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Journal articles on the topic 'Attention/concentration'

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Published: 4 June 2021
Last updated: 1 February 2022

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1

Wilson, John. "Attention and concentration." Educational Research 37, no. 1 (March 1995): 33–38. http://dx.doi.org/10.1080/0013188950370103.

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2

Moran, Aidan. "Chapter 52 - Concentration/attention." Routledge Online Studies on the Olympic and Paralympic Games 1, no. 44 (January 2012): 500–509. http://dx.doi.org/10.4324/9780203851043_chapter_52.

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3

TAHISA, HIROSHI. "Concentration of attention and TTS." AUDIOLOGY JAPAN 29, no. 5 (1986): 317–18. http://dx.doi.org/10.4295/audiology.29.317.

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4

Winston. "Command Attention Rather Than Demand Concentration." Journal of Aesthetic Education 55, no. 1 (2021): 109. http://dx.doi.org/10.5406/jaesteduc.55.1.0109.

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5

Lamba, Ms Sonika. "Impact of Teaching Time on Attention and Concentration." IOSR Journal of Nursing and Health Science 3, no. 4 (2014): 01–04. http://dx.doi.org/10.9790/1959-03410104.

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6

Garay-Jiménez, Laura-Ivoone, Elena Fabiola Ruiz Ledesma, Enrique Carmona-García, Asucena Lozano Gutiérrez, and Feggy Ostrosky Shejet. "Evaluation of Attention and Concentration Using Mobile Computing." International Journal on Advanced Science, Engineering and Information Technology 11, no. 1 (February 28, 2021): 408. http://dx.doi.org/10.18517/ijaseit.11.1.12631.

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7

Donofrio, N. "Attention, concentration, and information processing in a cardiac population." Archives of Clinical Neuropsychology 13, no. 1 (February 1998): 110–11. http://dx.doi.org/10.1016/s0887-6177(98)90573-x.

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8

Li, Songzhou, Gang Xie, Jinchang Ren, Lei Guo, Yunyun Yang, and Xinying Xu. "Urban PM2.5 Concentration Prediction via Attention-Based CNN–LSTM." Applied Sciences 10, no. 6 (March 12, 2020): 1953. http://dx.doi.org/10.3390/app10061953.

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Urban particulate matter forecasting is regarded as an essential issue for early warning and control management of air pollution, especially fine particulate matter (PM2.5). However, existing methods for PM2.5 concentration prediction neglect the effects of featured states at different times in the past on future PM2.5 concentration, and most fail to effectively simulate the temporal and spatial dependencies of PM2.5 concentration at the same time. With this consideration, we propose a deep learning-based method, AC-LSTM, which comprises a one-dimensional convolutional neural network (CNN), long short-term memory (LSTM) network, and attention-based network, for urban PM2.5 concentration prediction. Instead of only using air pollutant concentrations, we also add meteorological data and the PM2.5 concentrations of adjacent air quality monitoring stations as the input to our AC-LSTM. Hence, the spatiotemporal correlation and interdependence of multivariate air quality-related time-series data are learned by the CNN–LSTM network in AC-LSTM. The attention mechanism is applied to capture the importance degrees of the effects of featured states at different times in the past on future PM2.5 concentration. The attention-based layer can automatically weigh the past feature states to improve prediction accuracy. In addition, we predict the PM2.5 concentrations over the next 24 h by using air quality data in Taiyuan city, China, and compare it with six baseline methods. To compare the overall performance of each method, the mean absolute error (MAE), root-mean-square error (RMSE), and coefficient of determination (R2) are applied to the experiments in this paper. The experimental results indicate that our method is capable of dealing with PM2.5 concentration prediction with the highest performance.
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9

Ziółkowski, A., A. Gorkovenko, M. Pasek, P. Włodarczyk, B. Zarańska, M. Dornowski, and M. Graczyk. "EEG Correlates of Attention Concentration in Successful Amateur Boxers." Neurophysiology 46, no. 5 (October 2014): 422–27. http://dx.doi.org/10.1007/s11062-015-9468-3.

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10

Donofrio, N., and R. Petrucci. "Attention, concentration, and information processing in a cardiac population." Archives of Clinical Neuropsychology 13, no. 1 (February 1, 1998): 110–11. http://dx.doi.org/10.1093/arclin/13.1.110b.

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11

Dortier, Jean-François. "Focus. Attention et concentration : les clefs de la réussite." Sciences Humaines N° 262, no. 8 (August 1, 2014): 41. http://dx.doi.org/10.3917/sh.262.0041.

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12

Heo, Nan Seol, and Myung Kyung Lee. "ADHD Subtype Differences in Attention-Concentration Abilities and Learning Strategies." Journal of Emotional & Behavioral Disorders 34, no. 1 (March 31, 2018): 159–76. http://dx.doi.org/10.33770/jebd.34.1.9.

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13

Loleski, Mario, Sofija Loleska, and Nada Pop-Jordanova. "Mobile Application “Neurogame” for Assessment the Attention, Focus and Concentration." PRILOZI 38, no. 3 (December 1, 2017): 55–62. http://dx.doi.org/10.2478/prilozi-2018-0006.

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Abstract Smartphones are ubiquitous, but it is still unknown what physiological functions can be monitored at clinical quality. In medicine their use is cited in many fields (cardiology, pulmology, endocrinology, rheumatology, pediatrics as well as in the field of mental health). The aim of this paper is to explain how the use of mobile application can help clients to improve the index of their focus, concentration and motor skills. Our original developed application on Android operating system, named “neurogame” is based on an open source platform to enable assessment and therapeutic stimulation, focus and concentration with the ability to monitor the progress of the results obtained in a larger number of participants (normal subjects as well as patients with different disorders) over a period of time. Whilst nowadays the predominant focus is on the pharmacological treatments, there is a rapidly growing interest in research on alternative options that will offer help in many cases of disorder management in terms of mobile application games. In order to have some kind of “norms”, we evaluated a group of healthy population. Obtained results will serve as a database for comparison the future results. This article displays the results obtained as database.
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14

Kotipalli, Pushpa, and Murali Krishna Doma. "Concentration Building System for Children with Attention Deficit Hyperactivity Disorder." International Journal of Smart Home 10, no. 11 (November 30, 2016): 147–56. http://dx.doi.org/10.14257/ijsh.2016.10.11.13.

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15

Hercigonja Novkovic, Vesna, Vlasta Rudan, Nela Pivac, Gordana Nedic, and Dorotea Muck-Seler. "Platelet Serotonin Concentration in Children with Attention-Deficit/Hyperactivity Disorder." Neuropsychobiology 59, no. 1 (2009): 17–22. http://dx.doi.org/10.1159/000202825.

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16

Vast, Robyn Louise, Robyn Louise Young, and Patrick Robert Thomas. "Emotions in sport: Perceived effects on attention, concentration, and performance." Australian Psychologist 45, no. 2 (June 2010): 132–40. http://dx.doi.org/10.1080/00050060903261538.

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17

Hoshino, Yoshihiko, Yoshinori Ohno, Toshiaki Yamamoto, Motohisa Kaneko, and Hisashi Kumashiro. "Plasma Free Tryptophan Concentration in Children with Attention Deficit Disorder." Psychiatry and Clinical Neurosciences 39, no. 4 (December 1985): 531–35. http://dx.doi.org/10.1111/j.1440-1819.1985.tb00807.x.

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18

Fernández-Castillo, Antonio, and María J. Caurcel. "State test-anxiety, selective attention and concentration in university students." International Journal of Psychology 50, no. 4 (August 8, 2014): 265–71. http://dx.doi.org/10.1002/ijop.12092.

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19

kainthola, Sunil D. "A performance test of attention concentration for the visually handicapped." International Journal of Rehabilitation Research 11, no. 2 (June 1988): 203. http://dx.doi.org/10.1097/00004356-198806000-00027.

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20

Zhang, Jinsong, Yongtao Peng, Bo Ren, and Taoying Li. "PM2.5 Concentration Prediction Based on CNN-BiLSTM and Attention Mechanism." Algorithms 14, no. 7 (July 13, 2021): 208. http://dx.doi.org/10.3390/a14070208.

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The concentration of PM2.5 is an important index to measure the degree of air pollution. When it exceeds the standard value, it is considered to cause pollution and lower the air quality, which is harmful to human health and can cause a variety of diseases, i.e., asthma, chronic bronchitis, etc. Therefore, the prediction of PM2.5 concentration is helpful to reduce its harm. In this paper, a hybrid model called CNN-BiLSTM-Attention is proposed to predict the PM2.5 concentration over the next two days. First, we select the PM2.5 concentration data in hours from January 2013 to February 2017 of Shunyi District, Beijing. The auxiliary data includes air quality data and meteorological data. We use the sliding window method for preprocessing and dividing the corresponding data into a training set, a validation set, and a test set. Second, CNN-BiLSTM-Attention is composed of the convolutional neural network, bidirectional long short-term memory neural network, and attention mechanism. The parameters of this network structure are determined by the minimum error in the training process, including the size of the convolution kernel, activation function, batch size, dropout rate, learning rate, etc. We determine the feature size of the input and output by evaluating the performance of the model, finding out the best output for the next 48 h. Third, in the experimental part, we use the test set to check the performance of the proposed CNN-BiLSTM-Attention on PM2.5 prediction, which is compared by other comparison models, i.e., lasso regression, ridge regression, XGBOOST, SVR, CNN-LSTM, and CNN-BiLSTM. We conduct short-term prediction (48 h) and long-term prediction (72 h, 96 h, 120 h, 144 h), respectively. The results demonstrate that even the predictions of the next 144 h with CNN-BiLSTM-Attention is better than the predictions of the next 48 h with the comparison models in terms of mean absolute error (MAE), root mean square error (RMSE), and coefficient of determination (R2).
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21

Lee, Jinseok, and Changgoo Heo. "The Effect of Short-Term Meditation on the Attention Concentration and Class Concentration of Adult Learners." Journal of Lifelong Learning Society 15, no. 4 (November 30, 2019): 145–74. http://dx.doi.org/10.26857/jlls.2019.11.15.4.145.

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22

윤병수. "Effect of Concentration and Mindfulness Meditation on Attention Systems of Brain." Korean Journal of Health Psychology 17, no. 1 (March 2012): 65–77. http://dx.doi.org/10.17315/kjhp.2012.17.1.004.

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23

Giardina, Elsa-Grace V., Mindy E. Wechsler, Maria Dolgopiatova, and Robert Sciacca. "Moricizine Concentration to Guide Arrhythmia Treatment: With Attention to Elderly Patients." Journal of Clinical Pharmacology 34, no. 7 (July 1994): 725–33. http://dx.doi.org/10.1002/j.1552-4604.1994.tb02032.x.

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24

Gow, Alan J., and Ian J. Deary. "Is the PASAT Past It? Testing Attention and Concentration Without Numbers." Journal of Clinical and Experimental Neuropsychology 26, no. 6 (September 2004): 723–36. http://dx.doi.org/10.1080/13803390490509295.

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25

P, Sheela, Khaleel Manik, and Sudhir K. "Role of yoga in attention, concentration, and memory of medical students." National Journal of Physiology, Pharmacy and Pharmacology 8, no. 9 (2018): 1526. http://dx.doi.org/10.5455/njppp.2018.8.0723521082018.

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26

Hudaygulova, Galia Raisovna. "Observation as a method for studying concentration of attention of preschoolers." Pedagogical Education in Russia, no. 7 (2016): 266–73. http://dx.doi.org/10.26170/po16-07-37.

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27

Caamaño-Navarrete, Felipe, Pedro Ángel Latorre-Román, Juan Párraga-Montilla, Daniel Jerez-Mayorga, and Pedro Delgado-Floody. "Selective Attention and Concentration Are Related to Lifestyle in Chilean Schoolchildren." Children 8, no. 10 (September 27, 2021): 856. http://dx.doi.org/10.3390/children8100856.

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The objective of this investigation was to determine the association between selective attention and concentration with physical fitness (i.e., cardiorespiratory fitness (CRF), V˙O2max, the standing long jump test (SLJ) and handgrip muscle strength (HGS)), lifestyle parameters (i.e., physical activity (PA) level, screen time (ST), sleep duration and food habits) and anthropometric measures (i.e., body mass index (BMI) and waist circumference (WC)) among Chilean schoolchildren. Two hundred and forty-eight schoolchildren (137 boys, 111 girls, 11.80 ± 1.17 and 11.58 ± 1.09 years, respectively) participated. Selective attention, concentration and lifestyle (PA, ST, sleep duration and Mediterranean diet (MD) adherence) were determined using a standard questionnaire. CRF, SLJ, HGS and anthropometric indicators (BMI and WC) were also measured. Selective attention showed a positive association with MD adherence score (β; 5.012, p = p < 0.05). Concentration was linked inversely to ST (β; −5.498, p = p < 0.05). Likewise, concentration presented a positive association with MD adherence (β; 2.904, p = p < 0.05). In conclusion, children’s lifestyles are related to the selective attention and concentration of children; therefore, promoting healthy habits could be a cost-effective strategy in the promotion of cognitive development, as it relates to selective attention and concentration.
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28

Hamaguchi, Masayuki, Hiroshi Asada, and Kaoru Kitagawa. "A study of eyeblinking and attention concentration in Kendo practitioners." Taiikugaku kenkyu (Japan Journal of Physical Education, Health and Sport Sciences) 57, no. 1 (2012): 119–27. http://dx.doi.org/10.5432/jjpehss.11087.

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29

이명경 and 김아름. "Development and Validation of Attention-Concentration Ability Test for Children and Adolescent." Korea Journal of Counseling 12, no. 4 (August 2011): 1391–411. http://dx.doi.org/10.15703/kjc.12.4.201108.1391.

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30

Tudos, Stefan, Alexandra Predoiu, and Radu Predoiu. "Topographical Memory and the Concentration of Attention in Top Female Tennis Players." Procedia - Social and Behavioral Sciences 190 (May 2015): 293–98. http://dx.doi.org/10.1016/j.sbspro.2015.05.001.

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31

Pauli-Pott, Ursula, Susan Schloß, Nadine Skoluda, Urs M. Nater, and Katja Becker. "Low hair cortisol concentration predicts the development of attention deficit hyperactivity disorder." Psychoneuroendocrinology 110 (December 2019): 104442. http://dx.doi.org/10.1016/j.psyneuen.2019.104442.

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32

Meyers, John E., Chad E. Grills, Margaret M. Zellinger, and Ronald Mellado Miller. "Emotional Distress Affects Attention and Concentration: The Difference Between Mountains and Valleys." Applied Neuropsychology: Adult 21, no. 1 (June 14, 2013): 28–35. http://dx.doi.org/10.1080/09084282.2012.721148.

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33

KSS, Dr Anand, and Dr L. Shashikala. "Impact of haemoglobin level on attention and concentration in old Adults population." International Journal of Advanced Research in Medicine 3, no. 1 (January 1, 2021): 459–61. http://dx.doi.org/10.22271/27069567.2021.v3.i1h.181.

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34

Shi, Pengfei, Xiaolong Fang, Jianjun Ni, and Jinxiu Zhu. "An Improved Attention-Based Integrated Deep Neural Network for PM2.5 Concentration Prediction." Applied Sciences 11, no. 9 (April 28, 2021): 4001. http://dx.doi.org/10.3390/app11094001.

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The air quality prediction is a very important and challenging task, especially PM2.5 (particles with diameter less than 2.5 μm) concentration prediction. To improve the accuracy of the PM2.5 concentration prediction, an improved integrated deep neural network method based on attention mechanism is proposed in this paper. Firstly, the influence of exogenous series of other sites on the central site is considered to determine the best relevant site. Secondly, the data of all relevant sites are input into the improved dual-stage two-phase (DSTP) model, then the PM2.5 prediction result of each site is obtained. Finally, with the PM2.5 prediction result of each site, the attention-based layer predicts the PM2.5 concentration at the central site. The experimental results show that the proposed model is superior to most of the latest models.
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35

Schloß, Susan, Isabelle Ruhl, Viola Müller, Katja Becker, Nadine Skoluda, Urs M. Nater, and Ursula Pauli-Pott. "Low hair cortisol concentration and emerging attention-deficit/hyperactivity symptoms in preschool age." Developmental Psychobiology 60, no. 6 (March 23, 2018): 722–29. http://dx.doi.org/10.1002/dev.21627.

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36

Santamaría-Guzmán, Keven, Alejandro Salicetti-Fonseca, and José Moncada-Jiménez. "Balance, Attention and Concentration Improvements Following an Exergame Training Program in the Elderly." Medicine & Science in Sports & Exercise 47 (May 2015): 455. http://dx.doi.org/10.1249/01.mss.0000477678.38230.fd.

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37

Boulton, Michael. "Pupils’ perceptions of bullying and disruptions to concentration and attention to school work." Pastoral Care in Education 26, no. 2 (June 2008): 83–89. http://dx.doi.org/10.1080/02643940802062592.

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38

Southworth, Susan. "A study of the effects of cranial electrical stimulation on attention and concentration." Integrative Physiological and Behavioral Science 34, no. 1 (January 1999): 43–53. http://dx.doi.org/10.1007/bf02688709.

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39

Kirchkheli, Maia. "Holding and Visceral Attention: Bodily Concentration of an Analyst under COVID ‐19 Lockdown." British Journal of Psychotherapy 37, no. 3 (July 5, 2021): 404–16. http://dx.doi.org/10.1111/bjp.12642.

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40

Irfan, S. Marriyah, and S. Fatima Irfan. "Influence of Having Breakfast on Happiness and Attention-Concentration among High School Students." European Journal of Medical and Health Sciences 3, no. 2 (April 7, 2021): 111–16. http://dx.doi.org/10.24018/ejmed.2021.3.2.775.

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Background: Healthful nutrition has a positive connection with both physical and mental health. Breakfast is often considered as the most important meal of the day. Despite the benefits, skipping the morning meal is highly prevalent among adolescents. Healthy eating has an effect on happiness and concentration but a firm connection has not been established. Breakfast skipping can be a factor and a gap in the literature exists in this regard. The aim of this study was to evaluate the relationships between eating breakfast, happiness and attention concentration among high school students. Methods: In this descriptive cross-sectional study, a convenient sampling strategy was used to select the students from an International school located in Riyadh, Saudi Arabia. The 29-item Oxford Happiness Questionnaire along with demographic variables was employed as research instrument. Chi-square test, student t-test and ANOVA were used to compare different categorical variables. Results: The overall Happiness mean score was 3.621 ± 0.6637. Students who were regular at having breakfast every day had higher happiness mean scores. Overall, 40% of the participants reported to have decreased concentration/attentiveness during the first 4 lectures at school. Majority (55%) of the breakfast skippers were distracted in the lessons. A regular breakfast eating habit was found to be significantly associated with happiness (p=0.04) and concentration during lectures (p=0.04) respectively. Majority of the students had insufficient physical activity (72%) and had experienced stress (88%) in the last six months respectively. The prevalence of being overweight/ obese among breakfast skippers was higher (39%) than was in breakfast consumers (26%). Conclusion: Eating breakfast was associated with higher happiness scores and better concentration among high school students. An alarmingly high prevalence of stress among students is a cause of concern. Schools should start breakfast eating programs and promote physical activity to reduce stress. Future studies are needed to explore the factors associated with stress.
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41

Buchele Harris, Heidi, Kai Schnabel Cortina, Thomas Templin, Natalie Colabianchi, and Weiyun Chen. "Impact of Coordinated-Bilateral Physical Activities on Attention and Concentration in School-Aged Children." BioMed Research International 2018 (May 28, 2018): 1–7. http://dx.doi.org/10.1155/2018/2539748.

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Purpose. This study examined the effects of 4-week, daily 6-minute coordinated-bilateral physical activity (CBPA) breaks in classroom on attention and concentration in school-aged children. Methods. Participants (n=116) in fifth grade from two elementary schools were assigned to three groups: two intervention groups (n= 60) and one control group (n = 56). All three groups were pre- and post-tested with the d2 Test of Attention (d2 test). One intervention group (n = 31) took part in six minutes of daily classroom-based coordinated-bilateral physical activity (CBPA) break for four weeks. Another intervention group (n = 29), the Fitbit Only (Fitbit-O), wore Fitbits per day during a school, five days per week for four weeks without CBPA breaks. A 2 × 3 ANOVA was conducted, followed by the post hoc comparisons. Results. The CBPA showed significant increases in processing speed (F1 = 6.876, p = .010), focused attention (F1 = 10.688, p = .002), concentration performance (F1 = 26.46, p = .000), and attention span (F1 = 14.090, p = .000) over the control, but not in accuracy (Error %). The CBPA showed significant improvement in concentration performance (F1 = 24.162, p = .000) and attention span (F1 = 6.891, p = .011), compared to the Fitbit-O. No significant changes in all five attention parameters were found between the Fitbit-O and the control. Conclusion. It was concluded that daily brief coordinated-bilateral activities can improve attention and concentration in fifth-grade students over the course of four weeks.
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Sukmandari, Ni Made Ari, Ni Wayan Septarini, and Gede Ngurah Indraguna Pinatih. "Association between breakfast-eating habit and attention-concentration in primary school children: a cross-sectional study in Badung District." Public Health and Preventive Medicine Archive 6, no. 1 (July 1, 2018): 55. http://dx.doi.org/10.15562/phpma.v6i1.10.

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AbstractBackground and purpose: One of the main benefits of breakfast-eating habit for schoolchildren is to maintain the attention-concentration. The current trend shows a steady decline in the breakfast-eating habit among primary school children. This present study aims to examine the association between breakfast-eating habit and attention-concentration in primary school children. Methods: A cross-sectional study was conducted involving 160 primary school students year 5 and 6. Samples were selected from six public primary schools within two villages. There were a total of 16 classes of year 5 and 6 in these six schools, and five classes were selected randomly. All students from the selected classes included in the study. Attention-concentration was measured using a digit symbol test, and breakfast-eating habit and total calories intake were measured using the recall 24 hours and a standardised questionnaire. Multivariate analysis with logistic regression was employed to examine the association between breakfast-eating habit and attention-concentration.Results: The majority of students were found to have good concentration (60.63%), with breakfast-eating habit (75.00%), and consumed sufficient amount of calories (53.13%). Our multivariate analysis found a significant association between breakfast-eating habit and attention-concentration among schoolchildren (AOR=14.0; 95%CI: 4,9–67,8).Conclusions: Students with breakfast-eating habit tend to have a good attention-concentration. The total calories intake during breakfast is not associated with attention-concentration among primary school students in Badung District.
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Sukmandari, Ni Made Ari, Ni Wayan Septarini, and Gede Ngurah Indraguna Pinatih. "Association between breakfast-eating habit and attention-concentration in primary school children: a cross-sectional study in Badung District." Public Health and Preventive Medicine Archive Journal 6, no. 1 (July 1, 2018): 1. http://dx.doi.org/10.15562/pphma.v6i1.10.

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AbstractBackground and purpose: One of the main benefits of breakfast-eating habit for schoolchildren is to maintain the attention-concentration. The current trend shows a steady decline in the breakfast-eating habit among primary school children. This present study aims to examine the association between breakfast-eating habit and attention-concentration in primary school children. Methods: A cross-sectional study was conducted involving 160 primary school students year 5 and 6. Samples were selected from six public primary schools within two villages. There were a total of 16 classes of year 5 and 6 in these six schools, and five classes were selected randomly. All students from the selected classes included in the study. Attention-concentration was measured using a digit symbol test, and breakfast-eating habit and total calories intake were measured using the recall 24 hours and a standardised questionnaire. Multivariate analysis with logistic regression was employed to examine the association between breakfast-eating habit and attention-concentration.Results: The majority of students were found to have good concentration (60.63%), with breakfast-eating habit (75.00%), and consumed sufficient amount of calories (53.13%). Our multivariate analysis found a significant association between breakfast-eating habit and attention-concentration among schoolchildren (AOR=14.0; 95%CI: 4,9–67,8).Conclusions: Students with breakfast-eating habit tend to have a good attention-concentration. The total calories intake during breakfast is not associated with attention-concentration among primary school students in Badung District.
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44

Oh, Yun-Ah, Seon-Ok Kim, and Sin-Ae Park. "Real Foliage Plants as Visual Stimuli to Improve Concentration and Attention in Elementary Students." International Journal of Environmental Research and Public Health 16, no. 5 (March 5, 2019): 796. http://dx.doi.org/10.3390/ijerph16050796.

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This study was conducted to determine the physiological and psychological benefits of foliage plants as visual stimuli. Twenty-three elementary students (aged 11 to 13 years old) participated in this study. In a crossover design, electroencephalography (EEG) was used to measure and determine the psycho-physiological effects of four different visual stimuli: an actual plant, artificial plant, photograph of a plant, and no plant. Subjective evaluations of emotions were assessed using the profile of mood state and semantic differential methods immediately after exposure to each visual stimulus. A significant decrease in theta waves of the frontal lobe was associated with presentation of the actual plants. This response indicated that the viewing of living plants prompted improvements in the attention and concentration of the elementary students. Furthermore, the presentation of the living plants was associated with more positive mood states, such as feelings of comfort and naturalness. In conclusion, actual plants may improve attention and prompt psychological relaxation in elementary students relative to artificial plants, photographs of plants, or the absence of plants.
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45

Yato, Yuko, Shohei Hirose, Philippe Wallon, Claude Mesmin, and Matthieu Jobert. "A New Test to Measure Japanese Children's Concentration and Attention: The d2-R Test." Japanese Journal of Personality 23, no. 2 (2014): 91–95. http://dx.doi.org/10.2132/personality.23.91.

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mohamed, marwa, samah ibraheem, and mona aly. "urinary bisphenol A concentration in children with Attention-deficit/hyperactivity disorder : a pilot study." Egyptian Journal of Forensic Sciences and Applied Toxicology 20, no. 1 (March 1, 2020): 93–104. http://dx.doi.org/10.21608/ejfsat.2019.5553.1027.

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Rietschel, Robert L., Magnus Bruze, Birgitta Gruvberger, Kathryn A. Zug, Erin M. Warshaw, James S. Taylor, Frances J. Storrs, et al. "The Relationship of Vehicle and Concentration of Imidazolidinylurea, with Attention to Formaldehyde Allergy Status." Dermatitis 17, no. 1 (March 2006): 48–49. http://dx.doi.org/10.2310/6620.2006.05040.

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Thomas, Laura, and Michael Trimble. "The effects of vigabatrin on attention, concentration and mood: an investigation in healthy volunteers." Seizure 5, no. 3 (September 1996): 205–8. http://dx.doi.org/10.1016/s1059-1311(96)80037-9.

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Rice, Jessica, Aline Ferreira Correia, and Enid Schutte. "Attention and concentration functions in HIV-positive adolescents who are on anti-retroviral treatment." South African Journal of Psychology 44, no. 4 (July 2, 2014): 467–82. http://dx.doi.org/10.1177/0081246314540141.

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Kim, Su-Kyoung, Eun-Young Yoo, Jae-Shin Lee, Min-Ye Jung, Soo-Hyon Park, and Ji-Hyuk Park. "The Effects of Neurofeedback Training on Concentration in Children with Attention Deficit/Hyperactivity Disorder." International Journal of Bio-Science and Bio-Technology 6, no. 4 (August 31, 2014): 13–24. http://dx.doi.org/10.14257/ijbsbt.2014.6.4.02.

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