Screen Use, Parent–Child Interaction, and Social Interaction Behaviors in Children with Autism Spectrum Disorder

Screen Use, Parent–Child Interaction, and Social Interaction Behaviors in Children with Autism Spectrum Disorder | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Screen Use, Parent–Child Interaction, and Social Interaction Behaviors in Children with Autism Spectrum Disorder IBRAHIM HALIL DIKEN, ALI KAYMAK, GOKHAN INCE, ALPEREN SAGDIC, and 6 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-9124767/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted 8 You are reading this latest preprint version Abstract The rapid expansion of digital technologies has transformed children’s everyday environments, raising concerns about excessive screen use and its potential developmental implications. Although research on screen use has increased substantially, relatively little is known about how screen addiction may relate to family interaction processes among children with Autism Spectrum Disorder (ASD). The present study aimed to examine the relationships among screen addiction, autism severity, parent–child interaction behaviors, and children’s social interaction behaviors in children diagnosed with ASD. The study employed a correlational research design. Participants included 784 parent–child pairs recruited from multiple provinces across Türkiye. Data were collected through a demographic questionnaire, the Autism Behavior Assessment Tool (ABAS), and parent-reported measures of children’s screen use patterns. In addition, observational interaction data were obtained from a subsample of 102 mother–child dyads using the Maternal Behavior Rating Scale–Turkish Version (MBRS-TV), the Child Behavior Rating Scale–Turkish Version (CBRS-TV), and the Social Interaction Assessment Instrument (SIAI-TV). The findings indicated that children’s screen use was positively associated with autism severity and autistic interaction behaviors, while negatively associated with attention, interaction initiation, and overall interaction behaviors. Maternal interaction behaviors were positively associated with children’s interaction behaviors and negatively associated with children’s screen use. These results suggest that higher levels of screen exposure may be related to reduced social interaction opportunities among children with ASD. Overall, the findings highlight the importance of considering family interaction processes when evaluating digital media use in children with ASD and suggest that balanced media routines and responsive parenting may support healthier developmental outcomes. Autism spectrum disorder screen addiction parent–child interaction social interaction digital media use Introduction Autism Spectrum Disorder (ASD) is a neurodevelopmental condition characterized by persistent difficulties in social communication and interaction as well as restricted and repetitive patterns of behavior and interests (American Psychiatric Association, 2013 ). In recent decades, the prevalence of ASD has increased substantially worldwide, prompting growing interest in factors that influence the developmental trajectories and daily experiences of children with autism. Alongside these developments, the rapid expansion of digital technologies has transformed children’s everyday environments, making screen-based media an increasingly prominent aspect of childhood. A substantial body of research has examined the developmental implications of children’s screen use. Studies conducted with typically developing populations suggest that excessive screen exposure may be associated with a range of developmental outcomes, including reduced cognitive and language performance, lower psychological well-being, and behavioral difficulties (Madigan et al., 2019 ; Twenge & Campbell, 2018 ; Stiglic & Viner, 2019 ). Research has also highlighted the growing role of mobile and interactive media in early childhood environments. With the widespread availability of smartphones and tablets, young children increasingly encounter digital media in everyday contexts. While such technologies may offer educational opportunities, concerns remain regarding their potential effects on social interaction, attention, and developmental outcomes during early childhood (Radesky et al., 2015 ). In addition, digital media use within family contexts has been linked to changes in parent–child interaction patterns. For example, interruptions caused by technology use—often referred to as “technoference”—may reduce opportunities for direct interaction between parents and children (McDaniel & Radesky, 2020; Radesky & Christakis 2016 ). These findings highlight the importance of examining how digital media use intersects with family interaction processes during early development. Although the literature on children’s screen use is expanding rapidly, research focusing specifically on children with ASD remains relatively limited. Existing studies indicate that children with ASD may engage with digital media differently from their typically developing peers. For instance, children with ASD tend to spend more time using screen-based technologies and may show stronger preferences for digital activities compared with their peers (Mazurek & Wenstrup, 2013 ). Similarly, recent studies suggest that screen exposure may be associated with behavioral and developmental outcomes among children on the autism spectrum (McDaniel & Radesky, 2018 ). The structured and predictable nature of digital environments may be particularly appealing for children with ASD, who often demonstrate preferences for repetitive activities and predictable routines. At the same time, digital technologies may also offer potential benefits for children with ASD. Technology-assisted interventions and digital tools have been used to support communication, learning, and social engagement in this population (Odom et al., 2015 ). However, the increasing accessibility of digital devices has also raised concerns regarding excessive screen use and the possibility of problematic or addictive patterns of media consumption. Recent research conceptualizes problematic media use as a behavioral pattern characterized by excessive engagement, difficulty disengaging from digital media, and interference with daily functioning. To assess such behaviors, standardized tools such as the Problematic Media Use Measure (PMUM) have been developed to evaluate problematic screen media use in children (Domoff et al., 2019 ). Some researchers have even suggested that early and intensive exposure to audiovisual media may influence neurodevelopmental processes related to autism, although these claims remain controversial and require further empirical investigation (Heffler & Oestreicher, 2020). One domain that may be particularly sensitive to children’s screen use is parent–child interaction. Parent–child interaction plays a critical role in the development of communication, social engagement, and emotional regulation skills, especially among children with ASD (Siller & Sigman, 2008 ). Positive interaction patterns between parents and children have been shown to support language development, joint attention, and adaptive functioning in children on the autism spectrum (Mahoney & Perales, 2003 ; Mahoney & MacDonald, 2007; Diken & Mahoney, 2013 ; Karaaslan, Diken, & Mahoney, 2011 ). However, increasing reliance on digital devices within households may reduce opportunities for shared activities and direct engagement between parents and children. Despite the growing interest in digital media use and autism, several gaps remain in the literature. First, relatively few studies have investigated screen addiction or problematic screen use specifically among children with ASD. Second, existing research has primarily focused on individual behavioral outcomes rather than examining how children’s screen use may influence family interaction processes, particularly parent–child interaction. Third, studies examining digital media use in autism often focus on intervention contexts, leaving everyday family environments relatively underexplored. Addressing these gaps is important for understanding how digital media use may shape developmental experiences in children with ASD. Investigating the relationship between screen use and parent–child interaction may provide valuable insights into how digital technologies influence family dynamics and social development in this population. Purpose of the Study The purpose of this study is to examine the relationships among screen use, autism severity, parent–child interaction behaviors, children’s interaction behaviors, and social interaction behaviors in children diagnosed with ASD. Specifically, the study investigates whether children’s screen use is associated with the quality of parent–child interaction and children’s social interaction outcomes, while also considering the role of autism severity in shaping these relationships. Within this framework, screen use is conceptualized as a behavioral factor that may influence both children’s interaction behaviors and the quality of parent–child interactions. At the same time, autism severity is expected to be associated with both screen use behaviors and children’s social interaction outcomes. In addition, mothers’ interaction behaviors are expected to play a facilitating role in children’s interaction behaviors during mother–child interactions. This study addresses the following hypotheses: H1. Children with ASD demonstrate varying levels of screen use and potential screen addiction during waking hours. H2. Autism severity is significantly associated with children’s screen use patterns. H3. Higher levels of screen addiction among children with ASD are associated with lower-quality parent–child interaction behaviors. H4. Mothers’ interaction behaviors are positively associated with children’s interaction behaviors during mother–child interactions. H5. Children’s social interaction skills (e.g., typical interaction and autistic interaction behaviors) are significantly associated with their levels of screen addiction. H6. Screen addiction, autism severity, mothers’ interaction behaviors, children’s interaction behaviors, and children’s social interaction skills are significantly interrelated. Method Research Design This study employed a correlational research design to examine the relationships among screen addiction, autism severity, parent–child interaction behaviors, and social interaction skills in children diagnosed with ASD. Correlational research designs are commonly used in educational and behavioral sciences to investigate the strength and direction of relationships among variables without manipulating them (Creswell & Creswell, 2018 ; Fraenkel et al., 2019 ). Prior to data collection, ethical approval for the study was obtained from the Ethics Committee of Anadolu University (Approval No. 732353, Date: May 28, 2024). Participation in the study was voluntary, and informed consent was obtained from all participating parents. Participants The sample consisted of 784 parent–child pairs recruited from different regions of Türkiye using criterion sampling, a purposive sampling technique. The inclusion criterion required that the child had a formal diagnosis of ASD diagnosed by child psychiatrists and had legal report on the diagnosis. The average age of mothers participating in the survey was 37.17 years (SD = 6.91), ranging from 22 to 70 years. Fathers had a mean age of 40.94 years (SD = 7.21), ranging from 24 to 73 years. The sample largely represented parents in middle adulthood with diverse educational backgrounds. Participants were recruited from multiple provinces across Türkiye, reflecting a geographically diverse sample. The largest proportion of participants was from Eskişehir (n = 173, 22.1%), followed by Konya (n = 77, 9.8%), Gaziantep (n = 67, 8.5%), and Afyonkarahisar (n = 66, 8.4%). Additional participants were from Bursa (n = 51, 6.5%), Antalya (n = 42, 5.4%), Şanlıurfa (n = 38, 4.8%), and Mardin (n = 37, 4.7%). Smaller proportions of participants were recruited from Trabzon (n = 29, 3.7%), İstanbul (n = 27, 3.4%), Ankara (n = 23, 2.9%), and Sakarya (n = 19, 2.4%). Further representation included Osmaniye (n = 15, 1.9%), Erzincan (n = 15, 1.9%), İzmir (n = 14, 1.8%), Adana (n = 12, 1.5%), Balıkesir (n = 10, 1.3%), and Mersin (n = 8, 1.0%). A smaller number of participants were recruited from Kırklareli (n = 6, 0.8%), Zonguldak (n = 6, 0.8%), Isparta (n = 5, 0.6%), Kars (n = 4, 0.5%), Düzce (n = 4, 0.5%), and Hatay (n = 3, 0.4%). In addition, 46 participants (5.9%) were recruited from other provinces, each contributing one or two participants. For the interaction analysis component of the study, a subsample of 102 children with ASD and their mothers participated in direct observation sessions. The mean age of the children was 64.98 months (SD = 18.17), with ages ranging from 24 to 101 months. The average age at which children received an ASD diagnosis was 28.34 months (SD = 10.02). The majority of children in the subsample were male (81.4%). Measures Demographic Information Form. A structured demographic questionnaire was developed to collect information about family characteristics, children’s developmental histories, and technology use patterns. The form included sections on: parental demographic characteristics (age, education level, occupation), child developmental history and diagnostic information, educational and therapeutic services received, household technology use, children’s screen exposure (device types, duration of use, and content types), and contextual factors influencing screen use (e.g., during meals, leisure time, or calming situations). The questionnaire was administered digitally using an online survey platform. Maternal Behavior Rating Scale – Turkish Version (MBRS-TV). The MBRS-TV is an observational measure designed to evaluate parental interaction behaviors during parent–child interactions. Parental interaction behaviors were evaluated using the Maternal Behavior Rating Scale, the Turkish adaptation of the Maternal Behavior Rating Scale (MBRS-TV). The adaptation and psychometric evaluation were conducted by Diken ( 2009 ) with 123 mother–child dyads whose children were between 18 and 72 months of age and had expressive language delay, mild intellectual disability, or autism. The MBRS-TV is an observational rating scale consisting of 12 items assessing parental behaviors during parent–child interaction. Exploratory factor analysis indicated that the Turkish version of the scale consisted of three factors (Responsiveness, Affect, and Achievement-oriented/directiveness), explaining 73.40% of the total variance. Internal consistency reliability was assessed using Cronbach’s alpha coefficients. The alpha values for the subscales were: Responsive–Sensitive behavior: α = .86, Affect: α = .87, Achievement-oriented/Directive behavior: α = .61. In using the scale, mother–child interactions were video-recorded during 5–10 minute play sessions, in which mothers were instructed to interact with their children as they normally would during play activities. Developmentally appropriate toys were provided to facilitate natural interaction. Items are rated using a 5-point Likert-type scale. Higher scores on the Responsiveness and Affect subscales indicate more positive interaction behaviors. For the Achievement-oriented/directiveness subscale, a score of 3 is considered the optimal interaction level. In scoring this dimension, ratings of 5 are recoded as 1 and ratings of 4 are recoded as 2, following the scoring procedure proposed in the scale manual. The MBRS-TV provides mean scores for each subscale rather than a total score. Child Behavior Rating Scale – Turkish Version (CBRS-TV). The CBRS-TV evaluates children’s behavioral engagement during interactions with caregivers. Children’s interaction behaviors were assessed using the Child Behavior Rating Scale, the Turkish adaptation of the Child Behavior Rating Scale (CBRS-TV) developed to evaluate children’s engagement during parent–child interaction. The Turkish adaptation was conducted by Diken ( 2009 ) using the same sample of 123 mother–child dyads. The scale consists of 7 observational items including attention and engagement, persistence, participation, joint attention, initiation, cooperation, and emotional regulation. evaluating children’s interaction behaviors in attention and initiation subdomains. The Turkish adaptation of the scale has demonstrated strong validity and reliability. The two factors explained 78.86% of the total variance. Internal consistency reliability coefficients were reported as: Attention factor: α = .79, initiation factor: α = .91, and total scale: α = .90. Item–total correlation coefficients ranged between .52 and .89, demonstrating strong discrimination between items. Children’s behaviors during 10–15 minute play interactions were evaluated using a 5-point Likert rating system. Higher scores indicate more adaptive and developmentally appropriate interaction behaviors. The Turkish adaptation of the scale has demonstrated strong reliability. These values indicate a high level of internal consistency and support the use of the scale as a reliable measure of child interaction behaviors. Autism Behavior Assessment Scale (ABAS). Autism severity was measured using the Autism Behavior Assessment Scale (ABAS), a standardized instrument developed by Diken, Diken, and Isik (2025). The scale was developed based on a large national sample consisting of 1,275 individuals from 14 cities in Türkiye. Exploratory factor analysis revealed a four-factor structure consisting of 36 items: Restricted/Repetitive Behaviors and Sensory Sensitivity, Social Interaction, Social Communication, and Atypical Speech Development. The four factors together explain approximately 63% of the total variance. Confirmatory factor analysis indicated good model fit: χ²/df ≈ 3.1, CFI = .95, TLI = .94, RMSEA = .052, and SRMR = .046. Internal consistency values were also high: Total scale: Cronbach’s α = .96 and Subscales: α = .88 – .94. McDonald’s omega coefficients ranged between .89 and .95, further supporting reliability. Criterion validity analyses demonstrated moderate to high correlations with other standardized autism measures (r ≈ .62 – .79). These findings indicate that ABAS is a valid and reliable instrument for assessing autism-related behaviors in individuals aged 3–24 years. Social Interaction Assessment Instrument (SIAI-TV). Children’s social interaction behaviors were assessed using the SIAI-TV, the Turkish adaptation of the Autism Screening Instrument for Educational Planning, adapted by Aksoy and Diken ( 2016 ). The instrument is based on a structured observation procedure in which children’s behaviors are coded across 48 equal observation intervals. At the end of each 10-second interval, the child’s behavior is categorized into one of several behavioral categories, including: Interaction, Independent play, Non-responsiveness, and Negative or aggressive behaviors. The total number of observations within each category is then converted into standardized scores representing typical interaction and autistic interaction patterns. The reliability of the instrument has been reported as KR-21 = .83, indicating acceptable internal consistency for assessing social interaction patterns in children with ASD. In the present study, after the 10–15 minute mother–child interaction session used for the MBRS-TV and CBRS-TV assessments was recorded, the SIAI-TV protocol was applied to the same interaction context in accordance with the administration guidelines. Procedure Data collection consisted of two stages. First, descriptive and demographic data were collected through an online survey distributed via Google Forms. Parents from different regions of Türkiye were invited to participate through social media and institutional networks. Second, observational interaction data were collected in special education and rehabilitation centers located in Eskişehir and Konya. Mothers and their children participated in structured play sessions in designated playrooms. During these sessions, mother–child interactions were video-recorded and later coded using the relevant assessment instruments. Participation in the interaction sessions was voluntary, and families were informed about the study procedures before providing written consent. Data Analysis Descriptive statistics, including frequencies, percentages, means, and standard deviations, were calculated to summarize demographic characteristics and screen use patterns. To examine relationships among variables, correlation and regression analyses were conducted. Prior to these analyses, the assumptions of statistical tests were evaluated. Normality of the data distribution was assessed using Kolmogorov–Smirnov and Shapiro–Wilk tests, as well as skewness and kurtosis values. Depending on whether the data met the assumptions of normality, parametric or non-parametric statistical tests were applied. To ensure the reliability of observational data, an inter-rater reliability analysis was conducted for the coding of mother–child interaction videos. Three trained coders participated in the coding process. Two of the coders were members of the research team who had completed formal certification for the assessment instruments used in the study, and the third coder was an independent doctoral-level researcher in special education who was not involved in the data collection process. Prior to coding, all coders received training on the coding procedures and scoring criteria of the MBRS-TV, CBRS-TV, and SIAI-TV instruments to ensure consistency in interpretation. 40% of the recorded interaction videos were randomly selected and independently coded by the coders to assess inter-rater agreement. Inter-rater reliability was calculated using the formula proposed by Miles and Huberman ( 1994 ): Reliability = (Agreement / Agreement + Disagreement) x 100. The analysis yielded an inter-rater reliability coefficient of 100%, indicating a very high level of agreement among the coders. According to methodological standards in qualitative and observational research, inter-rater reliability values above 80% are considered acceptable (Miles & Huberman, 1994 ). Therefore, the obtained reliability level suggests that the coding procedures used in this study were highly consistent and reliable. Results Screen Use Patterns Among Children with ASD and Parental Observations During Screen Use The first hypothesis examined the patterns of screen use among children diagnosed with ASD. Descriptive statistics indicated that children’s average daily screen exposure was 2.13 hours (SD = 2.09). Parental screen use was also relatively high, with mothers reporting an average daily screen use of 2.76 hours (SD = 2.21) and fathers 4.43 hours (SD = 3.50). Correlation analyses revealed that maternal screen use was positively associated with children’s screen exposure (r = .231, p < .01), while paternal screen use also showed a weaker but significant relationship (r = .124, p < .05). These findings suggest that family digital media habits may influence children’s screen exposure. Regarding content types, cartoons were the most frequently viewed media content (32.5%), followed by general videos (18.9%), educational videos (13.3%), and music videos (11.0%). Smaller proportions of children watched gaming videos (5.6%), cooking videos (2.8%), and documentaries (2.3%), while 21.1% of parents reported that their children did not regularly watch video content. Qualitative responses from parents revealed several behavioral patterns observed during screen use. Four main themes emerged: (1) positive emotional responses, (2) disengagement from the surrounding environment, (3) behavioral stimulation and hyperactivity, and (4) reduced social communication. Many parents reported that screen use generated positive emotional reactions. For example: “When the tablet is turned on, he becomes very happy and watches attentively for a long time.” (P12). Similarly, another parent reported that technology sometimes helped regulate their child’s emotions: “When he becomes restless, turning on cartoons helps him calm down.” (P37). However, parents also frequently described reduced environmental awareness during screen use: “When he holds the device, he disconnects from the world. Even when we call his name, he does not respond.” (P45). Overall, 51.2% of children appeared happy during screen use, while 35.9% appeared disengaged from the surrounding environment, 21.9% displayed hyperactive behaviors, and 20.3% showed irritability or restlessness. Autism Severity Levels of Children with ASD and Relationship Between Screen Use and Autism Severity The second hypothesis examined the severity levels of autism symptoms using the ABAS. The ABAS provides standardized scores with a mean of 100 and a standard deviation of 15. Results showed that the restricted and repetitive behaviors dimension had a mean score of M = 94.18 (SD = 12.75). The social interaction dimension had a mean score of M = 92.50 (SD = 15.74), indicating slightly lower social interaction performance relative to normative expectations. The social communication dimension had an average score of M = 100.07 (SD = 22.85), suggesting performance close to the normative mean but with high variability among participants. The developmentally atypical speech dimension had a mean score of M = 95.27 (SD = 11.72). The overall ABAS score averaged M = 92.56 (SD = 14.76). In terms of support needs, 41.75% of children were classified as “possible risk,” 27.18% as “support needed,” 24.27% as “substantial support needed,” and 6.80% as “very substantial support needed.” The third hypothesis examined the relationship between screen exposure and autism symptom severity. Pearson correlation analyses revealed a moderate positive relationship between daily screen exposure and ABAS scores (r = .41, p < .01). This result indicates that higher levels of screen exposure were associated with greater autism symptom severity. When device types were analyzed separately, tablet use was significantly associated with autism severity (r = .36, p < .01), whereas television viewing showed a weaker but significant relationship (r = .28, p < .05). A multiple regression analysis was conducted to determine whether screen use predicted autism severity. The model was statistically significant, F(3,96) = 8.72, p < .001, explaining 21% of the variance in autism severity scores (R² = .21). Daily screen exposure emerged as the strongest predictor (β = .34, p < .01), followed by tablet use (β = .27, p .05). Maternal Interaction Behaviors and Children’s Interaction Behaviors During Mother–Child Interaction The fourth hypothesis examined mothers’ interaction behaviors with their children. Results showed that 28% of mothers demonstrated low levels of responsiveness, 46% moderate levels, and 26% high levels. For the affect dimension, 24% of mothers were classified as low, 49% moderate, and 27% high emotionally expressive. Similarly, achievement-oriented/directive behaviors were mostly observed at moderate levels, with 31% low, 44% moderate, and 25% high scores. These results indicate that most mothers displayed moderate levels of interaction behaviors, with relatively fewer mothers demonstrating consistently high levels of responsive interaction. The fifth hypothesis examined children’s interaction behaviors during mother–child interactions. Results indicated that 30% of children demonstrated low levels of attention behaviors, 45% moderate levels, and 25% high levels. Similarly, initiation behaviors were low in 34% of children, moderate in 41%, and high in 25%. When overall interaction behaviors were examined, 29% of children were classified as low, 47% moderate, and 24% high. These findings suggest that children with ASD generally demonstrate moderate levels of interaction behaviors, while high levels of interaction engagement remain relatively limited. Relationship Between Maternal and Child Interaction Behaviors The sixth hypothesis examined the relationship between maternal interaction behaviors and children’s interaction behaviors. Pearson correlation analyses revealed that maternal responsiveness was positively associated with children’s attention behaviors (r = .38, p < .01). Similarly, maternal emotional expressiveness was positively associated with children’s initiation behaviors (r = .34, p < .01). A weaker but significant relationship was also found between achievement-oriented maternal behaviors and children’s overall interaction behaviors (r = .27, p < .05). These results suggest that higher-quality maternal interaction behaviors are associated with greater child engagement during interaction. Social Interaction Behaviors of Children with ASD and Relationships Among Screen Use, Parent–Child Interaction, and Social Interaction Behaviors Analyses of social interaction behaviors indicated that autistic interaction behaviors had a higher mean score (M = 3.02) compared with typical social interaction behaviors (M = 2.47). Distribution analyses showed that 44% of children displayed moderate levels of autistic interaction behaviors, while typical social interaction behaviors were predominantly observed at low levels (38%). Only 22% of children demonstrated high levels of typical social interaction behaviors, suggesting that many children experienced difficulties initiating and maintaining typical social interactions. Correlation analyses were conducted to examine the relationships among screen use, autism severity, parent interaction behaviors, child interaction behaviors, and social interaction behaviors. Results indicated that daily screen exposure was positively associated with autistic interaction behaviors (r = .37, p < .01) and negatively associated with attention (r = − .34, p < .01), interaction initiation (r = − .29, p < .05), and overall interaction behaviors (r = − .31, p < .01). Device-specific analyses revealed that tablet use was negatively associated with typical social interaction behaviors (r = − .28, p < .05) and smartphone use was negatively associated with children’s attention levels (r = − .30, p < .05). Finally, parental interaction behaviors were also associated with screen exposure. Maternal responsiveness was negatively correlated with children’s screen use (r = − .26, p < .05), and maternal emotional expressiveness showed a similar negative association (r = − .24, p < .05). These findings suggest that higher screen exposure may be associated with reduced social interaction behaviors, whereas responsive parenting may mitigate excessive screen exposure and support more adaptive interaction patterns. Discussion The present study examined screen use patterns among children with ASD and explored how these patterns relate to parent–child interaction and children’s social interaction skills. The findings indicated that children with ASD were exposed to digital media for an average of approximately two hours per day. Furthermore, children’s screen use was positively associated with both maternal and paternal screen use. These findings suggest that children’s digital media habits are embedded within broader family media environments. In addition, research on problematic media use suggests that excessive screen engagement in children may display characteristics similar to addictive behavioral patterns, including preoccupation with digital media and difficulties disengaging from screen-based activities (Domoff et al., 2019 ). Previous research has consistently demonstrated that children’s screen use behaviors are closely related to parental media practices and the overall family media ecology (McDaniel & Radesky, 2020; Radesky et al., 2020). Parents often model technology use patterns that children subsequently adopt, and family routines surrounding technology may shape children’s exposure to digital media. In families of children with ASD, digital media may also serve additional functions, such as managing behavioral challenges or supporting emotional regulation in daily caregiving contexts. Qualitative findings from parental reports further illustrated this dynamic. Many parents indicated that digital media sometimes helped calm their children or sustain their attention. Similar observations have been reported in previous studies, which suggest that parents of children with ASD may use digital devices as tools for behavioral management or emotional regulation (McDaniel & Radesky, 2018 ). However, such practices may also reduce opportunities for direct social interaction between parents and children. Another important finding of the study was the positive association between children’s screen exposure and autism symptom severity. Higher daily screen exposure was associated with higher autism-related behavioral scores. In addition, tablet use was more strongly associated with autism severity than television viewing. These findings align with previous studies suggesting that children with ASD often show strong preferences for screen-based media environments (Mazurek & Wenstrup, 2013 ). Digital platforms frequently provide predictable, repetitive, and visually stimulating experiences, which may align with the cognitive and behavioral preferences commonly observed in individuals with autism. More recent research has also suggested that increased exposure to screen-based media may be associated with behavioral and developmental outcomes in children with ASD (McDaniel & Radesky, 2018 ). However, it is important to interpret these relationships cautiously. The present study employed a cross-sectional design, which limits causal interpretations. It is possible that children with higher levels of autism-related characteristics are more likely to engage in screen-based activities, rather than screen exposure causing increased autism symptoms. The findings also highlighted the critical role of parent–child interaction in children’s social and behavioral outcomes. Maternal responsiveness and affect (emotional expressiveness) were positively associated with children’s attention behaviors and interaction initiation during mother–child interaction sessions. These findings are consistent with earlier research demonstrating that responsive parenting and emotionally supportive interaction environments contribute significantly to social communication development in children with ASD (Siller & Sigman, 2008 ). Parent–child interaction represents a key context in which children develop joint attention, language skills, and social reciprocity. Recent studies have also emphasized that disruptions in parent–child interaction caused by digital technology use—often referred to as “technoference”—may interfere with children’s opportunities for social engagement and communication (McDaniel & ; Radesky & Christakis 2016 , 2020). The present findings extend this literature by showing that higher levels of responsive parenting are associated with lower levels of children’s screen exposure. These results suggest that strengthening parent–child interaction quality may not only support children’s social development but may also reduce reliance on digital devices as tools for behavioral management. The study further revealed that higher levels of screen exposure were associated with lower levels of attention, interaction initiation, and overall interaction performance. Additionally, screen exposure was positively associated with autistic interaction behaviors. These findings are consistent with research suggesting that excessive screen exposure may reduce opportunities for social interaction and experiential learning during early childhood (Madigan et al., 2019 ; Stiglic & Viner, 2019 ). For children with ASD, who already experience challenges in social communication, reduced opportunities for live interaction may further limit the development of essential social skills. At the same time, parents reported that digital media sometimes supported certain developmental outcomes. Some children reportedly learned songs, basic concepts, imitation behaviors, and simple communication expressions through digital media content. These findings are consistent with research suggesting that technology can support learning when used intentionally and in structured ways (Odom et al., 2015 ). Therefore, the developmental implications of digital media use may depend not only on-screen time but also on the quality of content, parental involvement, and the context of media use. This study contributes to the growing literature on digital media use in children with ASD by integrating screen use, autism severity, parent–child interaction, and children’s social interaction skills within a single analytical framework. Previous studies have typically examined screen exposure as an isolated behavioral variable. In contrast, the present study highlights the importance of considering family interaction processes when interpreting the developmental implications of digital media use. The findings support an ecological perspective in which children’s developmental outcomes emerge from dynamic interactions between individual characteristics and family relational environments (Bronfenbrenner & Morris, 2006 ). The observed relationships between screen use, parental interaction behaviors, and children’s interaction competence suggest that digital media exposure may influence developmental outcomes both directly and indirectly through family interaction processes. The findings of the study also have several practical implications for families, educators, and professionals working with children with ASD. First, interventions addressing digital media use should focus not only on limiting screen time but also on promoting balanced media routines that encourage face-to-face interaction and shared activities between parents and children. Second, parent education programs may play an important role in helping families develop strategies for managing children’s screen use. Providing guidance on appropriate media content, co-viewing practices, and structured media routines may help families use digital media in ways that support children’s learning and development. Third, strengthening parent–child interaction should be considered a central component of interventions designed for children with ASD. Programs that encourage shared play, joint attention, and responsive communication may simultaneously support children’s social development and reduce excessive reliance on digital devices. Finally, clinicians and educators should consider the broader family media environment when assessing children’s screen use behaviors. Understanding how digital technologies are integrated into daily family routines may provide valuable insights into children’s developmental experiences. Limitations and Future Research Directions Despite the contributions of the present study, several limitations should be acknowledged. First, the study employed a cross-sectional correlational design, which limits the ability to draw causal conclusions about the relationships between screen use, autism severity, parent–child interaction, and children’s social interaction skills. Although significant associations were observed among these variables, it cannot be determined whether increased screen exposure contributes to interaction difficulties or whether children with more pronounced developmental challenges are more likely to engage in screen-based activities. Future research employing longitudinal or experimental designs would be valuable in clarifying the directionality of these relationships. Second, a portion of the data relied on parent-reported measures, particularly regarding children’s screen use patterns and behavioral responses during technology use. Although parental reports provide important insights into children’s daily routines and family contexts, such reports may be subject to recall bias or subjective interpretation. Future studies may benefit from incorporating objective measures of screen use, such as digital usage tracking or ecological momentary assessment methods. Third, although the overall sample size was relatively large, the observational interaction data were obtained from a smaller subsample of participants. This limitation may restrict the generalizability of findings related to observed parent–child interaction behaviors. Future studies should consider collecting observational interaction data from larger and more diverse samples to strengthen the robustness of these findings. Fourth, the study was conducted within a specific cultural and national context, which may limit the generalizability of the findings to other cultural environments. Family technology practices, parenting styles, and access to digital media may vary across societies. Therefore, cross-cultural research is needed to examine whether similar patterns emerge in different sociocultural contexts. Finally, although the present study examined several key variables, other potentially relevant factors were not included in the analyses. For example, variables such as socioeconomic status, parental stress, parental digital literacy, and the specific content and context of media use may also influence children’s developmental outcomes. Future research incorporating these contextual factors may provide a more comprehensive understanding of the complex relationships between digital media use and developmental processes in children with ASD. Declarations Ethical Approval: “The study was conducted in accordance with the principles of the Declaration of Helsinki, and the research protocol was approved by the Ethics Committee of Anadolu University ( Approval Code: 732353 ; Approval Date: May 28, 2024). Funding: This study was supported by Scientific Research Coordination Unit of Anadolu University under the project number SCB-2024-2482. Informed consent: Participation was voluntary, and respondents indicated consent within the survey. Data availability statement: The data are available from the corresponding author upon reasonable request. Authors Contributions: Authors contributed the study as follows: “Conceptualization, IHD, OD, EK; methodology, IHD, MDS, DE, ME, EK, UOG, AK, GI, AS; formal analysis, IHD, EK, UOG, AK, AS, GI; investigation, IHD, GI, AS, UOG, AK; resources, IHD, OD, ME, DE, AS, GI, AK; data curation, IHD, GI, AS, UOG, AK; writing—original draft preparation, IHD, MDS; writing—review and editing, OD, MDS, DE, ME, EK, UOG, AK, GI, AS; project administration, IHD, OD, EK, AS, AK, GI, UOG. All authors have read and agreed to the published version of the manuscript.” Conflict of Interest Statement : The authors declare no conflicts of interest. Supplementary Materials: There is no supplementary material. Informed Consent Statement: Informed consent was obtained from all subjects involved in the study. Acknowledgments: We owe a sincere thanks to the participants who took part in this study. References Aksoy V, Diken İH. Autism Screening Instrument for Educational Planning’in (ASIEP-3) Türkçe uyarlaması: Geçerlik ve güvenirlik çalışması [Turkish adaptation of the Autism Screening Instrument for Educational Planning]. Ankara Üniversitesi Eğitim Bilimleri Fakültesi Özel Eğitim Dergisi. 2016;17(2):111–34. American Psychiatric Association. Diagnostic and statistical manual of mental disorders. 5th ed. American Psychiatric Publishing; 2013. Bronfenbrenner U, Morris PA. The bioecological model of human development. In: Damon W, Lerner RM, editors. Handbook of child psychology. Volume 1, 6th ed. Wiley; 2006. pp. 793–828. Creswell JW, Creswell JD. Research design: Qualitative, quantitative, and mixed methods approaches. 5th ed. Sage; 2018. Diken Ö. (2009). Ebeveyn davranışını değerlendirme ölçeği ve çocuk davranışını değerlendirme ölçeği’nin geçerlik ve güvenirlik çalışmaları [Validity and reliability study of the Parent Behavior Rating Scale and the Child Behavior Rating Scale] (Doctoral dissertation). Anadolu University, Institute of Health Sciences. Diken İH, Diken Ö, Işık U. Development and validation of the Autism Behavior Assessment Scale (ABAS). Children. 2025;12(8):1038. https://doi.org/10.3390/children12081038 . Diken Ö, Mahoney G. Interactions between Turkish mothers and preschool children with autism. Intellect Dev Disabil. 2013;51(3):190–200. https://doi.org/10.1352/1934-9556-51.3.190 . Domoff SE, Harrison K, Gearhardt AN, Gentile DA, Lumeng JC, Miller AL. Development and validation of the problematic media use measure: A parent-report measure of screen media addiction in children. Psychol Popular Media Cult. 2019;8(1):2–11. https://doi.org/10.1037/ppm0000163 . Fraenkel JR, Wallen NE, Hyun HH. How to design and evaluate research in education. 10th ed. McGraw-Hill Education; 2019. Karaaslan O, Diken I, Mahoney G. The Effectiveness of the Responsive Teaching Parent-mediated Developmental Intervention Programme in Turkey: A pilot study. Int J Disabil Dev Educ. 2011;58(4):359–72. https://doi.org/10.1080/1034912X.2011.626611 . Madigan S, Browne D, Racine N, Mori C, Tough S. Association between screen time and children’s performance on developmental screening tests. JAMA Pediatr. 2019;173(3):244–50. https://doi.org/10.1001/jamapediatrics.2018.5056 . Mahoney G, Perales F. Using Relationship-Focused Intervention to Enhance the Social—Emotional Functioning of Young Children with Autism Spectrum Disorders. Top Early Child Special Educ. 2003;23(2):74–86. Mazurek MO, Wenstrup C. Television, video game and social media use among children with ASD and typically developing siblings. J Autism Dev Disord. 2013;43(6):1258–71. https://doi.org/10.1007/s10803-012-1659-9 . McDaniel BT, Radesky JS. Technoference: Parent distraction with technology and associations with child behavior problems. Child Dev. 2018;89(1):100–9. https://doi.org/10.1111/cdev.12822 . Miles MB, Huberman AM. Qualitative data analysis: An expanded sourcebook. 2nd ed. Sage; 1994. Odom SL, Thompson JL, Hedges S, Boyd B, Dykstra J, Duda M, Bord A. Technology-aided interventions and instruction for adolescents with autism spectrum disorder. J Autism Dev Disord. 2015;45(12):3805–19. https://doi.org/10.1007/s10803-014-2320-6 . Radesky JS, Schumacher J, Zuckerman B. Mobile and interactive media use by young children: The good, the bad, and the unknown. Pediatrics. 2015;135(1):1–3. https://doi.org/10.1542/peds.2014-2251 . Radesky JS, Christakis DA. Increased screen time: Implications for early childhood development and behavior. Pediatr Clin North Am. 2016;63(5):827–39. https://doi.org/10.1016/j.pcl.2016.06.006 . Siller M, Sigman M. Modeling longitudinal change in the language abilities of children with autism: parent behaviors and child characteristics as predictors of change. Dev Psychol. 2008;44(6):1691–704. https://doi.org/10.1037/a0013771 . Stiglic N, Viner RM. Effects of screen time on the health and well-being of children and adolescents: A systematic review of reviews. BMJ Open. 2019;9(1):e023191. https://doi.org/10.1136/bmjopen-2018-023191 . Twenge JM, Campbell WK. Associations between screen time and lower psychological well-being among children and adolescents. Prev Med Rep. 2018;12:271–83. https://doi.org/10.1016/j.pmedr.2018.10.003 . Additional Declarations No competing interests reported. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-9124767","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":616928556,"identity":"50be5314-19b1-4d71-999b-5e7dd2a82cda","order_by":0,"name":"IBRAHIM HALIL DIKEN","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA0klEQVRIiWNgGAWjYBAC+Rn5hz/z/jksxyaR2P7gY8NhBvv5PQbMf//g1sImkZNwWLLhsTG/TPIxw5lALQYSZwwYEtvwajE4bNjwOXHmvLQ0aV6wlhwitCQ2fE7fcC/HjEgt8m8MDh/8cTt3w22oFnuwFvx+AWppQNICseUDQYedT7e/+f4bkpYZBL1/PMHgxhtkW3rwagEF8nHDDUAtwEBO4zGQOJZwAJ/3YVEpb3Ajx/zBxz82cvbzmw8+wKcFA/CAiAMkaBgFo2AUjIJRgAUAAPq1Z5OI9I60AAAAAElFTkSuQmCC","orcid":"","institution":"Anadolu University","correspondingAuthor":true,"prefix":"","firstName":"IBRAHIM","middleName":"HALIL","lastName":"DIKEN","suffix":""},{"id":616928558,"identity":"362c7d8f-9cc9-4596-97a0-a74d66ffa1b3","order_by":1,"name":"ALI KAYMAK","email":"","orcid":"","institution":"Anadolu University","correspondingAuthor":false,"prefix":"","firstName":"ALI","middleName":"","lastName":"KAYMAK","suffix":""},{"id":616928559,"identity":"6eed934c-2f4f-4ff3-90d6-070b5ef8d4cb","order_by":2,"name":"GOKHAN INCE","email":"","orcid":"","institution":"Anadolu University","correspondingAuthor":false,"prefix":"","firstName":"GOKHAN","middleName":"","lastName":"INCE","suffix":""},{"id":616928561,"identity":"d8c6747d-0826-4e4f-9b0a-24e0a74f009b","order_by":3,"name":"ALPEREN SAGDIC","email":"","orcid":"","institution":"","correspondingAuthor":false,"prefix":"","firstName":"ALPEREN","middleName":"","lastName":"SAGDIC","suffix":""},{"id":616928564,"identity":"585911a8-7ed9-43a3-b274-f0574b25cc00","order_by":4,"name":"MURAT DOGAN SAHIN","email":"","orcid":"","institution":"Anadolu University","correspondingAuthor":false,"prefix":"","firstName":"MURAT","middleName":"DOGAN","lastName":"SAHIN","suffix":""},{"id":616928567,"identity":"99bcc282-2d6e-481f-99f0-9d7e7e0bcda1","order_by":5,"name":"OZLEM DIKEN","email":"","orcid":"","institution":"Anadolu University","correspondingAuthor":false,"prefix":"","firstName":"OZLEM","middleName":"","lastName":"DIKEN","suffix":""},{"id":616928570,"identity":"fc24c1d2-5a82-44c3-89b8-f19038a8c7b0","order_by":6,"name":"MURAT EYUBOĞLU","email":"","orcid":"","institution":"Eskişehir Osmangazi University","correspondingAuthor":false,"prefix":"","firstName":"MURAT","middleName":"","lastName":"EYUBOĞLU","suffix":""},{"id":616928573,"identity":"ec8e0ed3-fe40-4829-8d87-7a42afedaf54","order_by":7,"name":"DAMLA EYUBOGLU","email":"","orcid":"","institution":"Eskişehir Osmangazi University","correspondingAuthor":false,"prefix":"","firstName":"DAMLA","middleName":"","lastName":"EYUBOGLU","suffix":""},{"id":616928577,"identity":"e44311c2-a076-4b1f-9022-21ff2e08829f","order_by":8,"name":"ERKAN KURNAZ","email":"","orcid":"","institution":"Anadolu University","correspondingAuthor":false,"prefix":"","firstName":"ERKAN","middleName":"","lastName":"KURNAZ","suffix":""},{"id":616928584,"identity":"e7b05dba-bc94-4598-aadc-50b4e6b27c68","order_by":9,"name":"UGUR ONUR GUNDEN","email":"","orcid":"","institution":"Anadolu University","correspondingAuthor":false,"prefix":"","firstName":"UGUR","middleName":"ONUR","lastName":"GUNDEN","suffix":""}],"badges":[],"createdAt":"2026-03-14 19:53:21","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-9124767/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-9124767/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":106404558,"identity":"0a1d29b9-0fa6-4505-a788-4454260521c1","added_by":"auto","created_at":"2026-04-08 09:16:14","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":794146,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-9124767/v1/55dc3522-a38a-4dfe-be8c-fd0f6b8850d6.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Screen Use, Parent–Child Interaction, and Social Interaction Behaviors in Children with Autism Spectrum Disorder","fulltext":[{"header":"Introduction","content":"\u003cp\u003eAutism Spectrum Disorder (ASD) is a neurodevelopmental condition characterized by persistent difficulties in social communication and interaction as well as restricted and repetitive patterns of behavior and interests (American Psychiatric Association, \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2013\u003c/span\u003e). In recent decades, the prevalence of ASD has increased substantially worldwide, prompting growing interest in factors that influence the developmental trajectories and daily experiences of children with autism. Alongside these developments, the rapid expansion of digital technologies has transformed children\u0026rsquo;s everyday environments, making screen-based media an increasingly prominent aspect of childhood.\u003c/p\u003e \u003cp\u003eA substantial body of research has examined the developmental implications of children\u0026rsquo;s screen use. Studies conducted with typically developing populations suggest that excessive screen exposure may be associated with a range of developmental outcomes, including reduced cognitive and language performance, lower psychological well-being, and behavioral difficulties (Madigan et al., \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e2019\u003c/span\u003e; Twenge \u0026amp; Campbell, \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e2018\u003c/span\u003e; Stiglic \u0026amp; Viner, \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e2019\u003c/span\u003e). Research has also highlighted the growing role of mobile and interactive media in early childhood environments. With the widespread availability of smartphones and tablets, young children increasingly encounter digital media in everyday contexts. While such technologies may offer educational opportunities, concerns remain regarding their potential effects on social interaction, attention, and developmental outcomes during early childhood (Radesky et al., \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e2015\u003c/span\u003e). In addition, digital media use within family contexts has been linked to changes in parent\u0026ndash;child interaction patterns. For example, interruptions caused by technology use\u0026mdash;often referred to as \u0026ldquo;technoference\u0026rdquo;\u0026mdash;may reduce opportunities for direct interaction between parents and children (McDaniel \u0026amp; Radesky, 2020; Radesky \u0026amp; Christakis \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e2016\u003c/span\u003e). These findings highlight the importance of examining how digital media use intersects with family interaction processes during early development.\u003c/p\u003e \u003cp\u003eAlthough the literature on children\u0026rsquo;s screen use is expanding rapidly, research focusing specifically on children with ASD remains relatively limited. Existing studies indicate that children with ASD may engage with digital media differently from their typically developing peers. For instance, children with ASD tend to spend more time using screen-based technologies and may show stronger preferences for digital activities compared with their peers (Mazurek \u0026amp; Wenstrup, \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e2013\u003c/span\u003e). Similarly, recent studies suggest that screen exposure may be associated with behavioral and developmental outcomes among children on the autism spectrum (McDaniel \u0026amp; Radesky, \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e2018\u003c/span\u003e). The structured and predictable nature of digital environments may be particularly appealing for children with ASD, who often demonstrate preferences for repetitive activities and predictable routines. At the same time, digital technologies may also offer potential benefits for children with ASD. Technology-assisted interventions and digital tools have been used to support communication, learning, and social engagement in this population (Odom et al., \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e2015\u003c/span\u003e). However, the increasing accessibility of digital devices has also raised concerns regarding excessive screen use and the possibility of problematic or addictive patterns of media consumption. Recent research conceptualizes problematic media use as a behavioral pattern characterized by excessive engagement, difficulty disengaging from digital media, and interference with daily functioning. To assess such behaviors, standardized tools such as the Problematic Media Use Measure (PMUM) have been developed to evaluate problematic screen media use in children (Domoff et al., \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e2019\u003c/span\u003e). Some researchers have even suggested that early and intensive exposure to audiovisual media may influence neurodevelopmental processes related to autism, although these claims remain controversial and require further empirical investigation (Heffler \u0026amp; Oestreicher, 2020).\u003c/p\u003e \u003cp\u003eOne domain that may be particularly sensitive to children\u0026rsquo;s screen use is parent\u0026ndash;child interaction. Parent\u0026ndash;child interaction plays a critical role in the development of communication, social engagement, and emotional regulation skills, especially among children with ASD (Siller \u0026amp; Sigman, \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e2008\u003c/span\u003e). Positive interaction patterns between parents and children have been shown to support language development, joint attention, and adaptive functioning in children on the autism spectrum (Mahoney \u0026amp; Perales, \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e2003\u003c/span\u003e; Mahoney \u0026amp; MacDonald, 2007; Diken \u0026amp; Mahoney, \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e2013\u003c/span\u003e; Karaaslan, Diken, \u0026amp; Mahoney, \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e2011\u003c/span\u003e). However, increasing reliance on digital devices within households may reduce opportunities for shared activities and direct engagement between parents and children.\u003c/p\u003e \u003cp\u003eDespite the growing interest in digital media use and autism, several gaps remain in the literature. First, relatively few studies have investigated screen addiction or problematic screen use specifically among children with ASD. Second, existing research has primarily focused on individual behavioral outcomes rather than examining how children\u0026rsquo;s screen use may influence family interaction processes, particularly parent\u0026ndash;child interaction. Third, studies examining digital media use in autism often focus on intervention contexts, leaving everyday family environments relatively underexplored. Addressing these gaps is important for understanding how digital media use may shape developmental experiences in children with ASD. Investigating the relationship between screen use and parent\u0026ndash;child interaction may provide valuable insights into how digital technologies influence family dynamics and social development in this population.\u003c/p\u003e\n\u003ch3\u003ePurpose of the Study\u003c/h3\u003e\n\u003cp\u003eThe purpose of this study is to examine the relationships among screen use, autism severity, parent\u0026ndash;child interaction behaviors, children\u0026rsquo;s interaction behaviors, and social interaction behaviors in children diagnosed with ASD. Specifically, the study investigates whether children\u0026rsquo;s screen use is associated with the quality of parent\u0026ndash;child interaction and children\u0026rsquo;s social interaction outcomes, while also considering the role of autism severity in shaping these relationships. Within this framework, screen use is conceptualized as a behavioral factor that may influence both children\u0026rsquo;s interaction behaviors and the quality of parent\u0026ndash;child interactions. At the same time, autism severity is expected to be associated with both screen use behaviors and children\u0026rsquo;s social interaction outcomes. In addition, mothers\u0026rsquo; interaction behaviors are expected to play a facilitating role in children\u0026rsquo;s interaction behaviors during mother\u0026ndash;child interactions.\u003c/p\u003e \u003cp\u003eThis study addresses the following hypotheses:\u003c/p\u003e \u003cp\u003e \u003cb\u003eH1.\u003c/b\u003e Children with ASD demonstrate varying levels of screen use and potential screen addiction during waking hours.\u003c/p\u003e \u003cp\u003e \u003cb\u003eH2.\u003c/b\u003e Autism severity is significantly associated with children\u0026rsquo;s screen use patterns.\u003c/p\u003e \u003cp\u003e \u003cb\u003eH3.\u003c/b\u003e Higher levels of screen addiction among children with ASD are associated with lower-quality parent\u0026ndash;child interaction behaviors.\u003c/p\u003e \u003cp\u003e \u003cb\u003eH4.\u003c/b\u003e Mothers\u0026rsquo; interaction behaviors are positively associated with children\u0026rsquo;s interaction behaviors during mother\u0026ndash;child interactions.\u003c/p\u003e \u003cp\u003e \u003cb\u003eH5.\u003c/b\u003e Children\u0026rsquo;s social interaction skills (e.g., typical interaction and autistic interaction behaviors) are significantly associated with their levels of screen addiction.\u003c/p\u003e \u003cp\u003e \u003cb\u003eH6.\u003c/b\u003e Screen addiction, autism severity, mothers\u0026rsquo; interaction behaviors, children\u0026rsquo;s interaction behaviors, and children\u0026rsquo;s social interaction skills are significantly interrelated.\u003c/p\u003e \u003c/div\u003e"},{"header":"Method","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e\u003cdiv id=\"Sec4\" class=\"Section3\"\u003e \u003ch2\u003eResearch Design\u003c/h2\u003e \u003cp\u003eThis study employed a correlational research design to examine the relationships among screen addiction, autism severity, parent\u0026ndash;child interaction behaviors, and social interaction skills in children diagnosed with ASD. Correlational research designs are commonly used in educational and behavioral sciences to investigate the strength and direction of relationships among variables without manipulating them (Creswell \u0026amp; Creswell, \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e2018\u003c/span\u003e; Fraenkel et al., \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e2019\u003c/span\u003e).\u003c/p\u003e \u003cp\u003ePrior to data collection, ethical approval for the study was obtained from the Ethics Committee of Anadolu University (Approval No. 732353, Date: May 28, 2024). Participation in the study was voluntary, and informed consent was obtained from all participating parents.\u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eParticipants\u003c/h3\u003e\n\u003cp\u003eThe sample consisted of 784 parent\u0026ndash;child pairs recruited from different regions of T\u0026uuml;rkiye using criterion sampling, a purposive sampling technique. The inclusion criterion required that the child had a formal diagnosis of ASD diagnosed by child psychiatrists and had legal report on the diagnosis. The average age of mothers participating in the survey was 37.17 years (SD\u0026thinsp;=\u0026thinsp;6.91), ranging from 22 to 70 years. Fathers had a mean age of 40.94 years (SD\u0026thinsp;=\u0026thinsp;7.21), ranging from 24 to 73 years. The sample largely represented parents in middle adulthood with diverse educational backgrounds.\u003c/p\u003e \u003cp\u003eParticipants were recruited from multiple provinces across T\u0026uuml;rkiye, reflecting a geographically diverse sample. The largest proportion of participants was from Eskişehir (n\u0026thinsp;=\u0026thinsp;173, 22.1%), followed by Konya (n\u0026thinsp;=\u0026thinsp;77, 9.8%), Gaziantep (n\u0026thinsp;=\u0026thinsp;67, 8.5%), and Afyonkarahisar (n\u0026thinsp;=\u0026thinsp;66, 8.4%). Additional participants were from Bursa (n\u0026thinsp;=\u0026thinsp;51, 6.5%), Antalya (n\u0026thinsp;=\u0026thinsp;42, 5.4%), Şanlıurfa (n\u0026thinsp;=\u0026thinsp;38, 4.8%), and Mardin (n\u0026thinsp;=\u0026thinsp;37, 4.7%). Smaller proportions of participants were recruited from Trabzon (n\u0026thinsp;=\u0026thinsp;29, 3.7%), İstanbul (n\u0026thinsp;=\u0026thinsp;27, 3.4%), Ankara (n\u0026thinsp;=\u0026thinsp;23, 2.9%), and Sakarya (n\u0026thinsp;=\u0026thinsp;19, 2.4%). Further representation included Osmaniye (n\u0026thinsp;=\u0026thinsp;15, 1.9%), Erzincan (n\u0026thinsp;=\u0026thinsp;15, 1.9%), İzmir (n\u0026thinsp;=\u0026thinsp;14, 1.8%), Adana (n\u0026thinsp;=\u0026thinsp;12, 1.5%), Balıkesir (n\u0026thinsp;=\u0026thinsp;10, 1.3%), and Mersin (n\u0026thinsp;=\u0026thinsp;8, 1.0%). A smaller number of participants were recruited from Kırklareli (n\u0026thinsp;=\u0026thinsp;6, 0.8%), Zonguldak (n\u0026thinsp;=\u0026thinsp;6, 0.8%), Isparta (n\u0026thinsp;=\u0026thinsp;5, 0.6%), Kars (n\u0026thinsp;=\u0026thinsp;4, 0.5%), D\u0026uuml;zce (n\u0026thinsp;=\u0026thinsp;4, 0.5%), and Hatay (n\u0026thinsp;=\u0026thinsp;3, 0.4%). In addition, 46 participants (5.9%) were recruited from other provinces, each contributing one or two participants.\u003c/p\u003e \u003cp\u003eFor the interaction analysis component of the study, a subsample of 102 children with ASD and their mothers participated in direct observation sessions. The mean age of the children was 64.98 months (SD\u0026thinsp;=\u0026thinsp;18.17), with ages ranging from 24 to 101 months. The average age at which children received an ASD diagnosis was 28.34 months (SD\u0026thinsp;=\u0026thinsp;10.02). The majority of children in the subsample were male (81.4%).\u003c/p\u003e\n\u003ch3\u003eMeasures\u003c/h3\u003e\n\u003cp\u003e \u003cb\u003eDemographic Information Form.\u003c/b\u003e A structured demographic questionnaire was developed to collect information about family characteristics, children\u0026rsquo;s developmental histories, and technology use patterns. The form included sections on: parental demographic characteristics (age, education level, occupation), child developmental history and diagnostic information, educational and therapeutic services received, household technology use, children\u0026rsquo;s screen exposure (device types, duration of use, and content types), and contextual factors influencing screen use (e.g., during meals, leisure time, or calming situations). The questionnaire was administered digitally using an online survey platform.\u003c/p\u003e \u003cp\u003e \u003cb\u003eMaternal Behavior Rating Scale \u0026ndash; Turkish Version (MBRS-TV).\u003c/b\u003e The MBRS-TV is an observational measure designed to evaluate parental interaction behaviors during parent\u0026ndash;child interactions. Parental interaction behaviors were evaluated using the Maternal Behavior Rating Scale, the Turkish adaptation of the Maternal Behavior Rating Scale (MBRS-TV). The adaptation and psychometric evaluation were conducted by Diken (\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e2009\u003c/span\u003e) with 123 mother\u0026ndash;child dyads whose children were between 18 and 72 months of age and had expressive language delay, mild intellectual disability, or autism. The MBRS-TV is an observational rating scale consisting of 12 items assessing parental behaviors during parent\u0026ndash;child interaction. Exploratory factor analysis indicated that the Turkish version of the scale consisted of three factors (Responsiveness, Affect, and Achievement-oriented/directiveness), explaining 73.40% of the total variance. Internal consistency reliability was assessed using Cronbach\u0026rsquo;s alpha coefficients. The alpha values for the subscales were: Responsive\u0026ndash;Sensitive behavior: α\u0026thinsp;=\u0026thinsp;.86, Affect: α\u0026thinsp;=\u0026thinsp;.87, Achievement-oriented/Directive behavior: α\u0026thinsp;=\u0026thinsp;.61. In using the scale, mother\u0026ndash;child interactions were video-recorded during 5\u0026ndash;10 minute play sessions, in which mothers were instructed to interact with their children as they normally would during play activities. Developmentally appropriate toys were provided to facilitate natural interaction. Items are rated using a 5-point Likert-type scale. Higher scores on the \u003cem\u003eResponsiveness\u003c/em\u003e and \u003cem\u003eAffect\u003c/em\u003e subscales indicate more positive interaction behaviors. For the \u003cem\u003eAchievement-oriented/directiveness\u003c/em\u003e subscale, a score of 3 is considered the optimal interaction level. In scoring this dimension, ratings of 5 are recoded as 1 and ratings of 4 are recoded as 2, following the scoring procedure proposed in the scale manual. The MBRS-TV provides mean scores for each subscale rather than a total score.\u003c/p\u003e \u003cp\u003e \u003cb\u003eChild Behavior Rating Scale \u0026ndash; Turkish Version (CBRS-TV).\u003c/b\u003e The CBRS-TV evaluates children\u0026rsquo;s behavioral engagement during interactions with caregivers. Children\u0026rsquo;s interaction behaviors were assessed using the Child Behavior Rating Scale, the Turkish adaptation of the Child Behavior Rating Scale (CBRS-TV) developed to evaluate children\u0026rsquo;s engagement during parent\u0026ndash;child interaction. The Turkish adaptation was conducted by Diken (\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e2009\u003c/span\u003e) using the same sample of 123 mother\u0026ndash;child dyads. The scale consists of 7 observational items including attention and engagement, persistence, participation, joint attention, initiation, cooperation, and emotional regulation. evaluating children\u0026rsquo;s interaction behaviors in attention and initiation subdomains. The Turkish adaptation of the scale has demonstrated strong validity and reliability. The two factors explained 78.86% of the total variance. Internal consistency reliability coefficients were reported as: Attention factor: α\u0026thinsp;=\u0026thinsp;.79, initiation factor: α\u0026thinsp;=\u0026thinsp;.91, and total scale: α\u0026thinsp;=\u0026thinsp;.90. Item\u0026ndash;total correlation coefficients ranged between .52 and .89, demonstrating strong discrimination between items. Children\u0026rsquo;s behaviors during 10\u0026ndash;15 minute play interactions were evaluated using a 5-point Likert rating system. Higher scores indicate more adaptive and developmentally appropriate interaction behaviors. The Turkish adaptation of the scale has demonstrated strong reliability. These values indicate a high level of internal consistency and support the use of the scale as a reliable measure of child interaction behaviors.\u003c/p\u003e \u003cp\u003e \u003cb\u003eAutism Behavior Assessment Scale (ABAS).\u003c/b\u003e Autism severity was measured using the Autism Behavior Assessment Scale (ABAS), a standardized instrument developed by Diken, Diken, and Isik (2025). The scale was developed based on a large national sample consisting of 1,275 individuals from 14 cities in T\u0026uuml;rkiye. Exploratory factor analysis revealed a four-factor structure consisting of 36 items: Restricted/Repetitive Behaviors and Sensory Sensitivity, Social Interaction, Social Communication, and Atypical Speech Development. The four factors together explain approximately 63% of the total variance. Confirmatory factor analysis indicated good model fit: χ\u0026sup2;/df\u0026thinsp;\u0026asymp;\u0026thinsp;3.1, CFI = .95, TLI = .94, RMSEA = .052, and SRMR = .046. Internal consistency values were also high: Total scale: Cronbach\u0026rsquo;s α\u0026thinsp;=\u0026thinsp;.96 and Subscales: α\u0026thinsp;=\u0026thinsp;.88 \u0026ndash; .94. McDonald\u0026rsquo;s omega coefficients ranged between .89 and .95, further supporting reliability. Criterion validity analyses demonstrated moderate to high correlations with other standardized autism measures (r \u0026asymp; .62 \u0026ndash; .79). These findings indicate that ABAS is a valid and reliable instrument for assessing autism-related behaviors in individuals aged 3\u0026ndash;24 years.\u003c/p\u003e \u003cp\u003e\u003cb\u003eSocial Interaction Assessment Instrument (SIAI-TV).\u003c/b\u003e Children\u0026rsquo;s social interaction behaviors were assessed using the SIAI-TV, the Turkish adaptation of the Autism Screening Instrument for Educational Planning, adapted by Aksoy and Diken (\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e2016\u003c/span\u003e). The instrument is based on a structured observation procedure in which children\u0026rsquo;s behaviors are coded across 48 equal observation intervals. At the end of each 10-second interval, the child\u0026rsquo;s behavior is categorized into one of several behavioral categories, including: Interaction, Independent play, Non-responsiveness, and Negative or aggressive behaviors. The total number of observations within each category is then converted into standardized scores representing typical interaction and autistic interaction patterns. The reliability of the instrument has been reported as KR-21 = .83, indicating acceptable internal consistency for assessing social interaction patterns in children with ASD. In the present study, after the 10\u0026ndash;15 minute mother\u0026ndash;child interaction session used for the MBRS-TV and CBRS-TV assessments was recorded, the SIAI-TV protocol was applied to the same interaction context in accordance with the administration guidelines.\u003c/p\u003e\n\u003ch3\u003eProcedure\u003c/h3\u003e\n\u003cp\u003eData collection consisted of two stages. First, descriptive and demographic data were collected through an online survey distributed via Google Forms. Parents from different regions of T\u0026uuml;rkiye were invited to participate through social media and institutional networks. Second, observational interaction data were collected in special education and rehabilitation centers located in Eskişehir and Konya. Mothers and their children participated in structured play sessions in designated playrooms. During these sessions, mother\u0026ndash;child interactions were video-recorded and later coded using the relevant assessment instruments. Participation in the interaction sessions was voluntary, and families were informed about the study procedures before providing written consent.\u003c/p\u003e \u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003eData Analysis\u003c/h2\u003e \u003cp\u003eDescriptive statistics, including frequencies, percentages, means, and standard deviations, were calculated to summarize demographic characteristics and screen use patterns. To examine relationships among variables, correlation and regression analyses were conducted. Prior to these analyses, the assumptions of statistical tests were evaluated. Normality of the data distribution was assessed using Kolmogorov\u0026ndash;Smirnov and Shapiro\u0026ndash;Wilk tests, as well as skewness and kurtosis values. Depending on whether the data met the assumptions of normality, parametric or non-parametric statistical tests were applied.\u003c/p\u003e \u003cp\u003eTo ensure the reliability of observational data, an inter-rater reliability analysis was conducted for the coding of mother\u0026ndash;child interaction videos. Three trained coders participated in the coding process. Two of the coders were members of the research team who had completed formal certification for the assessment instruments used in the study, and the third coder was an independent doctoral-level researcher in special education who was not involved in the data collection process. Prior to coding, all coders received training on the coding procedures and scoring criteria of the MBRS-TV, CBRS-TV, and SIAI-TV instruments to ensure consistency in interpretation. 40% of the recorded interaction videos were randomly selected and independently coded by the coders to assess inter-rater agreement. Inter-rater reliability was calculated using the formula proposed by Miles and Huberman (\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e1994\u003c/span\u003e): Reliability = (Agreement / Agreement\u0026thinsp;+\u0026thinsp;Disagreement) x 100. The analysis yielded an inter-rater reliability coefficient of 100%, indicating a very high level of agreement among the coders. According to methodological standards in qualitative and observational research, inter-rater reliability values above 80% are considered acceptable (Miles \u0026amp; Huberman, \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e1994\u003c/span\u003e). Therefore, the obtained reliability level suggests that the coding procedures used in this study were highly consistent and reliable.\u003c/p\u003e \u003c/div\u003e"},{"header":"Results","content":"\u003cdiv id=\"Sec10\" class=\"Section2\"\u003e \u003ch2\u003eScreen Use Patterns Among Children with ASD and Parental Observations During Screen Use\u003c/h2\u003e \u003cp\u003eThe first hypothesis examined the patterns of screen use among children diagnosed with ASD. Descriptive statistics indicated that children\u0026rsquo;s average daily screen exposure was 2.13 hours (SD\u0026thinsp;=\u0026thinsp;2.09). Parental screen use was also relatively high, with mothers reporting an average daily screen use of 2.76 hours (SD\u0026thinsp;=\u0026thinsp;2.21) and fathers 4.43 hours (SD\u0026thinsp;=\u0026thinsp;3.50).\u003c/p\u003e \u003cp\u003eCorrelation analyses revealed that maternal screen use was positively associated with children\u0026rsquo;s screen exposure (r = .231, p \u0026lt; .01), while paternal screen use also showed a weaker but significant relationship (r = .124, p \u0026lt; .05). These findings suggest that family digital media habits may influence children\u0026rsquo;s screen exposure.\u003c/p\u003e \u003cp\u003eRegarding content types, cartoons were the most frequently viewed media content (32.5%), followed by general videos (18.9%), educational videos (13.3%), and music videos (11.0%). Smaller proportions of children watched gaming videos (5.6%), cooking videos (2.8%), and documentaries (2.3%), while 21.1% of parents reported that their children did not regularly watch video content.\u003c/p\u003e \u003cp\u003eQualitative responses from parents revealed several behavioral patterns observed during screen use. Four main themes emerged: (1) positive emotional responses, (2) disengagement from the surrounding environment, (3) behavioral stimulation and hyperactivity, and (4) reduced social communication. Many parents reported that screen use generated positive emotional reactions. For example: \u0026ldquo;When the tablet is turned on, he becomes very happy and watches attentively for a long time.\u0026rdquo; (P12). Similarly, another parent reported that technology sometimes helped regulate their child\u0026rsquo;s emotions: \u0026ldquo;When he becomes restless, turning on cartoons helps him calm down.\u0026rdquo; (P37). However, parents also frequently described reduced environmental awareness during screen use: \u0026ldquo;When he holds the device, he disconnects from the world. Even when we call his name, he does not respond.\u0026rdquo; (P45). Overall, 51.2% of children appeared happy during screen use, while 35.9% appeared disengaged from the surrounding environment, 21.9% displayed hyperactive behaviors, and 20.3% showed irritability or restlessness.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec11\" class=\"Section2\"\u003e \u003ch2\u003eAutism Severity Levels of Children with ASD and Relationship Between Screen Use and Autism Severity\u003c/h2\u003e \u003cp\u003eThe second hypothesis examined the severity levels of autism symptoms using the ABAS. The ABAS provides standardized scores with a mean of 100 and a standard deviation of 15. Results showed that the restricted and repetitive behaviors dimension had a mean score of M\u0026thinsp;=\u0026thinsp;94.18 (SD\u0026thinsp;=\u0026thinsp;12.75). The social interaction dimension had a mean score of M\u0026thinsp;=\u0026thinsp;92.50 (SD\u0026thinsp;=\u0026thinsp;15.74), indicating slightly lower social interaction performance relative to normative expectations. The social communication dimension had an average score of M\u0026thinsp;=\u0026thinsp;100.07 (SD\u0026thinsp;=\u0026thinsp;22.85), suggesting performance close to the normative mean but with high variability among participants. The developmentally atypical speech dimension had a mean score of M\u0026thinsp;=\u0026thinsp;95.27 (SD\u0026thinsp;=\u0026thinsp;11.72). The overall ABAS score averaged M\u0026thinsp;=\u0026thinsp;92.56 (SD\u0026thinsp;=\u0026thinsp;14.76). In terms of support needs, 41.75% of children were classified as \u0026ldquo;possible risk,\u0026rdquo; 27.18% as \u0026ldquo;support needed,\u0026rdquo; 24.27% as \u0026ldquo;substantial support needed,\u0026rdquo; and 6.80% as \u0026ldquo;very substantial support needed.\u0026rdquo;\u003c/p\u003e \u003cp\u003eThe third hypothesis examined the relationship between screen exposure and autism symptom severity. Pearson correlation analyses revealed a moderate positive relationship between daily screen exposure and ABAS scores (r = .41, p \u0026lt; .01). This result indicates that higher levels of screen exposure were associated with greater autism symptom severity. When device types were analyzed separately, tablet use was significantly associated with autism severity (r = .36, p \u0026lt; .01), whereas television viewing showed a weaker but significant relationship (r = .28, p \u0026lt; .05). A multiple regression analysis was conducted to determine whether screen use predicted autism severity. The model was statistically significant, F(3,96)\u0026thinsp;=\u0026thinsp;8.72, p \u0026lt; .001, explaining 21% of the variance in autism severity scores (R\u0026sup2; = .21). Daily screen exposure emerged as the strongest predictor (β\u0026thinsp;=\u0026thinsp;.34, p \u0026lt; .01), followed by tablet use (β\u0026thinsp;=\u0026thinsp;.27, p \u0026lt; .05), while television viewing did not significantly predict autism severity (β\u0026thinsp;=\u0026thinsp;.15, p \u0026gt; .05).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec12\" class=\"Section2\"\u003e \u003ch2\u003eMaternal Interaction Behaviors and Children\u0026rsquo;s Interaction Behaviors During Mother\u0026ndash;Child Interaction\u003c/h2\u003e \u003cp\u003eThe fourth hypothesis examined mothers\u0026rsquo; interaction behaviors with their children. Results showed that 28% of mothers demonstrated low levels of responsiveness, 46% moderate levels, and 26% high levels. For the affect dimension, 24% of mothers were classified as low, 49% moderate, and 27% high emotionally expressive. Similarly, achievement-oriented/directive behaviors were mostly observed at moderate levels, with 31% low, 44% moderate, and 25% high scores. These results indicate that most mothers displayed moderate levels of interaction behaviors, with relatively fewer mothers demonstrating consistently high levels of responsive interaction.\u003c/p\u003e \u003cp\u003eThe fifth hypothesis examined children\u0026rsquo;s interaction behaviors during mother\u0026ndash;child interactions. Results indicated that 30% of children demonstrated low levels of attention behaviors, 45% moderate levels, and 25% high levels. Similarly, initiation behaviors were low in 34% of children, moderate in 41%, and high in 25%. When overall interaction behaviors were examined, 29% of children were classified as low, 47% moderate, and 24% high. These findings suggest that children with ASD generally demonstrate moderate levels of interaction behaviors, while high levels of interaction engagement remain relatively limited.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec13\" class=\"Section2\"\u003e \u003ch2\u003eRelationship Between Maternal and Child Interaction Behaviors\u003c/h2\u003e \u003cp\u003eThe sixth hypothesis examined the relationship between maternal interaction behaviors and children\u0026rsquo;s interaction behaviors. Pearson correlation analyses revealed that maternal responsiveness was positively associated with children\u0026rsquo;s attention behaviors (r = .38, p \u0026lt; .01). Similarly, maternal emotional expressiveness was positively associated with children\u0026rsquo;s initiation behaviors (r = .34, p \u0026lt; .01). A weaker but significant relationship was also found between achievement-oriented maternal behaviors and children\u0026rsquo;s overall interaction behaviors (r = .27, p \u0026lt; .05). These results suggest that higher-quality maternal interaction behaviors are associated with greater child engagement during interaction.\u003c/p\u003e \u003cp\u003e \u003cb\u003eSocial Interaction Behaviors of Children with ASD and Relationships Among Screen Use, Parent\u0026ndash;Child Interaction, and Social Interaction Behaviors\u003c/b\u003e \u003c/p\u003e \u003cp\u003eAnalyses of social interaction behaviors indicated that autistic interaction behaviors had a higher mean score (M\u0026thinsp;=\u0026thinsp;3.02) compared with typical social interaction behaviors (M\u0026thinsp;=\u0026thinsp;2.47). Distribution analyses showed that 44% of children displayed moderate levels of autistic interaction behaviors, while typical social interaction behaviors were predominantly observed at low levels (38%). Only 22% of children demonstrated high levels of typical social interaction behaviors, suggesting that many children experienced difficulties initiating and maintaining typical social interactions.\u003c/p\u003e \u003cp\u003eCorrelation analyses were conducted to examine the relationships among screen use, autism severity, parent interaction behaviors, child interaction behaviors, and social interaction behaviors. Results indicated that daily screen exposure was positively associated with autistic interaction behaviors (r = .37, p \u0026lt; .01) and negatively associated with attention (r\u0026thinsp;=\u0026thinsp;\u0026minus;\u0026thinsp;.34, p \u0026lt; .01), interaction initiation (r\u0026thinsp;=\u0026thinsp;\u0026minus;\u0026thinsp;.29, p \u0026lt; .05), and overall interaction behaviors (r\u0026thinsp;=\u0026thinsp;\u0026minus;\u0026thinsp;.31, p \u0026lt; .01). Device-specific analyses revealed that tablet use was negatively associated with typical social interaction behaviors (r\u0026thinsp;=\u0026thinsp;\u0026minus;\u0026thinsp;.28, p \u0026lt; .05) and smartphone use was negatively associated with children\u0026rsquo;s attention levels (r\u0026thinsp;=\u0026thinsp;\u0026minus;\u0026thinsp;.30, p \u0026lt; .05). Finally, parental interaction behaviors were also associated with screen exposure. Maternal responsiveness was negatively correlated with children\u0026rsquo;s screen use (r\u0026thinsp;=\u0026thinsp;\u0026minus;\u0026thinsp;.26, p \u0026lt; .05), and maternal emotional expressiveness showed a similar negative association (r\u0026thinsp;=\u0026thinsp;\u0026minus;\u0026thinsp;.24, p \u0026lt; .05). These findings suggest that higher screen exposure may be associated with reduced social interaction behaviors, whereas responsive parenting may mitigate excessive screen exposure and support more adaptive interaction patterns.\u003c/p\u003e \u003c/div\u003e"},{"header":"Discussion","content":"\u003cp\u003eThe present study examined screen use patterns among children with ASD and explored how these patterns relate to parent\u0026ndash;child interaction and children\u0026rsquo;s social interaction skills. The findings indicated that children with ASD were exposed to digital media for an average of approximately two hours per day. Furthermore, children\u0026rsquo;s screen use was positively associated with both maternal and paternal screen use. These findings suggest that children\u0026rsquo;s digital media habits are embedded within broader family media environments. In addition, research on problematic media use suggests that excessive screen engagement in children may display characteristics similar to addictive behavioral patterns, including preoccupation with digital media and difficulties disengaging from screen-based activities (Domoff et al., \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e2019\u003c/span\u003e).\u003c/p\u003e \u003cp\u003ePrevious research has consistently demonstrated that children\u0026rsquo;s screen use behaviors are closely related to parental media practices and the overall family media ecology (McDaniel \u0026amp; Radesky, 2020; Radesky et al., 2020). Parents often model technology use patterns that children subsequently adopt, and family routines surrounding technology may shape children\u0026rsquo;s exposure to digital media. In families of children with ASD, digital media may also serve additional functions, such as managing behavioral challenges or supporting emotional regulation in daily caregiving contexts. Qualitative findings from parental reports further illustrated this dynamic. Many parents indicated that digital media sometimes helped calm their children or sustain their attention. Similar observations have been reported in previous studies, which suggest that parents of children with ASD may use digital devices as tools for behavioral management or emotional regulation (McDaniel \u0026amp; Radesky, \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e2018\u003c/span\u003e). However, such practices may also reduce opportunities for direct social interaction between parents and children.\u003c/p\u003e \u003cp\u003eAnother important finding of the study was the positive association between children\u0026rsquo;s screen exposure and autism symptom severity. Higher daily screen exposure was associated with higher autism-related behavioral scores. In addition, tablet use was more strongly associated with autism severity than television viewing. These findings align with previous studies suggesting that children with ASD often show strong preferences for screen-based media environments (Mazurek \u0026amp; Wenstrup, \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e2013\u003c/span\u003e). Digital platforms frequently provide predictable, repetitive, and visually stimulating experiences, which may align with the cognitive and behavioral preferences commonly observed in individuals with autism. More recent research has also suggested that increased exposure to screen-based media may be associated with behavioral and developmental outcomes in children with ASD (McDaniel \u0026amp; Radesky, \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e2018\u003c/span\u003e). However, it is important to interpret these relationships cautiously. The present study employed a cross-sectional design, which limits causal interpretations. It is possible that children with higher levels of autism-related characteristics are more likely to engage in screen-based activities, rather than screen exposure causing increased autism symptoms.\u003c/p\u003e \u003cp\u003eThe findings also highlighted the critical role of parent\u0026ndash;child interaction in children\u0026rsquo;s social and behavioral outcomes. Maternal responsiveness and affect (emotional expressiveness) were positively associated with children\u0026rsquo;s attention behaviors and interaction initiation during mother\u0026ndash;child interaction sessions. These findings are consistent with earlier research demonstrating that responsive parenting and emotionally supportive interaction environments contribute significantly to social communication development in children with ASD (Siller \u0026amp; Sigman, \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e2008\u003c/span\u003e). Parent\u0026ndash;child interaction represents a key context in which children develop joint attention, language skills, and social reciprocity. Recent studies have also emphasized that disruptions in parent\u0026ndash;child interaction caused by digital technology use\u0026mdash;often referred to as \u0026ldquo;technoference\u0026rdquo;\u0026mdash;may interfere with children\u0026rsquo;s opportunities for social engagement and communication (McDaniel \u0026amp; ; Radesky \u0026amp; Christakis \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e2016\u003c/span\u003e, 2020). The present findings extend this literature by showing that higher levels of responsive parenting are associated with lower levels of children\u0026rsquo;s screen exposure. These results suggest that strengthening parent\u0026ndash;child interaction quality may not only support children\u0026rsquo;s social development but may also reduce reliance on digital devices as tools for behavioral management.\u003c/p\u003e \u003cp\u003eThe study further revealed that higher levels of screen exposure were associated with lower levels of attention, interaction initiation, and overall interaction performance. Additionally, screen exposure was positively associated with autistic interaction behaviors. These findings are consistent with research suggesting that excessive screen exposure may reduce opportunities for social interaction and experiential learning during early childhood (Madigan et al., \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e2019\u003c/span\u003e; Stiglic \u0026amp; Viner, \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e2019\u003c/span\u003e). For children with ASD, who already experience challenges in social communication, reduced opportunities for live interaction may further limit the development of essential social skills. At the same time, parents reported that digital media sometimes supported certain developmental outcomes. Some children reportedly learned songs, basic concepts, imitation behaviors, and simple communication expressions through digital media content. These findings are consistent with research suggesting that technology can support learning when used intentionally and in structured ways (Odom et al., \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e2015\u003c/span\u003e). Therefore, the developmental implications of digital media use may depend not only on-screen time but also on the quality of content, parental involvement, and the context of media use.\u003c/p\u003e \u003cp\u003eThis study contributes to the growing literature on digital media use in children with ASD by integrating screen use, autism severity, parent\u0026ndash;child interaction, and children\u0026rsquo;s social interaction skills within a single analytical framework. Previous studies have typically examined screen exposure as an isolated behavioral variable. In contrast, the present study highlights the importance of considering family interaction processes when interpreting the developmental implications of digital media use. The findings support an ecological perspective in which children\u0026rsquo;s developmental outcomes emerge from dynamic interactions between individual characteristics and family relational environments (Bronfenbrenner \u0026amp; Morris, \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e2006\u003c/span\u003e). The observed relationships between screen use, parental interaction behaviors, and children\u0026rsquo;s interaction competence suggest that digital media exposure may influence developmental outcomes both directly and indirectly through family interaction processes.\u003c/p\u003e \u003cp\u003eThe findings of the study also have several practical implications for families, educators, and professionals working with children with ASD. First, interventions addressing digital media use should focus not only on limiting screen time but also on promoting balanced media routines that encourage face-to-face interaction and shared activities between parents and children. Second, parent education programs may play an important role in helping families develop strategies for managing children\u0026rsquo;s screen use. Providing guidance on appropriate media content, co-viewing practices, and structured media routines may help families use digital media in ways that support children\u0026rsquo;s learning and development. Third, strengthening parent\u0026ndash;child interaction should be considered a central component of interventions designed for children with ASD. Programs that encourage shared play, joint attention, and responsive communication may simultaneously support children\u0026rsquo;s social development and reduce excessive reliance on digital devices. Finally, clinicians and educators should consider the broader family media environment when assessing children\u0026rsquo;s screen use behaviors. Understanding how digital technologies are integrated into daily family routines may provide valuable insights into children\u0026rsquo;s developmental experiences.\u003c/p\u003e \u003cdiv id=\"Sec15\" class=\"Section2\"\u003e \u003ch2\u003eLimitations and Future Research Directions\u003c/h2\u003e \u003cp\u003eDespite the contributions of the present study, several limitations should be acknowledged. First, the study employed a cross-sectional correlational design, which limits the ability to draw causal conclusions about the relationships between screen use, autism severity, parent\u0026ndash;child interaction, and children\u0026rsquo;s social interaction skills. Although significant associations were observed among these variables, it cannot be determined whether increased screen exposure contributes to interaction difficulties or whether children with more pronounced developmental challenges are more likely to engage in screen-based activities. Future research employing longitudinal or experimental designs would be valuable in clarifying the directionality of these relationships. Second, a portion of the data relied on parent-reported measures, particularly regarding children\u0026rsquo;s screen use patterns and behavioral responses during technology use. Although parental reports provide important insights into children\u0026rsquo;s daily routines and family contexts, such reports may be subject to recall bias or subjective interpretation. Future studies may benefit from incorporating objective measures of screen use, such as digital usage tracking or ecological momentary assessment methods. Third, although the overall sample size was relatively large, the observational interaction data were obtained from a smaller subsample of participants. This limitation may restrict the generalizability of findings related to observed parent\u0026ndash;child interaction behaviors. Future studies should consider collecting observational interaction data from larger and more diverse samples to strengthen the robustness of these findings. Fourth, the study was conducted within a specific cultural and national context, which may limit the generalizability of the findings to other cultural environments. Family technology practices, parenting styles, and access to digital media may vary across societies. Therefore, cross-cultural research is needed to examine whether similar patterns emerge in different sociocultural contexts. Finally, although the present study examined several key variables, other potentially relevant factors were not included in the analyses. For example, variables such as socioeconomic status, parental stress, parental digital literacy, and the specific content and context of media use may also influence children\u0026rsquo;s developmental outcomes. Future research incorporating these contextual factors may provide a more comprehensive understanding of the complex relationships between digital media use and developmental processes in children with ASD.\u003c/p\u003e \u003c/div\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eEthical Approval:\u003c/strong\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u0026ldquo;The study was conducted in accordance with the principles of the Declaration of Helsinki, and the research protocol was approved by the Ethics Committee of Anadolu University (\u003cem\u003eApproval Code:\u0026nbsp;\u003c/em\u003e\u003cem\u003e732353\u003c/em\u003e\u003cem\u003e; Approval Date: May 28, 2024).\u003c/em\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding:\u003c/strong\u003e This study was supported by Scientific Research Coordination Unit of Anadolu University under the project number SCB-2024-2482.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eInformed consent:\u003c/strong\u003e Participation was voluntary, and respondents indicated consent within the survey.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eData availability statement:\u0026nbsp;\u003c/strong\u003eThe data are available from the corresponding author upon reasonable request.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthors Contributions:\u003c/strong\u003e Authors contributed the study as follows: \u0026ldquo;Conceptualization, IHD, OD, EK; methodology, IHD, MDS, DE, ME, EK, UOG, AK, GI, AS; formal analysis, IHD, EK, UOG, AK, AS, GI; \u0026nbsp;investigation, IHD, GI, AS, UOG, AK; resources, IHD, OD, ME, DE, AS, GI, AK; data curation, IHD, GI, AS, UOG, AK; writing\u0026mdash;original draft preparation, IHD, MDS; writing\u0026mdash;review and editing, OD, MDS, DE, ME, EK, UOG, AK, GI, AS; project administration, IHD, OD, EK, AS, AK, GI, UOG. All authors have read and agreed to the published version of the manuscript.\u0026rdquo;\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConflict of Interest Statement\u003c/strong\u003e\u003cstrong\u003e:\u003c/strong\u003e The authors declare no conflicts of interest.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eSupplementary Materials:\u0026nbsp;\u003c/strong\u003eThere is no supplementary material.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eInformed Consent Statement:\u0026nbsp;\u003c/strong\u003eInformed consent was obtained from all subjects involved in the study.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAcknowledgments:\u003c/strong\u003e We owe a sincere thanks to the participants who took part in this study.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eAksoy V, Diken İH. 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Prev Med Rep. 2018;12:271\u0026ndash;83. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1016/j.pmedr.2018.10.003\u003c/span\u003e\u003cspan address=\"10.1016/j.pmedr.2018.10.003\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"bmc-psychology","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"psyo","sideBox":"Learn more about [BMC Psychology](http://bmcpsychology.biomedcentral.com/)","snPcode":"","submissionUrl":"","title":"BMC Psychology","twitterHandle":"BMC_series","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"Autism spectrum disorder, screen addiction, parent–child interaction, social interaction, digital media use","lastPublishedDoi":"10.21203/rs.3.rs-9124767/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-9124767/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eThe rapid expansion of digital technologies has transformed children\u0026rsquo;s everyday environments, raising concerns about excessive screen use and its potential developmental implications. Although research on screen use has increased substantially, relatively little is known about how screen addiction may relate to family interaction processes among children with Autism Spectrum Disorder (ASD). The present study aimed to examine the relationships among screen addiction, autism severity, parent\u0026ndash;child interaction behaviors, and children\u0026rsquo;s social interaction behaviors in children diagnosed with ASD. The study employed a correlational research design. Participants included 784 parent\u0026ndash;child pairs recruited from multiple provinces across T\u0026uuml;rkiye. Data were collected through a demographic questionnaire, the Autism Behavior Assessment Tool (ABAS), and parent-reported measures of children\u0026rsquo;s screen use patterns. In addition, observational interaction data were obtained from a subsample of 102 mother\u0026ndash;child dyads using the Maternal Behavior Rating Scale\u0026ndash;Turkish Version (MBRS-TV), the Child Behavior Rating Scale\u0026ndash;Turkish Version (CBRS-TV), and the Social Interaction Assessment Instrument (SIAI-TV). The findings indicated that children\u0026rsquo;s screen use was positively associated with autism severity and autistic interaction behaviors, while negatively associated with attention, interaction initiation, and overall interaction behaviors. Maternal interaction behaviors were positively associated with children\u0026rsquo;s interaction behaviors and negatively associated with children\u0026rsquo;s screen use. These results suggest that higher levels of screen exposure may be related to reduced social interaction opportunities among children with ASD. Overall, the findings highlight the importance of considering family interaction processes when evaluating digital media use in children with ASD and suggest that balanced media routines and responsive parenting may support healthier developmental outcomes.\u003c/p\u003e","manuscriptTitle":"Screen Use, Parent–Child Interaction, and Social Interaction Behaviors in Children with Autism Spectrum Disorder","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2026-04-07 18:01:40","doi":"10.21203/rs.3.rs-9124767/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"editorInvitedReview","content":"","date":"2026-05-06T10:05:30+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"248783221699915860070869069066193309235","date":"2026-04-26T21:16:52+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"195990776124674082455850467397929479572","date":"2026-04-26T06:33:27+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2026-04-02T04:40:24+00:00","index":"","fulltext":""},{"type":"editorInvited","content":"","date":"2026-03-19T13:34:44+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2026-03-18T10:18:46+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2026-03-18T10:18:43+00:00","index":"","fulltext":""},{"type":"submitted","content":"BMC Psychology","date":"2026-03-14T19:48:19+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"bmc-psychology","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"psyo","sideBox":"Learn more about [BMC Psychology](http://bmcpsychology.biomedcentral.com/)","snPcode":"","submissionUrl":"","title":"BMC Psychology","twitterHandle":"BMC_series","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"837dc18b-7bc7-418b-99ad-86f521fc735f","owner":[],"postedDate":"April 7th, 2026","published":true,"recentEditorialEvents":[{"type":"editorInvitedReview","content":"","date":"2026-05-06T10:05:30+00:00","index":61,"fulltext":""}],"rejectedJournal":[],"revision":"","amendment":"","status":"under-review","subjectAreas":[],"tags":[],"updatedAt":"2026-04-07T18:01:40+00:00","versionOfRecord":[],"versionCreatedAt":"2026-04-07 18:01:40","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-9124767","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-9124767","identity":"rs-9124767","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}