Sports Medicine

, Volume 48, Issue 6, pp 1389–1404 | Cite as

Behavioral and Neural Evidence of the Rewarding Value of Exercise Behaviors: A Systematic Review

  • Boris Cheval
  • Rémi Radel
  • Jason L. Neva
  • Lara A. Boyd
  • Stephan P. Swinnen
  • David Sander
  • Matthieu P. BoisgontierEmail author
Systematic Review



In a time of physical inactivity pandemic, attempts to better understand the factors underlying the regulation of exercise behavior are important. The dominant neurobiological approach to exercise behavior considers physical activity to be a reward; however, negative affective responses during exercise challenge this idea.


Our objective was to systematically review studies testing the automatic reactions triggered by stimuli associated with different types of exercise behavior (e.g. physical activity, sedentary behaviors) and energetic cost variations (e.g. decreased energetic cost, irrespective of the level of physical activity). We also examined evidence supporting the hypothesis that behaviors minimizing energetic cost (BMEC) are rewarding.


Two authors systematically searched, screened, extracted, and analyzed data from articles in the MEDLINE database.


We included 26 studies. Three outcomes of automatic processes were tested: affective reactions, attentional capture, and approach tendencies. Behavioral results show that physical activity can become attention-grabbing, automatically trigger positive affect, and elicit approach behaviors. These automatic reactions explain and predict exercise behaviors; however, the use of a wide variety of measures prevents drawing solid conclusions about the specific effects of automatic processes. Brain imaging results are scarce but show that stimuli associated with physical activity and, to a lesser extent, sedentary behaviors activate regions involved in reward processes. Studies investigating the rewarding value of behaviors driving energetic cost variations such as BMEC are lacking.


Reward is an important factor in exercise behavior. The literature based on the investigation of automatic behaviors seems in line with the suggestion that physical activity is rewarding, at least for physically active individuals. Results suggest that sedentary behaviors could also be rewarding, although this evidence remains weak due to a lack of investigations. Finally, from an evolutionary perspective, BMEC are likely to be rewarding; however, no study has investigated this hypothesis. In sum, additional studies are required to establish a strong and complete framework of the reward processes underlying automatic exercise behavior.


Author Contributions

MB and BC conceived the new approach to exercise behavior as described in the Introduction, conducted the systematic review, and wrote the first draft of the manuscript. All authors subsequently contributed to improvement of the manuscript.

Compliance with Ethical Standards


Matthieu Boisgontier is supported by research Grants (1504015N, 1501018N), a post-doctoral fellowship, and a Grant for a long stay abroad from the Research Foundation—Flanders (FWO). The other authors report no sources of funding used to assist in the preparation of this article.

Conflict of interest

Boris Cheval, Rémi Radel, Jason Neva, Lara Boyd, Stephan Swinnen, David Sander, and Matthieu Boisgontier declare that they have no conflicts of interest relevant to the content of this review.


  1. 1.
    Chodzko-Zajko WJ. The World Health Organization issues guidelines for promoting physical activity among older persons. J Aging Phys Act. 1997;5:1–8.CrossRefGoogle Scholar
  2. 2.
    WHO. Global recommendations on physical activity for health. World Health Organization, Geneva, Switzerland. 2010. Accessed 24 Oct 2017.
  3. 3.
    Hallal PC, Andersen LB, Bull FC, Guthold R, Haskell W, Ekelund U, et al. Global physical activity levels: surveillance progress, pitfalls, and prospects. Lancet. 2012;380:247–57.PubMedCrossRefGoogle Scholar
  4. 4.
    Kohl HW, Craig CL, Lambert EV, Inoue S, Alkandari JR, Leetongin G, et al. The pandemic of physical inactivity: global action for public health. Lancet. 2012;380:294–305.PubMedCrossRefGoogle Scholar
  5. 5.
    Boecker H, Sprenger T, Spilker ME, Henriksen G, Koppenhoefer M, Wagner KJ, et al. The runner’s high: opioidergic mechanisms in the human brain. Cereb Cortex. 2008;18:2523–31.PubMedCrossRefGoogle Scholar
  6. 6.
    Brené S, Bjørnebekk A, Åberg E, Mathé AA, Olson L, Werme M. Running is rewarding and antidepressive. Physiol Behav. 2007;92:136–40.PubMedPubMedCentralCrossRefGoogle Scholar
  7. 7.
    Dietrich A, McDaniel WF. Endocannabinoids and exercise. Br J Sports Med. 2004;38:536–41.PubMedPubMedCentralCrossRefGoogle Scholar
  8. 8.
    Koltyn KF, Brellenthin AG, Cook DB, Sehgal N, Hillard C. Mechanisms of exercise-induced hypoalgesia. J Pain. 2014;15:1294–304.PubMedPubMedCentralCrossRefGoogle Scholar
  9. 9.
    Olsen CM. Natural rewards, neuroplasticity, and non-drug addictions. Neuropharmacology. 2011;61:1109–22.PubMedPubMedCentralCrossRefGoogle Scholar
  10. 10.
    Yau SY, Li A, Hoo RL, Ching YP, Christie BR, Lee TM, et al. Physical exercise-induced hippocampal neurogenesis and antidepressant effects are mediated by the adipocyte hormone adiponectin. Proc Natl Acad Sci USA. 2014;111:15810–5.PubMedPubMedCentralCrossRefGoogle Scholar
  11. 11.
    Ekkekakis P, Parfitt G, Petruzzello SJ. The pleasure and displeasure people feel when they exercise at different intensities: decennial update and progress towards a tripartite rationale for exercise intensity prescription. Sports Med. 2011;41:641–71.PubMedCrossRefGoogle Scholar
  12. 12.
    Ekkekakis P. People have feelings! Exercise psychology in paradigmatic transition. Curr Opin Psychol. 2017;16:84–8.PubMedCrossRefGoogle Scholar
  13. 13.
    Brand R, Ekkekakis P. Affective-reflective theory of physical inactivity and exercise. Ger J Exerc Sport Res. 2018;48(1):48–58.CrossRefGoogle Scholar
  14. 14.
    Ding D, Lawson KD, Kolbe-Alexander TL, Finkelstein EA, Katzmarzyk PT, van Mechelen W, et al. The economic burden of physical inactivity: a global analysis of major non-communicable diseases. Lancet. 2016;388:1311–24.PubMedCrossRefGoogle Scholar
  15. 15.
    Lee IM, Shiroma EJ, Lobelo F, Puska P, Blair SN, Katzmarzyk PT, et al. Effect of physical inactivity on major non-communicable diseases worldwide: an analysis of burden of disease and life expectancy. Lancet. 2012;380:219–29.PubMedPubMedCentralCrossRefGoogle Scholar
  16. 16.
    Dickinson A. Actions and habits: the development of behavioural autonomy. Phil Trans of R Soc Lond B. 1985;308:67–78.CrossRefGoogle Scholar
  17. 17.
    Gawronski B, Creighton LA. Dual-process theories. The Oxford handbook of social cognition. New York: Oxford University Press; 2013.CrossRefGoogle Scholar
  18. 18.
    Shiffrin RM, Schneider W. Controlled and automatic human information processing: II. Perceptual learning, automatic attending and a general theory. Psychol Rev. 1977;84:127–90.CrossRefGoogle Scholar
  19. 19.
    Strack F, Deutsch R. Reflective and impulsive determinants of social behavior. Pers Soc Psychol Rev. 2004;8:220–47.PubMedCrossRefGoogle Scholar
  20. 20.
    Gawronski B, De Houwer J. Implicit measures in social and personality psychology. In: Reis HT, Judd CM, editors. Handbook of research methods in social and personality psychology. Cambridge: Cambridge University Press; 2014.Google Scholar
  21. 21.
    Moors A, De Houwer J. Automaticity: a theoretical and conceptual analysis. Psychol Bull. 2006;132:297–326.PubMedCrossRefGoogle Scholar
  22. 22.
    Marteau TM, Hollands GJ, Fletcher PC. Changing human behavior to prevent disease: the importance of targeting automatic processes. Science. 2012;337:1492–5.PubMedCrossRefGoogle Scholar
  23. 23.
    Hagger MS, Chatzisarantis NL. Integrating the theory of planned behaviour and self-determination theory in health behaviour: a meta-analysis. Br J Health Psychol. 2009;14:275–302.PubMedCrossRefGoogle Scholar
  24. 24.
    Cheval B, Sarrazin P, Isoard-Gautheur S, Radel R, Friese M. Reflective and impulsive processes explain (in)effectiveness of messages promoting physical activity: a randomized controlled trial. Health Psychol. 2015;34:10–9.PubMedCrossRefGoogle Scholar
  25. 25.
    Cheval B, Sarrazin P, Pelletier L. Impulsive approach tendencies towards physical activity and sedentary behaviors, but not reflective intentions, prospectively predict non-exercise activity thermogenesis. PLoS One. 2014;9:e115238.PubMedPubMedCentralCrossRefGoogle Scholar
  26. 26.
    Conroy DE, Hyde AL, Doerksen SE, Ribeiro NF. Implicit attitudes and explicit motivation prospectively predict physical activity. Ann Behav Med. 2010;39:112–8.PubMedCrossRefGoogle Scholar
  27. 27.
    Hagger MS. Non-conscious processes and dual-process theories in health psychology. Health Psychol Rev. 2016;10:375–80.PubMedCrossRefGoogle Scholar
  28. 28.
    Schultz W, Tremblay L, Hollerman JR. Reward processing in primate orbitofrontal cortex and basal ganglia. Cereb Cortex. 2000;10:272–83.PubMedCrossRefGoogle Scholar
  29. 29.
    Berridge KC, Robinson TE. Parsing reward. Trends Neurosci. 2003;26:507–13.PubMedCrossRefGoogle Scholar
  30. 30.
    Dickinson A, Balleine B. Motivational control of instrumental performance following a shift from thirst to hunger. Q J Exp Psychol. 1990;42:413–31.Google Scholar
  31. 31.
    Pool E, Sennwald V, Delplanque S, Brosch T, Sander D. Measuring wanting and liking from animals to humans: a systematic review. Neurosci Biobehav Rev. 2016;63:124–42.PubMedCrossRefGoogle Scholar
  32. 32.
    Corbit LH, Balleine BW. Double dissociation of basolateral and central amygdala lesions on the general and outcome-specific forms of pavlovian-instrumental transfer. J Neurosci. 2005;25:962–70.PubMedCrossRefGoogle Scholar
  33. 33.
    Wyvell CL, Berridge KC. Intra-accumbens amphetamine increases the conditioned incentive salience of sucrose reward: enhancement of reward “wanting” without enhanced “liking” or response reinforcement. J Neurosci. 2000;20:8122–30.PubMedCrossRefGoogle Scholar
  34. 34.
    Berridge KC. Food reward: brain substrates of wanting and liking. Neurosci Biobehav Rev. 1996;20:1–25.PubMedCrossRefGoogle Scholar
  35. 35.
    Blackburn JR, Pfaus JG, Phillips AG. Dopamine functions in appetitive and defensive behaviours. Prog Neurobiol. 1992;39:247–79.PubMedCrossRefGoogle Scholar
  36. 36.
    Born J, Lemmens S, Rutters F, Nieuwenhuizen A, Formisano E, Goebel R, et al. Acute stress and food-related reward activation in the brain during food choice during eating in the absence of hunger. Int J Obes. 2010;34:172–81.CrossRefGoogle Scholar
  37. 37.
    Knutson B, Adams CM, Fong GW, Hommer D. Anticipation of increasing monetary reward selectively recruits nucleus accumbens. J Neurosci. 2001;21:RC159.PubMedCrossRefGoogle Scholar
  38. 38.
    Murray EA. The amygdala, reward and emotion. Trends Cogn Sci. 2007;11:489–97.PubMedCrossRefGoogle Scholar
  39. 39.
    Roesch MR, Olson CR. Neuronal activity related to reward value and motivation in primate frontal cortex. Science. 2004;304:307–10.PubMedCrossRefGoogle Scholar
  40. 40.
    Corbit LH, Balleine BW. The general and outcome-specific forms of Pavlovian-instrumental transfer are differentially mediated by the nucleus accumbens core and shell. J Neurosci. 2011;31:11786–94.PubMedPubMedCentralCrossRefGoogle Scholar
  41. 41.
    Epstein LH, Leddy JJ, Temple JL, Faith MS. Food reinforcement and eating: a multilevel analysis. Psychol Bull. 2007;133:884–906.PubMedPubMedCentralCrossRefGoogle Scholar
  42. 42.
    Gottfried JA, O’Doherty J, Dolan RJ. Encoding predictive reward value in human amygdala and orbitofrontal cortex. Science. 2003;301:1104–7.PubMedCrossRefGoogle Scholar
  43. 43.
    Kelley A, Bakshi V, Haber S, Steininger T, Will M, Zhang M. Opioid modulation of taste hedonics within the ventral striatum. Physiol Behav. 2002;76:365–77.PubMedCrossRefGoogle Scholar
  44. 44.
    Kelley AE, Baldo BA, Pratt WE, Will MJ. Corticostriatal-hypothalamic circuitry and food motivation: integration of energy, action and reward. Physiol Behav. 2005;86:773–95.PubMedCrossRefGoogle Scholar
  45. 45.
    Prévost C, Liljeholm M, Tyszka JM, O’Doherty JP. Neural correlates of specific and general Pavlovian-to-instrumental transfer within human amygdalar subregions: a high-resolution fMRI study. J Neurosci. 2012;32:8383–90.PubMedCrossRefGoogle Scholar
  46. 46.
    Small DM, Jones-Gotman M, Dagher A. Feeding-induced dopamine release in dorsal striatum correlates with meal pleasantness ratings in healthy human volunteers. Neuroimage. 2003;19:1709–15.PubMedCrossRefGoogle Scholar
  47. 47.
    Söderpalm AH, Berridge KC. The hedonic impact and intake of food are increased by midazolam microinjection in the parabrachial nucleus. Brain Res. 2000;877:288–97.PubMedCrossRefGoogle Scholar
  48. 48.
    Pool E, Brosch T, Delplanque S, Sander D. Where is the chocolate? Rapid spatial orienting toward stimuli associated with primary rewards. Cognition. 2014;130:348–59.PubMedCrossRefGoogle Scholar
  49. 49.
    Kuss DJ, Griffiths MD. Internet and gaming addiction: a systematic literature review of neuroimaging studies. Brain Sci. 2012;2:347–74.PubMedPubMedCentralCrossRefGoogle Scholar
  50. 50.
    Pursey KM, Stanwell P, Callister RJ, Brain K, Collins CE, Burrows TL. Neural responses to visual food cues according to weight status: a systematic review of functional magnetic resonance imaging studies. Front Nutr. 2014;1:7.PubMedPubMedCentralCrossRefGoogle Scholar
  51. 51.
    Schacht JP, Anton RF, Myrick H. Functional neuroimaging studies of alcohol cue reactivity: a quantitative meta-analysis and systematic review. Addict Biol. 2013;18:121–33.PubMedCrossRefGoogle Scholar
  52. 52.
    Nijs IM, Franken IH, Muris P. Food-related Stroop interference in obese and normal-weight individuals: behavioral and electrophysiological indices. Eat Behav. 2010;11:258–65.PubMedCrossRefGoogle Scholar
  53. 53.
    Nijs IM, Muris P, Euser AS, Franken IH. Differences in attention to food and food intake between overweight/obese and normal-weight females under conditions of hunger and satiety. Appetite. 2010;54:243–54.PubMedCrossRefGoogle Scholar
  54. 54.
    Castellanos EH, Charboneau E, Dietrich MS, Park S, Bradley BP, Mogg K, et al. Obese adults have visual attention bias for food cue images: evidence for altered reward systemfunction. Int J Obes (Lond). 2009;33:1063–73.CrossRefGoogle Scholar
  55. 55.
    Graham R, Hoover A, Ceballos NA, Komogortsev O. Body mass index moderates gaze orienting biases and pupil diameter to high and low calorie foodimages. Appetite. 2011;56:577–86.PubMedCrossRefGoogle Scholar
  56. 56.
    Sambrook TD, Goslin J. A neural reward prediction error revealed by a meta-analysis of ERPs using great grand averages. Psychol Bull. 2015;141:213–35.PubMedCrossRefGoogle Scholar
  57. 57.
    Conroy DE, Berry TR. Automatic affective evaluations of physical activity. Exerc Sport Sci Rev. 2017;45:230–7.PubMedCrossRefGoogle Scholar
  58. 58.
    Berridge KC, Kringelbach ML. Neuroscience of affect: brain mechanisms of pleasure and displeasure. Curr Opin Neurobiol. 2013;23:294–303.PubMedPubMedCentralCrossRefGoogle Scholar
  59. 59.
    Srinivasan M, Ruina A. Computer optimization of a minimal biped model discovers walking and running. Nature. 2006;439:72–5.PubMedCrossRefGoogle Scholar
  60. 60.
    Rodman PS, McHenry HM. Bioenergetics and the origin of hominid bipedalism. Am J Phys Anthropol. 1980;52:103–6.PubMedCrossRefGoogle Scholar
  61. 61.
    Lee HH, Emerson JA, Williams DM. The exercise–affect–adherence pathway: an evolutionary perspective. Front Psychol. 2016;7:1285.PubMedPubMedCentralGoogle Scholar
  62. 62.
    Lieberman DE. Is exercise really medicine? An evolutionary perspective. Curr Sports Med Rep. 2015;14:313–9.PubMedCrossRefGoogle Scholar
  63. 63.
    Pellegrini AD, Smith PK. Physical activity play: the nature and function of a neglected aspect of play. Child Dev. 1998;69:577–98.PubMedCrossRefGoogle Scholar
  64. 64.
    Garland T, Schutz H, Chappell MA, Keeney BK, Meek TH, Copes LE, et al. The biological control of voluntary exercise, spontaneous physical activity and daily energy expenditure in relation to obesity: human and rodent perspectives. J Exp Biol. 2011;214:206–29.PubMedCrossRefGoogle Scholar
  65. 65.
    Chakravarthy MV, Booth FW. Eating, exercise, and “thrifty” genotypes: connecting the dots toward an evolutionary understanding of modern chronic diseases. J Appl Physiol. 2004;96:3–10.PubMedCrossRefGoogle Scholar
  66. 66.
    Chen YW, Wable GS, Chowdhury TG, Aoki C. Enlargement of axo-somatic contacts formed by GAD-immunoreactive axon terminals onto layer V pyramidal neurons in the medial prefrontal cortex of adolescent female mice is associated with suppression of food restriction-evoked hyperactivity and resilience to activity-based anorexia. Cereb Cortex. 2016;26:2574–89.PubMedCrossRefGoogle Scholar
  67. 67.
    Weed J, Lane M, Roth G, Speer D, Ingram D. Activity measures in rhesus monkeys on long-term calorie restriction. Physiol Behav. 1997;62:97–103.PubMedCrossRefGoogle Scholar
  68. 68.
    Gutierrez E. A rat in the labyrinth of anorexia nervosa: contributions of the activity-based anorexia rodent model to the understanding of anorexia nervosa. Int J Eat Disord. 2013;46:289–301.PubMedCrossRefGoogle Scholar
  69. 69.
    Alexander RM. Optima for animals. Princeton: Princeton University Press; 1996.Google Scholar
  70. 70.
    Selinger JC, O’Connor SM, Wong JD, Donelan JM. Humans can continuously optimize energetic cost during walking. Curr Biol. 2015;25:2452–6.PubMedCrossRefGoogle Scholar
  71. 71.
    Skvortsova V, Palminteri S, Pessiglione M. Learning to minimize efforts versus maximizing rewards: computational principles and neural correlates. J Neurosci. 2014;34:15621–30.PubMedCrossRefGoogle Scholar
  72. 72.
    Williams DM, Dunsiger S, Ciccolo JT, Lewis BA, Albrecht AE, Marcus BH. Acute affective response to a moderate-intensity exercise stimulus predicts physical activity participation 6 and 12 months later. Psychol Sport Exerc. 2008;9:231–45.PubMedPubMedCentralCrossRefGoogle Scholar
  73. 73.
    Cheval B, Sarrazin P, Boisgontier MP, Radel R. Temptations toward behaviors minimizing energetic costs (BMEC) automatically activate physical activity goals in successful exercisers. Psychol Sport Exerc. 2017;30:110–7.CrossRefGoogle Scholar
  74. 74.
    Robinson MJ, Berridge KC. Instant transformation of learned repulsion into motivational “wanting”. Curr Biol. 2013;23:282–9.PubMedPubMedCentralCrossRefGoogle Scholar
  75. 75.
    Aarts H, Dijksterhuis A, Vries P. On the psychology of drinking: being thirsty and perceptually ready. Br J Psychol. 2001;92:631–42.PubMedCrossRefGoogle Scholar
  76. 76.
    Seibt B, Häfner M, Deutsch R. Prepared to eat: how immediate affective and motivational responses to food cues are influenced by food deprivation. Eur J Soc Psychol. 2007;37:359–79.CrossRefGoogle Scholar
  77. 77.
    Moher D, Shamseer L, Clarke M, Ghersi D, Liberati A, Petticrew M, et al. Preferred reporting items for systematic review and meta-analysis protocols (PRISMA-P) 2015 statement. Syst Rev. 2015;4:1.PubMedPubMedCentralCrossRefGoogle Scholar
  78. 78.
    Keatley DA, Chan DK, Caudwell K, Chatzisarantis NL, Hagger MS. A consideration of what is meant by automaticity and better ways to measure it. Front Psychol. 2014;5:1537.PubMedCrossRefGoogle Scholar
  79. 79.
    Gardner B, de Bruijn GJ, Lally P. A systematic review and meta-analysis of applications of the self-report habit index to nutrition and physical activity behaviours. Ann Behav Med. 2011;42:174–87.PubMedCrossRefGoogle Scholar
  80. 80.
    Lenhard W, Lenhard A. Calculation of effect sizes. Bibergau: Psychometrica. 2016. Accessed 16 Mar 2018.
  81. 81.
    Greenwald AG, McGhee DE, Schwartz JL. Measuring individual differences in implicit cognition: the implicit association test. J Pers Soc Psychol. 1998;74:1464–80.PubMedCrossRefGoogle Scholar
  82. 82.
    Fazio RH, Sanbonmatsu DM, Powell MC, Kardes FR. On the automatic activation of attitudes. J Pers Soc Psychol. 1986;50:229–38.PubMedCrossRefGoogle Scholar
  83. 83.
    De Houwer J. The extrinsic affective Simon task. Exp Psychol. 2003;50:77–85.PubMedCrossRefGoogle Scholar
  84. 84.
    Payne BK, Cheng CM, Govorun O, Stewart BD. An inkblot for attitudes: affect misattribution as implicit measurement. J Pers Soc Psychol. 2005;89:277–93.PubMedCrossRefGoogle Scholar
  85. 85.
    MacLeod C, Mathews A, Tata P. Attentional bias in emotional disorders. J Abnorm Psychol. 1986;95:15–20.PubMedCrossRefGoogle Scholar
  86. 86.
    Cox WM, Fadardi JS, Pothos EM. The addiction-Stroop test: theoretical considerations and procedural recommendations. Psychol Bull. 2006;132:443–76.PubMedCrossRefGoogle Scholar
  87. 87.
    Krieglmeyer R, Deutsch R. Comparing measures of approach-avoidance behaviour: the manikin task vs. two versions of the joystick task. Cogn Emot. 2012;24:810–28.CrossRefGoogle Scholar
  88. 88.
    Mogg K, Bradley BP, Field M, De Houwer J. Eye movements to smoking-related pictures in smokers: relationship between attentional biases and implicit and explicit measures of stimulus valence. Addiction. 2003;98:825–36.PubMedCrossRefGoogle Scholar
  89. 89.
    Batterink L, Yokum S, Stice E. Body mass correlates inversely with inhibitory control in response to food among adolescent girls: an fMRI study. Neuroimage. 2010;52:1696–703.PubMedPubMedCentralCrossRefGoogle Scholar
  90. 90.
    Schulz KP, Fan J, Magidina O, Marks DJ, Hahn B, Halperin JM. Does the emotional go/no-go task really measure behavioral inhibition? Convergence with measures on a non-emotional analog. Arch Clin Neuropsychol. 2007;22:151–60.PubMedPubMedCentralCrossRefGoogle Scholar
  91. 91.
    Antoniewicz F, Brand R. Automatic evaluations and exercise setting preference in frequent exercisers. J Sport Exerc Psychol. 2014;36:631–6.PubMedCrossRefGoogle Scholar
  92. 92.
    Berry TR, Spence JC, Clark ME. Exercise is in! Implicit exercise and sedentary-lifestyle bias held by in-groups. J Appl Soc Psychol. 2011;41:2985–98.CrossRefGoogle Scholar
  93. 93.
    Bluemke M, Brand R, Schweizer G, Kahlert D. Exercise might be good for me, but I don’t feel good about it: do automatic associations predict exercise behavior? J Sport Exerc Psychol. 2010;32:137–53.PubMedCrossRefGoogle Scholar
  94. 94.
    Brand R, Antoniewicz F. Affective evaluations of exercising: the role of automatic-reflective evaluation discrepancy. J Sport Exerc Psychol. 2016;38:631–8.PubMedCrossRefGoogle Scholar
  95. 95.
    Brand R, Schweizer G. Going to the gym or to the movies?: situated decisions as a functional link connecting automatic and reflective evaluations of exercise with exercising behavior. J Sport Exerc Psychol. 2015;37:63–73.PubMedCrossRefGoogle Scholar
  96. 96.
    Chevance G, Caudroit J, Romain AJ, Boiché J. The adoption of physical activity and eating behaviors among persons with obesity and in the general population: the role of implicit attitudes within the theory of planned behavior. Psychol Health Med. 2017;22:319–24.PubMedCrossRefGoogle Scholar
  97. 97.
    Craeynest M, Crombez G, De Houwer J, Deforche B, Tanghe A, De Bourdeaudhuij I. Explicit and implicit attitudes towards food and physical activity in childhood obesity. Behav Res Ther. 2005;43:1111–20.PubMedCrossRefGoogle Scholar
  98. 98.
    Eves FF, Scott EJ, Hoppé R, French DP. Using the affective priming paradigm to explore the attitudes underlying walking behaviour. Br J Health Psychol. 2007;12:571–85.PubMedCrossRefGoogle Scholar
  99. 99.
    Antoniewicz F, Brand R. Dropping out or keeping up? Early-dropouts, late-dropouts, and maintainers differ in their automatic evaluations of exercise already before a 14-week exercise course. Front Psychol. 2016;7:838.PubMedPubMedCentralCrossRefGoogle Scholar
  100. 100.
    Chevance G, Héraud N, Varray A, Boiché J. Change in explicit and implicit motivation toward physical activity and sedentary behavior in pulmonary rehabilitation and associations with postrehabilitation behaviors. Rehab Psychol. 2017;62:119–29.CrossRefGoogle Scholar
  101. 101.
    Rebar AL, Ram N, Conroy DE. Using the EZ-diffusion model to score a single-category implicit association test of physical activity. Psychol Sport Exerc. 2015;16:96–105.PubMedCrossRefGoogle Scholar
  102. 102.
    Endrighi R, Basen-Engquist K, Szeto E, Perkins H, Baum G, Cox-Martin M, et al. Self-reported and automatic cognitions are associated with exercise behavior in cancer survivors. Health Psychol. 2016;35:824–8.PubMedPubMedCentralCrossRefGoogle Scholar
  103. 103.
    Karpinski A, Steinman RB. The single category implicit association test as a measure of implicit social cognition. J Pers Soc Psychol. 2006;91:16–32.PubMedCrossRefGoogle Scholar
  104. 104.
    Antoniewicz F, Brand R. Learning to like exercising: evaluative conditioning changes automatic evaluations of exercising and influences subsequent exercising behavior. J Sport Exerc Psychol. 2016;38:138–48.PubMedCrossRefGoogle Scholar
  105. 105.
    Hyde AL, Elavsky S, Doerksen SE, Conroy DE. The stability of automatic evaluations of physical activity and their relations with physical activity. J Sport Exerc Psychol. 2012;34:715–36.PubMedCrossRefGoogle Scholar
  106. 106.
    Markland D, Hall CR, Duncan LR, Simatovic J. The effects of an imagery intervention on implicit and explicit exercise attitudes. Psychol Sport Exerc. 2015;17:24–31.CrossRefGoogle Scholar
  107. 107.
    Berry TR. Who’s even interested in the exercise message? Attentional bias for exercise and sedentary-lifestyle related words. J Sport Exerc Psychol. 2006;28:4–17.CrossRefGoogle Scholar
  108. 108.
    Berry TR, Spence JC, Stolp SM. Attentional bias for exercise-related images. Res Q Exerc Sport. 2011;82:302–9.PubMedCrossRefGoogle Scholar
  109. 109.
    Calitri R, Lowe R, Eves FF, Bennett P. Associations between visual attention, implicit and explicit attitude and behaviour for physical activity. Psychol Health. 2009;24:1105–23.PubMedCrossRefGoogle Scholar
  110. 110.
    Giel KE, Kullmann S, Preißl H, Bischoff SC, Thiel A, Schmidt U, et al. Understanding the reward system functioning in anorexia nervosa: crucial role of physical activity. Biol Psychol. 2013;94:575–81.PubMedCrossRefGoogle Scholar
  111. 111.
    Cheval B, Sarrazin P, Pelletier L, Friese M. Effect of retraining approach-avoidance tendencies on an exercise task: a randomized controlled trial. J Phys Act Health. 2016;13:1396–403.PubMedCrossRefGoogle Scholar
  112. 112.
    Crémers J, Dessoullières A, Garraux G. Hemispheric specialization during mental imagery of brisk walking. Hum Brain Mapp. 2012;33:873–82.PubMedCrossRefGoogle Scholar
  113. 113.
    Jackson T, Gao X, Chen H. Differences in neural activation to depictions of physical exercise and sedentary activity: an fMRI study of overweight and lean Chinese women. Int J Obes. 2014;38:1180–5.CrossRefGoogle Scholar
  114. 114.
    Kullmann S, Giel KE, Hu X, Bischoff SC, Teufel M, Thiel A, et al. Impaired inhibitory control in anorexia nervosa elicited by physical activity stimuli. Soc Cogn Affect Neurosci. 2013;9:917–23.PubMedPubMedCentralCrossRefGoogle Scholar
  115. 115.
    Rebar AL, Dimmock JA, Jackson B, Rhodes RE, Kates A, Starling J, et al. A systematic review of the effects of non-conscious regulatory processes in physical activity. Health Psychol Rev. 2016;10:395–407.PubMedCrossRefGoogle Scholar
  116. 116.
    Schinkoeth M, Antoniewicz FF. Automatic evaluations and exercising: systematic review and implications for future research. Front Psychol. 2017;8:2103.PubMedPubMedCentralCrossRefGoogle Scholar
  117. 117.
    Zhang J, Berridge KC, Tindell AJ, Smith KS, Aldridge JW. A neural computational model of incentive salience. PLoS Comput Biol. 2009;5:e1000437.PubMedPubMedCentralCrossRefGoogle Scholar
  118. 118.
    Radel R, Clément-Guillotin C. Evidence of motivational influences in early visual perception: hunger modulates conscious access. Psychol Sci. 2012;23:232–4.PubMedCrossRefGoogle Scholar
  119. 119.
    Zenko Z, Ekkekakis P, Kavetsos G. Changing minds: bounded rationality and heuristic processes in exercise-related judgments and choices. Sport Exerc Perform Psychol. 2016;5:337–51.CrossRefGoogle Scholar

Copyright information

© Springer International Publishing AG, part of Springer Nature 2018

Authors and Affiliations

  1. 1.Swiss NCCR “LIVES, Overcoming Vulnerability: Life Course Perspectives”University of GenevaGenevaSwitzerland
  2. 2.Department of General Internal Medicine, Rehabilitation and GeriatricsUniversity of GenevaGenevaSwitzerland
  3. 3.Laboratoire Motricité Humaine Expertise Sport Santé (LAMHESS)Université Côte d’AzurNiceFrance
  4. 4.Brain Behavior LaboratoryUniversity of British ColumbiaVancouverCanada
  5. 5.Movement Control and Neuroplasticity Research Group, Department of Movement SciencesKU LeuvenLeuvenBelgium
  6. 6.Leuven Research Institute for Neuroscience and Disease (LIND)KU LeuvenLeuvenBelgium
  7. 7.Swiss Center for Affective SciencesUniversity of GenevaGenevaSwitzerland
  8. 8.Laboratory for the Study of Emotion Elicitation and Expression, Department of PsychologyUniversity of GenevaGenevaSwitzerland

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