Kancharla K, Kanagaraj S, Gopal C. N. R. Neuropsychological Evaluation of Cognitive Failure and Excessive Smart Phone Use: A Path Model Analysis. Biomed Pharmacol J 2022;15(4).
Manuscript received on :13-04-2022
Manuscript accepted on :13-10-2022
Published online on: 17-11-2022
Plagiarism Check: Yes
Reviewed by: Dr. B. KIrthika
Second Review by: Dr. Ana Golez
Final Approval by: Dr. Ian James Martin

How to Cite    |   Publication History
Views Views: (Visited 1,518 times, 2 visits today)   Downloads PDF Downloads: 331

Kinjari Kancharla*, Sagayaraj Kanagaraj and C. N. Ram Gopal*

 Faculty of Allied Health Sciences, Chettinad Hospital and Research Institute, Chettinad Academy of Research and Education, Kelambakkam - 603 103, Tamil Nadu, India.

Corresponding Author E-mail: kinjarik@gmail.com

DOI : https://dx.doi.org/10.13005/bpj/2555

Abstract

Smartphones and other mobile-related technologies are commonly viewed as indispensable tools for enhancing human cognition; prolonged use of these devices may have a detrimental and long-term effect on users’ abilities to think, recall, and pay attention. The purpose of this study is to determine the effect of phone usage on people’s cognitive capacities. Excessive smartphone use may have a detrimental effect on an individual’s mental health. It has the ability to affect an individual’s memory, capacity for effective thought, and cognitive and learning capacities. The purpose of this study is to determine the effect of smartphone use on people’s cognitive abilities. Excessive smartphone use and cognitive failures were measured using the Smartphone Addiction Scale (Kwon et al., 2013) and the Cognitive Failures Questionnaire (Broadbent et al., 1982; revised by Wallace et al., 2002), which were used to collect data from 200 young adults using a purposive sampling strategy. Pearson’s product-moment correlation was used to measure the strength of the relationship between the variables, and regression analysis was used to measure the function relating to the variables. The results of the study conclude that excessive smartphone use is related to forgetfulness, distractibility, and false triggering. Hence, it can be concluded that excessive use of smartphones may be prone to cognitive failures such as forgetfulness, distractibility, and false triggering. Excessive smartphone use has been linked to a higher risk of cognitive impairment.

Keywords

Cognitive Failure; Memory; Smartphone Use; Young Adults

Download this article as: 
Copy the following to cite this article:

Kancharla K, Kanagaraj S, Gopal C. N. R. Neuropsychological Evaluation of Cognitive Failure and Excessive Smart Phone Use: A Path Model Analysis. Biomed Pharmacol J 2022;15(4).

Copy the following to cite this URL:

Kancharla K, Kanagaraj S, Gopal C. N. R. Neuropsychological Evaluation of Cognitive Failure and Excessive Smart Phone Use: A Path Model Analysis. Biomed Pharmacol J 2022;15(4). Available from: https://bit.ly/3ObY1qb

Introduction

The phone has grown from a device used solely for communication–calls–to a computer-replacement device capable of online surfing, gaming, instant communication via social media platforms, and work-related productivity applications. Within the last decade, the Western world has witnessed a remarkable expansion in the use of mobile technologies. While smartphones have become a more integrated part of everyday life, they have also become more capable of enhancing, if not entirely replacing, critical cognitive processes. With the ability to act as a telephone directory, appointment scheduler, tip calculator, navigator, and gaming device, smartphones appear capable of doing an unlimited number of cognitive activities and satisfying a significant number of our affective demands on our behalf.1 While smartphones clearly keep us connected, many people have developed an unhealthy obsession with them.

Smartphones have a tendency to immediately capture the attention of those engaged in an activity that is unrelated to the smartphone.2-4 A three-second distraction such as reaching for a cell phone is sufficient to divert attention away from a cognitive task5, and it has been demonstrated that the mere possession of a smartphone has a detrimental effect on working memory capacity, fluid intelligence, and attentional processes.4-6 Additionally, compulsive use of these devices can cause disruptions in the workplace, school, and personal relationships when individuals spend more time on social media or gaming than on actual human interaction. Also, a recent study reveals that psychological dependence on a mobile phone diminishes the effect of smartphone presence on cognitive function.4

Cognitive failures are considered a normal occurrence in everyday life and typically manifest as lapses in attention. Exogenous variables, such as distracting stimuli, or endogenous processes, such as ruminations or daydreaming, may contribute to these attentional deficiencies.7 This distraction is detrimental to following cognitive tasks, resulting in increased errors as the distraction interval lengthens, which is especially noticeable in the classroom where students who use their phones in class take less notes8 and perform poorly academically.9-10 Students at college are likely to suffer unfavorable repercussions as a result of these exogenous disruptions.11-14 Indeed, recent research indicates that smartphone use during class and study time is distracting and reduces information retention.

Similarly, the sound of a notification from the smartphone or even the mere existence of a smartphone can impair a college student’s ability to concentrate on a lecture, and both the ringing of a cell phone during class and the mere presence of a smartphone, negatively affect college students’ performance.10-12,15 While smartphones and other mobile technologies have the potential to alter a wide variety of cognitive areas, empirical research on the cognitive effects of smartphone technology is currently fairly limited. This is acceptable, given that technology is still continually evolving. As a result, it is critical to understand how smartphones impact us in order to take the required precautions to avoid harmful outcomes.1 The aim of the present study is to investigate the correlation between smartphone use and different dimensions of cognitive failure in daily life among young adults.

Materials and methods

Hypotheses: Based on the review of the literature, the following alternative research hypotheses were formed:

H1  There will be a significant relationship between smartphone use and forgetfulness.

H2 There will be a significant relationship between smartphone use and distractibility.

H3 There will be a significant relationship between smartphone use and false triggering.

Sample Description

An ex-post facto survey research design was used, where the researchers examined the operation of variables without manipulating them to assess the relationship between smartphone use and cognitive failure variables in young adults. A total of 200 young adult students from Chennai, India, were included in the study out of which 99 are male and 101 are female. The average was 22.54± 2.75 years. A purposive sampling technique was used in the study where participants between the ages of 18 and 35 were included, and participants above age 35 were excluded. Similarly, participants diagnosed with severe cognitive impairment and other psychiatric disorders were excluded.

Tools Used

The Smartphone Addiction Scale by Kwon et al., 2013 is a 33-item self-report measure of problematic smartphone use habits.17 The measure has a six-point Likert scale response format, with a maximum total score of 198. Responses range from “1” (strongly disagree) to “6” (strongly agree). In the initial validation research, the measure revealed a relatively good level of internal consistency (Cronbach’s alpha = 0.967). A high score implies increased smartphone use and is associated with a greater risk of smartphone addiction.

The Cognitive Failures Questionnaire by Broadbent et al., 1982,17 focuses on cognitive failures in daily life and was developed to examine cognitive failures in three critical areas: perception, memory, and motor performance. Later, researchers recognized that the CFQ has multiple additional elements, with Wallace and his colleagues presenting a four-factor solution.18 They discovered four factors: Memory, Distractibility, Blunders, and: Names. Later, Rast and his colleagues did a study and found that CFQ has three factors: Forgetfulness, Distractibility, and False Triggering.19 Subscale scores representing these aspects are obtained by adding the scores from all relevant items. The simplest way to score the scale is to add up the ratings of the 25 separate items, providing a score between 0 and 100.

Procedure

Online and offline versions of the Smartphone Addiction Scale and Cognitive Failure Questionnaire were accessible to the participants, and the participants chose whether to fill out the questionnaire online or not based on their comfort and desires. Before the questionnaire was distributed, participants signed an informed consent form, and only after consent was obtained the Smartphone Addiction Scale and Cognitive Failure Questionnaire were distributed for data collection. The participants were informed that “There is no correct or incorrect response. Kindly circle/click the values between 1 and 7 that most accurately reflects your memory assessment. Consider your options carefully and strive to be truthful. Your responses will be kept private. Kindly respond to all questions.”

Additionally, participants were informed of their choice to withdraw and guaranteed that the information gathered would be kept confidential and utilized for research purposes only. 140 individuals completed the Smartphone Addiction Scale and Cognitive Failure Questionnaire, and 60 completed the data via the Smartphone Addiction Scale and Cognitive Failure Questionnaire’s online form.

Data Analysis

Following data collection, it was analyzed using SPSS 20.0 (Statistical Package for the Social Sciences). Descriptive statistics and Pearson’s product-moment correlation were utilized to determine the strength of the association between the variables. Also, regression analysis was used to measure the function relating to the variables.

Results and discussions

Table 1: Demographic details of the participants

Variables n = 200 Percentage %
Gender
Male 99 49
Female 101 51
Age
18 15 6
19 35 15
20 28 12
21 45 20
22 32 14
23 18 8
24 25 11
27 32 14

Table 2: Smartphone usage levels among young adults (n=200)

Smartphone usage levels n Percentage %
High 110 55%
Normal 90 45%

Smartphone usage levels are observed among young adults as the increased amount of smartphone use is associated with a greater risk of smartphone addiction. From the results, we can see that 55% of young adults’ smartphone usage is at a normal level, and about 45% of young adults’ smartphone usage is at a high level.

Table 3: Characteristics of Cognitive Failure among young adults (n=200).

Cognitive Failure Dimensions Mean Std. Deviation Std. Error Mean
Forgetfulness 14.60 3.49 0.20
Distractibility 17.92 3.13 0.18
False Triggering 15.04 3.27 0.18

Several dimensions of cognitive failure, such as forgetfulness, distractibility, and false triggering, are observed in young adults. The mean and standard deviation of forgetfulness is 14.60 ± 3.49, distractibility is 17.92 ± 3.13, and false triggering is 15.04 ± 3.27, as shown in Table 3.

Table 4: Cognitive Failure dimension scores based on Smartphone Usage levels (n=200).

Cognitive Failure Domains Smartphone Usage Levels n Mean Std. Deviation Std. Error Mean
Forgetfulness High 110 14.82 3.71 0.29
Normal 90 14.35 3.22 0.27
Distractibility High 110 18.13 3.10 0.24
Normal 90 17.68 3.16 0.27
False Triggering High 110 15.07 3.32 0.26
Normal 90 15.01 3.23 0.27

According to Table 4, the most frequent cognitive failure at a high level of smartphone usage was distractibility (18.13 ± 3.10), followed by false triggering (15.07 ± 3.32) and forgetfulness (14.82 ± 3.71). Similarly, it was discovered that the most frequent cognitive failure at a normal level of smartphone usage was distractibility (17.68 ± 3.10), followed by false triggering (15.01 ± 3.23) and forgetfulness (14.35 ± 3.22).

Vol19No4_Neu_Kinj_fig1 Figure 1: Cognitive Failure dimension scores with error bar based on Smartphone Usage levels

Click here to view figure 

Figure 1. represents the participants’ dimension-specific responses and the overall mean score of cognitive failure. Error bars convey a broad sense of how precise a measurement is or how far the reported value may be from the true or error-free value.

Table 5: Correlates of smartphone use and cognitive failure (n=200).

Variables Forgetfulness Distractibility False Triggering Smartphone Usage
Forgetfulness 1
Distractibility 0.104 1
False Triggering 0.164* -0.451** 1
Smartphone Usage 0.354* 0.427** 0.317* 1

**. Correlation is significant at the 0.01 level (2-tailed).

*. Correlation is significant at the 0.05 level (2-tailed).

Preliminary results revealed that there is a significant moderate relationship between smartphone usage and dimensions of cognitive failure (forgetfulness, distractibility, and false triggering). This indicates that forgetfulness, distractibility, and false triggering increase as smartphone usage increases. Similarly, there is a significant relationship between dimensions of cognitive failure as well. There is a significant weak relationship between false triggering and forgetfulness. In other words, when false triggering occurs, the individual tends to forget what they were remembering or were trying to recall. Similarly, there is a significantly moderate negative relationship between false triggering and distractibility. This indicates that when false triggering occurs, distractibility is reduced among individuals (Table 5). Hence, we can conclude that H1 (There will be a significant relationship between smartphone usage and forgetfulness), H2 (There will be a significant relationship between smartphone usage and distractibility), and H3 (There will be a significant relationship between smartphone usage and false triggering) are accepted.

Vol19No4_Neu_Kinj_fig2 Figure 2: Path Model of Excessive Smartphone usage leading to Cognitive failures among young adults.

Click here to view figure 

Note: Excessive Smartphone Usage: Assessed by Smartphone Addiction Scale by Kwon et al., 2013. Cognitive Failures: Assessed by Cognitive Failures Questionnaire by Broadbent et al., 1982

Figure 2 depicts the path analysis model and the significant correlation between Excessive Smartphone Use and Cognitive Failures in domains such as forgetfulness, distractibility, and False triggering.

While previous studies show that cell phone addiction is related to negative emotional effects, very intermittent study has looked into the relationships between mobile phone use and cognitive outcomes related to daily cognitive functioning. The prevalence of smartphones nowadays is a topic of discussion for healthcare practitioners, mental health professionals, educators, parents, and anyone who regularly uses a smartphone. A recent study reveals that smartphone use has an effect on the brain, while the long-term ramifications are unknown.20 Many people check their phones when they wake up, use them on the way to work, and keep an eye on them at all times while at work. Many people’s last sight before falling asleep is a phone screen. These habits have become so engrained in people’s lives that they rarely take a step back to assess the effects on their bodies and brains.21

Interaction with technology typically requires mental shifts from one context to another. Phones make individuals always available for contact and information from various aspects of life. Work-related emails, personal instant chats, social media posts, news, and entertainment are all mingled and intertwined in a never-ending stream of beeps, pings, and flashing notification symbols.22 People have evolved in various ways during the last decade to deal with this onslaught of information. The most noticeable feature is media multitasking, which involves continually juggling media and non-media tasks while often utilizing numerous digital devices linked to various internet sites.23

Diffusion MRI was employed in a recent study to examine white matter structural connectivity, and it revealed a link between activity in the right amygdala and excessive smartphone use in adolescents.24 Several reviews have been published in recent years that have evaluated the impact of whether excessive smartphone use may be considered a kind of behavioral addiction.25 Studies have also investigated whether there are any distinctions between excessive smartphone use and Internet use disorder and additional research is underway.26 A number of recent research have found that excessive smartphone use is related to mental health concerns and a reduction in psychological well-being. There is persistent evidence of a link between excessive smartphone use and other mental diseases, such as depression, anxiety, OCD, and ADHD, in a manner similar to the link between Internet addiction and other psychiatric disorders.27

Our study was supported by previous studies indicating the possible influence of smartphone use which might have a high risk of causing cognitive failures. Though the overall correlation between smartphone use and cognitive failure domains has a significant relationship, the linear regression also predicted that smartphone use might cause cognitive failures. This study will have its uniqueness in the research area on cognitive psychology, digital well-being, and additive behaviors towards technology.

The study’s findings can serve as a guide and source of evidence for developing and implementing pertinent intervention strategies aimed at reducing cognitive failure issues and excessive smartphone use, which have a detrimental effect on mental health and cognitive performance, thereby alleviating the burden on family caregivers, the healthcare system, and society as a whole. However, the number of participants analyzed in this study was adequate for the problem we investigated, considering this as pilot work. However, future studies should focus on larger participants with various geographical locations, ages, gender, and working style that might influence the predictors and relationships between the variables.

Conclusion

This study establishes a link between excessive smartphone use and forgetfulness, distractibility, and false triggering. According to this study, need-based smartphone use may be causing cognitive failure in young individuals, including forgetfulness, distractibility, and false triggering. Excessive smartphone use has been linked to a higher risk of cognitive impairment.

Acknowledgment

The First author wishes to thank and acknowledge Prof. Dr. O. T. Sabari Sridhar, Head-Department of Psychiatry, Sri Ramachandra Institute of Higher Education and Research, for their insightful comments and assistance throughout the work. She also wishes to express her gratitude to the study’s participants for their unwavering support and cooperation throughout the course of the study. This work was carried out as a part of the Ph.D. research by the first author; hence she is highly thankful to the Chettinad Academy of Research and Education for the Junior Research Fellowship.

Conflict of Interest

There is no conflict of interest.

Funding Sources

The research was funded by Chettinad Academy of Research and Education, Junior Research Fellowship (CARE – JRF) with grant number 083/CARE/AR (Research@-Ph.D.-Program)/2020-01.

References

  1. Wilmer HH, Sherman LE, Chein JM. Smartphones and Cognition: A Review of Research Exploring the Links between Mobile Technology Habits and Cognitive Functioning. Front Psychol. 2017 Apr 25;8:605–605.
    CrossRef
  2. Clapp WC, Rubens MT, Gazzaley A. Mechanisms of working memory disruption by external interference. Cereb Cortex. 2010 Apr;20(4):859–72.
    CrossRef
  3. Clapp WC, Gazzaley A. Distinct mechanisms for the impact of distraction and interruption on working memory in aging. Neurobiol Aging. 2012 Jan;33(1):134–48.
    CrossRef
  4. Ward AF, Duke K, Gneezy A, Bos MW. Brain Drain: The Mere Presence of One s Own Smartphone Reduces Available Cognitive Capacity. Journal of the Association for Consumer Research. 2017;2:140–54.
    CrossRef
  5. Altmann EM, Trafton JG, Hambrick DZ. Momentary interruptions can derail the train of thought. J Exp Psychol Gen. 2014 Feb;143(1):215–26.
    CrossRef
  6. Thornton B, Faires A, Robbins M, Rollins E. The Mere Presence of a Cell Phone May be Distracting. Social Psychology. 2014;45:479–88.
    CrossRef
  7. Unsworth N, McMillan BD, Brewer GA, Spillers GJ. Everyday attention failures: an individual differences investigation. J Exp Psychol Learn Mem Cogn. 2012 Nov;38(6):1765–72.
    CrossRef
  8. Kuznekoff JH, Titsworth S. The Impact of Mobile Phone Use  on Student Learning. null. 2013 Jul 1;62(3):233–52.
    CrossRef
  9. Froese AD, Carpenter CN, Inman DA, Schooley J, Barnes RB, Brecht PW, et al. Effects of Classroom Cell Phone Use on Expected and Actual Learning. College student journal. 2012;46:323–32.
  10. Mendoza JS, Pody BC, Lee S, Kim M, McDonough IM. The effect of cellphones on attention and learning: The influences of time, distraction, and nomophobia. Comput Hum Behav. 2018;86:52–60.
    CrossRef
  11. Bjornsen CA, Archer KJ. Relations between college students’ cell phone use during class and grades. Scholarship of Teaching and Learning in Psychology. 2015;1(4):326–36.
    CrossRef
  12. Junco R, Cotten SR. No A 4 U: The relationship between multitasking and academic performance. Computers & Education. 2012;59(2):505–14.
    CrossRef
  13. Yildirim C, Sumuer E, Adnan M, Yildirim S. A growing fear: Prevalence of nomophobia among Turkish college students. Information Development. 2016 Nov 1;32(5):1322–31.
    CrossRef
  14. Yildirim C, Correia A. Exploring the dimensions of nomophobia: Development and validation of a self-reported questionnaire. Comput Hum Behav. 2015;49:130–7.
    CrossRef
  15. End CM, Worthman S, Mathews MB, Wetterau K. Costly cell phones: The impact of cell phone rings on academic performance. Teaching of Psychology. 2010;37(1):55–7.
    CrossRef
  16. Kwon M, Lee J-Y, Won W-Y, Park J-W, Min J-A, Hahn C, et al. Development and Validation of a Smartphone Addiction Scale (SAS). PLOS ONE. 2013 Feb 27;8(2):e56936.
    CrossRef
  17. Broadbent DE, Cooper PF, FitzGerald P, Parkes KR. The Cognitive Failures Questionnaire (CFQ) and its correlates. Br J Clin Psychol. 1982 Feb;21(1):1–16.
    CrossRef
  18. Wallace JC, Kass SJ, Stanny CJ. The Cognitive Failures Questionnaire Revisited: Dimensions and Correlates. null. 2002 Jul 1;129(3):238–56.
    CrossRef
  19. Rast P, Zimprich D, Van Boxtel M, Jolles J. Factor structure and measurement invariance of the cognitive failures questionnaire across the adult life span. Assessment. 2008;16(2):145–158.
    CrossRef
  20. Hong W, Liu R, Ding Y, Sheng X, Zhen R. Mobile phone addiction and cognitive failures in daily life: The mediating roles of sleep duration and quality and the moderating role of trait self-regulation. Addictive behaviors. 2020;107:106383.
    CrossRef
  21. Duke É, Montag C. Smartphone addiction, daily interruptions and self-reported productivity. Addictive Behaviors Reports. 2017;6: 90–95.
    CrossRef
  22. van Velthoven MH, Powell J, Powell G. Problematic smartphone use: Digital approaches to an emerging public health problem. Digital Health. 2018.
    CrossRef
  23. Popławska A, Szumowska E, Kuś J. Why Do We Need Media Multitasking? A Self-Regulatory Perspective. Front Psychol. 2021;12:624649.
    CrossRef
  24. Tymofiyeva O, Yuan JP, Kidambi R, Huang CY, Henje E, Rubinstein ML, Jariwala N, Max JE, Yang TT, Xu D. Neural Correlates of Smartphone Dependence in Adolescents. Front Hum Neurosci. 2020 Oct 7;14:564629.
    CrossRef
  25. Panova T, Carbonell X. Is smartphone addiction really an addiction? J Behav Addict. 2018 Jun 1;7(2):252-259.
    CrossRef
  26. Montag C, Wegmann E, Sariyska R, Demetrovics Z, Brand M. How to overcome taxonomical problems in the study of Internet use disorders and what to do with “smartphone addiction”? J Behav Addict. 2021 Jan 15;9(4):908-914.
    CrossRef
  27. Weinstein A, Feder K, Rosenberg K, Dannon P. Internet addiction-criteria evidence and treatment. Behavioral Addictions: Criteria, Evidence and Treatment. 2014;99–117.
    CrossRef
Share Button
(Visited 1,518 times, 2 visits today)

Creative Commons License
This work is licensed under a Creative Commons Attribution 4.0 International License.