The effect of alpha neurofeedback training on cognitive performance in healthy adults
Open accessAbstract
This study investigates the effect of long-term alpha neurofeedback training (NFT) in healthy adults using music stimuli. The optimal protocol for future research is presented in this study. The data from 40 healthy participants, divided into two groups (NFT group and Control group), were analyzed in the current study. We found a significantly enhanced alpha rhythm after training in the NFT group which was not observed in the control group. The immediate subsequent effects were greater in more than 80% of the sessions from the initial recordings. Stroop task and behavioral questionnaires, mini-mental state exam (MMSE), and perceived stress scale (PSS) did not reveal any training-specific changes. Within-training session effects were significant from the baseline and were more pronounced at the beginning of the session as compared to the end of the session. It is also observed that a shorter session length with multiple sessions may be more effective than a long and continuous run of a single session.
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
Training the alpha band can improve cognitive abilities such as reaction time, cognitive control and selective attention in healthy patients.
“Moreover, cognitive abilities such as reaction time, cognitive control and selective attention could also be improved in healthy patients by training the alpha band.15”
From Evaluation of a manualised neurofeedback training in psychosomatic-psychotherapeutic outpatient treatment (Neuro-pp-out): study protocol for a clinical mixed-methods pilot study (2024) · cites this paper as [15]
The Introduction links alpha activity with attention and identifies the Stroop task as a measure of selective attention and cognitive control. But the Behavioral Results (§3.1) and Discussion (§4.3) report no significant training-related improvement in reaction time or Stroop performance, so this study does not establish the claimed cognitive benefits. (LLM, conf=0.85)
Experimental — accuracy not yet measured
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Cites
Folstein, M. F., Folstein, S. E., & McHugh, P. R. (1975) · Journal of Psychiatric Research · doi:10.1016/0022-3956(75)90026-6 · Cited by 88,282 · see citing works
Delorme, A., & Makeig, S. (2004) · Journal of Neuroscience Methods · doi:10.1016/j.jneumeth.2003.10.009 · Cited by 24,371 · see citing works
(1988) · Cited by 4,111 · see citing works
Lee, T.-W., Girolami, M., & Sejnowski, T. J. (1999) · Neural Computation · doi:10.1162/089976699300016719 · Cited by 1,967 · see citing works
Aftanas, L. I., & Golocheikine, S. A. (2001) · Neuroscience Letters · doi:10.1016/s0304-3940(01)02094-8 · Cited by 865 · see citing works
Renard, Y., Lotte, F., Gibert, G., Congedo, M., Maby, E., Delannoy, V., Bertrand, O., & Lécuyer, A. (2010) · Presence: Teleoperators and Virtual Environments · doi:10.1162/pres.19.1.35 · Cited by 830 · see citing works
Cooper, N. R., Croft, R. J., Dominey, S. J. J., Burgess, A., & Gruzelier, J. H. (2003) · International Journal of Psychophysiology · doi:10.1016/s0167-8760(02)00107-1 · Cited by 615 · see citing works
Gruzelier, J. H. (2013) · Neuroscience & Biobehavioral Reviews · doi:10.1016/j.neubiorev.2013.09.015 · Cited by 596 · see citing works
Chang, C.-Y., Hsu, S.-H., Pion-Tonachini, L., & Jung, T. (2019) · IEEE Transactions on Biomedical Engineering · doi:10.1109/tbme.2019.2930186 · Cited by 545 · see citing works
EEG-Neurofeedback as a Tool to Modulate Cognition and Behavior: A Review Tutorial
Enriquez‐Geppert, S., Huster, R. J., & Herrmann, C. S. (2017) · Frontiers in Human Neuroscience · doi:10.3389/fnhum.2017.00051 · Cited by 526 · see citing works
Neurofeedback training of the upper alpha frequency band in EEG improves cognitive performance
Zoefel, B., Huster, R. J., & Herrmann, C. S. (2010) · NeuroImage · doi:10.1016/j.neuroimage.2010.08.078 · Cited by 498 · see citing works
The effect of training distinct neurofeedback protocols on aspects of cognitive performance
Vernon, D. J., Egner, T., Cooper, N., Compton, T., Neilands, C., Sheri, A., & Gruzelier, J. H. (2003) · International Journal of Psychophysiology · doi:10.1016/s0167-8760(02)00091-0 · Cited by 474 · see citing works
Is neurofeedback an efficacious treatment for ADHD? A randomised controlled clinical trial.
Gevensleben, H., Holl, B., Albrecht, B., Vogel, C., Schlamp, D., Kratz, O., Studer, P., Rothenberger, A., Moll, G., & Heinrich, H. (2009) · Journal of Child Psychology and Psychiatry and Allied Disciplines · doi:10.1111/j.1469-7610.2008.02033.x · Cited by 442 · see citing works
Pangman, V. C., Sloan, J., & Guse, L. (2000) · Applied Nursing Research · doi:10.1053/apnr.2000.9231 · Cited by 440 · see citing works
Gruzelier, J. H. (2014) · Neuroscience & Biobehavioral Reviews · doi:10.1016/j.neubiorev.2014.03.015 · Cited by 270 · see citing works
Nacke, L. E., Kalyn, M. R., Lough, C., & Mandryk, R. L. (2011) · CHI Conference on Human Factors in Computing Systems · doi:10.1145/1978942.1978958 · Cited by 256 · see citing works
Learning to modulate one’s own brain activity: The effect of spontaneous mental strategies
Kober, S. E., Witte, M., Ninaus, M., Neuper, C., & Wood, G. (2013) · Frontiers in Human Neuroscience · doi:10.3389/fnhum.2013.00695 · Cited by 225 · see citing works
Individual alpha neurofeedback training effect on short term memory
Nan, W., Rodrigues, J., Ma, J., Qu, X., Wan, F., Mak, P., Mak, P. U., Vai, M. I., & Rosa, A. C. (2012) · International Journal of Psychophysiology · doi:10.1016/j.ijpsycho.2012.07.182 · Cited by 210 · see citing works
Upper alpha ERD and absolute power: their meaning for memory performance.
Klimesch, W., Doppelmayr, M., & Hanslmayr, S. (2006) · Progress in Brain Research · doi:10.1016/s0079-6123(06)59010-7 · Cited by 196 · see citing works
EEG alpha power and intelligence
Doppelmayr, M. M., Klimesch, W., Stadler, W., Pöllhuber, D., & Heine, C. (2002) · Intelligence · doi:10.1016/s0160-2896(01)00101-5 · Cited by 195 · see citing works
Khan, S., Nobili, L., Khatami, R., Loddenkemper, T., Cajochen, C., Dijk, D., & Eriksson, S. H. (2018) · The Lancet Neurology · doi:10.1016/s1474-4422(18)30335-1 · Cited by 168 · see citing works
Franco‐Marina, F., González, J. J. G., Wagner-Echeagaray, F., Gallo, J. J., Ugalde, Ó., Sánchez‐García, S., Espinel-Bermúdez, C., Juárez‐Cedillo, T., Rodríguez, M., & García‐Peña, C. (2009) · International Psychogeriatrics · doi:10.1017/s1041610209990822 · Cited by 167 · see citing works
Frontal alpha asymmetry neurofeedback for the reduction of negative affect and anxiety
Mennella, R., Patron, E., & Palomba, D. (2017) · Behaviour Research and Therapy · doi:10.1016/j.brat.2017.02.002 · Cited by 165 · see citing works
Using Unity 3D to facilitate mobile augmented reality game development
Kim, S. L., Suk, H., Kang, J. H., Jung, J. M., Laine, T. H., & Westlin, J. (2014) · IEEE World Forum on Internet of Things (WF-IoT) · doi:10.1109/wf-iot.2014.6803110 · Cited by 149 · see citing works
Musical neurofeedback for treating depression in elderly people
Ramírez, R., Palencia-Lefler, M., Giraldo, S., & Vamvakousis, Z. (2015) · Frontiers in Neuroscience · doi:10.3389/fnins.2015.00354 · Cited by 139 · see citing works
EEG-based upper alpha neurofeedback training improves working memory performance
Escolano, C., Aguilar, M., & Mínguez, J. (2011) · doi:10.1109/iembs.2011.6090651 · Cited by 134 · see citing works
Modulation of frontal-midline theta by neurofeedback
Enriquez‐Geppert, S., Huster, R. J., Scharfenort, R., Mokom, Z. N., Zimmermann, J., & Herrmann, C. S. (2013) · Biological Psychology · doi:10.1016/j.biopsycho.2013.02.019 · Cited by 115 · see citing works
Rogala, J., Jurewicz, K., Paluch, K., Kublik, E., Cetnarski, R., & Wróbel, A. (2016) · Frontiers in Human Neuroscience · doi:10.3389/fnhum.2016.00301 · Cited by 115 · see citing works
Zuberer, A., Brandeis, D., & Drechsler, R. (2015) · Frontiers in Human Neuroscience · doi:10.3389/fnhum.2015.00135 · Cited by 113 · see citing works
MeditAid: a wearable adaptive neurofeedback-based system for training mindfulness state
Sas, C., & Chopra, R. (2015) · Personal and Ubiquitous Computing · doi:10.1007/s00779-015-0870-z · Cited by 104 · see citing works
Neurofeedback training of EEG alpha rhythm enhances episodic and working memory
Hsueh, J.-J., Chen, T.-S., Chen, J., & Shaw, F. (2016) · Human Brain Mapping · doi:10.1002/hbm.23201 · Cited by 100 · see citing works
Frontal Alpha Oscillations and Attentional Control: A Virtual Reality Neurofeedback Study
Berger, A. M., & Davelaar, E. J. (2017) · Neuroscience · doi:10.1016/j.neuroscience.2017.06.007 · Cited by 79 · see citing works
Identifying Indices of Learning for Alpha Neurofeedback Training
Dempster, T., & Vernon, D. J. (2009) · Applied Psychophysiology and Biofeedback · doi:10.1007/s10484-009-9112-3 · Cited by 77 · see citing works
The Impact of Stimuli on Affect in Persons With Dementia
Cohen‐Mansfield, J., Marx, M. S., Thein, K., & Dakheel‐Ali, M. (2011) · The Journal of Clinical Psychiatry · doi:10.4088/jcp.09m05694oli · Cited by 69 · see citing works
A novel self-guided approach to alpha activity training
Boxtel, G. J. M. V., Denissen, A. J. M., Jäger, M., Vernon, D. J., Dekker, M. K. J., Mihajlović, V., & Sitskoorn, M. M. (2011) · International Journal of Psychophysiology · doi:10.1016/j.ijpsycho.2011.11.004 · Cited by 68 · see citing works
EEG-based alpha neurofeedback training for mood enhancement
Phneah, S. W., & Nisar, H. (2017) · Australasian Physical & Engineering Sciences in Medicine · doi:10.1007/s13246-017-0538-2 · Cited by 67 · see citing works
Nawaz, R., Nisar, H., & Voon, Y. V. (2018) · IEEE Access · doi:10.1109/access.2018.2855194 · Cited by 61 · see citing works
EEG biofeedback in the treatment of attention deficit hyperactivity disorder.
Friel, P. N. (2007) · PubMed · Cited by 58 · see citing works
Brandmeyer, T., & Arnaud Delorme, A. (2020) · Frontiers in Human Neuroscience · doi:10.3389/fnhum.2020.00246 · Cited by 57 · see citing works
Jurewicz, K., Paluch, K., Kublik, E., Rogala, J., Mikicin, M., & Wróbel, A. (2017) · Neuropsychologia · doi:10.1016/j.neuropsychologia.2017.11.021 · Cited by 53 · see citing works
A novel EEG for alpha brain state training, neurobiofeedback and behavior change
Stinson, B., & Arthur, D. (2013) · Complementary Therapies in Clinical Practice · doi:10.1016/j.ctcp.2013.03.003 · Cited by 52 · see citing works
Alpha neurofeedback improves the maintaining ability of alpha activity
Cho, M. K., Jang, H. S., Jeong, S.-H., Jang, I., Choi, B., & Lee, M. (2008) · Neuroreport · doi:10.1097/wnr.0b013e3282f4f022 · Cited by 51 · see citing works
Mechanisms of Biofeedback Control
Lacroix, J. M. (1986) · Springer eBooks · doi:10.1007/978-1-4757-0629-1_6 · Cited by 43 · see citing works
Autenrieth, M., Kober, S. E., Neuper, C., & Wood, G. M. D. O. (2020) · Frontiers in Human Neuroscience · doi:10.3389/fnhum.2020.00218 · Cited by 37 · see citing works
EEG Frequency Changes Prior to Making Errors in an Easy Stroop Task
Atchley, R., Klee, D., & Oken, B. (2017) · Frontiers in Human Neuroscience · doi:10.3389/fnhum.2017.00521 · Cited by 34 · see citing works
Naas, A., Rodrigues, J., Knirsch, J.-P., & Sonderegger, A. (2019) · PLoS ONE · doi:10.1371/journal.pone.0211668 · Cited by 33 · see citing works
Neurofeedback Games to Improve Cognitive Abilities
Liu, Y., Sourina, O., & Hou, X. (2014) · International Conference on Cyberworlds (CW) · doi:10.1109/cw.2014.30 · Cited by 30 · see citing works
The Sensorium: A Multimodal Neurofeedback Environment
Hinterberger, T. (2010) · Advances in Human-Computer Interaction · doi:10.1155/2011/724204 · Cited by 28 · see citing works
NFBLab—A Versatile Software for Neurofeedback and Brain-Computer Interface Research
Smetanin, N., Volkova, K., Zabodaev, S. V., Lebedev, M., & Ossadtchi, A. E. (2018) · Frontiers in Neuroinformatics · doi:10.3389/fninf.2018.00100 · Cited by 21 · see citing works
Can background music help to relieve stress? An EEG analysis
Nawaz, R., Ng, J. T., Nisar, H., & Voon, Y. V. (2019) · IEEE International Conference on Signal and Image Processing Applications (ICSIPA) · doi:10.1109/icsipa45851.2019.8977763 · Cited by 15 · see citing works
Nawaz, R., Nisar, H., & Voon, Y. V. (2020) · IEEE Access · doi:10.1109/access.2020.3012565 · Cited by 14 · see citing works
Reaction time in Stroop test in Nepalese Medical Students
Ghimire, N. (2014) · JOURNAL OF CLINICAL AND DIAGNOSTIC RESEARCH · doi:10.7860/jcdr/2014/10615.4891 · Cited by 11 · see citing works
Recognition of Useful Music for Emotion Enhancement Based on Dimensional Model
Nawaz, R., Nisar, H., & Yap, V. V. (2018) · International Conference on BioSignal Analysis, Processing and Systems (ICBAPS) · doi:10.1109/icbaps.2018.8527390 · Cited by 11 · see citing works
Neurofeedback: A challenge for integrative clinical neurophysiological studies
Micoulaud‐Franchi, J., Jeunet, C., & Lotte, F. (2020) · Neurophysiologie Clinique · doi:10.1016/j.neucli.2020.01.001 · Cited by 11 · see citing works
Flagged first, then by citations
Research works printed but not linked: 2
- Pigott, E.; Alter, G.; Marikis, D. Frequency-Based Light & Sound Neurotherapy (LSN) Research: A Review of the Research. 2015. Available online: https://www.semanticscholar.org/paper/Frequency-Based-Light-%26-Sound-Neurotherapy-(-LSN-)-Pigott- Alter/396df55b4e3ce3ef9197007df4af723cae8ad61b (accessed on 5 January 2021).
- Marzbani, H.; Marateb, H.R.; Mansourian, M. Neurofeedback: A comprehensive review on system design, methodology and clinical applications. Basic Clin. Neurosci. 2016, 7, 143.
Cited by
Sorted by citations
Nawaz, R., Wood, G. M. D. O., Nisar, H., & Yap, V. V. (2023) · Bioengineering · doi:10.3390/bioengineering10020200 · Cited by 26 · see citing works
Musical Neurofeedback Advancements, Feedback Modalities, and Applications: A Systematic Review
Bhavsar, P., Shah, P., Sinha, S., & Kumar, D. (2024) · Applied Psychophysiology and Biofeedback · doi:10.1007/s10484-024-09647-0 · Cited by 21 · see citing works
Chikhi, S., Matton, N., Sanna, M., & Blanchet, S. (2023) · Biological Psychology · doi:10.1016/j.biopsycho.2023.108521 · Cited by 21 · see citing works
Mahmood, D., Nisar, H., & Tsai, C. (2024) · Expert Systems with Applications · doi:10.1016/j.eswa.2024.124415 · Cited by 14 · see citing works
Effects of one session of theta or high alpha neurofeedback on EEG activity and working memory
Chikhi, S., Matton, N., Sanna, M., & Blanchet, S. (2024) · Cognitive Affective & Behavioral Neuroscience · doi:10.3758/s13415-024-01218-4 · Cited by 10 · see citing works
Mahmood, D., Nisar, H., Nawaz, R., Yap, V. V., & Tsai, C. (2023) · Biomedical Signal Processing and Control · doi:10.1016/j.bspc.2023.105431 · Cited by 10 · see citing works
Feasibility of a novel neurofeedback system: a parallel randomized single-blinded pilot study
Horváth, D., Négyesi, J., Rácz, M., Győri, T., Matics, Z., Puskin, A., Csipor, J., & Rácz, L. (2023) · Scientific Reports · doi:10.1038/s41598-023-44545-1 · Cited by 10 · see citing works
Introduction to Non-Invasive Biomedical Signals for Healthcare
Mahmood, D., Riaz, H. N., & Nisar, H. (2023) · Springer eBooks · doi:10.1007/978-3-031-23239-8_1 · Cited by 8 · see citing works
Chang, M., Suzuki, S., Kurose, T., & Ibaraki, T. (2024) · Frontiers in Neuroergonomics · doi:10.3389/fnrgo.2024.1399578 · Cited by 5 · see citing works
Wang, M., Konharn, K., Eungpinichpong, W., Wanpen, S., & Sangpara, P. (2025) · Scientific Reports · doi:10.1038/s41598-025-90510-5 · Cited by 5 · see citing works
Mahmood, D., Leong, H. J., & Nisar, H. (2022) · International Conference on Emerging Trends in Smart Technologies (ICETST) · doi:10.1109/icetst55735.2022.9922942 · Cited by 5 · see citing works
EEG-Based Biometrics for User Identification Using Deep Learning Method
Nisar, H., Cheong, J. Y., & Yap, V. V. (2024) · IEEE International Conference on Signal and Image Processing Applications (ICSIPA) · doi:10.1109/icsipa62061.2024.10686270 · Cited by 4 · see citing works
Schmidt, K. L., Kowalski, A., Schweda, A., Dörrie, N., Skoda, E. M., Bäuerle, A., & Teufel, M. (2024) · BMJ Open · doi:10.1136/bmjopen-2023-079098 · Cited by 3 · see citing works
“15 While theta reduction can be used to improve attention skill, 16 the high-beta band is associated with stress experience.”
MethodMapping the Digital Mind: A Meta-Analysis of EEG Biomarkers in Cognition, Emotion, and Mental Health
Halkiopoulos, C., Gkintoni, E., & Boutsinas, B. (2026) · Brain Sciences · doi:10.3390/brainsci16040368 · Cited by 2 · see citing works
Ali, S. A., & Nisar, H. (2023) · IEEE National Biomedical Engineering Conference (NBEC) · doi:10.1109/nbec58134.2023.10352610 · Cited by 2 · see citing works
Effect of Neurofeedback Based on Imaginary Movement in Parkinson's Disease
Han, X., Shi, Z., Pei, G., Fang, B., & Yan, T. (2023) · ICME International Conference on Complex Medical Engineering (CME) · doi:10.1109/cme60059.2023.10565497 · Cited by 2 · see citing works
Nisar, H., Ong, Y. N., & Mahmood, D. (2024) · IEEE International Conference on Signal and Image Processing Applications (ICSIPA) · doi:10.1109/icsipa62061.2024.10686849 · Cited by 1 · see citing works
Integrated Circuit Packaging Recognition with Tilt Auto Adjustment using Deep Learning Approach
Loh, S. H., Teh, P. C., Sim, J. J., Yeap, K. H., & Lee, Y. K. (2023) · Journal of Engineering Technology and Applied Physics · doi:10.33093/jetap.2023.5.2.9 · Cited by 1 · see citing works
Einführung in nicht-invasive biomedizinische Signale für die Gesundheitsversorgung
Mahmood, D., Riaz, H. N., & Nisar, H. (2024) · Springer eBooks · doi:10.1007/978-3-031-52856-9_1
Puyvelde, M. V., & Pattyn, N. (2024) · Routledge eBooks · doi:10.4324/9781003378969-11
Mahmood, D., Nisar, H., & Ali, S. A. (2024) · IEEE Eurasia Conference on Biomedical Engineering, Healthcare and Sustainability (ECBIOS) · doi:10.1109/ecbios61468.2024.10885517
Iqbal, S., Nisar, H., & Yeap, K. H. (2025) · International Conference on Smart Cities, Automation & Intelligent Computing Systems (ICON-SONICS) · doi:10.1109/icon-sonics67145.2025.11309240
Matsuo, N., Mikata, K., Okumura, N., Inoue, W., Matsui, K., & Kodama, T. (2026) · Brain Sciences · doi:10.3390/brainsci16080886
Zhe, J. L. W., Nisar, H., Yeap, K. H., & Shin, V. (2026) · IEEE International Conference on Signal and Image Processing Applications (ICSIPA) · doi:10.1109/icsipa69622.2026.11720083
Theta-To-Beta Ratio-Based EEG Neurofeedback Game for Attention Enhancement: A Pilot Study
Riaz, H. N., Iqbal, S., Nisar, H., Chi-Kin, I. Y., Leow, K. Z., Kok, Y. X., Lee, J. W. Z., Shin, V., & Yap, V. V. (2026) · IEEE International Conference on Signal and Image Processing Applications (ICSIPA) · doi:10.1109/icsipa69622.2026.11720067
- Authors
- Nawaz, R., Nisar, H., Yap, V. V., & Tsai, C.-Y.
- Affiliations
- University of Glasgow (GB)
- Universiti Tunku Abdul Rahman (MY)
- Tamkang University (TW)
- Corresponding author
- Nisar, Humaira
- Venue
- Mathematics
- Publisher
- MDPI AG
- Published
- 2022-03-29
- Volume
- 10
- Issue
- 7
- Pages
- 1095
- ISSN
- 2227-7390 (ISSN-L)
- OpenAlex
- W4220958781
- Cited by
- 25
- References
- 54
- Citations by year
- 2026: 4 · 2025: 2 · 2024: 10 · 2023: 8 · 2022: 1
- FWCI
- 2.71
- Type
- journal article
- Language
- en
- Open access
- gold
- doi.org
- Licence
- Locations
- Mathematics (publishedVersion, cc-by)
- ENLIGHTEN (Jurnal Bimbingan dan Konseling Islam) (acceptedVersion, cc-by-sa)
- Open Access at Essex (University of Essex) (acceptedVersion)
- Tamkang University Institutional Repository (TKUIR) (submittedVersion)
- RePEc: Research Papers in Economics (submittedVersion)
- DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion)
- Funders
- Universiti Tunku Abdul Rahman (IPSR/RMC/UTARRF/2020-C2/H01, IPSR/RMC/UTARRF/2021-C2/H03, Excellent Research Center Award Fund, Centre for Healthcare Science and Technology)
- Topics
- Life Sciences › Neuroscience › Cognitive Neuroscience › EEG and Brain-Computer Interfaces
- Life Sciences › Neuroscience › Cognitive Neuroscience › Neural dynamics and brain function
- Social Sciences › Psychology › Social Psychology › Music Therapy and Health
- Keywords
- alpha rhythm, cognitive performance, training protocols, session duration, healthy adults, Stroop task, perceived stress, Mini-Mental State Examination
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
