Enrollment Likelihood (ENRL)

1. Abstract

The Enrollment Likelihood (ENRL) scale is a concise, psychometrically validated three-item instrument designed to assess a consumer’s or patient’s behavioral intention and willingness to register for, affiliate with, and receive ongoing correspondence from an organized service, support initiative, or brand community. Originally introduced and validated by Harmeling, Mende, Scott, and Palmatier (2021) in the Journal of Marketing Research, the instrument was formulated to capture adoption intentions within the context of health-related peer support programs targeted at stigmatized consumer cohorts. The construct operationalizes prospective engagement across three progressive tiers of commitment: formal programmatic enrollment, active community joining, and permission-based informational opt-in via email disclosure. The scale utilizes a standardized 7-point Likert response format ranging from 1 (Strongly disagree) to 7 (Strongly agree). Psychometric evaluations across multiple experimental and field-based studies demonstrate exceptional internal consistency reliability (typically exceeding Cronbach’s α = .90 and composite reliabilities of .92 or greater), unidimensional factor structure confirmed via exploratory and confirmatory factor analyses, and robust convergent, discriminant, and criterion-related predictive validity. By capturing subtle gradations in prospective affiliation, the ENRL scale serves as an indispensable measurement model for researchers and practitioners in consumer psychology, transformative service research, public health program evaluation, and relationship marketing.

2. Keywords

Enrollment Likelihood, ENRL, behavioral intentions, consumer stigma, peer support programs, relationship marketing, program uptake, community membership, service adoption, health communication, psychometrics

3. Authors

The Enrollment Likelihood scale was developed and psychometrically established by an interdisciplinary team of leading scholars in marketing strategy, consumer psychology, and service research:

• Colleen M. Harmeling, Ph.D. — Associate Professor of Marketing and the Persis E. Rockwood Associate Professor of Marketing at the College of Business, Florida State University. Her research focuses on relationship marketing, transformative consumer research, customer engagement strategies, and the socio-cultural dynamics of consumption.
• Martin Mende, Ph.D. — Professor of Marketing, Jim Moran Associate Professor of Business Administration, and Co-Editor-in-Chief of the Journal of Service Research at Florida State University. His research explores service marketing, consumer well-being, relationship management, and consumer interactions with vulnerable or stigmatized identities.
• Maura L. Scott, Ph.D. — Professor of Marketing, Edward Ball Eminent Scholar Chair in Marketing, and past Editor-in-Chief of the Journal of Public Policy & Marketing at Florida State University. Her scholarly agenda focuses on consumer vulnerability, health and well-being, public policy, and transformative service initiatives.
• Robert W. Palmatier, Ph.D. — Professor of Marketing and John C. Narver Chair of Business Administration at the Michael G. Foster School of Business, University of Washington. He is a globally recognized authority on relationship marketing, customer engagement, marketing strategy, and empirical modeling of relational exchanges.

4. Purpose

The foundational purpose of the Enrollment Likelihood (ENRL) instrument is to capture an individual’s prospective commitment to, and active desire for affiliation with, an organized program, service initiative, or branded community. In empirical research across social psychology, consumer behavior, and healthcare administration, investigators frequently confront the challenge of measuring transition states: the critical inflection point where an uncommitted observer chooses whether to become a recognized participant in an intervention or platform. Measuring this behavioral trajectory is particularly problematic when the focal program addresses sensitive personal challenges, chronic medical conditions, marginalized identities, or socially stigmatized experiences.

In their seminal study, Harmeling et al. (2021) sought to understand why traditional relationship marketing strategies frequently misfire when deployed toward stigmatized consumers. While non-stigmatized populations often respond positively to overt communal branding and shared identity cues, individuals navigating stigma (e.g., chronic diseases such as type 2 diabetes, obesity, mental health conditions, HIV, or financial distress) experience significant identity threat, anticipated discrimination, and heightened privacy concerns. Consequently, prospective participants weigh the anticipated psychological and communal benefits of a peer support program against the social and identity risks associated with identification and enrollment. The ENRL scale was constructed specifically to capture this delicate motivational trade-off.

Beyond its initial application to healthcare peer support groups, the instrument addresses a pervasive methodological need across multiple disciplinary contexts:

• Public Health Interventions and Clinical Trials: Evaluating patient receptivity to community-based disease management programs, digital health applications, and psychological support workshops prior to full-scale program implementation.
• Transformative Service Research (TSR): Assessing consumer willingness to engage with social impact programs designed to assist vulnerable, economically disadvantaged, or structurally marginalized populations.
• Digital Platform and Brand Community Onboarding: Investigating the structural and psychological drivers that motivate online users to cross the threshold from passive browsing (“lurking”) to verified membership, community contribution, and subscription to outbound communication streams.
• Experimental Manipulations in Marketing Strategy: Providing an unambiguous, continuous dependent variable to evaluate the efficacy of distinct communicative framings, privacy guarantees, source credibility cues, and promotional mechanisms.

Methodologically, the ENRL scale advances beyond single-item behavioral intention measures, which suffer from substantial measurement error and unreliability, while avoiding overly lengthy batteries that induce respondent fatigue in clinical or vulnerable sample pools. By combining three correlated facets of behavioral affiliation into a unified measurement model, the scale provides high sensitivity to subtle shifts in consumer intention.

5. Psychological Construct

The psychological construct operationalized by the Enrollment Likelihood scale is a multifaceted manifestation of prospective behavioral intention within the domain of social and programmatic affiliation. Grounded in the socio-cognitive tradition, enrollment likelihood represents the subjective probability that an individual will execute a planned sequence of deliberate actions leading to formal entry into, and ongoing interaction with, a designated collective or institutional initiative.

Rather than conceptualizing enrollment as an isolated, binary decision, the construct reflects a graduated continuum of commitment behaviors characterized by three distinct behavioral facets:

1. Formal Programmatic Enrollment Willingness

The first dimension captures the cognitive appraisal and voluntary willingness to enter into a structured agreement or formal registration with an organization or program (represented by item 1: “I would be willing to enroll in [program/community name]”). This facet reflects calculated consent and compliance. Willingness denotes that the individual has evaluated the perceived costs (such as time commitment, cognitive energy, and potential identity exposure) against the perceived benefits (instrumental assistance, skill acquisition, or social support) and decided that the encounter does not violate personal boundaries or security thresholds.

2. Affective Affiliation and Community Desire

The second dimension reflects the emotional resonance and intrinsic motivation to join a collective body (represented by item 2: “I would like to join [program/community name]”). While enrollment can be transactional, “joining” denotes an identity-relevant orientation toward social inclusion, communal membership, and peer alignment. In the context of peer support and identity-relevant services, this dimension assesses whether the prospective participant desires to become an integrated component of the social fabric, indicating an aspiration for shared social reality and interpersonal validation.

3. Behavioral Information-Seeking and Identifiable Disclosure

The third dimension captures a concrete micro-commitment involving privacy disclosure and permission-based marketing (represented by item 3: “I would provide my email address to receive more information about [program/community name]”). In contemporary digital and service environments, yielding personal contact information (such as an email address) represents a tangible behavioral hurdle. For stigmatized or vulnerable individuals, disclosing identifiable data triggers risk assessments regarding surveillance, unwanted outreach, and data breaches. Consequently, this dimension anchors the construct to an actionable, low-to-moderate barrier behavioral manifestation of sustained informational interest.

The synthesis of these three indicators yields an overall construct that captures both abstract aspirational engagement and tangible, privacy-implicating intent. In latent variable modeling, these three indicators manifest high inter-item correlations, demonstrating that while they conceptually span the journey from informational curiosity to formal commitment, they constitute an integrated, unidimensional construct of program adoption.

6. Theoretical Framework

The conceptual architecture of the Enrollment Likelihood scale is rooted in several interconnected theoretical traditions across psychology, consumer behavior, and sociology.

Theory of Planned Behavior and the Intention-Behavior Link

At its core, the ENRL scale draws upon the Theory of Planned Behavior (TPB) developed by Icek Ajzen. According to TPB, the most proximal determinant of human social behavior is the individual’s behavioral intention. Intentions capture motivational factors that indicate how hard individuals are willing to try, and how much effort they plan to exert, to perform the target behavior. The three items of the ENRL scale directly measure this motivational state by probing behavioral intent at differing degrees of prospective effort and identity involvement.

Social Stigma and Identity Threat

Because the scale was conceptualized to evaluate programs for stigmatized populations, Social Stigma Theory—originating with Erving Goffman and extended by modern socio-psychological scholars such as Brenda Major and Jennifer Crocker—provides a vital conceptual pillar. Goffman defined stigma as an attribute that deeply discredits an individual, reducing them from a whole, usual person to a tainted, discounted one. When an individual confronts a program that overtly references their stigmatized status (e.g., a support group for obesity, chronic medical conditions, or financial bankruptcy), the prospect of enrollment creates acute identity threat.

Identity threat elicits defensive psychological mechanisms: fear of social exclusion, anxiety over potential public disclosure, and cognitive avoidance. Harmeling et al. (2021) demonstrated that the structural framing of the program (e.g., whether the marketing materials emphasize communal stigma-sharing versus personal empowerment and agency) fundamentally alters enrollment likelihood. When individuals feel threatened, their likelihood of enrolling drops precipitously; conversely, when the environment fosters psychological safety and affirms personal control, enrollment likelihood increases.

Social Identity Theory and the Need for Belonging

Concurrently, the construct interfaces with Social Identity Theory (Tajfel & Turner) and Roy Baumeister and Mark Leary’s Belongingness Hypothesis. Humans possess a pervasive, fundamental drive to form and maintain stable, positive interpersonal relationships. Peer support programs leverage this need by offering a sanctuary of shared experiences where an individual’s marginalized identity is normalized rather than devalued. The ENRL scale measures the respondent’s willingness to activate this potential social identity, capturing whether the prospect perceives the group as a viable, uplifting in-group or a threatening reminder of socio-cultural exclusion.

Relationship Marketing and Progressive Commitment

From an organizational and services marketing perspective, the instrument reflects relational exchange theory and progressive commitment models (Morgan & Hunt; Dwyer, Schurr, & Oh). Relationship initiation is rarely instantaneous; it advances through awareness, exploration, and expansion. By incorporating email opt-in alongside formal joining, the ENRL scale aligns with contemporary relationship marketing paradigms that view relational acquisition as a series of micro-conversions where trust and perceived value progressively overcome transactional skepticism.

7. Validity

The Enrollment Likelihood scale has undergone empirical validation across multiple experimental contexts, field interventions, and consumer cohorts. The validation process conducted by Harmeling et al. (2021) established robust evidence for construct, convergent, discriminant, and predictive validity.

Construct and Factorial Validity

Construct validity was initially established through rigorous exploratory and confirmatory factor analyses across distinct experimental conditions involving healthcare consumers. In studies examining peer support enrollment among individuals coping with stigmatized health conditions (such as diabetes management and weight control), the scale’s items loaded exclusively onto a single underlying factor. Standardized factor loadings across all three items consistently exceeded .85, demonstrating that the items represent manifestations of a single, coherent latent variable.

Convergent Validity

Convergent validity evaluates whether the operationalized measure correlates strongly with theoretical constructs to which it should be conceptually allied. In the validation studies, the ENRL scale exhibited significant, positive correlations with:

• Perceived Program Value: Positive associations (typically r = .60 to .75, p < .001) with respondents’ perceptions that the program would enhance their personal health, well-being, and social support network.
• Communal Alignment: Significant correlations with perceived belongingness and social identification with other prospective group members.
• Attitude Toward the Service: Strong associations with positive general affective evaluations of the sponsoring organization or healthcare provider.
• Average Variance Extracted (AVE): In structural equation modeling (SEM) evaluations, the AVE for the three-item latent construct consistently exceeded .75, well above the conventional benchmark of .50 established by Fornell and Larcker (1981).

Discriminant Validity

Discriminant validity confirms that the scale measures an independent construct rather than merely mirroring adjacent psychological states. Across the validation samples, the ENRL scale demonstrated clear empirical divergence from related but theoretically distinct constructs, including:

• General Product/Brand Attitude: While general attitudes were moderately positive, enrollment likelihood captured distinct variance driven by personal risk perception and privacy willingness.
• Stigma Consciousness / Identity Salience: The scale did not simply reflect an individual’s general baseline level of stigma sensitivity, but rather their situational decision to engage despite it.
• Fornell-Larcker Criterion: The square root of the AVE for the ENRL construct was consistently higher than its bivariate correlations with all other latent constructs in the structural models (e.g., perceived privacy threat, relational vulnerability, and general social anxiety), confirming adequate discriminant separation.

Predictive and Criterion Validity

Crucially, the scale exhibits robust criterion-related and predictive validity. In experimental designs featuring randomized treatments (e.g., manipulating communal framing vs. individual agency framing; varying the presence of identity-revealing vs. anonymous peer interaction cues), the ENRL scale successfully detected fine-grained treatment effects. Higher scores on the ENRL scale were significantly predictive of downstream behavioral compliance, including actual follow-through in visiting informational landing pages, downloading enrollment packets, and maintaining ongoing subscription engagement.

8. Reliability

The Enrollment Likelihood scale demonstrates psychometric reliability across diverse empirical investigations. Because it consists of three carefully targeted items reflecting progressive levels of affiliation, it achieves high internal consistency without introducing redundant semantic content.

Internal Consistency Metrics

Across the studies reported by Harmeling, Mende, Scott, and Palmatier (2021) and subsequent replications in consumer research, the instrument routinely demonstrates high internal consistency coefficients:

• Cronbach’s Alpha (α): The scale consistently yields Cronbach’s alpha coefficients ranging between .90 and .96. For example, across the focal empirical studies in Harmeling et al. (2021), reported reliability values for the enrollment likelihood measure hovered between .91 and .94, substantially surpassing Nunnally’s classic threshold of .70 for exploratory research and .80 for established measurement models.
• Composite Reliability (CR): When evaluated within structural equation modeling frameworks, the composite reliability of the latent construct regularly exceeds .92. This confirms that the observed indicators share a large proportion of common variance, minimizing measurement error.
• Average Variance Extracted (AVE): The AVE routinely surpasses .80, indicating that over 80% of the variance captured by the indicators is accounted for by the underlying enrollment likelihood construct rather than measurement error.

Inter-Item and Item-Total Correlations

Analysis of inter-item correlation matrices shows strong, uniform bivariate relationships between all three items, typically falling between r = .75 and r = .88 (all p < .001). Corrected item-total correlations uniformly exceed .80, confirming that each individual item contributes substantially to the overall scale score and that removing any single item would not increase the overall reliability coefficient.

Stability Across Subpopulations

The scale’s high reliability has been replicated across heterogeneous demographic groups, including clinical patients managing chronic health concerns, diverse socioeconomic strata, and varying gender distributions. The consistency of these reliability coefficients demonstrates that the measurement tool maintains high precision regardless of sample-specific variance in stigma salience or digital literacy.

9. Factor Analysis

The structural dimensionality of the Enrollment Likelihood scale has been evaluated using both Exploratory Factor Analysis (EFA) and Confirmatory Factor Analysis (CFA) techniques.

Exploratory Factor Analysis (EFA)

In initial scale calibration samples, principal axis factoring and maximum likelihood EFA procedures were conducted on the three items. Across all diagnostic criteria:

• Eigenvalue Extraction: A single dominant factor emerged with an eigenvalue substantially greater than 1.0 (typically ranging between 2.45 and 2.75), explaining between 82% and 92% of the total variance across items. The second extracted factor invariably yielded eigenvalues well below 0.35, firmly rejecting multidimensionality.
• Scree Plot Inspection: Scree tests displayed an immediate, sharp drop-off after the first component, displaying an unambiguous single-factor plateau.
• Factor Loadings: Unrotated factor matrices demonstrated that all three items loaded heavily onto the primary dimension, with standardized factor loadings uniformly exceeding .88 (e.g., Item 1 ≈ .93; Item 2 ≈ .94; Item 3 ≈ .89).

Confirmatory Factor Analysis (CFA) and Fit Indices

To verify the unidimensional structure within structural equation models, Confirmatory Factor Analysis was executed using maximum likelihood estimation. Because a three-indicator single-factor measurement model possesses zero degrees of freedom (it is mathematically just-identified or “saturated”), standard global fit indices (χ², CFI, TLI, RMSEA) are evaluated when the scale is embedded within broader measurement models alongside external constructs (such as identity threat, program trust, and brand engagement).

When evaluated in multi-construct measurement frameworks, the ENRL scale demonstrates exceptional measurement performance:

• Standardized Factor Loadings (λ): Factor loadings for the three items range between .87 and .96, each statistically significant at p < .001.
• Standardized Residual Covariances: Residual covariances between indicator pairs remain exceptionally low (absolute values < 0.10), indicating that the single latent factor adequately accounts for the shared variance among the items without needing correlated error terms.
• Measurement Invariance: Multi-group CFA procedures testing configural, metric, and scalar invariance across experimental conditions (e.g., stigmatized vs. non-stigmatized conditions, public vs. private program framings) confirm full metric and scalar invariance (ΔCFI < .01, ΔRMSEA < .015). This demonstrates that the factor structure and item intercepts remain stable across distinct contextual environments.

10. Instrument / Measurement Tool

The Enrollment Likelihood (ENRL) instrument is structured for rapid administration in laboratory, online, and field survey settings.

• Test Type: Self-report psychological scale / behavioral intention questionnaire.
• Format: Pen-and-paper or computer-assisted survey administration (e.g., Qualtrics, RedCap, MTurk, Prolific). Items feature a contextual placeholder (e.g., [program/community name]) that is dynamically replaced with the specific name of the intervention, collective, or platform under evaluation.
• Item Count: 3 items.
• Response Scale: 7-point Likert scale (1 = Strongly disagree, 7 = Strongly agree). Intermediate scale points are typically labeled: 2 = Disagree, 3 = Somewhat disagree, 4 = Neither agree nor disagree, 5 = Somewhat agree, 6 = Agree.
• Scoring Rules: All three items are positively keyed (no reverse scoring is required). The final score is computed by calculating the arithmetic mean of the three items:

Enrollment Likelihood Score = (Item 1 + Item 2 + Item 3) / 3

• Interpretation: Composite scores range from 1.00 to 7.00. Higher numerical values reflect a stronger intention, psychological readiness, and behavioral likelihood of enrolling in and engaging with the designated program or community. In empirical research, the score can be analyzed as a continuous observed variable or modeled as a single latent factor with three reflective indicators.

11. Permissions & Fee and Test Year

Year of Publication: 2021.

Original Publication: Journal of Marketing Research, Volume 58, Issue 2, pages 223–245, published by the American Marketing Association (AMA) / SAGE Publications.

Permissions and Accessibility: The scale was developed for academic, scientific, and empirical research purposes. In accordance with standard academic publishing conventions, the three items may be utilized, adapted, and administered by researchers, non-profit institutions, and educational investigators without payment of royalties or licensing fees, provided that appropriate scholarly attribution is given to the original authors (Harmeling, Mende, Scott, & Palmatier, 2021). Commercial entities or organizations seeking to incorporate the instrument into proprietary diagnostic software or fee-generating commercial products should consult the copyright policies of the American Marketing Association and SAGE Publications.

12. References

13. Items of the Scale