Physiological correlates of mathematical anxiety in resting state and during anticipation of math
Keywords:
mathematical anxiety, physiological indicators, electrodermal activity, heart rate, heart rate variability
Abstract
Introduction. Math anxiety (MA) is a feeling of discomfort or fear during performing any kind of math related tasks. It is shown that MA affects performance in mathematics. People with high math anxiety have a moderate response in brain activity, not even to the task itself, but to the anticipation of math. Electrodermal activity and heart rate and heart rate variability are known to be sensitive indicators of stress. Aim. Our purpose was to investigate changes in physiological measures such as: electrodermal activity, heart rate and heart rate variability; during resting state and while anticipation of math in participants with different levels of math anxiety. Materials and methods. Our sample included 84 participants with high and low levels of math anxiety. Experimental procedure included recording of physiological measures during resting state, without specific instruction and during anticipation of math task, when they were informed that they will be performing calculation. Results. Study showed that heart rate was significantly higher during anticipation of math in all participants, with no regards to math anxiety level. However, a small effect was shown. Also it was found differences in amplitude of electrodermal activity in participants with different levels of math anxiety. Conclusion. Overall study suggests that heart rate is sensitive to such emotional state as anticipating math and electrodermal activity can be one of the indicators of math anxiety.
Downloads
Download data is not yet available.
References
1. Budakova A.V., Likhanov M.V., Bloniewski T. et al. Mathematical anxiety: etiology, development and relation with math performance. Voprosy Psikhologii = Questions of Psychology. 2020;66(1):109–119 (in Russ.).
2. Núñez-Peña M.I., Suárez-Pellicioni M., Bono R. Effects of Math Anxiety on Student Success in Higher Education. International Journal of Educational Research. 2013;58:36–43. DOI: https://doi.org/10.1016/J.IJER.2012.12.004
3. Sarkar A., Dowker A., Cohen Kadosh R. Cognitive enhancement or cognitive cost: trait-specific outcomes of brain stimulation in the case of mathematics anxiety. The Journal of neuroscience: the official journal of the Society for Neuroscience. 2014;34(50):16605–16610. DOI: https://doi.org/ 10.1523/JNEUROSCI.3129-14.2014
4. Malanchini M., Rimfeld K., Wang Z. et al. Genetic factors underlie the association between anxiety, attitudes and performance in mathematics. Translational Psychiatry. 2020;10(12). DOI: https://doi.org/10.1038/s41398-020-0711-3
5. Chang H., Beilock S.L. The math anxiety-math performance link and its relation to individual and environmental factors: A review of current behavioral and psychophysiological research. Current Opinion in Behavioral Sciences. 2016;10:33–38. DOI: https://doi.org/10.1016/j.cobeha.2016.04.011
6. Johnston-Wilder S., Brindley J., Dent P. A survey of mathematics anxiety and mathematical resilience among existing apprentices. London, Gatsby Charitable Foundation. 2014:48.
7. Dowker A., Sarkar A., Looi C.Y. Mathematics Anxiety: What Have We Learned in 60 Years? Frontiers in psychology. 2016;7(508). DOI: https://doi.org/10.3389/fpsyg.2016.00508
8. Organization for Economic Cooperation and Development. PISA 2012 results: Ready to learn: Students engagement, drive and self-beliefs (Vol. III). Paris, France. 2013. DOI: https://doi.org/ 10.1787/9789264201170-en
9. Pizzie R. G., Kraemer D. The Association between Emotion Regulation, Physiological Arousal, and Performance in Math Anxiety. Frontiers in psychology. 2021;12(639448). DOI: https://doi.org/10.3389/fpsyg.2021.639448
10. Matsepuro D.M., Esipenko Е.А., Terekhina О.V. Essential methods of math anxiety regulation. Nauchno-pedagogicheskoe obozrenie = Pedagogical Review. 2021;2(36):189–198. (in Russ.).
11. Cipora K., Santos F.H., Kucian K., Dowker A. Mathematics anxiety – where are we and where shall we go? PsyArXiv 2021. DOI: https://doi.org/10.31234/osf.io/2xpcg
12. Ganley C.M., Conlon R.A., McGraw A.L. et al. The Effect of Brief Anxiety Interventions on Reported Anxiety and Math Test Performance. Journal of Numerical Cognition. 2021;7:4–19. DOI: https://doi.org/10.5964/jnc.6065.
13. Mathematics anxiety: what is known and what is still to be understood / Ed. by Mammarella C.I., Caviola S., Dowker A. Publ. Routledge. London and New York. 238. DOI: https://doi.org/ 10.1080/00071005.2019.1622307
14. Lyons I.M., Beilock S.L. When Math Hurts: Math Anxiety Predicts Pain Network Activation in Anticipation of Doing Math. PLOS ONE. 2012;7(10):e48076. DOI: https://doi.org/10.1371/journal.pone.0048076
15. Boucsein W., Fowles D.C., Grimnes S. et. al. Publication recommendations for electrodermal measurements. Society for Psychophysiological Research Ad Hoc Committee on Electro-dermal Measures. Psychophysiology. 2012;49(8):1017–1034. DOI: https://doi.org/10.1111/j.1469-8986.2012.01384.x
16. Crider A. Personality and Electrodermal Response Lability: An Interpretation. Applied psychophysiology and biofeedback. 2008;33:141–148. DOI: https://doi.org/10.1007/s10484-008-9057-y.
17. Gertler J., Novotny S., Poppe A. et al. Neural correlates of non-specific skin conductance responses during resting state fMRI. NeuroImage. 2020;214:116721. DOI: https://doi.org/10.1016/ j.neuroimage.2020.116721
18. Sarchiapone M., Gramaglia C., Iosue M. et al. The association between electrodermal activity (EDA), depression and suicidal behaviour: A systematic review and narrative synthesis. BMC psychiatry. 2018;18(1):22. DOI: https://doi.org/10.1186/s12888-017-1551-4
19. Botvinick M.M., Rosen Z.B. Anticipation of cognitive demand during decision-making. Psychological Research. 2009;73(6):835–842. DOI: https://doi.org/10.1007/s00426-008-0197-8
20. Miu A., Heilman R., Houser D. Anxiety impairs decision-making: psychophysiological ev-idence from an Iowa gambling task. Biological psychology. 2008;77:353–358. DOI: https://doi.org/10.1016/j.biopsycho.2007.11.010.
21. Eidlin Levy H., Rubinsten O. Numbers (but not words) make math anxious individuals sweat: Physiological evidence. Biological psychology. 2021;165:108187. DOI: https://doi.org/10.1016/ j.biopsycho.2021.108187
22. Trotman G., Veldhuijzen van Zanten J., Davies J. et al. Associations between heart rate, perceived heart rate, and anxiety during acute psychological stress. Anxiety, Stress and Coping. 2019;32:1–17. DOI: https://doi.org/10.1080/10615806.2019.1648794.
23. Pham T., Lau Z. J., Chen S., Makowski D. Heart Rate Variability in Psychology: A Review of HRV Indices and an Analysis Tutorial. Sensors (Basel, Switzerland). 2021;21(12):3998. DOI: https://doi.org/10.3390/s21123998
24. Castaldo R., Montesinos L., Melillo P. et al. Ultra-short term HRV features as surrogates of short term HRV: A case study on mental stress detection in real life. BMC Medical Informatics and Decision Making. 2019;19. DOI: https://doi.org/10.1186/s12911-019-0742-y.
25. Shaffer F., Ginsberg J.P. An Overview of Heart Rate Variability Metrics and Norms. Frontiers in public health. 2017;5(258). DOI: https://doi.org/10.3389/fpubh.2017.00258
26. Francesco B., Maria Grazia B., Emanuele G. et al. Linear and nonlinear heart rate variabil-ity indexes in clinical practice. Computational and mathematical methods in medicine. 2012;219080. DOI: https://doi.org/10.1155/2012/219080
27. Strohmaier A.R., Schiepe-Tiska A., Reiss K.M. A Comparison of Self-Reports and Electrodermal Activity as Indicators of Mathematics State Anxiety. An Application of the Control-Value Theory. Frontline Learning Research. 2020;8(1):16–32. DOI: https://doi.org/10.14786/flr.v8i1.427
28. Qu Z., Chen J., Li B. et al. Measurement of High-School Students Trait Math Anxiety Using Neurophysiological Recordings During Math Exam. IEEE Access. 2020;8:57460-57471. DOI: https://doi.org/10.1109/ACCESS.2020.2982198.
29. Tang J., Su Y., Yao Y. et al. Respiratory Sinus Arrhythmia Mediates the Relation Between “Specific Math Anxiety” and Arithmetic Speed. Frontiers in psychology. 2021;12:615601. DOI: https://doi.org/10.3389/fpsyg.2021.615601
30. Hopko D.R., Mahadevan R., Bare R.L., Hunt M.K. The Abbreviated Math Anxiety Scale (AMAS): Construction, Validity, and Reliability. Assessment. 2003;10(2):178–182. DOI: https://doi.org/ 10.1177/1073191103010002008
31. Gramfort A., Luessi M., Larson E. et al. MEG and EEG data analysis with MNE-Python. Frontiers in Neuroscience. 2013;7(267). DOI: https://doi.org/10.3389/fnins.2013.00267
32. Makowski D., Pham T., Lau Z.J. et al. NeuroKit2: A Python toolbox for neurophysiological signal processing. Behavior research methods. 2021;53(4):1689–1696. DOI: https://doi.org/ 10.3758/s13428-020-01516-y
33. de Pedro-Carracedo J., Fuentes-Jimenez D., Ugena A.M., Gonzalez-Marcos A.P. Trans-cending Conventional Biometry Frontiers: Diffusive Dynamics PPG Biometry. Sensors. 2021;21(16):5661. DOI: https://doi.org/https://doi.org/10.3390/s21165661
2. Núñez-Peña M.I., Suárez-Pellicioni M., Bono R. Effects of Math Anxiety on Student Success in Higher Education. International Journal of Educational Research. 2013;58:36–43. DOI: https://doi.org/10.1016/J.IJER.2012.12.004
3. Sarkar A., Dowker A., Cohen Kadosh R. Cognitive enhancement or cognitive cost: trait-specific outcomes of brain stimulation in the case of mathematics anxiety. The Journal of neuroscience: the official journal of the Society for Neuroscience. 2014;34(50):16605–16610. DOI: https://doi.org/ 10.1523/JNEUROSCI.3129-14.2014
4. Malanchini M., Rimfeld K., Wang Z. et al. Genetic factors underlie the association between anxiety, attitudes and performance in mathematics. Translational Psychiatry. 2020;10(12). DOI: https://doi.org/10.1038/s41398-020-0711-3
5. Chang H., Beilock S.L. The math anxiety-math performance link and its relation to individual and environmental factors: A review of current behavioral and psychophysiological research. Current Opinion in Behavioral Sciences. 2016;10:33–38. DOI: https://doi.org/10.1016/j.cobeha.2016.04.011
6. Johnston-Wilder S., Brindley J., Dent P. A survey of mathematics anxiety and mathematical resilience among existing apprentices. London, Gatsby Charitable Foundation. 2014:48.
7. Dowker A., Sarkar A., Looi C.Y. Mathematics Anxiety: What Have We Learned in 60 Years? Frontiers in psychology. 2016;7(508). DOI: https://doi.org/10.3389/fpsyg.2016.00508
8. Organization for Economic Cooperation and Development. PISA 2012 results: Ready to learn: Students engagement, drive and self-beliefs (Vol. III). Paris, France. 2013. DOI: https://doi.org/ 10.1787/9789264201170-en
9. Pizzie R. G., Kraemer D. The Association between Emotion Regulation, Physiological Arousal, and Performance in Math Anxiety. Frontiers in psychology. 2021;12(639448). DOI: https://doi.org/10.3389/fpsyg.2021.639448
10. Matsepuro D.M., Esipenko Е.А., Terekhina О.V. Essential methods of math anxiety regulation. Nauchno-pedagogicheskoe obozrenie = Pedagogical Review. 2021;2(36):189–198. (in Russ.).
11. Cipora K., Santos F.H., Kucian K., Dowker A. Mathematics anxiety – where are we and where shall we go? PsyArXiv 2021. DOI: https://doi.org/10.31234/osf.io/2xpcg
12. Ganley C.M., Conlon R.A., McGraw A.L. et al. The Effect of Brief Anxiety Interventions on Reported Anxiety and Math Test Performance. Journal of Numerical Cognition. 2021;7:4–19. DOI: https://doi.org/10.5964/jnc.6065.
13. Mathematics anxiety: what is known and what is still to be understood / Ed. by Mammarella C.I., Caviola S., Dowker A. Publ. Routledge. London and New York. 238. DOI: https://doi.org/ 10.1080/00071005.2019.1622307
14. Lyons I.M., Beilock S.L. When Math Hurts: Math Anxiety Predicts Pain Network Activation in Anticipation of Doing Math. PLOS ONE. 2012;7(10):e48076. DOI: https://doi.org/10.1371/journal.pone.0048076
15. Boucsein W., Fowles D.C., Grimnes S. et. al. Publication recommendations for electrodermal measurements. Society for Psychophysiological Research Ad Hoc Committee on Electro-dermal Measures. Psychophysiology. 2012;49(8):1017–1034. DOI: https://doi.org/10.1111/j.1469-8986.2012.01384.x
16. Crider A. Personality and Electrodermal Response Lability: An Interpretation. Applied psychophysiology and biofeedback. 2008;33:141–148. DOI: https://doi.org/10.1007/s10484-008-9057-y.
17. Gertler J., Novotny S., Poppe A. et al. Neural correlates of non-specific skin conductance responses during resting state fMRI. NeuroImage. 2020;214:116721. DOI: https://doi.org/10.1016/ j.neuroimage.2020.116721
18. Sarchiapone M., Gramaglia C., Iosue M. et al. The association between electrodermal activity (EDA), depression and suicidal behaviour: A systematic review and narrative synthesis. BMC psychiatry. 2018;18(1):22. DOI: https://doi.org/10.1186/s12888-017-1551-4
19. Botvinick M.M., Rosen Z.B. Anticipation of cognitive demand during decision-making. Psychological Research. 2009;73(6):835–842. DOI: https://doi.org/10.1007/s00426-008-0197-8
20. Miu A., Heilman R., Houser D. Anxiety impairs decision-making: psychophysiological ev-idence from an Iowa gambling task. Biological psychology. 2008;77:353–358. DOI: https://doi.org/10.1016/j.biopsycho.2007.11.010.
21. Eidlin Levy H., Rubinsten O. Numbers (but not words) make math anxious individuals sweat: Physiological evidence. Biological psychology. 2021;165:108187. DOI: https://doi.org/10.1016/ j.biopsycho.2021.108187
22. Trotman G., Veldhuijzen van Zanten J., Davies J. et al. Associations between heart rate, perceived heart rate, and anxiety during acute psychological stress. Anxiety, Stress and Coping. 2019;32:1–17. DOI: https://doi.org/10.1080/10615806.2019.1648794.
23. Pham T., Lau Z. J., Chen S., Makowski D. Heart Rate Variability in Psychology: A Review of HRV Indices and an Analysis Tutorial. Sensors (Basel, Switzerland). 2021;21(12):3998. DOI: https://doi.org/10.3390/s21123998
24. Castaldo R., Montesinos L., Melillo P. et al. Ultra-short term HRV features as surrogates of short term HRV: A case study on mental stress detection in real life. BMC Medical Informatics and Decision Making. 2019;19. DOI: https://doi.org/10.1186/s12911-019-0742-y.
25. Shaffer F., Ginsberg J.P. An Overview of Heart Rate Variability Metrics and Norms. Frontiers in public health. 2017;5(258). DOI: https://doi.org/10.3389/fpubh.2017.00258
26. Francesco B., Maria Grazia B., Emanuele G. et al. Linear and nonlinear heart rate variabil-ity indexes in clinical practice. Computational and mathematical methods in medicine. 2012;219080. DOI: https://doi.org/10.1155/2012/219080
27. Strohmaier A.R., Schiepe-Tiska A., Reiss K.M. A Comparison of Self-Reports and Electrodermal Activity as Indicators of Mathematics State Anxiety. An Application of the Control-Value Theory. Frontline Learning Research. 2020;8(1):16–32. DOI: https://doi.org/10.14786/flr.v8i1.427
28. Qu Z., Chen J., Li B. et al. Measurement of High-School Students Trait Math Anxiety Using Neurophysiological Recordings During Math Exam. IEEE Access. 2020;8:57460-57471. DOI: https://doi.org/10.1109/ACCESS.2020.2982198.
29. Tang J., Su Y., Yao Y. et al. Respiratory Sinus Arrhythmia Mediates the Relation Between “Specific Math Anxiety” and Arithmetic Speed. Frontiers in psychology. 2021;12:615601. DOI: https://doi.org/10.3389/fpsyg.2021.615601
30. Hopko D.R., Mahadevan R., Bare R.L., Hunt M.K. The Abbreviated Math Anxiety Scale (AMAS): Construction, Validity, and Reliability. Assessment. 2003;10(2):178–182. DOI: https://doi.org/ 10.1177/1073191103010002008
31. Gramfort A., Luessi M., Larson E. et al. MEG and EEG data analysis with MNE-Python. Frontiers in Neuroscience. 2013;7(267). DOI: https://doi.org/10.3389/fnins.2013.00267
32. Makowski D., Pham T., Lau Z.J. et al. NeuroKit2: A Python toolbox for neurophysiological signal processing. Behavior research methods. 2021;53(4):1689–1696. DOI: https://doi.org/ 10.3758/s13428-020-01516-y
33. de Pedro-Carracedo J., Fuentes-Jimenez D., Ugena A.M., Gonzalez-Marcos A.P. Trans-cending Conventional Biometry Frontiers: Diffusive Dynamics PPG Biometry. Sensors. 2021;21(16):5661. DOI: https://doi.org/https://doi.org/10.3390/s21165661
References on translit
-
Published
2022-04-03
How to Cite
Esipenko, E., Matsepuro, D., Arkhipova, O., Shamakov, V., & Budakova, A. (2022). Physiological correlates of mathematical anxiety in resting state and during anticipation of math. Psychology. Psychophysiology, 15(1), 131-141. https://doi.org/10.14529/jpps220112
Issue
Section
Psychophysiology
Copyright (c) 2022 Psychology. Psychophysiology
This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.
