The effect of screen time on auditory processing and working memory skills in tweens (pre-adolescents)

Abstract

Background

This study investigates the impact of screen time on auditory processing and working memory in tweens, considering the subtle relationship proposed by the Goldilocks Hypothesis. The research aims to contribute insights into the potential effects of different screen exposure levels on auditory processing and working memory skills, recognizing the prevalence of screen use among tweens.

Method

Fifty-seven tweens were randomly selected and categorized into three groups based on their daily screen exposure. Auditory processing and working memory were assessed by measuring temporal resolution, auditory closure, binaural integration, and digit span tasks. Comprehensive screenings for hearing, speech, language, and IQ skills were conducted, ensuring the inclusion of tweens with normal hearing and cognitive functions.

Results

The study results revealed a non-linear relationship between screen time and auditory processing. Tweens with moderate screen exposure exhibited superior auditory processing skills, while high screen time was associated with deficits in temporal resolution, speech perception, binaural integration, and working memory. The Goldilocks Hypothesis was supported, indicating that too much screen time may have negative consequences, while too little exposure may not exploit the potential benefits of digital media usage. The findings emphasize the importance of moderation in screen time for optimal auditory processing and working memory in tweens. Prolonged screen exposure, especially beyond three hours daily, negatively affected auditory processing and working memory abilities.

Conclusion

The study highlights the need for a balanced approach to screen time, aligning with the broader literature on child development.

Introduction

Screen usage has become an inevitable part of childhood and adolescence. Screen time in tweens (pre-adolescents) doubled after the COVID-19 pandemic [1]. Despite several guidelines on limiting screen time [2, 3–4], there appears to be no significant reduction. While moderate time spent on screen is associated with both positive [5] and adverse outcomes [6], excessive screen time adversely affects physical and mental health, leading to sleep disturbances, processing disorders, and emotional and psychosocial problems [7, 8, 9–10]. The effect of moderate and high screen time on auditory processing and working memory is a less investigated area. Understanding such impact is crucial as these processes play critical roles in cognitive development during the tween years. Considering the integration of technology in education, it is vital to comprehend how screen time may affect auditory processing and focus in the learning environment. Additionally, investigating the educational implications helps optimize teaching strategies and curriculum design for pre-adolescents.

Two contradicting views explain the association between screen time and children’s physical and mental health. Sanders et al. [6] termed one a less-is-better hypothesis, which states a negative linear association between screen time and children’s physical health, health-related quality of life, socio-emotional outcomes, and school achievements. Second, the Goldilocks hypothesis [11] states a curvilinear association between screen time and children’s health and well-being. They found that a moderate amount of electronic screen time was associated with higher mental well-being of children, compared to low and high levels. In the present study, we tested these two hypotheses in the context of auditory processing and working memory.

Recently, tweens have used screens for various academic and leisure activities. Screen-based activities requiring a high cognitive load may reduce cognitive resources [12]. Tweens are also susceptible to sleep disruption due to excessive screen time, mainly if they use screens late at night [13]. Several researchers have established a causal relationship between sleep disturbances and auditory processing disorders [14, 15]. Overemphasis on digital communication may limit opportunities for face-to-face interactions and real-world language experiences [16]. Screen-based content for tweens, such as fast-paced video games or multimedia presentations, can also be visually and auditory stimulating [17]. Thus, screen time involves passive content consumption, limiting the brain's opportunities to adapt and rewire neural pathways related to auditory processing [18]. Hence, excessive reliance on screens may limit the brain's ability to integrate and process sensory information effectively [19], potentially affecting auditory processing.

Despite such close connections, researchers rarely investigated the association between screen time and auditory processing and working memory in tweens. In light of such a possible relationship, the present study poses two research questions: "Does screen time influence working memory and auditory processing skills in tweens?" and "How does the duration of screen time influence working memory and auditory processing skills in tweens?".

Auditory Processing Disorder (APD) is a neurological condition that affects the brain’s ability to process and interpret auditory information. It is characterized by poor auditory discrimination, pattern perception, sound localization-lateralization, temporal processing, and performance in competing and degraded signals [20]. Auditory processing and working memory represent foundational aspects of cognitive functioning, making them valuable indicators of the potential cognitive impact of screen time exposure.

India has the second-highest mobile phone usage in the world. A 2022 McAfee® connected family study of India [21] stated that 83% of children in India in the age range of 10-14 years are mobile phone users, which is 7% above the global average. This reflects the ubiquity of screen exposure among tweens in the country. This implies that screen exposure is common and occurs at an early age, making it challenging to find tweens without screen exposure. We measured the effect of low, moderate, and high screen time on tweens' auditory processing and working memory. The classification of low, moderate, and high is based on the WHO guidelines on limiting screen time in children [4].

Method

Subjects

Fifty-seven tweens in the age range from 9 to 12 years from three different schools volunteered for the study. All tweens belonged to a similar socioeconomic and cultural background. We used the Questionnaire for Screen Time of Adolescents (QueST) (Appendix 1) [22] to measure their daily screen exposure. The respondents included the tweens, their parents, and other family members. The measurement was based on the time each tween spent on a typical day on five parameters: studying, class-related activities, watching videos, playing video games, and using social media/chat applications. Details were collected for various situations under each parameter, and the total time spent on screens was calculated by summing the screen time for each parameter. The average screen time per day was determined by averaging the responses of the respondents over five typical weekdays (Monday to Friday) and two weekends (Saturday and Sunday). We only selected tweens exposed to screens for more than two years. Based on the QueST results, we categorized them into three groups. Group 1 tweens were exposed to more than three hours (180 min) of average daily screen time (high screen exposure). Group 2 consisted of those with one to two hours (60–120 min) of average daily screen time exposure (moderate screen exposure), while Group 3 had less than 0.5 h (30 min) of daily average screen time exposure (low screen exposure). We included only children who met the following criteria:

• Normal hearing sensitivity on pure tone audiometry (PTA ≤ 15 dBHL).

• Speech recognition thresholds (SRT) within ± 6 dB of PTA and speech identification scores (SIS) greater than 90%.

• Normal middle ear status on immittance audiometry (bilateral A-type tympanogram) and presence of ipsilateral acoustic reflex for 500, 1000, and 2000 Hz at or below 100 dB HL.

• No indication of outer hair cell dysfunction on screening distortion product otoacoustic emissions measured for four frequencies in the range of 500-4000 Hz (F2/F1 = 1.22; L1/L2 = 65/55 dB; SNR ≥ 6 dB for three consecutive frequencies).

All selected tweens demonstrated normal speech and language skills and had an IQ greater than 90. However, those with a history of ear infection, ear discharge, continuous exposure to noise/chemicals, current medication for other medical conditions, or present or past complaints of tinnitus, vertigo, behavioral, psychological, or related problems, as well as previously exposed to the tests used in this study, were excluded from the beginning. Table 1 shows the detailed demographics of the tweens of three groups. We obtained written consent from all parents/caregivers, and they were informed about the test details, their significance, and the approximate time required to complete the testing procedure before conducting the tests. The study adhered to the institutional ethical guidelines to test human subjects.

Table 1. Demographic details, hearing thresholds, and QueST results of the subjects of three groups

	Group 1		Group 2		Group 3
Demographic Details
Number of Subjects	23		16		18
(Males+Females)	(15M+08F)		(10M+06F)		(12M+06F)
Mean age (in years)	9.48		9.12		9.72
SDa	0.88		1.07		0.43
Range	8-11		8-11		8-11
Hearing Thresholds	Right Ear	Left Ear	Right Ear	Left Ear	Right Ear	Left Ear
Mean PTAb (in dB HL)	11.68	11.84	11.01	11.87	11.38	11.11
SD	1.66	1.05	1.04	1.44	1.27	1.27
Range	7.5-15	10-13.75	10-12.5	10-15	10-12.5	10-13.75
Mean SRTc (in dB HL)	15.21	15.00	14.37	13.12	12.77	12.50
SD	2.37	3.01	1.70	2.50	2.55	2.57
Range	10-20	10-20	10-15	10-15	10-15	10-15
Mean SISd (in %)	96.52	94.78	96.56	96.56	97.22	96.66
SD	3.82	4.64	3.01	3.52	3.52	2.97
Range	90-100	90-100	90-100	90-100	90-100	90-100
Mean MCLe (in dB HL)	59	62	61	59	62	64
SD	5.32	5.87	4.71	6.83	5.63	6.37
Range	50-75	50-75	50-75	50-75	50-75	50-75
UCLf (in dB HL)	>100	>100	>100	>100	>100	>100
QueSTgResults
Mean Screentime Duration (in min.) per day	212		93		23
SD	19.81		25.13		4.09
Range	180-234		67-120		17-30

^aStandard Deviation; ^bPure Tone Average- Average hearing thresholds for 500, 1000, 2000, & 4000 Hz test frequencies; ^cSpeech Recognition Thresholds; ^dSpeech Identification Scores; ^eMost Comfortable Loudness level measured for speech stimuli; ^fUncomfortable Loudness Level measured for speech stimuli; ^gQuestioner for Screening Time of Adolescents

Test environment

We assessed auditory processing and working memory using a personal computer (HP Notebook core i7, equipped with an EVGA sound card) connected to Sennheiser HDA 201 headphones via an Mx141 adapter. The headphone output was calibrated using a B&K 4150 artificial ear and a B&K 2250 sound level meter. Testing was conducted in a quiet environment within each tween's home, with ambient noise levels consistently measuring below 30 dB SPL, as determined by the sound level meter. The stimuli were presented at 60 dB SPL [23]. It took around 2 h to test each tween.

Measurement of auditory processing

We measured temporal resolution, auditory closure, and binaural integration under auditory processing testing. These processes comprehensively represent all auditory processing abilities.

Temporal resolution

The Gap Detection Test (GDT) measured the ability to perceive temporal changes or interruptions in the auditory signal, representing temporal resolution [24]. The GDT was administered using a 750 ms Gaussian noise stimulus. Employing a 3-alternative forced choice (3-AFC) adaptive paradigm, two standard stimuli contained no gap, while the third variable stimulus had a gap at its temporal center. Gap durations in the variable stimuli ranged from 0.1 ms to 64 ms. Tweens were required to identify the variable stimuli. Matlab's Psychoacoustic toolbox estimated the gap detection threshold, which adapted a maximum likelihood procedure with 79.8% sensitivity [25]. Five practice trials preceded the actual testing.

Auditory closure

Speech perception in noise (SPIN) is a component of auditory closure [26]. SPIN was measured using two lists of twenty-five Kannada bisyllabic words [27], each presented at 0 dB signal-to-noise ratio (SNR). The noise comprised a 4-talker speech babble mixed with words, with a noise onset 100 ms before the word began and an offset 100 ms after the word ended. They were tasked with repeating the words, and scoring was based on the number of correctly repeated words. Five practice trials preceded the actual test.

Binaural integration

Binaural integration was tested using a Dichotic Consonant-Vowel (DCV) test. The test involved the presentation of six CVs (/pa/, /ta/, /ka/, /ba/, /da/, and /ga/) dichotically with a 0-msec lag using headphones. Each stimulus pair was randomly presented five times to ensure reliable results. Permutations and combinations of CVs led to 30 stimuli pairs. Tweens repeated the CV heard in both ears, in any order of presentation. The test was scored in terms of single and double correct scores. Practice trials were given before actual testing.

Measurement of working memory

Digit span procedures (forward and backward paradigm; FDS & BDS, respectively) were used to assess working memory. Tweens were presented with a sequence of digits, binaurally, through headphones. Sequences started relatively short (e.g., 1–2 digits) and progressively increased in length adaptively based on an 80% correct criterion. Each sequence was presented auditorily only, with a 3000 ms inter-sequence interval to allow participants to respond. In FDS, tweens verbally repeated the digit sequence in the same order, and in BDS, they repeated the digit sequences in reverse order. The Smriti Shravan software [28] measures the FDS and BDS threshold using logistic regression.

Results

The Shapiro-Wilk test indicated normally distributed data for each group across tests (p > 0.05). One-way ANOVA assessed the significance of differences across the groups. Between-group pairwise comparisons were conducted with Bonferroni's corrections. Pearson's correlation correlated the GDT, SPIN, and DCV data with FDS and BDS. The results are presented as follows:

GDT

Figure 1(a) illustrates the GDT values across the three groups. The normative of GDT for children aged 9-12 years is 2.68 ± 0.64 ms. [29]. GDT was lowest for tweens in group 2 (3.32 ± 0.70 for the right ear, 3.61 ± 0.68 for the left ear; values within the normative range) and highest for those in group 1 (4.68 ± 0.47 for the right ear, 4.90 ± 0.49 for the left ear), with lower GDT values indicating better performance. Eight children of group 1 (for right ear) and seven (for left ear) had scores of 2 SD higher than the mean scores of children of group 2. Table 2 shows the inferential statistics results. Pairwise comparisons revealed significant differences between Group 1 and Group 2; Group 2 and Group 3 for both ears. However, no significant differences were observed between Group 1 and Group 3 for the right and the left ears.

Fig. 1 [Images not available. See PDF.]

Bar graph representing Mean and SD of (a) gap detection thresholds (GDT) (b) speech perception in noise (SPIN) (c) Dichotic CV (DCV) and (d) Digit span scores for three distinct groups of tweens

Table 2. The inferential statistics results show the effect of the duration of screen exposure on auditory processing, and working memory

Process	Test	Ear	One Way ANOVA		Pairwise Comparison with Bonferroni’s Correction
			F-value	p-value	Group 1 vs 2			Group 1 vs 3			Group 2 vs 3
					M.D.	S.E.	p-value	M.D.	S.E.	p-value	M.D.	S.E.	p-value
Temporal Resolution	GDT	Right	22.982	<.001	1.357	0.204	<.001	.341	0.197	.265	1.016	0.215	<.001
		Left	20.645	<.001	1.295	0.205	<.001	.335	0.198	.285	.959	0.216	<.001
Auditory Closure	SPIN	Right	100.415	<.001	7.399	0.534	<.001	4.420	0.516	<.001	2.979	0.564	<.001
		Left	95.578	<.001	7.214	0.536	<.001	4.429	0.518	<.001	2.784	0.565	<.001
Binaural Integration	DCV	Right	38.187	<.001	5.638	0.647	<.001	2.714	0.626	<.001	2.923	0.683	<.001
		Left	18.680	<.001	3.369	0.583	<.001	.369	0.563	>.998	3.000	0.615	<.001
		Double correct	30.687	<.001	4.964	0.658	<.001	3.263	0.637	<.001	1.701	0.695	.053
Working Memory	FDS	Binaural	71.252	<.001	1.898	0.159	<.001	.699	0.154	<.001	1.198	0.168	<.001
	BDS	Binaural	55.044	<.001	1.480	0.141	<.001	.647	0.136	<.001	.833	0.149	<.001

SPIN

In this testing, the number of correctly identified words in the right and left ears was plotted as a function of the groups in Fig. 1(b). The normative of SPIN for children aged 9–12 years is 21.20 ± 2.08 for the right ear and 20.76 ± 2.44 for the left ear [30]. Scores were highest for Group 2 (21.31 ± 1.49 for the right ear, 20.56 ± 1.78 for the left ear; values within normative range) compared to Group 1 (13.91 ± 1.72 for the right ear, 13.34 ± 1.61 for the left ear) and 3 (18.33 ± 1.64 for the right ear, 17.77 ± 1.55 for the left ear). Higher SPIN scores indicate better performances. Group 3 subjects also outperformed those of Group 1. 18 children of Group 1 for SPIN-R scores, and 21 for SPIN-L showed scores of less than 2 SD of the mean SPIN scores of children of Group 2. Table 2 shows the inferential statistics results. SPIN scores exhibited significant differences between groups for both ears. Pairwise comparisons demonstrated significant differences between Group 1 and Group 2, Group 2 and Group 3, and Group 1 and Group 3 for both ears.

DCV

Figure 1(c) presents the single and double correct scores of subjects in the three groups. The normative of double correct scores in DCV for children aged 9–12 is 14.03 ± 6.32 [30]. Group 1 had the lowest double correct scores (11.34 ± 2.34), and Group 2 had the highest double correct scores scores (16.31 ± 2.21; values within the normative range). The results revealed that the right ear scores were significantly higher than the left ear scores for children of Group 1 (M.D. = 1.403, t = 5.127, p ≤ 0.001, Cohen’s D = 0.602), Group 2 (M.D. = 3.312, t = 10.600, p ≤ 0.001, Cohen’s D = 1.479), and Group 3 (M.D. = 3.388, t = 20.604, p ≤ 0.001, Cohen’s D = 1.934). These results indicate a clear right ear advantage in the dichotic perception. Fourteen children of group 1 had single correct-right scores of 2 SD less than the mean scores of children of group 2. Similarly, ten children for single correct-left and 11 children for double correct scores of 2 SD less than the mean scores of children of group 2. Higher scores indicate better performances. Table 2 shows the inferential statistics results. Significant right ear advantages were observed in each group's DCV responses for single correct scores. Pairwise comparisons indicated significant differences between Group 1, Group 2, and Group 1 and Group 3, but no significant difference between Group 2 and Group 3.

FDS and BDS

The FDS and BDS scores are depicted in Fig. 1(d) for subjects across all groups. The normative for children aged 9-12 is 6 ± 2 digits for FDS and 5 ± 2 digits for BDS [29]. The scores were highest for subjects of Group 2 and lowest for those of Group 1. The scores of Group 2 subjects were within the normative range. Higher FDS and BDS scores indicate better performances. Table 2 shows the inferential statistics results. Screen time had a significant impact on FDS and BDS scores. Pairwise comparisons revealed significant differences between Group 1 and Group 2, Group 2 and Group 3, and Group 1 and Group 3 for FDS and BDS.

Relation between auditory processing and working memory

Pearson's correlation between auditory processing and FDS and BDS (working memory) test scores was done. Results showed that GDT (GDT Right-p = −0.692, p < 0.01; GDT Left-p = −0.654, p < 0.01), SPIN (SPIN Right- p = 0.793, p < 0.01; SPIN Left- p = 0.733, p < 0.01), and DCV double correct scores (p = 0.591, p < 0.01) significantly correlated with FDS. Similalry, GDT (GDT Right-p = −0.667, p < 0.01; GDT Left-p = −0.677, p < 0.01), SPIN (SPIN Right- p = 0.774, p < 0.01; SPIN Left- p = 0.715, p < 0.01), and DCV doubl;e correct scores (p = 0.556, p < 0.01) significantly correlated with BDS.

The scatterplot in Fig. 2 presents auditory processing test scores on the x-axis and digit span scores on the y-axis. The trend line in the figure illustrates the relationship between these variables. The adjusted R-squared value in the figure represents the regression coefficient. The figure reveals a linear positive relationship between SPIN and FDS, as well as with BDS. This indicates that as working memory capacity increases, SPIN scores also increase. Conversely, GDT shows a negative linear relationship with FDS and BDS. The GDT scores decrease as FDS/BDS scores increase. DCV exhibits a positive but weak relationship with FDS and BDS.

Fig. 2 [Images not available. See PDF.]

The scatterplot shows the relationship between auditory processing test scores and FDS/BDS (working memory) scores

Discussion

The results showed that tweens with moderate screen time exposure had better auditory processing, specifically temporal resolution, auditory closure, binaural integration, and auditory working memory, than low and high-screen-time-exposed tweens. Their scores for all five tests were within the normative range. 20/23 children of high screentime exposed group fulfilled the ASHA diagnostic criterion of APD [31]. Although GDT scores showed a significant improvement from low to moderate and became poor from moderate to high screen time, there was no significant difference between low and high screen time exposed tweens. Temporal processing tasks involve less cognitive load than other auditory processes [32]. Screen activities that primarily require timing judgments (temporal processing) may not tax cognitive resources as heavily as tasks that require complex auditory closure and binaural integration.

DCV scores showed no difference between moderate to high screen time. Although scores were less for high screen time exposed tweens, it was not statistically significant. Individuals engaged in screen-based activities may naturally focus on distinguishing and processing the auditory stimuli presented to each ear. Further, screen-based activities that involve gaming, virtual reality, or immersive audio experiences often require strong binaural listening skills. Engaging in such activities may improve binaural processing abilities and, consequently, better performance on dichotic perception tasks. We also found a weak relationship between DCV and FDS/BDS. As DCV is attention controlled, FDS/BDS are memory-related, and both are different cognitive processes, the relationship may be weak. Eissa et al. [33] reported abnormalities in Speech-in-Noise Perception, Dichotic Digits, Memory (specifically memory for sequences), and Auditory Vigilance in children who use mobile phones. They found a significant negative correlation between the duration of daily mobile phone use and the scores on central auditory processing tests. In another study, Hazzaa et al. [34] reported that video gaming negatively affects central auditory processing (CAP) abilities in children, particularly impacting auditory attention and memory.

Overall, we found a non-linear relationship between screen time and auditory processing, and these results support the Goldilocks Hypothesis [11]. The Goldilocks Hypothesis introduces a compelling perspective on the association between screen time and children's health and well-being. This hypothesis asserts a curvilinear relationship, suggesting that the impact of screen time is not a straightforward linear trajectory but follows a nuanced pattern. The fundamental proposition is that an optimal or moderate amount of screen time exists that aligns with the best outcomes for children's health and well-being. This concept is often illustrated as an inverted U-shaped curve, implying that too little and too much screen time may be associated with negative consequences. At the same time, a balanced or "just right" amount could yield positive effects.

The results, however, must be interpreted with caution as we had no baseline data, i.e., before screen exposure data on these tests, to comment on whether the between-group difference is only because of the screen time. This may be a potential limitation of the present study. The study design is cross-sectional, where we collected the data at a single point, and baseline data collection is not a part of the research design. Our primary objective was to assess the effect of low, moderate, and high screen time. We assumed that all tweens before screen exposure must be within normal limits, as we randomly selected the tween, and none reported any history of relevant difficulty. It is not easy to test the children before screen exposure, as most children start using screens from early childhood, and testing auditory processing at that stage is impossible. Meena et al. [35] found that the prevalence and practice of exposure to screen-based media in children aged 15-18 months is 99.7% in India. Thus, we are practically left out with no child having ‘0’ screen exposure.

Our study aligns with most others in finding that high screen time (> 3 h) is negatively associated with auditory processing. Although we cannot establish a causal relationship, prolonged exposure to digital devices may indirectly affect auditory processing in several ways. Excessive screen time, especially for video games or online videos, can contribute to attention deficits [36], affecting auditory information processing. Our results on dichotic listening tasks also showed that divided attention is affected in high screen time exposed tweens.

Walsh et al. [37] suggested that limiting screen time to two hours a day can help children improve their memory, attention, and information processing speed. Liu et al. [38] also stated that when used properly, screen time positively affects the memory of children and adolescents. However, prolonged screen time negatively affects memory function to varying degrees. When children spend moderate time on screens, they may be more actively involved and engaged, resulting in better-sustained attention [39]. Liebherr et al. [39] found a non-linear relationship between the amount of digital media usage and attention performances in 6–to 10-year-old children. Low to moderate usage positively affects attention; however, prolonged usage significantly reduces attention performance.

Conclusion

We found a curvilinear relationship between the duration of screen time, auditory processing, and working memory abilities. The study's findings suggest that moderation in screen time is crucial for tween's auditory processing skills, in line with Goldilock’s hypothesis. However, it can be stated that moderate exposure did not affect the temporal resolution and that the duration time had an effect on auditory processing skills.

Acknowledgements

Not applicable.

Authors’ contributions

SJ: Conceptualization, Formal analysis, Funding Acquisition, Writing - Original Draft, review & editing, Visualization, Supervision. CJ: Conceptualization, Data Curation, Resources, Writing - review & editing, Supervision. SV: Methodology, Project Administration, Resources. SS: Methodology, Resources. RTK: Investigations. AD: Investigations.

Funding

The data collection is partially funded by the Educational, Research and Innovation Committee, National Council of Educational Research and Training [Project no. F 4-51 (798)/DER-2020] dated 18.02.2022, Government of India.

Data availability

Data is provided within the manuscript.

Declarations

Ethics approval and consent to participate

In the current study, all of the testing procedures were accomplished using a noninvasive technique and adhered to the conditions of the institutional ethical approval committee (SH/IRB/AP1255). The authors obtained written consent from all parents/caregivers, and they were informed about the test details, their significance, and the approximate time required to complete the testing procedure before conducting the tests. The study adhered to the institutional ethical guidelines to test human subjects.

Consent for publication

Not applicable.

Competing interests

The authors declare no competing interests.

Publisher’s Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

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