Iranian Journal of Information Processing and Management

Iranian Journal of Information Processing and Management

Comparison of Theta Waves During Different Stages of Web Search: An Indicator for Sustained Attention

Document Type : Original Article

Authors
1 PhD In Information Science, Department of Information Science, Faculty of Education and Psychology, Shiraz University, Iran
2 PhD. in Information Science, Associate Professor at Shiraz University, Shiraz, Iran
3 Fars, Shiraz, Shiraz University
4 PhD. in Clinical Psychology; Professor; Department of Clinical Psychology, Faculty of Education and Psychology, Shiraz University, Shiraz, Iran
5 University of Strathclyde, Glasgow, UK.
Abstract
Web search, as a primary tool for accessing a vast amount of data, plays a crucial role in information retrieval. This study aims to compare the level of sustained attention across different stages of web searching. This research is foundational in its purpose and employs a quasi-experimental method for collecting quantitative data. The research sample consisted of 12 graduate students from Shiraz University, selected using a purposive sampling method. This approach was chosen because graduate students typically engage in more search activities due to their research requirements. Initially, G-Power software estimated that a sample size of 12 participants would suffice; however, to ensure reliability, data were gathered from 14 participants. The main variable of the study was the level of sustained attention, which was measured by recording theta wave activity using a 21-electrode electroencephalography (EEG) device. For data preprocessing and analysis, the MNE library in Python was utilised. The preprocessed data were organised according to time intervals participants spent on each web search stage: reading the question, formulating the search query, reviewing the search engine results page, and judging relevance. Ultimately, the relative power of the theta wave was calculated as an indicator of sustained attention for each stage and was compared across different stages using repeated measures analysis of variance. The findings indicated that the relative power of the theta wave during the relevance judgment stage was significantly higher than during the review stage of the search engine results page. Moreover, no significant differences were found between the reading question and formulating query stages. This suggests that sustained attention is greater during the relevance judgment stage, as users tend to engage more deeply in reading the information pages, assessing their relevance, and seeking the desired answers to their search tasks. In contrast, during the review phase of the search engine results page, users do not require as high a level of sustained attention, since they often skim titles and maintain shorter attention spans. The results of this research could inform the design of personalised search engines using EEG data. Monitoring users’ theta wave activity on content pages could serve as a reliable metric for gauging user engagement and assessing content relevance.
Keywords
Subjects

، محسن نوکاریزی، رضا رستمی، و علی مقیمی. 1398. واکاوی مؤلفه‌های شناختی در فراگرد رفتار اطلاع‌یابی درمانگران با استفاده از ابزارهای پژوهشی علوم عصب‌شناختی. پژوهشنامه پردازش و مدیریت اطلاعات 35 (2). 323–348. doi:10.35050/JIPM010.2020.053.
خانلرخانی، المیرا. 1402. مقایسه تغییرات امواج مغزی مرتبط با بار شناختی در فرایند جست‌وجوی اطلاعات گوگل در کاربران با سبک شناختی کل‌گرا-تحلیلی و کلامی-تصویری. رساله دکتری. دانشگاه شیراز. شیراز.
_____، مهدیه میرزابیگی، هاجر ستوده، مسعود فضیلت‌پور، و محمد نامی. 1401.«مطالعه‌ی رفتار اطلاع‌جویی کاربران از طریق ثبت امواج مغزی با کمک الکتروآنسفالوگرافی: یک مرور نظام‌مند. پژوهشنامه پردازش و مدیریت اطلاعات 38 (2). 337–377. .doi:10.35050/JIPM010.2022.038
زاهدی نوقابی، مهدی. 1396. تأثیر توانمندی‌های کاربران و مؤلفه‌های رابط کاربر وب‌سایت‌ها بر فرایند تعامل در وب (بر پایه نظریه پردازش اطلاعات با استفاده از رویکرد چشم-ذهن). مشهد: دانشگاه فردوسی مشهد. https://ganj.irandoc.ac.ir/#/articles/7e94d989810ae6f684e720ea5ea6a856 (دسترسی در 20/3/1403)
References:
Ahn, Jae-Hyeon, Yoon-Soo Bae, Jaehyeon Ju & Wonseok Oh. 2018. Attention Adjustment, Renewal, and Equilibrium Seeking in Online Search: An Eye-Tracking Approach. Journal of Management Information Systems 35 (4): 1218–50. doi:10.1080/07421222.2018.1523595.
Allegretti, Marco, Yashar Moshfeghi, Maria Hadjigeorgieva, Frank E. Pollick, Joemon M. Jose & Gabriella Pasi. 2015. When Relevance Judgement Is Happening? An EEG-Based Study. In Proceedings of the 38th International ACM SIGIR Conference on Research and Development in Information Retrieval, 799–22. Santiago Chile: ACM. doi:10.1145/2766462.2767811.
Al-Samarraie, Hosam, Atef Eldenfria, Fahed Zaqout & Melissa Lee Price. 2019. How Reading in Single- and Multiple-Column Types Influence Our Cognitive Load: An EEG Study. The Electronic Library 37 (4): 593–606. doi: 10.1108/EL-01-2019-0006.
Antonenko, Pavlo, Fred Paas, Roland Grabner & Tamara Van Gog. 2010. Using Electroencephalography to Measure Cognitive Load. Educational Psychology Review 22 (4): 425–438. doi: 10.1007/s10648-010-9130-y.
Bauer, Clemens C. C., Liron Rozenkrantz, Camila Caballero, Alfonso Nieto-Castanon, Ethan Scherer, Martin R. West, Michael Mrazek, Dawa T. Phillips, John D. E. Gabrieli & Susan Whitfield-Gabrieli. 2020. Mindfulness training preserves sustained attention and resting state anticorrelation between default-mode network and dorsolateral prefrontal cortex: a randomized controlled trial. Human Brain Mapping 41 (18): 5356–5369. doi:10.1002/hbm.25197.
Berger, Jonah, Wendy W. Moe & David A. Schweidel. 2023. What Holds Attention? Linguistic Drivers of Engagement. Journal of Marketing 87 (5). SAGE Publications Inc: 793–809. doi: 10.1177/00222429231152880.
Boardman، Rosy & Helen Mccormick. 2021. Attention and behaviour on fashion retail websites: an eye-tracking study. Information Technology & People 35 (7): 2219–2240. doi: 10.1108/ITP-08-2020-0580.
Bose, Joy, Amit Singhai, Anish Patankar & Ankit Kumar. 2016. Attention Sensitive Web Browsing. arXiv. doi:10.48550/arXiv.1601.01092.
Botturi, Luca, Martin Hermida, Loredana Addimando & Chiara Beretta. 2024. Visualizing Online Search Processes for Information Literacy Education. In Information Experience and Information Literacy ed.: Serap Kurbanoğlu, Sonja Špiranec, Joumana Boustany, Yurdagül Ünal, İpek Şencan, Denis Kos, Esther Grassian, Diane Mizrachi & Loriene Roy, 277–289. Cham: Springer Nature Switzerland. doi: 10.1007/978-3-031-52998-6_24.
Byrom, Bill, Marie McCarthy, Peter Schueler & Willie Muehlhausen. 2018. Brain Monitoring Devices in Neuroscience Clinical Research: The Potential of Remote Monitoring Using Sensors, Wearables, and Mobile Devices. Clinical Pharmacology and Therapeutics 104 (1): 59–71. doi:10.1002/cpt.1077.
Cona, Giorgia, Francesco Chiossi, Silvia Di Tomasso, Giovanni Pellegrino, Francesco Piccione, Patrizia Bisiacchi & Giorgio Arcara. 2020. Theta and Alpha Oscillations as Signatures of Internal and External Attention to Delayed Intentions: A Magnetoencephalography (MEG) Study. NeuroImage 205 (March): 116295. doi:10.1016/j.neuroimage.2019.116295.
Cowley, Benjamin Ultan. 2018. Studying the integrated functional cognitive basis of sustained attention with a Primed Subjective-Illusory-Contour Attention Task. Scientific Reports 8 (November): 13514. doi: 10.1038/s41598-018-31876-7.
Debue, Nicolas, Cécile Van De Leemput, Anish Pradhan & Robert Atkinson. 2018. Comparative Study of Laptops and Touch-Screen PCs for Searching on the Web. In: Engineering Psychology and Cognitive Ergonomics ed.: Don Harris, 10906: 403–18. Lecture Notes in Computer Science. Cham: Springer International Publishing. doi: 10.1007/978-3-319-91122-9_33.
Djamasbi, Soussan, Adrienne Hall-Phillips & Ruijiao (Rachel) Yang. 2013. Search Results Pages and Competition for Attention Theory: An Exploratory Eye-Tracking Study. In: Human Interface and the Management of Information. Information and Interaction Design. ed.: Sakae Yamamoto, 576–83. Berlin, Heidelberg: Springer. doi: 10.1007/978-3-642-39209-2_64.
Dreyer, Pauline, Aline Roc, Léa Pillette, Sébastien Rimbert & Fabien Lotte. 2023. A Large EEG Database with Users’ Profile Information for Motor Imagery Brain-Computer Interface Research. Scientific Data 10 (1): 580. doi: 10.1038/s41597-023-02445-z.
Esqueda-Elizondo, José Jaime, Reyes Juárez-Ramírez, Oscar Roberto López-Bonilla, Enrique Efrén García-Guerrero, Gilberto Manuel Galindo-Aldana, Laura Jiménez-Beristáin, Alejandra Serrano-Trujillo, Esteban Tlelo-Cuautle, Everardo Inzunza-González. 2022. Attention Measurement of an Autism Spectrum Disorder User Using EEG Signals: A Case Study. Mathematical and Computational Applications 27 (2): 21. doi: 10.3390/mca27020021.
Esterman, Michael & David Rothlein. 2019. Models of Sustained Attention.» Current Opinion in Psychology 29 (January): 174–180. doi:10.1016/j.copsyc.2019.03.005.
Eugster, Manuel J.A., Tuukka Ruotsalo, Michiel M. Spapé, Ilkka Kosunen, Oswald Barral, Niklas Ravaja, Giulio Jacucci & Samuel Kaski. 2014. Predicting Term-Relevance from Brain Signals. In: Proceedings of the 37th International ACM SIGIR Conference on Research & Development in Information Retrieval, 425–34. Gold Coast Queensland Australia: ACM. doi:10.1145/2600428.2609594.
Faber, Jorge & Lilian Martins Fonseca. 2014. How Sample Size Influences Research Outcomes. Dental Press Journal of Orthodontics 19 (4): 27. doi:10.1590/2176-9451.19.4.027-029.ebo.
Fortenbaugh, Francesca C., Joseph DeGutis & Michael Esterman. 2017. Recent theoretical, neural, and clinical advances in sustained attention research. Annals of the New York Academy of Sciences 1396 (1): 70–91. doi:10.1111/nyas.13318.
Frerejean، Jimmy, Gerdo J. Velthorst, Johan L.H. Van Strien, Paul A. Kirschner & Saskia Brand-Gruwel. 2019. Embedded Instruction to Learn Information Problem Solving: Effects of a Whole Task Approach. Computers in Human Behavior 90 (April): 117–130. doi:10.1016/j.chb.2018.08.043.
Gallen, Courtney L., Simon Schaerlaeken, Jessica W. Younger, Joaquin A. Anguera & Adam Gazzaley. 2023. Contribution of sustained attention abilities to real-world academic skills in children. Scientific Reports 13 (May): 2673. doi: 10.1038/s41598-023-29427-w.
Gevins, Alan & Michael E. Smith. 2003. Neurophysiological Measures of Cognitive Workload during Human-Computer Interaction. Theoretical Issues in Ergonomics Science 4 (1–2): 113–31. doi: 10.1080/14639220210159717.
González-Ibáñez, Roberto, María Escobar-Macaya & Manuel Manriquez. 2016. Using Low-Cost Electroencephalography (EEG) Sensor to Identify Perceived Relevance on Web Search: Using Low-Cost Electroencephalography (EEG) Sensor to Identify Perceived Relevance on Web Search. Proceedings of the Association for Information Science and Technology 53 (1): 1–5. doi:10.1002/pra2.2016.14505301146.
Gramfort, Alexandre, Martin Luessi, Eric Larson, Denis A. Engemann, Daniel Strohmeier, Christian Brodbeck, Roman Goj & & et al. 2013. MEG and EEG Data Analysis with MNE-Python. Frontiers in Neuroscience 7 (March). Frontiers. doi:10.3389/fnins.2013.00267.
Gu, Feng, Anmin Gong, Yi Qu, Ling Lu, Qidi Shi & Yunfa Fu. 2022. Brain Network Research of Skilled Shooters in the Shooting Preparation Stage under the Condition of Limited Sensory Function. Brain Sciences 12 (10): 1373. doi: 10.3390/brainsci12101373.
Gwizdka, Jacek. 2009. Assessing Cognitive Load on Web Search Tasks. The Ergonomics Open Journal 2 (1). https://benthamopen.com/ABSTRACT/TOERGJ-2-114. (accessed Jul. 05, 2024)
———. 2018. Inferring Web Page Relevance Using Pupillometry and Single Channel EEG. In: Information Systems and Neuroscience Ed.: Fred D. Davis, René Riedl, Jan Vom Brocke, Pierre-Majorique Léger & Adriane B. Randolph, 25: 175–183. Lecture Notes in Information Systems and Organisation. Cham: Springer International Publishing. doi: 10.1007/978-3-319-67431-5_20.
Gwizdka, Jacek, Rahilsadat Hosseini, Michael Cole & Shouyi Wang. 2017. Temporal Dynamics of Eye-Tracking and EEG during Reading and Relevance Decisions. Journal of the Association for Information Science and Technology 68 (10): 2299–2312. doi:10.1002/asi.23904.
Harvey, Morgan & Matthew Pointon. 2017. Searching on the Go: The Effects of Fragmented Attention on Mobile Web Search Tasks. In: Proceedings of the 40th International ACM SIGIR Conference on Research and Development in Information Retrieval 155–64. Shinjuku Tokyo Japan: ACM. doi:10.1145/3077136.3080770.
Helfrich, Randolph F., Ian C. Fiebelkorn, Sara M. Szczepanski, Jack J. Lin, Josef Parvizi, Robert T. Knight & Sabine Kastner. 2018. Neural mechanisms of sustained attention are rhythmic. Neuron 99 (4): 854-865.e5. doi:10.1016/j.neuron.2018.07.032.
Hennink, Monique & Bonnie N. Kaiser. 2022. Sample sizes for saturation in qualitative research: A systematic review of empirical tests. Social Science & Medicine 292 (April): 114523 doi:10.1016/j.socscimed.2021.114523.
Hopkin, Cameron R., Rick H. Hoyle & Nisha C. Gottfredson. 2015. Maximizing the Yield of Small Samples in Prevention Research: A Review of General Strategies and Best Practices. Prevention science : the official journal of the Society for Prevention Research 16 (7): 950–55. doi: 10.1007/s11121-014-0542-7.
Huang, Huimin, Rui Li & Junsong Zhang. 2023. A review of visual sustained attention: neural mechanisms and computational models. PeerJ 11 (August): e15351. doi:10.7717/peerj.15351.
Huang, Jeff. 2013. Modeling User Behavior and Attention in Search. Thesis. https://digital.lib.washington.edu:443/researchworks/handle/1773/24188 (accessed Jul. 05, 2024)
Hwu, Shiow-Lin. 2023. Developing SAMM: A Model for Measuring Sustained Attention in Asynchronous Online Learning. Sustainability 15 (12). Multidisciplinary Digital Publishing Institute: 9337. doi: 10.3390/su15129337.
Jacucci, Giulio, Oswald Barral, Pedram Daee, Markus Wenzel, Baris Serim, Tuukka Ruotsalo, Patrik Pluchino, & et al. 2019 Integrating Neurophysiologic Relevance Feedback in Intent Modeling for Information Retrieval. Journal of the Association for Information Science and Technology 70 (9): 917–30. doi:10.1002/asi.24161.
Kaspar, Kai, Ricardo Ramos Gameiro & Peter König. 2015. Feeling Good, Searching the Bad: Positive Priming Increases Attention and Memory for Negative Stimuli on Webpages. Computers in Human Behavior 53 (February): 332–43. doi: 10.1016/j.chb.2015.07.020.
Kerick, Scott E., Justin Asbee, Derek P. Spangler, Justin B. Brooks, Javier O. Garcia,Thomas D. Parsons, Nilanjan Bannerjee & Ryan Robucci. 2023. Neural and behavioral adaptations to frontal theta neurofeedback training: A proof of concept study. PLOS ONE 18 (3): e0283418. doi:10.1371/journal.pone.0283418.
Keshmiri, Soheil, Maryam Alimardani, Masahiro Shiomi, Hidenobu Sumioka, Hiroshi Ishiguro & Kazuo Hiraki. 2020. Higher hypnotic suggestibility is associated with the lower EEG signal variability in theta, alpha, and beta frequency bands. PLoS ONE 15 (4): e0230853. doi:10.1371/journal.pone.0230853.
Klimesch, Wolfgang. 2012. Alpha-Band Oscillations, Attention, and Controlled Access to Stored Information. Trends in Cognitive Sciences 16 (12): 606–17. doi:10.1016/j.tics.2012.10.007.
Kubota, Yasutaka, Wataru Sato, Motomi Toichi, Toshiya Murai, Takashi Okada, Akiko Hayashi & Akira Sengoku. 2001. Frontal Midline Theta Rhythm Is Correlated with Cardiac Autonomic Activities during the Performance of an Attention Demanding Meditation Procedure. Cognitive Brain Research 11 (2): 281–87. doi: 10.1016/S0926-6410(00)00086-0.
Lagun, Dmitry & Eugene Agichtein. 2014. Effects of task and domain on searcher attention. In: Proceedings of the 37th international ACM SIGIR conference on Research & development in information retrieval 1087–90. SIGIR ’14. New York, NY, USA: Association for Computing Machinery. doi:10.1145/2600428.2609516.
Lajtos, Melissa, Luis Alberto Barradas-Chacón & Selina Christin Wriessnegger. 2023. Effects of Handedness on Brain Oscillatory Activity during Imagery and Execution of Upper Limb Movements. Frontiers in Psychology 14 (August). doi:10.3389/fpsyg.2023.1161613.
Li, Zhao, Long Zhang, Chenyi Lei, Xia Chen, Jianliang Gao & Jun Gao. 2020. Attention with Long-Term Interval-Based Deep Sequential Learning for Recommendation. Complexity 2020 (September). Hindawi: e6136095. doi:10.1155/2020/6136095.
Liu, Jingjing, Chang Liu & Nicholas J. Belkin. 2020. Personalization in Text Information Retrieval: A Survey. Journal of the Association for Information Science and Technology 71 (3): 349–69. doi:10.1002/asi.24234.
Massar, Stijn A.A., Julian Lim, Karen Sasmita & Michael W.L. Chee. 2016. Rewards Boost Sustained Attention through Higher Effort: A Value-Based Decision Making Approach. Biological Psychology 120 (January): 21–27. doi:10.1016/j.biopsycho.2016.07.019.
Matravers, Derek. 2011. Arousal Theories. In: The Routledge Companion to Philosophy and Music. Routledge:
Matsuo, Moemi, Takashi Higuchi, Hiroya Miyabara, Misako Higashijima, Takeshi Oshikawa, Masatoshi Nakamura, Yuji Yamaguchi & Takuya Higashionna. 2023. «\Assessing attentional task-related electroencephalogram signal variations by using mobile electroencephalogram technology: An experimental study. Medicine 102 (42): e35801. doi: 10.1097/MD.0000000000035801.
McElroy, James C., Anthony R. Hendrickson, Anthony M. Townsend & Samuel M. DeMarie. 2007. Dispositional Factors in Internet Use: Personality versus Cognitive Style. MIS Quarterly 31 (4). Management Information Systems Research Center, University of Minnesota: 809–20. doi:10.2307/25148821.
Möller, C. & T. Schierl. 2012. Attention and selection behavior on ‘universal search’ result pages. In: https://www.semanticscholar.org/paper/Attention-and-selection-behavior-on-%E2%80%98universal-M%C3%B6ller-Schierl/1d8cddae1c8b8fc0db11dcc130625546392f9249 (accessed Jul. 05, 2024)
Moshfeghi, Yashar & Joemon M. Jose. 2013. An Effective Implicit Relevance Feedback Technique Using Affective, Physiological and Behavioural Features. In: Proceedings of the 36th International ACM SIGIR Conference on Research and Development in Information Retrieval 133–42. Dublin Ireland: ACM. doi:10.1145/2484028.2484074.
Nam, Chang S., Matthew Moore, Inchul Choi & Yueqing Li. 2015. Designing Better, Cost-Effective Brain–Computer Interfaces. Ergonomics in Design 23 (4). SAGE Publications Inc: 13–19. doi: 10.1177/1064804615572625.
Niosi, Andrea. 2021. The Perceptual Process», August. BCcampus. https://opentextbc.ca/introconsumerbehaviour/chapter/the-perceptual-process/. (accessed Jul. 05, 2024)
Peng, Ming, Xianke Chen, Qingbai Zhao & Zongkui Zhou. 2018. Attentional scope is reduced by Internet use: A behavior and ERP study. PLoS ONE 13 (6): e0198543. doi:10.1371/journal.pone.0198543.
Putkonen, Aini, Aurélien Nioche, Markku Laine, Crista Kuuramo & Antti Oulasvirta. 2023. Fragmented Visual Attention in Web Browsing: Weibull Analysis of Item Visit Times. In: Advances in Information Retrieval. Ed.: Jaap Kamps, Lorraine Goeuriot, Fabio Crestani, Maria Maistro, Hideo Joho, Brian Davis, Cathal Gurrin, Udo Kruschwitz & Annalina Caputo, 62–78. Lecture Notes in Computer Science. Cham: Springer Nature Switzerland. doi: 10.1007/978-3-031-28238-6_5.
Román, Cristina A. F., John DeLuca, Bing Yao, Helen M. Genova & Glenn R. Wylie. 2022. Signal Detection Theory as a Novel Tool to Understand Cognitive Fatigue in Individuals With Multiple Sclerosis. Frontiers in Behavioral Neuroscience 16 (June): 828566. doi:10.3389/fnbeh.2022.828566.
Sarraf, Niloufar. 2019. Mapping the Neural Activities and Affective Dimensions of the ISP Model: Correlates in the Search Exploration, Formulation, and Collection Stages. PhD, Queensland University of Technology. doi:10.5204/thesis.eprints.127009.
Scharinger, Christian, Yvonne Kammerer & Peter Gerjets. 2015. Pupil Dilation and EEG Alpha Frequency Band Power Reveal Load on Executive Functions for Link-Selection Processes during Text Reading. Ed.: Antonio Verdejo-García. PLOS ONE 10 (6): e0130608. doi:10.1371/journal.pone.0130608.
Schoot, Rens van de & Milica Miočević. 2020. Small sample size solutions: a guide for applied researchers and practitioners. Abingdon, Oxon; New York, NY: Routledge, an imprint of the Taylor & Francis Group, an informa business.
Segal, Dorit. 2023. Sustained Attention Plays a Critical Role in Reading Comprehension of Adults with and without ADHD. Learning and Individual Differences 105 (September). JAI: 102300. doi:10.1016/j.lindif.2023.102300.
Shovon, Md. Hedayetul Islam, D (Nanda) Nandagopal, Jia Tina Du, Ramasamy Vijayalakshmi & Bernadine Cocks. 2015. Cognitive Activity during Web Search. In.: Proceedings of the 38th International ACM SIGIR Conference on Research and Development in Information Retrieval, 967–70. Santiago Chile: ACM. doi:10.1145/2766462.2767784.
Sohlberg, McKay Moore & Catherine A. Mateer. 1987. Effectiveness of an Attention-Training Program. Journal of Clinical and Experimental Neuropsychology 9 (2): 117–30. doi: 10.1080/01688638708405352.
Sridhar, Sruthi, Abdulrahman Khamaj & Manish Kumar Asthana. 2023. Cognitive Neuroscience Perspective on Memory: Overview and Summary. Frontiers in Human Neuroscience 17. Frontiers Media SA. doi:10.3389/fnhum.2023.1217093.
Thomson, David R., Derek Besner & Daniel Smilek. 2015. A Resource-Control Account of Sustained Attention: Evidence from Mind-Wandering and Vigilance Paradigms. Perspectives on Psychological Science 10 (1). SAGE Publications Inc: 82–96. doi: 10.1177/1745691614556681.
Ülgen, Zehra, Christina Schmiedt-Fehr, Çağdaş Güdücü & Canan Basar-Eroglu. 2024. Event-Related Theta Oscillations During Sustained Attention. SSRN Scholarly Paper. Rochester, NY. doi:10.2139/ssrn.4753497.
Verghese, Preeti. 2001. Visual Search and Attention. Neuron 31 (4): 523–35. doi: 10.1016/S0896-6273(01)00392-0.
Wacholder, Nina. 2011. Interactive Query Formulation. Annual Review of Information Science and Technology 45 (1): 157–96. doi:10.1002/aris.2011.1440450111.
Wei, Jinwen, Zhiguo Zhang, Ziqing Yao, Dong Ming & Peng Zhou. 2021. Modulation of Sustained Attention by Theta-tACS over the Lateral and Medial Frontal Cortices. Neural Plasticity 2021 (August). Hindawi: e5573471. doi:10.1155/2021/5573471.
Welhaf, Matthew S. & Michael J. Kane. 2024. A Combined Experimental-Correlational Approach to the Construct Validity of Performance-Based and Self-Report-Based Measures of Sustained Attention. Attention, Perception & Psychophysics 86 (1): 109–45. doi: 10.3758/s13414-023-02786-2.
Wu, Dan & Shutian Zhang. 2022. Does visual attention help? Towards better understanding and predicting users’ good abandonment behavior in mobile search. Library Hi Tech ahead-of-print (ahead-of-print). doi: 10.1108/LHT-01-2022-0076.
Wu, Jiun-Yu & Chen Xie. 2018. Using Time Pressure and Note-Taking to Prevent Digital Distraction Behavior and Enhance Online Search Performance: Perspectives from the Load Theory of Attention and Cognitive Control. Computers in Human Behavior 88 (February): 244–54. doi:10.1016/j.chb.2018.07.008.
Yang, Yidong, Lei Mo, Guillaume Lio, Yulong Huang, Thomas Perret, Angela Sirigu & Jean-René Duhamel. 2023. Assessing the Allocation of Attention during Visual Search Using Digit-Tracking, a Calibration-Free Alternative to Eye Tracking. Scientific Reports 13 (1). Nature Publishing Group: 2376. doi: 10.1038/s41598-023-29133-7.
Zhao, Guozhen, Yulin Zhang & Yan Ge. 2018. Frontal EEG Asymmetry and Middle Line Power Difference in Discrete Emotions. Frontiers in Behavioral Neuroscience 12 (February): 225. doi:10.3389/fnbeh.2018.00225.
Zheng, Yukun, Jiaxin Mao, Yiqun Liu, Mark Sanderson, Min Zhang & Shaoping Ma. 2020. «Investigating Examination Behavior in Mobile Search. In,: Proceedings of the 13th International Conference on Web Search and Data Mining, 771–79. WSDM ’20. New York, NY, USA: Association for Computing Machinery. doi:10.1145/3336191.3371797.
Zielinska, Olga Anna. 2017. Examining the Attentional and Behavioral Factors Associated with Escalation in Web Health Searches. http://www.lib.ncsu.edu/resolver/1840.20/34759.
Zivan, Michal, Sasson Vaknin, iNmrod Peleg, Rakefet Ackerman & Tzipi Horowitz-Kraus. 2023. «Higher theta-beta ratio during screen-based vs. printed paper is related to lower attention in children: An EEG study. PLOS ONE 18 (5): e0283863. doi: 10.1371/journal.pone.0283863

  • Receive Date 16 June 2024
  • Revise Date 29 July 2024
  • Accept Date 30 September 2024