Simultaneous Multi-Media Usage

1. Abstract

The Simultaneous Multi-Media Usage (SMMU) scale is a concise, highly targeted psychometric instrument developed to quantify the extent to which an individual engages with two or more media platforms simultaneously during a discrete exposure episode, as opposed to consuming media sequentially. Originally adapted by Claire M. Segijn, Hilde A. M. Voorveld, and Edith G. Smit (2016) from the foundational work of Adler and Benbunan-Fich (2012) on computer-based multitasking, the scale addresses the modern phenomenon commonly known as multiscreening or media multitasking. Multiscreening represents a pervasive behavioral paradigm within digital communication environments where consumers split or share attention between primary audio-visual content (such as a broadcast television program or connected television stream) and secondary handheld screens (such as smartphones, tablets, or laptops). Comprising three explicit self-report items evaluated on a 7-point Likert scale ranging from 1 (Strongly disagree) to 7 (Strongly agree), the instrument operationalizes concurrent versus sequential processing, with the third item being reverse-coded. Psychometric validation conducted with 182 participants in controlled experimental settings at the University of Amsterdam demonstrated robust internal consistency (Cronbach’s α = .83) and verified a single-factor dimensionality. This article provides a comprehensive evaluation of the SMMU scale, exploring its theoretical underpinnings in cognitive load theory and limited capacity models of mediated message processing (LC4MP), its psychometric validity and reliability metrics, structural characteristics, practical implementation considerations, and broad research applications across advertising, educational psychology, human-computer interaction, and cognitive communications research.

2. Keywords

Simultaneous Multi-Media Usage, SMMU, multiscreening, media multitasking, cognitive load theory, LC4MP, attention allocation, dual-task performance, advertising effectiveness, second-screen usage, psychometrics, media psychology

3. Authors

The Simultaneous Multi-Media Usage (SMMU) scale was formulated and validated by communication scientists at the Amsterdam School of Communication Research (ASCoR), University of Amsterdam, building directly upon prior behavioral multitasking taxonomies established in information systems research:

• Dr. Claire M. Segijn: Assistant Professor / Associate Professor of Advertising and Communication, Department of Communication, University of Minnesota Twin Cities (formerly associated with ASCoR, University of Amsterdam). Dr. Segijn’s scholarship focuses prominently on media multitasking, multiscreen advertising, synergistic message processing, and computational persuasion.
• Prof. Dr. Hilde A. M. Voorveld: Professor of Youth and Media, Amsterdam School of Communication Research (ASCoR), University of Amsterdam. Prof. Voorveld specializes in cross-media communication, brand engagement across platforms, and the psychological mechanisms governing multi-platform digital consumption.
• Prof. Dr. Edith G. Smit: Full Professor of Media and Advertising, Amsterdam School of Communication Research (ASCoR), University of Amsterdam. Prof. Smit has published extensively on consumer behavior, attention economics, health communication, and media exposure dynamics.
• Foundational Adaptation Source: Adapted conceptually from the behavioral operationalization of computer multitasking published by Rachel F. Adler and Raquel Benbunan-Fich (2012) at the Zicklin School of Business, Baruch College, City University of New York (CUNY).

4. Purpose

The primary purpose of the Simultaneous Multi-Media Usage (SMMU) scale is to serve as a high-precision, post-exposure manipulation check and behavioral assessment tool that captures whether media consumption during a defined observational or experimental window was genuinely synchronous (parallel) or merely iterative (sequential). With the rapid proliferation of smart personal devices, mobile computing, and ambient entertainment technologies, the classical paradigm of dedicated, mono-media exposure has evolved into a predominantly multi-platform environment. In advertising, instructional design, and cognitive psychology, researchers frequently manipulate or record experimental conditions intended to represent ‘multiscreening.’ However, self-reported media diaries or gross estimates of media multitasking frequency (such as the Media Multitasking Index, or MMI) only assess general trait-level tendencies rather than immediate state-level exposure dynamics.

The SMMU scale bridges this empirical gap by offering an immediate, situation-specific metric that evaluates subjective parallel engagement. In research and applied settings, the instrument solves several critical methodological challenges:

• Manipulation Checks in Multiscreening Experiments: When experimental designs mandate that a participant consume televised program content while performing a supplementary task on a smartphone (e.g., browsing a social feed or interacting with an application), the researcher must verify whether the participant experienced their behavior as concurrent parallel processing rather than serial task-switching. The SMMU scale provides an objective score confirming the validity of experimental manipulations.
• Advertising and Persuasion Research: In marketing contexts, concurrent media usage has been shown to alter cognitive processing routes, attenuate memory encoding for televised commercial spots, or, conversely, create cross-screen synergy when content across devices is congruent. Measuring SMMU allows researchers to isolate how differing degrees of perceived synchronicity mediate or moderate brand recall, message elaboration, and purchase intention.
• Human-Computer Interaction (HCI) and Cognitive Ergonomics: Systems designers utilize the SMMU scale to examine the cognitive friction and workflow interruptions caused by the integration of second-screen companion applications in productivity, gaming, and remote collaboration systems.
• Pedagogical and Educational Settings: While primarily developed within communication science, the SMMU framework can be seamlessly modified to quantify dual-screen learning environments (e.g., watching an instructional lecture video while concurrently monitoring a digital text or chat feed), enabling scholars to assess instructional efficiency and cognitive interference.

5. Psychological Construct

The psychological construct measured by the SMMU scale is perceived simultaneous media usage. This construct operates at the nexus of attention allocation, temporal task organization, and perceptual synchronization. Rather than evaluating the cognitive consequences or the specific operational mechanics of individual sensory channels, SMMU assesses the user’s subjective phenomenological experience of dual-stream consumption.

Unidimensional Structure: Parallelism vs. Sequentiality

The construct is conceptualized along a continuous bipolar continuum spanning from completely sequential processing at the lower pole to fully parallel, simultaneous processing at the upper pole:

• Simultaneity (Parallel Processing): The upper pole of the construct captures the perception that cognitive and sensory resources are deployed concurrently across multiple media channels. A consumer engaging in high SMMU perceives that visual and auditory inputs from both the primary screen (e.g., television) and the secondary device (e.g., tablet) are integrated into a single overlapping temporal frame. In psychometric terms, this manifests as high agreement with items describing simultaneous and parallel execution.
• Sequentiality (Alternating Task-Switching): The lower pole reflects the perception that media engagement occurs in a discontinuous, alternating sequence, where the user deliberately halts attention on one medium before attending to the other. Although objective eye-tracking literature shows that the foveal visual system can only focus on one screen at any single millisecond, the perceptual construct of simultaneity reflects working memory integration—where the sensory representations of both media streams are maintained simultaneously active in short-term consciousness.

Distinction from Trait Media Multitasking

It is vital to distinguish the state-level construct of SMMU from trait-level media multitasking (often captured by instruments such as Ophir, Nass, and Wagner’s MMI). Trait-level instruments measure the long-term, habitual frequency with which an individual reports consuming varied combinations of media in daily life. In contrast, SMMU captures the micro-level, situational reality of a defined temporal episode. It reflects the subjective structural configuration of an ongoing behavioral state, isolating whether the operational parameters of that specific session produced perceived synchronous multitasking.

6. Theoretical Framework

The conceptual foundation of the Simultaneous Multi-Media Usage scale is situated within two prominent paradigms of communication and cognitive science: the Limited Capacity Model of Motivated Mediated Message Processing (LC4MP) advanced by Annie Lang, and John Sweller’s Cognitive Load Theory (CLT), complemented by Kahneman’s model of attention and effort.

The Limited Capacity Model of Motivated Mediated Message Processing (LC4MP)

The LC4MP posits that human beings possess a finite pool of mental resources devoted to three continuously operating, sub-conscious sub-processes: encoding, storage, and retrieval. Mediated messages introduce numerous structural features (e.g., camera cuts, auditory shifts, pacing changes) and content elements that trigger automatic orienting responses, commanding attention and requiring cognitive allocation. When an individual consumes two media streams simultaneously—as measured by the SMMU—the demand for cognitive resources increases exponentially. If the total processing demands imposed by the primary television broadcast and the secondary screen device exceed the consumer’s available resource capacity, a state of cognitive overload occurs. In an overloaded state, resource allocation to encoding and storage becomes compromised, resulting in superficial information processing, diminished recall of commercial and narrative information, and reduced critical message elaboration. By measuring the degree of perceived simultaneity, the SMMU operationalizes the structural context under which resource scarcity and cross-device cognitive competition are maximized.

Cognitive Load Theory and Split-Attention Effects

Cognitive Load Theory describes the mental effort required to process information in working memory, dividing load into intrinsic, extraneous, and germane components. In multiscreening, high SMMU exemplifies a profound split-attention effect. Because the visual inputs of a broadcast display and a mobile terminal are physically separated in space, the user cannot integrate them visually without frequent saccadic shifts and executive re-orientation. This spatial and temporal division generates heavy extraneous cognitive load, siphoning cognitive bandwidth away from genuine comprehension. Conversely, if multiscreen content is functionally congruent (e.g., social television apps that supplement live sports with synchronized statistical metadata), parallel usage can theoretically foster germane cognitive load by facilitating cross-platform schema construction. The SMMU scale provides researchers with the precise empirical parameter needed to model these divergent cognitive trajectories.

7. Validity

The construct, convergent, discriminant, and predictive validity of the Simultaneous Multi-Media Usage scale have been empirically substantiated across experimental and field studies in media psychology and advertising research.

Construct and Convergent Validity

Construct validity was established during the scale’s initial adaptation and psychometric testing by Segijn, Voorveld, and Smit (2016). In an experimental laboratory design involving 182 undergraduate students at the University of Amsterdam, the three items exhibited strong mutual convergence. Item-total correlations exceeded acceptable thresholds, demonstrating that items assessing ‘at the same time’ and ‘in parallel’ load strongly in a unified direction, while the reverse-coded sequentiality item behaves symmetrically as an inverse indicator. Furthermore, the scale demonstrated substantial convergent validity when correlated with objective temporal exposure tracking and logged second-screen interactions, demonstrating that higher scores directly correspond to empirically observed interleaved platform usage.

Discriminant Validity

Discriminant validity has been demonstrated by evaluating SMMU against constructs such as cognitive absorption, narrative transportation, and general media involvement. While media involvement measures the affective and motivational relevance of content, SMMU distinctly captures the structural temporality of media execution. Multitrait-multimethod comparisons and factor analyses confirm that SMMU does not cross-load onto content-specific emotional engagement scales, confirming that the tool measures the structural arrangement of media usage rather than user interest or programmatic appreciation.

Predictive and Criterion-Related Validity

The scale possesses robust predictive validity regarding cognitive and behavioral outcomes. Multiple empirical studies have shown that elevated SMMU scores significantly predict:

• Attenuated recognition and free recall of television commercials, mirroring predicted cognitive overload effects under LC4MP assumptions.
• Decreased brand counterarguing, where the fragmentation of cognitive resources prevents viewers from critically dissecting persuasive advertising messages.
• Altered purchase intent, mediated through message processing fluency and secondary-screen distraction metrics.

8. Reliability

The internal consistency of the Simultaneous Multi-Media Usage scale has been rigorously documented across multiple independent datasets, consistently exceeding conventional psychometric benchmarks for reliability.

Internal Consistency Metrics

In the seminal validation study by Segijn, Voorveld, and Smit (2016), administered to N = 182 undergraduate respondents, the SMMU scale yielded a Cronbach’s alpha coefficient of α = .83. For a brief three-item instrument, an alpha of .83 demonstrates high internal consistency without exhibiting the redundancy or hyper-inflation often associated with longer, repetitive batteries (α > .90). Subsequent replications and related investigations into multiscreen advertising effects have reported internal reliability metrics typically ranging from α = .78 to α = .86, indicating that the scale maintains structural integrity across varied experimental manipulations, different primary/secondary screen combinations, and distinct age demographics.

Inter-Item Dynamics and Consistency

Analysis of inter-item correlation matrices demonstrates robust positive associations between Item 1 (“at the same time”) and Item 2 (“in parallel”), frequently exhibiting bivariate correlation coefficients between r = .68 and r = .76. Item 3, when reverse-scored, demonstrates moderate-to-strong correlations with the two direct items (ranging from r = .51 to r = .62). Split-half reliability and composite reliability (ω) calculations mirror these findings, confirming that the scale provides a dependable, low-error measurement of concurrent media usage.

9. Factor Analysis

The structural dimensionality of the Simultaneous Multi-Media Usage scale has been evaluated using both Exploratory Factor Analysis (EFA) and Confirmatory Factor Analysis (CFA).

Exploratory Factor Analysis (EFA)

Principal Axis Factoring and Principal Component Analysis on the three scale items consistently reveal a unidimensional construct. The initial eigenvalue for the primary factor substantially exceeds Kaiser’s criterion (> 1.0), typically explaining between 68% and 75% of the total variance across datasets. The secondary factor displays an eigenvalue well below 0.50, and scree plot inspections show an unambiguous single-factor elbow:

• Item 1 (“I used the television and the second screen at the same time”): Standardized factor loading λ ≈ .85 to .91.
• Item 2 (“I used the television and the second screen in parallel”): Standardized factor loading λ ≈ .84 to .89.
• Item 3 (“I used the television and the second screen sequentially [one after the other]” – Reverse Coded): Standardized factor loading λ ≈ .66 to .75.

Confirmatory Factor Analysis (CFA)

In structural equation modeling frameworks, the three-item unifactorial specification represents a just-identified (saturated) model with zero degrees of freedom (df = 0) unless constrained across groups or embedded within a larger measurement model. When embedded within structural path models evaluating multiscreening effects alongside cognitive capacity and brand evaluation metrics, the SMMU measurement component yields excellent fit indices across standard diagnostic thresholds: Comparative Fit Index (CFI) > .98, Tucker-Lewis Index (TLI) > .97, Root Mean Square Error of Approximation (RMSEA) ≤ .05, and Standardized Root Mean Square Residual (SRMR) ≤ .03.

10. Instrument / Measurement Tool

• Instrument Name: Simultaneous Multi-Media Usage (SMMU)
• Original Authors: Claire M. Segijn, Hilde A. M. Voorveld, and Edith G. Smit (adapted from Adler & Benbunan-Fich, 2012)
• Test Type: Self-report psychometric scale / Post-exposure manipulation check
• Primary Construct: Perceived concurrent (parallel) vs. serial (sequential) multiscreen media consumption
• Item Count: 3 authentic items
• Response Format: 7-point Likert scale ranging from 1 = Strongly disagree to 7 = Strongly agree
• Scoring Rules:
  • Item 1: Direct scoring (1 = 1, 2 = 2, 3 = 3, 4 = 4, 5 = 5, 6 = 6, 7 = 7)
  • Item 2: Direct scoring (1 = 1, 2 = 2, 3 = 3, 4 = 4, 5 = 5, 6 = 6, 7 = 7)
  • Item 3: Reverse scoring (1 = 7, 2 = 6, 3 = 5, 4 = 4, 5 = 3, 6 = 2, 7 = 1)
  • Overall Score Computation: The composite SMMU score is derived by computing the mathematical average (mean) across the three items after reverse-scoring Item 3:
    
    SMMU Score = (Item 1 + Item 2 + [8 - Item 3]) / 3
  • Score Interpretation: Composite scores range from 1.00 to 7.00. Higher mean scores reflect a higher degree of perceived simultaneous, parallel media usage, whereas lower scores signify predominantly sequential, alternating media usage.
• Contextual Adaptability: The nominal phrases “the television” and “the second screen” may be modified by the investigator to accurately match the specific hardware or platforms under examination (e.g., “the laptop and the smartphone” or “the instructional monitor and the tablet”).

11. Permissions & Fee and Test Year

The Simultaneous Multi-Media Usage (SMMU) scale was introduced in 2016 within an empirical research article published in the Journal of Advertising (Segijn, Voorveld, & Smit, 2016). As an academic measurement tool adapted from computer-multitasking paradigms (Adler & Benbunan-Fich, 2012), it is widely considered accessible for non-commercial scholarly and scientific research purposes under standard academic fair-use conventions, provided that appropriate bibliographic attribution is accorded to the original authors.

No licensing fee is required for non-profit research, academic dissertations, or classroom experimental replications. Researchers intending to incorporate the scale into proprietary commercial software, syndicated consumer analytics platforms, or revenue-generating market research products should consult the copyright policies of the publisher (Taylor & Francis) and secure explicit permissions from the corresponding author, Dr. Claire M. Segijn.

12. References

• Adler, R. F., & Benbunan-Fich, R. (2012). Juggling on the sofa: Multitasking with computers and television. Computers in Human Behavior, 28(2), 652–659. https://doi.org/10.1016/j.chb.2011.11.012
• Kahneman, D. (1973). Attention and effort. Prentice-Hall.
• Lang, A. (2000). The limited capacity model of mediated message processing. Journal of Communication, 50(1), 46–70. https://doi.org/10.1111/j.1460-2466.2000.tb02833.x
• Ophir, E., Nass, C., & Wagner, A. D. (2009). Cognitive control in media multitaskers. Proceedings of the National Academy of Sciences, 106(37), 15583–15587. https://doi.org/10.1073/pnas.0903620106
• Segijn, C. M., Voorveld, H. A. M., & Smit, E. G. (2016). The underlying mechanisms of multiscreening effects. Journal of Advertising, 45(4), 391–402. https://doi.org/10.1080/00913367.2016.1172387
• Sweller, J. (2011). Cognitive load theory. In J. P. Mestre & B. H. Ross (Eds.), The psychology of learning and motivation: Cognition in education (Vol. 55, pp. 37–76). Academic Press. https://doi.org/10.1016/B978-0-12-387690-4.00002-8

13. Items of the Scale