct category.
In the second trial, the categories were switched:
“flowers and bad” on one side and “insects and
good” were on the other side.13,18
•  Each trial was timed for 20 seconds. When the task
is easier, subjects were able to categorize more
words in the 20 second time period.5,18,19
•  After the two practice trials, six weight IAT were
performed. The target categories of “fat people” and
“thin people” paired with one attitude attribute
category of “good” vs. “bad”, and two stereotype
attribute categories of “lazy” vs. “motivated” and
“stupid” vs. “smart”.
•  The IAT was scored by counting how many words
the subject were able to classify on each trial. If
subjects were able to classify more words in the
matched task (fat people: bad, lazy, stupid) than the
mismatched task (fat people: good, motivated,
smart) in the 20 second time frame, then it is
considered an anti-fat bias.
•  Demographic Questionnaire: included gender,
whether the subject attended a private or public
institution, and year in doctor of physical therapy
program.
Participants
•  Subjects who classified less than five words or had
an error rate of 35% or greater were disqualified
from the study.20
•  IAT data was examined using a sample t-test.
•  There was a significant implicit anti-fat bias on each
of the three attribute categories: bad-good, t(111) =
18.307 (p < .000); lazy-motivated, t (111) = 15.758 (p
< .000); stupid-smart, t(111) = 12.477 (p < .000).
•  Public vs. private DPT program: There were 59
public school subjects and 53 private school
subjects.
•  The public school expressed a stronger anti-fat bias
compared with the private school on the bad-good
IAT with the mean score for public of 9.68 ± 5.24
compared with 7.77 ± 4.73 for private. This was the
only IAT test that had a statistical significance (<
0.05).
•  Sex: There were 63 females and 49 males included
in the statistical analyses.
•  Women expressed a slightly stronger bias than men
on the implicit fat-bad and fat-lazy measure.
•  Bad-good IAT: mean score for women 9.03 ± 5.65
compared with 8.08 ± 5.48 for men.
•  Lazy-motivated IAT: mean score for women 6.63 ±
4.79 compared with 5.98 ± 4.61 for men.
Results
•  Physical therapy students from DPT programs in
both settings (public and private) in Kansas
demonstrated significant implicit anti-fat bias. The
findings in this study were consistent with initial
studies assessing other healthcare professionals.
3,4,5-9,15
•  Subjects associated the words bad, lazy and stupid
with fat people more easily than with thin
individuals. Demonstrating a significant presence of
implicit weight biases amongst the subjects in this
study. This is important to know, due to the fact that
physical therapists often work with obese individuals
and it is imperative to know what biases may be
present in order to address them.
•  This could prove that providing information to
students about obesity and emphasizing that it
could potentially impact the quality of patient care,
could lead to improvements in the healthcare of
these individuals.23
•  Subjects were drawn from a convenience sampling
of individuals
•  A large percentage (25%) of subjects were excluded
from the study and statistical analyses.
•  Limited research involving weight biases amongst
physical therapy students presents a large gap in
knowledge.
•  The Stefani Doctor of Physical Therapy Program at
the University of Saint Mary for the funding of the
study.
•  Dr. Anand Shetty for his assistance in statistical
analysis
Candace Bahner PT, DPT, MS:
candy.bahner@stmary.edu
Cecilia Benton SPT: cecilia.benton@my.stmary.edu
Brianne Davis SPT: brianne.davis@my.stmary.edu
Brittany Gardner SPT: Brittany.garder@my.stmary.edu
Conclusion
Limitations
Acknowledgements
Contact Information
Weight Bias Among Physical Therapy Students in Two Kansas
Doctor of Physical Therapy Programs
Candace Bahner PT, DPT, MS, Cecilia Benton SPT, Brianne Davis SPT, Brittany Gardner SPT
Stefani Doctor of Physical Therapy, University of Saint Mary
•  Total subjects (N = 150) were students in the DPT
programs in two universities (1 private and 1 public)
in the state of Kansas.
•  There were 77 public school subjects and 73
private school subjects.
•  Eighty-four women and 62 men with 4 subjects not
indicating their gender.
•  There were first year students, 35 second year
students, and 33 third year students; 4 individuals
did not indicate their year in school.
•  Each school only had two of the three class years
on campus to participate due to students being on
clinical affiliations.
References

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Gardner_Brittany_Research_Poster

  • 1. •  Purpose: To investigate the level of implicit anti-fat bias of physical therapy students in two Kansas Doctor of Physical Therapy (DPT) Programs. •  Research Methods and Procedures: Paper and pencil version of the Implicit Association Test (IAT) for one private and one public DPT program. The IAT was used to assess implicit weight bias utilizing the target categories of “fat people” and “thin people” paired with one attitude attribute category of “good” vs. “bad”, and two stereotype attribute categories of “lazy” vs. “motivated” and “stupid” vs. “smart. •  Results: Both programs exhibited significant implicit anti-fat bias. The public university exhibited a greater implicit anti-fat bias for only one IAT pairing compared to the private university. There was no difference between males and females. •  Discussion: Physical therapy students show a strong anti-fat bias. Identification of implicit anti-fat bias is important to allow for implementation of educational strategies to eliminate such bias. Abstract •  Two-thirds of Americans are overweight or obese.1 •  Obesity is a rising global epidemic.2 •  Research has consistently documented weight bias in various healthcare professionals including physicians, nurses, medical students, dietitians and psychologists.3,4,5,6-9 •  Physical Therapy students are taught the importance of exercise and nutrition, but the increasing normalcy of inactivity and obesity could have a complacent and negative impact on the treatment of this ever-rising disease. •  Implicit biases are unconscious biases that occur automatically and are usually measured by response-latency techniques, such as the Implicit Association Test (IAT). These tests measure the strength of association between target categories and attribute categories.12,13,14 •  Explicit biases are conscious and intentional and they are measured through self-reports (i.e. Likert Scale).3,6-9,12 •  Bringing forward an implicit bias is more difficult because the individual is not aware of how their subconscious feelings could possibly affect patient care. •  The development and use of the IAT has been widely accepted because of the challenges presented with measuring implicit attitudes. Introduction Methods •  This study used the paper and pencil version of the IAT. •  Subjects were given two trial IAT. In the first trial, the categories are paired with two on one side (flowers and good) and two on the other side (insects and bad). To classify the word, the subject place checkmark on either the right or left side of the word that corresponds to the correct category. In the second trial, the categories were switched: “flowers and bad” on one side and “insects and good” were on the other side.13,18 •  Each trial was timed for 20 seconds. When the task is easier, subjects were able to categorize more words in the 20 second time period.5,18,19 •  After the two practice trials, six weight IAT were performed. The target categories of “fat people” and “thin people” paired with one attitude attribute category of “good” vs. “bad”, and two stereotype attribute categories of “lazy” vs. “motivated” and “stupid” vs. “smart”. •  The IAT was scored by counting how many words the subject were able to classify on each trial. If subjects were able to classify more words in the matched task (fat people: bad, lazy, stupid) than the mismatched task (fat people: good, motivated, smart) in the 20 second time frame, then it is considered an anti-fat bias. •  Demographic Questionnaire: included gender, whether the subject attended a private or public institution, and year in doctor of physical therapy program. Participants •  Subjects who classified less than five words or had an error rate of 35% or greater were disqualified from the study.20 •  IAT data was examined using a sample t-test. •  There was a significant implicit anti-fat bias on each of the three attribute categories: bad-good, t(111) = 18.307 (p < .000); lazy-motivated, t (111) = 15.758 (p < .000); stupid-smart, t(111) = 12.477 (p < .000). •  Public vs. private DPT program: There were 59 public school subjects and 53 private school subjects. •  The public school expressed a stronger anti-fat bias compared with the private school on the bad-good IAT with the mean score for public of 9.68 ± 5.24 compared with 7.77 ± 4.73 for private. This was the only IAT test that had a statistical significance (< 0.05). •  Sex: There were 63 females and 49 males included in the statistical analyses. •  Women expressed a slightly stronger bias than men on the implicit fat-bad and fat-lazy measure. •  Bad-good IAT: mean score for women 9.03 ± 5.65 compared with 8.08 ± 5.48 for men. •  Lazy-motivated IAT: mean score for women 6.63 ± 4.79 compared with 5.98 ± 4.61 for men. Results •  Physical therapy students from DPT programs in both settings (public and private) in Kansas demonstrated significant implicit anti-fat bias. The findings in this study were consistent with initial studies assessing other healthcare professionals. 3,4,5-9,15 •  Subjects associated the words bad, lazy and stupid with fat people more easily than with thin individuals. Demonstrating a significant presence of implicit weight biases amongst the subjects in this study. This is important to know, due to the fact that physical therapists often work with obese individuals and it is imperative to know what biases may be present in order to address them. •  This could prove that providing information to students about obesity and emphasizing that it could potentially impact the quality of patient care, could lead to improvements in the healthcare of these individuals.23 •  Subjects were drawn from a convenience sampling of individuals •  A large percentage (25%) of subjects were excluded from the study and statistical analyses. •  Limited research involving weight biases amongst physical therapy students presents a large gap in knowledge. •  The Stefani Doctor of Physical Therapy Program at the University of Saint Mary for the funding of the study. •  Dr. Anand Shetty for his assistance in statistical analysis Candace Bahner PT, DPT, MS: candy.bahner@stmary.edu Cecilia Benton SPT: cecilia.benton@my.stmary.edu Brianne Davis SPT: brianne.davis@my.stmary.edu Brittany Gardner SPT: Brittany.garder@my.stmary.edu Conclusion Limitations Acknowledgements Contact Information Weight Bias Among Physical Therapy Students in Two Kansas Doctor of Physical Therapy Programs Candace Bahner PT, DPT, MS, Cecilia Benton SPT, Brianne Davis SPT, Brittany Gardner SPT Stefani Doctor of Physical Therapy, University of Saint Mary •  Total subjects (N = 150) were students in the DPT programs in two universities (1 private and 1 public) in the state of Kansas. •  There were 77 public school subjects and 73 private school subjects. •  Eighty-four women and 62 men with 4 subjects not indicating their gender. •  There were first year students, 35 second year students, and 33 third year students; 4 individuals did not indicate their year in school. •  Each school only had two of the three class years on campus to participate due to students being on clinical affiliations. References