Literature DB >> 31003876

Influence of weight etiology information and trainee characteristics on Physician-trainees' clinical and interpersonal communication.

Rachel W Cohen1, Susan Persky2.   

Abstract

OBJECTIVE: This analysis explores the effects of relaying information about the genetic and behavioral causes of obesity (vs. control) on physician trainees' verbal communication behavior with a virtual patient with obesity. Moderation by physician trainees' gender and BMI was also assessed.
METHODS: 119 physician trainees' verbal responses were recorded and coded using a close-ended content analytic approach.
RESULTS: Physician trainees in the behavioral and genetic information conditions were more likely to discuss weight (behavioral: AOR = 5.40; genetic: AOR = 6.58,) and provide lifestyle counseling (behavioral: AOR = 10.92; genetic: AOR = 3.50). Those in the behavioral condition were more likely to make assumptions about the patient's lifestyle behavior (AOR = 5.53) and use stigmatizing language (AOR = 4.69). Heavier physician trainees in the genetic condition had shorter interactions (β = -0.53, p <  0.01).
CONCLUSION: Emphasizing the genetic causes of overweight offers a potential avenue for encouraging clinical communication with patients with obesity, without also increasing prejudice and bias. Additional efforts may be needed to reap the benefits of genetic information for providers with higher weight. PRACTICE IMPLICATIONS: For providers, considering genetic factors underlying patient body weight and obesity risk may serve to reduce stigmatizing communication with patients. Published by Elsevier B.V.

Entities:  

Keywords:  Healthcare communication; Medical students; Weight management; Weight stigma

Mesh:

Year:  2019        PMID: 31003876      PMCID: PMC6660982          DOI: 10.1016/j.pec.2019.04.011

Source DB:  PubMed          Journal:  Patient Educ Couns        ISSN: 0738-3991


  33 in total

1.  Motivating or stigmatizing? Public perceptions of weight-related language used by health providers.

Authors:  R Puhl; J L Peterson; J Luedicke
Journal:  Int J Obes (Lond)       Date:  2012-07-10       Impact factor: 5.095

Review 2.  Precision behavioral medicine: Implications of genetic and genomic discoveries for behavioral weight loss treatment.

Authors:  Jeanne M McCaffery
Journal:  Am Psychol       Date:  2018-11

3.  The influence of one's own body weight on implicit and explicit anti-fat bias.

Authors:  Marlene B Schwartz; Lenny R Vartanian; Brian A Nosek; Kelly D Brownell
Journal:  Obesity (Silver Spring)       Date:  2006-03       Impact factor: 5.002

4.  Reducing anti-fat prejudice in preservice health students: a randomized trial.

Authors:  Kerry S O'Brien; Rebecca M Puhl; Janet D Latner; Azeem S Mir; John A Hunter
Journal:  Obesity (Silver Spring)       Date:  2010-04-15       Impact factor: 5.002

5.  A multinational examination of weight bias: predictors of anti-fat attitudes across four countries.

Authors:  R M Puhl; J D Latner; K O'Brien; J Luedicke; S Danielsdottir; M Forhan
Journal:  Int J Obes (Lond)       Date:  2015-03-20       Impact factor: 5.095

6.  Patients' perceived health information needs in inflammatory arthritis: A systematic review.

Authors:  Kathryn Connelly; Julian Segan; Alicia Lu; Meher Saini; Flavia M Cicuttini; Louisa Chou; Andrew M Briggs; Kaye Sullivan; Maheeka Seneviwickrama; Anita E Wluka
Journal:  Semin Arthritis Rheum       Date:  2018-08-18       Impact factor: 5.532

7.  Medical student bias and care recommendations for an obese versus non-obese virtual patient.

Authors:  S Persky; C P Eccleston
Journal:  Int J Obes (Lond)       Date:  2010-09-07       Impact factor: 5.095

Review 8.  NIH working group report-using genomic information to guide weight management: From universal to precision treatment.

Authors:  Molly S Bray; Ruth J F Loos; Jeanne M McCaffery; Charlotte Ling; Paul W Franks; George M Weinstock; Michael P Snyder; Jason L Vassy; Tanya Agurs-Collins
Journal:  Obesity (Silver Spring)       Date:  2016-01       Impact factor: 5.002

9.  Disparities in physician-patient communication by obesity status.

Authors:  Patrick Richard; Christine Ferguson; Anthony S Lara; Jennifer Leonard; Mustafa Younis
Journal:  Inquiry       Date:  2014-01-01       Impact factor: 1.730

10.  Preferences for physician weight status among women with overweight.

Authors:  M R Goldring; S Persky
Journal:  Obes Sci Pract       Date:  2018-04-17
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