Skip to main content

Advertisement

Log in

Goal pursuit and energy conservation: energy investment increases with task demand but does not equal it

  • Original Paper
  • Published:
Motivation and Emotion Aims and scope Submit manuscript

Abstract

According to motivational intensity theory, energy investment in goal pursuit is determined by the motivation to avoid wasting energy. Two experiments tested this hypothesis by manipulating the difficulty of an isometric hand grip task across four levels in a between-persons (Study 1) and a within-persons (Study 2) design. Supporting motivational intensity theory’s prediction, the results showed that invested energy—indicated by exerted grip force—was a function of task difficulty: The higher the difficulty, the higher the energy investment. However, the data also indicated that participants invested considerably more energy than required, questioning the primacy of energy conservation.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Fig. 1
Fig. 2

Similar content being viewed by others

Notes

  1. These predictions only hold if task difficulty is fixed and known. A comprehensive discussion of all predictions of motivational intensity theory can be found in Richter (2013).

  2. Participants' maximum force was assessed to assure that the requested force standards did not exceed participants' maximum force (i.e., to assure that task success was possible). It was also assessed to control for individual differences in maximum force in the statistical analysis of exerted force.

  3. Bayesian t tests were conducted using a unit-information prior with known variance, the same prior that underlies the BIC calculation.

  4. Classical null hypothesis significance testing resulted in F(1, 68) = 25.16, p < .001, MSE = 1,126.29 for the linear effect of task difficulty on peak force and F(1, 68) = 10.56, p = .002, MSE = 642,391.26 for the linear effect of task difficulty on FTI.

  5. For both experiments, all analyses were also conducted controlling for participants' maximum force. Given that this did virtually not change the results, only the uncorrected analyses are reported.

  6. The mean of the individual coefficients of variation was 25.41. The ICC [1, 1] was .64.

  7. Classical null hypothesis significance testing resulted in F(1, 48) = 50.03, p < .001, MSE = 388.92 for the linear effect of task difficulty on peak force and F(1, 48) = 78.99, p < .001, MSE = 96,549.39 for the linear effect of task difficulty on FTI.

References

  • Backs, R. W., & Seljos, K. A. (1994). Metabolic and cardiorespiratory measures of mental effort: The effects of level of difficulty in a working memory task. International Journal of Psychophysiology, 16, 57–68.

    Article  PubMed  Google Scholar 

  • Boska, M. (1994). ATP production rates as a function of force level in the human gastrocnemius/soleus using 31P MRS. Magnetic Resonance in Medicine, 32, 1–10. doi:10.1002/mrm.1910320102.

    Article  PubMed  Google Scholar 

  • Brehm, J. W., & Self, E. A. (1989). The intensity of motivation. Annual Review of Psychology, 40, 109–131. doi:10.1146/annurev.ps.40.020189.000545.

    Article  PubMed  Google Scholar 

  • Brener, J. (1987). Behavioural energetics: Some effects of uncertainty on the mobilization and distribution of energy. Psychophysiology, 24, 499–512.

    Article  PubMed  Google Scholar 

  • Brener, J., & Mitchell, S. (1989). Changes in energy expenditure and work during response acquisition in rats. Journal of Experimental Psychology: Animal Behavior Process, 15, 166–175.

    Google Scholar 

  • Carroll, D., Turner, J. R., & Prasad, R. (1986). The effects of level of difficulty of mental arithmetic challenge on heart rate and oxygen consumption. International Journal of Psychophysiology, 4, 167–173.

    Article  PubMed  Google Scholar 

  • Dixon, P. (2003). The p-value fallacy and how to avoid it. Canadian Journal of Experimental Psychology, 57, 189–202.

    Article  PubMed  Google Scholar 

  • Eubanks, L., Wright, R. A., & Williams, B. J. (2002). Reward influences on the heart: Cardiovascular response as a function of incentive value at five levels of task demand. Motivation and Emotion, 26, 139–152. doi:10.1023/A:1019863318803.

    Article  Google Scholar 

  • Fagraeus, L., & Linnarsson, D. (1976). Autonomic origin of heart rate fluctuations at the onset of muscular exercise. Journal of Applied Physiology, 40, 679–682.

    PubMed  Google Scholar 

  • Fairclough, S. H., & Houston, K. (2004). A metabolic measure of mental effort. Biological Psychology, 66, 177–190. doi:10.1016/j.biopsycho.2003.10.001.

    Article  PubMed  Google Scholar 

  • Filion, R. D. L., Fowler, S. C., & Notterman, J. N. (1970). Effort expenditure during proportionally reinforced responding. Quarterly Journal of Experimental Psychology, 22, 398–405. doi:10.1080/14640747008401913.

    Article  Google Scholar 

  • Gendolla, G. H. E., Richter, M., & Silvia, P. J. (2008). Self-focus and task difficulty effects on effort-related cardiovascular reactivity. Psychophysiology, 45, 653–662. doi:10.1111/j.1469-8986.2008.00655.x.

    Article  PubMed  Google Scholar 

  • Gendolla, G. H. E., Wright, R. A., & Richter, M. (2012). Effort intensity: Some insights from the cardiovascular system. In R. M. Ryan (Ed.), The oxford handbook on motivation (pp. 420–438). New York, NY: Oxford University Press.

    Google Scholar 

  • Jeneson, J. A. L., Westerhoff, H. V., Brown, T. R., Van Echteld, C. J. A., & Berger, R. (1995). Quasi-linear relationship between Gibbs free energy of ATP hydrolysis and power output in human forearm muscle. American Journal of Physiology. Cell Physiology, 37, C1474–C1484.

    Google Scholar 

  • Johansson, T. (2011). Hail the impossible: p-Values, evidence, and likelihhod. Scandinavian Journal of Psychology, 52, 113–125. doi:10.1111/j.1467-9450.2010.00852.x.

    Article  PubMed  Google Scholar 

  • Lay, B. S., Sparrow, W. A., Hughes, K. M., & O’Dwyer, N. J. (2002). Practice effects on coordination and control, metabolic energy expenditure, and muscle activation. Human Movement Science, 21, 807–830. doi:10.1016/S0167-9457(02)00166-5.

    Article  PubMed  Google Scholar 

  • Masson, M. E. J. (2011). A tutorial on a practical Bayesian alternative to null-hypothesis. Behavior Research Methods, 43, 679–690. doi:10.3758/s13428-010-0049-5.

    Article  PubMed  Google Scholar 

  • Maughan, R. J., & Gleeson, M. (2010). The biochemical basis of sports performance. Oxford: Oxford University Press.

    Google Scholar 

  • McClelland, D. C., Atkinson, J. W., Clark, R. A., & Lowell, E. L. (1953). The achievement motive. East Norwalk, CT: Appleton-Century-Crofts.

    Book  Google Scholar 

  • Obrist, P. A. (1981). Cardiovascular psychophysiology: A perspective. New York, NY: Plenum.

    Book  Google Scholar 

  • Potma, E. J., Stienen, G. J. M., Barends, J. P. F., & Elzinga, G. (1994). Myofibrillar ATPase activity and mechanical performance of skinned fibres from rabbit psoas muscle. Journal of Physiology, 474, 303–317.

    Article  PubMed Central  PubMed  Google Scholar 

  • Prompers, J. J., Jeneson, J. A. L., Drost, M. R., Oomens, C. C. W., Strijkers, G. J., & Nicolay, K. (2006). Dynamic MRS and MRI of skeletal muscle function and biomechanics. NMR in Biomedicine, 19, 927–953. doi:10.1002/nbm.

    Article  PubMed  Google Scholar 

  • Proske, U., & Gandevia, S. C. (2012). The proprioceptive senses: Their roles in signaling body shape, body position and movement, and muscle force. Physiological Reviews, 92, 1651–1697. doi:10.1152/physrev.00048.2011.

    Article  PubMed  Google Scholar 

  • Raftery, A. E. (1995). Bayesian model selection in social research. Sociological Methodology, 25, 111–163. doi:10.2307/271063.

    Article  Google Scholar 

  • Richter, M. (2013). A closer look into the multi-layer structure of motivational intensity theory. Social and Personality Psychology Compass, 7, 1–12. doi:10.1111/spc3.12007.

    Article  Google Scholar 

  • Richter, M., Friedrich, A., & Gendolla, G. H. E. (2008). Task difficulty effects on cardiac activity. Psychophysiology, 45, 869–875. doi:10.1111/j.1469-8986.2008.00688.x.

    Article  PubMed  Google Scholar 

  • Richter, M., & Gendolla, G. H. E. (2009). The heart contracts to reward: Monetary incentives and preejection period. Psychophysiology, 46, 451–457. doi:10.1111/j.1469-8986.2009.00795.x451-457.

    Article  PubMed  Google Scholar 

  • Rouder, J. N., Morey, R. D., Speckman, P. L., & Province, J. M. (2012). Default Bayes factors for ANOVA designs. Journal of Mathematical Psychology, 56, 356–374. doi:10.1016/j.jmp.2012.08.001.

    Article  Google Scholar 

  • Rouder, J. N., Speckman, P. L., Sun, D., Morey, R. D., & Iverson, G. (2009). Bayesian t tests for accepting and rejecting the null hypothesis. Psychonomic Bulletin & Review, 16, 225–237. doi:10.3758/PBR.16.2.225.

    Article  Google Scholar 

  • Russ, D. W., Elliott, M. A., Vandenborne, K., Walter, G. A., & Binder-Macleod, S. A. (2002). Metabolic costs of isometric force generation and maintenance of human skeletal muscle. American Journal of Physiology—Endocrinology and Metabolism, 282, E448–E457. doi:10.1152/ajpendo.00285.2001.

    PubMed  Google Scholar 

  • Scholey, A. B., Harper, S., & Kennedy, D. O. (2001). Cognitive demand and blood glucose. Physiology & Behavior, 73, 585–592.

    Article  Google Scholar 

  • Sherwood, A., Allen, M. T., Obrist, P. A., & Langer, A. W. (1986). Evaluation of beta-adrenergic influences on cardiovascular and metabolic adjustments to physical and psychological stress. Psychophysiology, 23, 89–104.

    Article  PubMed  Google Scholar 

  • Sherwood, A., Brener, J., & Moncur, D. (1983). Information and states of motor readiness: Their effects on the covariation of heart rate and energy expenditure. Psychophysiology, 20, 513–529.

    Article  PubMed  Google Scholar 

  • Sims, J., & Carroll, D. (1990). Cardiovascular and metabolic activity at rest and during psychological and physical challenge in normotensives and subjects with mildly elevated blood pressure. Psychophysiology, 27, 149–156.

    Article  PubMed  Google Scholar 

  • Sparrow, W. A., & Newell, K. M. (1994). Energy expenditure and motor performance relationships in humans learning a motor task. Psychophysiology, 31, 338–346. doi:10.1111/j.1469-8986.1994.tb02442.x.

    Article  PubMed  Google Scholar 

  • Stienen, G. J., Kiers, J. L., Bottinelli, R., & Reggiani, C. (1996). Myofibrillar ATPase activity in skinned human skeletal muscle fibres: Fibre type and temperature dependence. Journal of Physiology, 493, 299–307.

    Article  PubMed Central  PubMed  Google Scholar 

  • Szentesi, P., Zaremba, R., van Mechelen, W., & Stienen, G. J. M. (2001). ATP utilization for calcium uptake and force production in different types of human skeletal muscle fibres. Journal of Physiology, 531, 393–403.

    Article  PubMed Central  PubMed  Google Scholar 

  • Turner, J. R., & Carroll, D. (1985). Heart rate and oxygen consumption during mental arithmetic, a video game, and graded exercise: Further evidence of metabolically-exaggerated cardiac adjustments? Psychophysiology, 22, 261–267.

    Article  PubMed  Google Scholar 

  • Victor, R. G., Seals, D. R., Mark, A. L., & Kempf, J. (1987). Differential control of heart rate and sympathetic nerve activity during dynamic exercise. Insight from intraneural recordings in humans. The Journal of Clinical Investigation, 79, 508–516. doi:10.1172/JCI112841.

    Article  PubMed Central  PubMed  Google Scholar 

  • Wagenmakers, E.-J. (2007). A practical solution to the pervasive problems of p values. Psychonomic Bulletin & Review, 14, 779–804.

    Article  Google Scholar 

  • Wigfield, A., & Eccles, J. S. (2000). Expectancy-value theory of achievement motivation. Contemporary Educational Psychology, 25, 68–81. doi:10.1006/ceps.1999.1015.

    Article  PubMed  Google Scholar 

  • Wright, R. A. (1996). Brehm’s theory of motivation as a model of effort and cardiovascular response. In P. M. Gollwitzer & J. A. Bargh (Eds.), The psychology of action: Linking cognition and motivation to behavior (pp. 424–453). New York, NY: Guilford.

    Google Scholar 

  • Wright, R. A. (2008). Refining the prediction of effort: Brehm’s distinction between potential motivation and motivation intensity. Social and Personality Psychology Compass, 2, 682–701. doi:10.1111/j.1751-9004.2008.00093.x.

    Article  Google Scholar 

Download references

Acknowledgments

This research was supported by a research Grant (10014_134586) from the Swiss National Science Foundation. I am grateful to Kerstin Brinkmann and Guido H. E. Gendolla for comments on an early version of this article.

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Michael Richter.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Richter, M. Goal pursuit and energy conservation: energy investment increases with task demand but does not equal it. Motiv Emot 39, 25–33 (2015). https://doi.org/10.1007/s11031-014-9429-y

Download citation

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11031-014-9429-y

Keywords

Navigation