The Digital Technology Preoccupation Scale<\/strong> (DTPS; Topi\u0107, Brklja\u010di\u0107, & Braj\u0161a-\u017dganec, 2023<\/a>) is a psychometrically validated, child-centric self-report instrument designed to quantify the degree of cognitive preoccupation, mental absorption, and psychological salience that elementary school children attribute to digital technology in their everyday lives. Developed in response to growing empirical dissatisfaction with traditional, quantitative measures of screen time (such as daily hours logged on devices), the DTPS shifts analytical focus toward the internal, cognitive-affective engagement of the child. Comprising five concise, age-appropriate items, the scale captures the frequency with which digital devices, online activities, video games, and multimedia content occupy a child’s thoughts, anticipate their daily routines, and intrude upon offline activities, such as schoolwork, family meals, and peer interactions.<\/p>\n The scale was developed through a comprehensive literature synthesis examining children\u2019s media cultures (Buckingham, 2006<\/a>; Livingstone & Bovill, 2001) and experiential insights drawn from direct fieldwork with children (Topi\u0107 et al., 2023<\/a>). Psychometric evaluation was conducted on a normative sample of elementary school pupils aged 8 to 13 years old across primary educational institutions in Croatia. Exploratory and confirmatory factor analyses verified a robust, unidimensional factor structure explaining 56.7% of the total variance, confirming that cognitive preoccupation operates as a coherent, unified latent construct in childhood. The internal consistency of the scale demonstrated strong reliability, yielding a Cronbach\u2019s alpha<\/a> of .802, which is remarkably high for a brief five-item measure administered to young populations.<\/p>\n Empirical findings utilizing the DTPS demonstrate that cognitive preoccupation with digital technology represents a distinct psychological phenomenon from objective device usage duration. Crucially, research indicates that preoccupation serves as a more powerful, nuanced predictor of children\u2019s subjective well-being, peer relations, and life satisfaction than crude metrics of duration. Consequently, the DTPS represents an indispensable, methodologically rigorous psychometric tool for developmental psychologists, educational researchers, pediatric mental health professionals, and media scholars seeking to evaluate the cognitive footprint of modern digital environments.<\/p>\n Digital Technology Preoccupation Scale, cognitive preoccupation, childhood development, screen time, media psychology, digital technology, psychometrics, elementary school children, cognitive absorption, subjective well-being, life satisfaction, human-computer interaction<\/p>\n The Digital Technology Preoccupation Scale was developed and validated by a multidisciplinary team of developmental and social psychologists affiliated with the Institute of Social Sciences Ivo Pilar<\/strong> in Zagreb, Croatia:<\/p>\n The primary purpose of the Digital Technology Preoccupation Scale is to provide an empirically sound, psychometrically robust, and developmentally tailored instrument capable of quantifying the psychological weight, mental absorption, and cognitive prominence that children ascribe to digital devices (e.g., smartphones, tablets, gaming consoles, computers). Over the past two decades, developmental science has grappled with the pervasive integration of digital technologies into youth culture. Historically, both clinical paradigms and empirical investigations have relied heavily on quantitative metrics, specifically \u201cscreen time\u201d\u2014defined as the absolute number of hours and minutes spent looking at digital displays per day (American Psychological Association, 2020<\/a>). However, an emerging body of critical literature in media psychology and pediatrics has underscored the severe limitations of duration-focused paradigms (Przybylski & Weinstein, 2019<\/a>).<\/p>\n Screen time metrics inherently treat all digital engagement as homogeneous, failing to differentiate between educational utilization, passive consumption, creative production, and social connectivity. More importantly, crude screen time indices overlook the intrapsychic dimension of media use: the extent to which digital technology dominates a child\u2019s internal cognitive life when they are not<\/em> actively using devices. The DTPS was purposefully constructed to fill this critical methodological void. Rather than capturing physical interaction, the scale measures cognitive preoccupation<\/strong>\u2014a state in which children continuously reflect upon past digital experiences, mentally plan future gaming or browsing sessions, experience intrusive thoughts about digital platforms during non-digital tasks, and struggle to disengage their attention from virtual environments.<\/p>\n The clinical and educational applications of the DTPS are manifold. In educational settings, heightened preoccupation serves as a vital early indicator of attentional fragmentation and academic disengagement. Children whose cognitive resources are heavily invested in anticipating video game levels or monitoring social media alerts frequently exhibit reduced executive functioning and impaired working memory performance during classroom instruction. In clinical and counseling contexts, the scale functions as an assessment tool that distinguishes normative, enthusiastic media consumption from problematic, sub-clinical addictive patterns. Unlike adult-focused Internet addiction<\/a> scales that impose pathologizing criteria (e.g., severe withdrawal, deceit, functional collapse), the DTPS captures a developmentally normative continuum of cognitive salience that can identify children at risk of escalating toward compulsive media use before severe socio-emotional impairment occurs.<\/p>\n From a theoretical perspective, the DTPS addresses the growing demand for child-centered research methodologies. Rather than relying entirely on parental proxy reports\u2014which are notoriously inaccurate regarding children’s internal states and subjective values\u2014the scale draws directly upon children\u2019s self-reported experiences, validating their subjective perceptions of media importance in late childhood and early adolescence.<\/p>\n The central construct operationalized by the Digital Technology Preoccupation Scale is digital technology preoccupation<\/strong>, conceptualized as a unidimensional, cognitive-affective state characterized by continuous mental immersion, prospective anticipation, and perseverative ideation regarding digital media and interactive devices. In psychometric literature, preoccupation is grounded in the broader cognitive architecture of attentional bias<\/a>, intrusive thinking, and cognitive salience (Griffiths, 2005<\/a>).<\/p>\n Although the DTPS functions empirically as a single-factor instrument, the underlying construct encompasses several inter-related cognitive and affective processes that manifest across the five items:<\/p>\n Crucially, the construct of preoccupation must be distinguished from quantitative device usage (screen time). A child may engage with a computer for three hours to complete a school project without developing cognitive preoccupation; conversely, a child subject to strict parental screen time limits of thirty minutes may spend the remainder of the day completely immersed in thoughts, fantasies, and plans regarding their digital devices. The DTPS isolates this cognitive-emotional footprint, demonstrating that psychological involvement\u2014rather than mere clock-time\u2014is the active ingredient linking technology exposure to child well-being and developmental adjustment.<\/p>\n The conceptual foundation of the Digital Technology Preoccupation Scale intersects multiple influential frameworks within developmental psychology<\/a>, media ecology, and cognitive neuroscience.<\/p>\n At the theoretical core of preoccupation is Mark Griffiths’ (2005<\/a>) Components Model of Addiction<\/em>, which posits six core dimensions underlying problematic behaviors: salience, mood modification, tolerance, withdrawal, conflict, and relapse. The DTPS isolates the foundational component: salience<\/strong>. According to Griffiths, cognitive salience occurs when a particular activity becomes the most important activity in an individual\u2019s life, dominating their thinking (preoccupation and cognitive distortions), feelings (cravings), and behavior (deterioration of alternative pursuits). Even when the individual is not physically engaged in the behavior, they are continuously thinking about the next time they will be. By focusing specifically on cognitive salience rather than the destructive socio-pathological consequences of late-stage addiction, the DTPS provides an age-appropriate lens for evaluating youth who exhibit early cognitive immersion without necessarily fulfilling clinical criteria for psychiatric behavioral disorders.<\/p>\n Complementing addiction paradigms, the scale draws upon positive and organizational models of human-computer interaction, specifically the theory of Cognitive Absorption<\/em> (Agarwal & Karahanna, 2000<\/a>), which builds upon Csikszentmihalyi\u2019s concept of Flow<\/a>. Cognitive absorption is defined as a state of deep involvement with software and digital technology, underpinned by temporal dissociation, focused immersion, heightened enjoyment, and perceived control. When children experience profound cognitive absorption during interactive gaming or social media use, the neural reward circuitry reinforces mental representations of these activities. Consequently, the child\u2019s default cognitive processing mode outside the digital sphere defaults to rehearsal and prospective ideation regarding those high-reward experiences.<\/p>\n The scale\u2019s focus on children aged 8 to 13 is firmly grounded in developmental neuroscience, specifically the Dual-Systems Model<\/em> of adolescent brain development (Steinberg, 2008<\/a>; Casey et al., 2011<\/a>). During middle childhood and early adolescence, the subcortical dopaminergic reward system (notably the ventral striatum) undergoes rapid development and heightened sensitivity to socio-emotional and novel stimuli. In contrast, the prefrontal cortex\u2014responsible for top-down cognitive control, attentional switching, and impulse inhibition\u2014matures protracted into early adulthood. Interactive digital technologies are intentionally engineered with variable reward schedules, gamified notifications, and hyper-stimulating sensory inputs that maximally stimulate the maturing limbic system. Elementary school children naturally lack fully developed inhibitory control mechanisms to suppress intrusive thoughts related to these rewarding stimuli, rendering them uniquely vulnerable to persistent cognitive preoccupation.<\/p>\n Finally, the DTPS is situated within Uses and Gratifications Theory<\/a> (Blumler & Katz, 1974) and contemporary sociology of childhood (Buckingham, 2006<\/a>; Livingstone & Bovill, 2001). This perspective views children not as passive recipients of technological conditioning, but as active agents who use digital tools to fulfill fundamental psychological needs: autonomy, competence, identity exploration, and peer connection (Ryan & Deci, 2000<\/a>). Preoccupation reflects the substantial psychological and subjective value children assign to the digital realm as a primary arena for play, agency, and social affirmation.<\/p>\n The psychometric validity of the Digital Technology Preoccupation Scale was rigorously evaluated in a cross-sectional investigation involving elementary school children across two distinct counties in Croatia (Topi\u0107, Brklja\u010di\u0107, & Braj\u0161a-\u017dganec, 2023<\/a>). Validity assessments focused on content validity, construct validity, and criterion-related predictive validity regarding child developmental outcomes.<\/p>\n Content validity was established through an iterative, two-stage developmental process. First, the authors conducted a systematic synthesis of foundational literature addressing child-computer interaction, digital literacy, and children’s everyday media environments (Buckingham, 2006<\/a>; Fitton et al., 2013; Hutchby & Moran-Ellis, 2001; Livingstone & Bovill, 2001). Second, items were formulated based on qualitative and empirical data obtained from children’s direct expressions regarding digital technology in their lives, drawn from prior research projects (e.g., Consortium of the ‘ADD-Free Training’ project, 2022; Kotrla Topi\u0107 & Perkovi\u0107 Kova\u010devi\u0107, 2017). The final five items reflect authentic, child-friendly linguistic phrasings that preserve ecological validity while capturing internal psychological processes without technical jargon.<\/p>\n Construct validity was confirmed via exploratory and confirmatory factor analytic procedures. The five items converged decisively onto a single common factor representing digital technology preoccupation, exhibiting robust communalities and salient factor loadings (all exceeding accepted psychometric thresholds > .60). The unidimensional structure demonstrated that children do not distinguish between prospective anticipation and retrospective immersion; rather, cognitive preoccupation operates as a coherent, unified cognitive schema<\/span>.<\/p>\n The criterion-related validity of the DTPS was evaluated by examining its predictive power regarding children\u2019s subjective well-being<\/a> and life satisfaction (Topi\u0107 et al., 2023<\/a>). In hierarchical regression models controlling for socio-demographic covariates and raw device screen time, the DTPS emerged as a statistically significant predictor of children’s overall life satisfaction and domain-specific satisfaction (including self-perception, peer relationships, and family functioning).<\/p>\n Crucially, while sheer volume of digital technology use (hours per day) demonstrated negligible or weak relationships with child life satisfaction, cognitive preoccupation exhibited meaningful predictive variance. High preoccupation scores were consistently associated with lower life satisfaction, diminished emotional well-being, and heightened interpersonal strain. These findings confirmed the scale\u2019s incremental and construct validity, establishing that internal cognitive absorption is psychologically distinct from, and developmentally more impactful than, behavioral device usage duration.<\/p>\n The reliability of the Digital Technology Preoccupation Scale has been demonstrated through empirical assessments of internal consistency<\/a> within normative school-aged populations.<\/p>\n In the primary psychometric validation study conducted by Topi\u0107, Brklja\u010di\u0107, and Braj\u0161a-\u017dganec (2023)<\/a> among Croatian elementary school students aged 8 to 13 years, the scale exhibited high internal reliability:<\/p>\n In classical test theory, an alpha value exceeding .80 is considered strong, particularly for an ultra-brief instrument comprising only five items. Because Cronbach\u2019s alpha is mathematically dependent upon test length (with fewer items inherently driving down alpha coefficients via the Spearman-Brown prophecy formula), achieving an alpha of .802 with only five items confirms exceptional item homogeneity and high shared variance among the indicators.<\/p>\n Analysis of item-total correlations confirmed that each individual item contributed positively to the total scale reliability, with corrected item-total correlations well above the standard .40 psychometric cutoff. Deletion of any single item did not result in an increase in Cronbach’s alpha, verifying that all five items are essential and mutually reinforcing indicators of the underlying latent construct. The standard error of measurement (SEM) associated with the instrument is low, providing high precision across the central and upper-moderate ranges of the latent trait distribution.<\/p>\n The dimensional structure of the Digital Technology Preoccupation Scale was determined through comprehensive factor analytic protocols designed to evaluate latent dimensionality, item loading patterns, and explained variance (Topi\u0107 et al., 2023<\/a>).<\/p>\n Prior to factor extraction, sample adequacy and data factorability were confirmed using the Kaiser-Meyer-Olkin (KMO) measure of sampling adequacy and Bartlett\u2019s Test of Sphericity. The analysis yielded a statistically significant Bartlett\u2019s test (p<\/em> < .001) and an optimal KMO coefficient, validating the correlation matrix for factor extraction<\/span>.<\/p>\n The confirmation of unidimensionality carries vital practical and theoretical implications. It confirms that cognitive preoccupation in children does not fragment into divergent behavioral or cognitive sub-facets (such as gaming vs. browsing preoccupation). Instead, it operates as a generalized, overarching cognitive orientation toward digital environments. Consequently, researchers and clinicians can confidently sum or average the items into a single composite score representing the child\u2019s global level of digital preoccupation.<\/p>\n The technical specifications, administration parameters, and scoring protocols for the Digital Technology Preoccupation Scale are summarized below:<\/p>\n $$\\text{DTPS Total Score} = \\frac{\\sum_{i=1}^{5} \\text{Item}_i}{5}$$<\/span><\/p>\n \n Dr. Marina Kotrla Topi\u0107<\/strong> Agarwal, R., & Karahanna, E. (2000). Time flies when you’re having fun: Cognitive absorption and beliefs about information technology usage. MIS Quarterly<\/em>, 24(4), 665\u2013694. https:\/\/doi.org\/10.2307\/3250951<\/a><\/p>\n American Psychological Association. (2020). Screen time: Health advisory on social media and technology use in children<\/em>. APA Publishing.<\/p>\n Buckingham, D. (2006). Beyond technology: Children\u2019s learning in the age of digital culture<\/em>. Polity Press.<\/p>\n Casey, B. J., Jones, R. M., & Somerville, L. H. (2011). Braking and accelerating of the adolescent brain. Developmental Cognitive Neuroscience<\/em>, 1(1), 21\u201333. https:\/\/doi.org\/10.1016\/j.dcn.2010.12.002<\/a><\/p>\n Consortium of the ‘ADD-Free Training’ project. (2022). Digital addiction prevention among school children: Transnational report and curriculum guidelines<\/em>. European Commission Erasmus+ Program.<\/p>\n Fitton, D., Read, J. C., & Dempsey, J. (2013). Exploring the design of mobile technologies for teenagers. In Proceedings of the 27th International BCS Human Computer Interaction Conference (HCI 2013)<\/em> (pp. 1\u20136). British Computer Society. https:\/\/doi.org\/10.14236\/ewic\/HCI2013.29<\/a><\/p>\n Griffiths, M. (2005). A \u2018components\u2019 model of addiction within a biopsychosocial framework. Journal of Substance Use<\/em>, 10(4), 191\u2013197. https:\/\/doi.org\/10.1080\/08897070500169009<\/a><\/p>\n Hutchby, I., & Moran-Ellis, J. (2001). Children, technology and culture: The impacts of technologies in children’s everyday lives<\/em>. Routledge.<\/p>\n Kotrla Topi\u0107, M., & Perkovi\u0107 Kova\u010devi\u0107, M. (2017). Digitalna tehnologija u obitelji: Stavovi roditelja i u\u010ditelja [Digital technology in the family: Attitudes of parents and teachers]. Dru\u0161tvena istra\u017eivanja<\/em>, 26(3), 329\u2013348. https:\/\/doi.org\/10.5559\/di.26.3.02<\/a><\/p>\n Livingstone, S., & Bovill, M. (2001). Children and their changing media environment: A European comparative study<\/em>. Lawrence Erlbaum Associates.<\/p>\n Przybylski, A. K., & Weinstein, N. (2019). A large-scale test of the Goldilocks Hypothesis: Quantifying the relations between screens and the mental well-being of adolescents. Psychological Science<\/em>, 28(2), 204\u2013215. https:\/\/doi.org\/10.1177\/0956797616678438<\/a><\/p>\n Ryan, R. M., & Deci, E. L. (2000). Self-determination theory and the facilitation of intrinsic motivation, social development, and well-being. American Psychologist<\/em>, 55(1), 68\u201378. https:\/\/doi.org\/10.1037\/0003-066X.55.1.68<\/a><\/p>\n Steinberg, L. (2008). A social neuroscience perspective on adolescent risk-taking. Developmental Review<\/em>, 28(1), 78\u2013106. https:\/\/doi.org\/10.1016\/j.dr.2007.08.002<\/a><\/p>\nKeywords<\/h2>\n
Authors<\/h2>\n
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Purpose<\/h2>\n
Psychological Construct<\/h2>\n
Facets of the Preoccupation Construct<\/h3>\n
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Preoccupation versus Behavioral Duration<\/h3>\n
Theoretical Framework<\/h2>\n
1. The Components Model of Behavioral Addiction and Cognitive Salience<\/h3>\n
2. Cognitive Absorption Theory and Flow<\/h3>\n
3. Developmental Dual-Systems Model and Executive Functioning<\/h3>\n
4. Uses and Gratifications Theory and Children’s Agency<\/h3>\n
Validity<\/h2>\n
Content and Face Validity<\/h3>\n
Construct and Factorial Validity<\/h3>\n
Predictive and Criterion-Related Validity<\/h3>\n
Reliability<\/h2>\n
Internal Consistency Metrics<\/h3>\n
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Item Homogeneity and Standard Error<\/h3>\n
Factor Analysis<\/h2>\n
Exploratory Factor Analysis (EFA)<\/h3>\n
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Implications of Unidimensionality<\/h3>\n
Instrument \/ Measurement Tool<\/h2>\n
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Permissions & Fee and Test Year<\/h2>\n
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\n Institute of Social Sciences Ivo Pilar
\n Maruli\u0107ev trg 19\/I, 10000 Zagreb, Croatia
\n Email: marina.kotrla.topic@pilar.hr<\/a>\n <\/p>\n<\/ul>\nReferences<\/h2>\n