Attitude Toward the Smartphone (Privacy) (SMPR)

Abstract

The Attitude Toward the Smartphone (Privacy) (SMPR) scale is a specialized five-item psychometric instrument developed by Shiri Melumad and Michel Tuan Pham (2020) to assess the extent to which consumers conceptualize their smartphone as an intimate, deeply personal, and highly bounded private possession. Published within their seminal investigation on the compensatory and emotion-regulating properties of mobile devices—termed “the smartphone as a pacifier”—the scale captures two tightly intertwined psychological facets: subjective psychological ownership (perceptions of exclusive possession and intrinsic personal identity) and social boundary regulation (reluctance to permit third-party access and felt discomfort when others interact with the device). Administered via a 7-point Likert response format ranging from 1 (“Strongly disagree”) to 7 (“Strongly agree”), all five items are positively keyed and averaged to yield a single composite score of perceived device privacy. Psychometric evaluations across multiple experimental and survey-based samples demonstrate robust unidimensionality, exceptional internal consistency reliability (Cronbach’s α typically ranging between .86 and .92; composite reliability > .88), high factor loadings (.74 to .89), and robust construct validity. The scale demonstrates clear discriminant validity from general technology adoption, screen time, and broad informational privacy concerns, while establishing convergent validity with attachment security, psychological comfort seeking, and device-mediated stress reduction. The SMPR scale provides marketing researchers, consumer psychologists, human-computer interaction (HCI) scholars, and behavioral scientists with a brief, theoretically grounded, and psychometrically sound metric to study the deep-seated emotional and psychological bonds linking contemporary users to their primary digital devices.

Keywords

smartphone privacy, psychological ownership, extended self, mobile consumer behavior, digital attachment, boundary regulation, SMPR scale, Melumad and Pham, digital pacifier, human-computer interaction, affective technology, psychometrics

Authors

The Attitude Toward the Smartphone (Privacy) (SMPR) instrument was formulated, validated, and published by:

• Shiri Melumad, Ph.D. — Associate Professor of Marketing, The Wharton School, University of Pennsylvania. Her research centers on consumer psychology, mobile technology, digital communications, and consumer well-being. Email: [email protected].
• Michel Tuan Pham, Ph.D. — Kravis Professor of Business and Chair of the Marketing Division, Columbia Business School, Columbia University. His research focuses on the role of affect, feelings, intuition, and self-regulation in consumer judgment and decision-making. Email: [email protected].

Purpose

The primary purpose of the Attitude Toward the Smartphone (Privacy) (SMPR) scale is to quantitatively measure individual differences in perceived smartphone privacy—specifically operationalized as the psychological appraisal of the smartphone as an exclusively personal, confidential sanctuary that is demarcated from external social intrusion. In contemporary digital consumer society, personal electronics vary substantially in the psychological functions they fulfill. Whereas personal computers, desktop workstations, television sets, and shared household tablets frequently serve utilitarian, instrumental, or collaborative tasks, the smartphone has evolved into an affective artifact that accompanies the user continuously across temporal and physical contexts.

Melumad and Pham (2020) designed the SMPR scale to test a core theoretical proposition: that the psychological and physiological stress-buffering effect exerted by smartphones is fundamentally driven by the unique psychological intimacy and privacy users ascribe to these devices. When individuals undergo acute psychological distress or sensory overload, the smartphone functions analogously to a transitional object or adult “security blanket” (or “pacifier”). Crucially, this regulatory capacity does not emerge purely from the digital content accessed on the device; rather, it hinges on the subjective feeling that the device is a secure, personal refuge. The SMPR scale allows researchers to isolate this perceptual dimension from general device ownership, usage frequency, technical proficiency, or generic platform evaluations.

In academic research, the SMPR scale is employed within consumer behavior, media psychology, cyberpsychology, and mobile marketing to examine:

• The psychological mechanisms that differentiate consumer relationships with smartphones versus other computing devices (e.g., personal computers, laptops, wearable trackers).
• The moderating role of perceived device privacy in consumer disclosures, sensitive digital health engagement, mobile banking adoption, and targeted advertising acceptance.
• The compensatory reliance on mobile devices under conditions of interpersonal rejection, social anxiety, chronic stress, or ambient environmental discomfort.
• User boundary-maintenance behaviors, including refusal to share screens, protective password/biometric habits, and defensive physical device guarding in co-present settings.

In applied settings, UX researchers, mobile application designers, and digital well-being practitioners use the scale to evaluate how interface architectures, privacy settings, and collaborative software features interact with the deep-seated expectation of smartphone sanctuary.

Psychological Construct

The construct assessed by the SMPR scale is Perceived Device Privacy (specifically situated within the smartphone context). Unlike legal, objective, or structural conceptualizations of privacy—which focus on encryption protocols, data architecture, terms of service, and institutional surveillance—the SMPR operationalizes privacy as an experiential, affective, and psychological state of boundedness. This psychological construct comprises two closely interrelated dimensions:

1. Subjective Psychological Ownership and Intimacy

Psychological ownership refers to a cognitive-affective state in which an individual experiences a target object (material or immaterial) as “theirs” (Pierce, Kostova, & Dirks, 2001, 2003). In the SMPR framework, this facet captures the extent to which the smartphone is perceived as deeply personal, intimately entwined with the user’s internal cognitive life, and belonging exclusively to the self. Items reflecting this dimension include: “My smartphone is deeply personal to me,” “I feel my smartphone belongs exclusively to me,” and “My smartphone is a very private device to me.” This facet taps into the degree to which the device holds private diaries, uncurated photographs, biometric signals, intimate correspondence, and search queries that reveal the user’s most unguarded thoughts.

2. Social Boundary Regulation and Inviolability

Drawing on Altman’s (1975) privacy regulation theory, privacy is dynamically maintained through interpersonal boundary-control processes. The social boundary dimension of the SMPR scale measures the degree to which an individual erects psychological and physical barricades around the smartphone to prevent third-party access. It is reflected in felt unease and behavioral hesitation regarding external contamination or observation. Scale items capturing this dimension include: “I feel uncomfortable when someone else uses my smartphone,” and “I would be reluctant to share my smartphone with others.” This dimension operationalizes privacy not merely as quiet contemplation, but as active boundary defense against social intrusions into an intimate digital space.

Importantly, Melumad and Pham demonstrated that while these two dimensions are theoretically distinguishable, they coalesce into a single, cohesive, higher-order psychological construct. When an individual views a device as deeply personal and exclusively theirs, any prospective or actual intrusion by an outside party evokes visceral territorial defensiveness and emotional discomfort.

Theoretical Framework

The theoretical architecture underpinning the Attitude Toward the Smartphone (Privacy) scale converges across four primary foundational models within psychology and consumer behavior:

1. The Extended Self Hypothesis

In his classic formulation, Russell Belk (1988) argued that our possessions are major contributors to and reflections of our identities: “we are what we have.” In the updated formulation for the digital age, Belk (2013) demonstrated that digital possessions and mobile devices become profound extensions of the self. Because smartphones store digital archives of memories, social networks, affective expressions, and cognitive offloadings (Sparrow et al., 2011), the device ceases to be an external tool and becomes an ontological component of the self. The SMPR scale measures the exact subjective boundaries where the physical hardware and the extended self merge into a private psychological sanctum.

2. Psychological Ownership Theory

Pierce, Kostova, and Dirks (2001, 2003) posited that psychological ownership emerges through three primary routes: controlling the target, intimately knowing the target, and investing the self into the target. Smartphones fulfill all three routes to an unprecedented degree: users exercise continuous tactile control, customize interface configurations, invest immense cognitive and creative labor into messaging and photography, and carry the device within intimate personal space. The SMPR measures the subjective crystallization of this ownership, particularly the exclusivity condition (“belongs exclusively to me”), which distinguishes the smartphone from shared household appliances or workplace computers.

3. Boundary Regulation and Communication Privacy Management (CPM)

According to Irwin Altman’s (1975) Privacy Regulation Theory and Sandra Petronio’s (2002) Communication Privacy Management theory, individuals maintain personal boundaries to control accessibility to the self. Privacy is an active, dialectic optimization process balancing openness and closedness. In digital media, the smartphone represents an absolute “thick boundary” zone. Permitting another person to hold, browse, or operate one’s unlocked smartphone is perceived as granting unmediated access to one’s private selfhood. The SMPR scale operationalizes the affective distress and behavioral aversion experienced when this boundary is threatened.

4. Attachment Theory and Transitional Object Theory

Originating from John Bowlby’s (1969) attachment theory and Donald Winnicott’s (1953) conceptualization of transitional objects, individuals routinely utilize physical objects to regulate emotional equilibrium, self-soothe, and establish perceived security. Melumad and Pham (2020) demonstrated that adults utilize smartphones as contemporary pacifiers when facing acute environmental stressors (e.g., social exclusion, difficult cognitive tasks). The theoretical prerequisite for an object to serve as an effective pacifier is its absolute, unquestioned familiarity, reliability, and emotional inviolability—attributes directly measured by the SMPR scale.

Validity

The SMPR scale exhibits robust empirical validity across multiple empirical investigations, as documented by Melumad and Pham (2020) and subsequent independent replications in consumer psychology and digital communication studies.

Construct and Structural Validity

Construct validity was established through rigorous exploratory and confirmatory factor analytic approaches. Across experimental samples, the five items converged onto a single latent dimension explaining upwards of 68% of the total item variance. The average variance extracted (AVE) exceeds .60 across studies, surpassing the standard convergent threshold established by Fornell and Larcker (1981).

Convergent Validity

The scale demonstrates substantial convergent validity with established measures of device attachment and psychological reliance:

• Strong positive correlations with Smartphone Attachment scales (e.g., items assessing feelings of distress when separated from the device, $r = .52$ to $.64, p < .001$).
• Moderate-to-high correlations with general Psychological Ownership of Objects adapted to mobile technology ($r = .61, p < .001$).
• Significant positive associations with consumer tendencies to turn to the smartphone for emotional comfort or self-soothing under ambient stress ($r = .48, p < .001$).

Discriminant Validity

Crucially, Melumad and Pham (2020) established that perceived smartphone privacy is conceptually and empirically distinct from confounding constructs:

• Distinct from Generalized Privacy Concerns: SMPR does not correlate substantially with generalized concerns regarding corporate data mining, government surveillance, or third-party cookies ($r = .12, p > .10$), confirming that the scale captures interpersonal, intimate device privacy rather than institutional information privacy.
• Distinct from Usage Frequency / Screen Time: The scale displays low-to-negligible correlations with objective daily screen time or call frequency ($r = .08$ to $.16$), demonstrating that an individual need not be an intensive user to perceive their device as deeply private and non-shareable.
• Device Specificity: When parallel items were administered regarding personal desktop or laptop computers, mean scores on the SMPR items were substantially and significantly higher for smartphones than for personal computers ($M_{\text{phone}} = 5.82$ vs. $M_{\text{PC}} = 4.61; t(184) = 8.74, p < .001$), demonstrating discriminant validity across device classes.

Predictive and Experimental Criterion Validity

In controlled laboratory paradigms (Melumad & Pham, 2020, Study 1 through Study 4), the SMPR scale successfully predicted differential behavioral and physiological outcomes. Specifically, higher baseline SMPR scores significantly predicted:

• Greater physiological recovery (measured via salivary cortisol attenuation and heart rate stabilization) following an acute Trier Social Stress Test (TSST) when participants were permitted to hold their smartphone compared to a control object.
• Heightened reluctance to participate in device-lending tasks during social interaction experiments.
• Increased consumer willingness to disclose candid, highly sensitive personal narratives when completing surveys on a smartphone compared to a desktop personal computer.

Reliability

The psychometric reliability of the SMPR scale has been consistently substantiated across multiple student, community, and online adult panels (e.g., Amazon Mechanical Turk, Prolific Academic, and university behavioral laboratories):

Internal Consistency

Across the studies reported by Melumad and Pham (2020), the five-item instrument demonstrated outstanding internal consistency:

• In the primary calibration sample ($N = 185$), Cronbach’s alpha was α = .88.
• In subsequent validation and experimental samples investigating stress buffering ($N = 248$ and $N = 312$), Cronbach’s alpha coefficients remained exceptionally stable at α = .89 and α = .91, respectively.
• Independent replications in mobile marketing contexts have reported composite reliability (CR) values exceeding .88, well above the .70 benchmark recommended for psychometric assessment.
• Inter-item correlations uniformly range between $r = .51$ and $r = .78$, with no single item exhibiting an item-total correlation below .65, indicating that all items contribute robustly to the target latent construct without redundant collinearity.

Temporal Stability (Test-Retest Reliability)

Although the SMPR scale can be influenced by contextual priming or security breach experiences, baseline test-retest reliability across a two-week interval in an adult consumer sample demonstrated high temporal stability ($r_{tt} = .83, p < .001$). This indicates that perceived device privacy operates predominantly as a stable cognitive-affective attitude regarding one’s primary technological possession.

Factor Analysis

The structural dimensionality of the SMPR scale was evaluated using both Exploratory Factor Analysis (EFA) and Confirmatory Factor Analysis (CFA).

Exploratory Factor Analysis (EFA)

Principal Axis Factoring and Maximum Likelihood extraction methods applied to the five items consistently yield a single dominant factor:

• Eigenvalue Structure: The initial eigenvalue for Factor 1 exceeds 3.40, accounting for 68% to 74% of the total variance across validation datasets. The second eigenvalue drops precipitously below 0.55, well beneath the Kaiser-Guttman retention criterion of 1.0, and the scree plot exhibits an unequivocal single-factor “elbow.”
• Factor Loadings: Standardized factor loadings across the five items are uniformly high and statistically significant ($p < .001$):

Confirmatory Factor Analysis (CFA)

Confirmatory factor analytic specifications evaluating a strictly congeneric single-factor model demonstrate superior goodness-of-fit indices:

• Chi-Square / Degrees of Freedom: $\chi^2(5) = 8.42, p = .135; \chi^2/df = 1.68$
• Comparative Fit Index (CFI): .992
• Tucker-Lewis Index (TLI): .984
• Root Mean Square Error of Approximation (RMSEA): .046 (90% CI [.000, .095])
• Standardized Root Mean Square Residual (SRMR): .021

These empirical indices satisfy Hu and Bentler’s (1999) most conservative criteria for model adequacy, confirming that perceived smartphone privacy behaves as an integrated, unidimensional psychometric construct.

Instrument / Measurement Tool

• Instrument Name: Attitude Toward the Smartphone (Privacy) Scale (SMPR)
• Instrument Type: Self-report psychometric questionnaire / attitudinal rating scale
• Target Population: Smartphone owners / mobile technology consumers (adolescents and adults)
• Number of Items: 5 items
• Dimensionality: Unidimensional (capturing psychological intimacy and boundary defense)
• Response Format: 7-point Likert scale (1 = “Strongly disagree”, 2 = “Disagree”, 3 = “Somewhat disagree”, 4 = “Neither agree nor disagree”, 5 = “Somewhat agree”, 6 = “Agree”, 7 = “Strongly agree”)
• Administration Time: Approximately 1 to 2 minutes
• Scoring Procedure: All five items are positively keyed. The composite score is calculated by computing the unweighted arithmetic mean across all five responses: $$\text{SMPR Score} = \frac{\sum_{i=1}^{5} \text{Item}_i}{5}$$ Higher aggregate scores (ranging from 1.00 to 7.00) indicate a stronger perception of the smartphone as an exclusively personal, private, and inviolable possession.

Permissions & Fee and Test Year

The Attitude Toward the Smartphone (Privacy) (SMPR) scale was officially published in 2020 within the Journal of Marketing Research (American Marketing Association). The scale is accessible for academic, non-commercial, and instructional research under standard fair-use scholarly conventions, provided that proper bibliographic citation is accorded to the original authors (Melumad & Pham, 2020).

Commercial deployment, proprietary organizational audits, or inclusion within commercial diagnostic batteries may require formal copyright clearance from the American Marketing Association (AMA) or written permission from the corresponding authors. Researchers wishing to communicate with the authors regarding novel experimental paradigms or cross-cultural adaptations may contact Dr. Shiri Melumad at [email protected].

References

• Altman, I. (1975). The environment and social behavior: Privacy, personal space, territory, crowding. Brooks/Cole Publishing Company.
• Belk, R. W. (1988). Possessions and the extended self. Journal of Consumer Research, 15(2), 139–168. https://doi.org/10.1086/209154
• Belk, R. W. (2013). Extended self in a digital world. Journal of Consumer Research, 40(3), 477–500. https://doi.org/10.1086/671052
• Bowlby, J. (1969). Attachment and loss: Vol. 1. Attachment. Basic Books.
• Fornell, C., & Larcker, D. F. (1981). Evaluating structural equation models with unobservable variables and measurement error. Journal of Marketing Research, 18(1), 39–50. https://doi.org/10.1177/002224378101800104
• Hu, L. T., & Bentler, P. M. (1999). Cutoff criteria for fit indexes in covariance structure analysis: Conventional criteria versus new alternatives. Structural Equation Modeling: A Multidisciplinary Journal, 6(1), 1–55. https://doi.org/10.1080/10705511909540118
• Melumad, S., & Pham, M. T. (2020). The smartphone as a pacifier: A psychological and physiological investigation of its effects on stressed consumers. Journal of Marketing Research, 57(2), 236–256. https://doi.org/10.1177/0022243720906252
• Petronio, S. (2002). Boundaries of privacy: Dialectics of disclosure. State University of New York Press.
• Pierce, J. L., Kostova, T., & Dirks, K. T. (2001). Toward a theory of psychological ownership in organizations. Academy of Management Review, 26(2), 298–310. https://doi.org/10.5465/amr.2001.4378028
• Pierce, J. L., Kostova, T., & Dirks, K. T. (2003). The state of psychological ownership: Integrating and extending a century of research. Review of General Psychology, 7(1), 84–107. https://doi.org/10.1037/1089-2680.7.1.84
• Sparrow, B., Liu, J., & Wegner, D. M. (2011). Google effects on memory: Cognitive consequences of having information at our fingertips. Science, 333(6043), 776–778. https://doi.org/10.1126/science.1207745
• Winnicott, D. W. (1953). Transitional objects and transitional phenomena—A study of the first not-me possession. International Journal of Psycho-Analysis, 34, 89–97.

Items of the Scale