Literature DB >> 25620843

Public and health professionals' misconceptions about the dynamics of body weight gain/loss.

Tarek Abdel-Hamid1, Felix Ankel2, Michele Battle-Fisher3, Bryan Gibson4, Gilberto Gonzalez-Parra5, Mohammad Jalali6, Kirsikka Kaipainen7, Nishan Kalupahana8, Ozge Karanfil9, Achla Marathe10, Brian Martinson11, Karma McKelvey12, Suptendra Nath Sarbadhikari13, Stephen Pintauro14, Patrick Poucheret15, Nicolaas Pronk16, Ying Qian17, Edward Sazonov18, Kim Van Oorschot19, Akshay Venkitasubramanian20, Philip Murphy21.   

Abstract

Human body energy storage operates as a stock-and-flow system with inflow (food intake) and outflow (energy expenditure). In spite of the ubiquity of stock-and-flow structures, evidence suggests that human beings fail to understand stock accumulation and rates of change, a difficulty called the stock-flow failure. This study examines the influence of health care training and cultural background in overcoming stock-flow failure. A standardized protocol assessed lay people's and health care professionals' ability to apply stock-and-flow reasoning to infer the dynamics of weight gain/loss during the holiday season (621 subjects from seven countries). Our results indicate that both types of subjects exhibited systematic errors indicative of use of erroneous heuristics. Stock-flow failure was found across cultures and was not improved by professional health training. The problem of stock-flow failure as a transcultural global issue with education and policy implications is discussed.

Entities:  

Year:  2014        PMID: 25620843      PMCID: PMC4300993          DOI: 10.1002/sdr.1517

Source DB:  PubMed          Journal:  Syst Dyn Rev        ISSN: 0883-7066


  7 in total

Review 1.  Dynamic decision making: human control of complex systems.

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2.  Energy balance and its components: implications for body weight regulation.

Authors:  Kevin D Hall; Steven B Heymsfield; Joseph W Kemnitz; Samuel Klein; Dale A Schoeller; John R Speakman
Journal:  Am J Clin Nutr       Date:  2012-04       Impact factor: 7.045

3.  Weight loss expectations in obese patients and treatment attrition: an observational multicenter study.

Authors:  Riccardo Dalle Grave; Simona Calugi; Enrico Molinari; Maria Letizia Petroni; Mario Bondi; Angelo Compare; Giulio Marchesini
Journal:  Obes Res       Date:  2005-11

4.  A prospective study of holiday weight gain.

Authors:  J A Yanovski; S Z Yanovski; K N Sovik; T T Nguyen; P M O'Neil; N G Sebring
Journal:  N Engl J Med       Date:  2000-03-23       Impact factor: 91.245

Review 5.  Global burden of obesity in 2005 and projections to 2030.

Authors:  T Kelly; W Yang; C-S Chen; K Reynolds; J He
Journal:  Int J Obes (Lond)       Date:  2008-07-08       Impact factor: 5.095

6.  Mistakes were made: misperception as a barrier to reducing overweight.

Authors:  F Kuchler; J N Variyam
Journal:  Int J Obes Relat Metab Disord       Date:  2003-07

7.  Myths, presumptions, and facts about obesity.

Authors:  Krista Casazza; Kevin R Fontaine; Arne Astrup; Leann L Birch; Andrew W Brown; Michelle M Bohan Brown; Nefertiti Durant; Gareth Dutton; E Michael Foster; Steven B Heymsfield; Kerry McIver; Tapan Mehta; Nir Menachemi; P K Newby; Russell Pate; Barbara J Rolls; Bisakha Sen; Daniel L Smith; Diana M Thomas; David B Allison
Journal:  N Engl J Med       Date:  2013-01-31       Impact factor: 91.245

  7 in total
  4 in total

1.  Dynamics of intervention adoption, implementation, and maintenance inside organizations: The case of an obesity prevention initiative.

Authors:  Mohammad S Jalali; Hazhir Rahmandad; Sally Lawrence Bullock; Seung Hee Lee-Kwan; Joel Gittelsohn; Alice Ammerman
Journal:  Soc Sci Med       Date:  2018-12-23       Impact factor: 4.634

2.  Dynamics of Implementation and Maintenance of Organizational Health Interventions.

Authors:  Mohammad S Jalali; Hazhir Rahmandad; Sally Lawrence Bullock; Alice Ammerman
Journal:  Int J Environ Res Public Health       Date:  2017-08-15       Impact factor: 3.390

3.  A Dynamic Model of Post-Traumatic Stress Disorder for Military Personnel and Veterans.

Authors:  Navid Ghaffarzadegan; Alireza Ebrahimvandi; Mohammad S Jalali
Journal:  PLoS One       Date:  2016-10-07       Impact factor: 3.240

4.  Interpreting time-series COVID data: reasoning biases, risk perception, and support for public health measures.

Authors:  Jason L Harman; Justin M Weinhardt; James W Beck; Ivy Mai
Journal:  Sci Rep       Date:  2021-08-02       Impact factor: 4.379

  4 in total

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