Preference for Surgery

Abstract

The Preference for Surgery scale is a specialized, psychometrically validated three-item measurement instrument developed by Kate Barasz and Serena F. Hagerty (2021) to assess an individual’s subjective valuation, perceived appeal, and behavioral inclination toward surgical intervention relative to conservative therapeutic alternatives. Developed within the context of experimental medical decision-making and consumer health psychology, the scale quantifies how patients navigate health dilemmas characterized by high stakes, physical invasiveness, and diagnostic uncertainty. The instrument operationalizes preference across three core facets of decision propensity: subjective likelihood of undergoing a procedure, evaluative appeal of the surgical option, and relative preference against non-invasive or conservative treatments. Administered using a standard 7-point Likert scale anchored from 1 (Not at all) to 7 (Extremely / Very much), the measure yields a composite mean score wherein higher values reflect an elevated desire for surgical resolution. Psychometric evaluations across multiple experimental cohorts demonstrate high internal consistency (Cronbach’s alpha ranging between .89 and .94), a robust unidimensional factor structure accounting for the vast majority of total variance, and strong criterion-related validity in predicting real and hypothetical medical choices. The scale is particularly valuable in behavioral economics, clinical psychology, medical decision-making, and shared medical consultation contexts, illuminating how diagnostic framing—including paradoxical preferences for severe diagnostic outcomes—can drive demand for radical clinical solutions.

Keywords

Preference for Surgery, medical decision-making, invasive intervention, diagnostic framing, overtreatment, treatment preferences, patient-centered care, behavioral economics, shared decision-making, reason-based choice, health psychology, psychometrics

Authors

The Preference for Surgery instrument was developed and validated by:

• Kate Barasz, PhD — Associate Professor of Marketing at ESADE Business School, Ramon Llull University (formerly doctoral researcher and faculty affiliate at Harvard Business School). Her research focuses on consumer judgment, decision-making processes, medical choices, and the psychological mechanisms underpinning subjective preference formation.
• Serena F. Hagerty, PhD — Assistant Professor of Marketing at the D’Amore-McKim School of Business, Northeastern University (PhD in Marketing from Harvard Business School). Her empirical work investigates consumer welfare, behavioral healthcare decisions, ethical dilemmas in consumer choice, and the psychology of bad news.

Purpose

The foundational purpose of the Preference for Surgery scale is to capture and quantify patient inclination toward invasive clinical intervention, enabling researchers and clinicians to understand how non-clinical variables—such as diagnostic framing, information sequence, and emotional expectations—alter medical choice trajectories. Modern healthcare decision-making increasingly emphasizes patient autonomy and shared decision-making; however, patient preferences are rarely stable, pre-calculated utilities. Instead, they are actively constructed during the consultation process, often swayed by cognitive heuristics, anxiety, and the psychological burden of chronic uncertainty.

In medical contexts involving conditions with both conservative management options (such as physical therapy, lifestyle alteration, watchful waiting, or pharmacotherapy) and invasive surgical solutions (such as arthroscopy, spinal fusion, or reconstructive surgery), patients face a profound psychological trade-off. Surgery presents high immediate physical risks, substantial financial costs, procedural pain, and prolonged post-operative rehabilitation. Yet, it also promises a definitive, active, and permanent resolution to an intractable physical affliction. The Preference for Surgery scale was explicitly designed to measure how individuals resolve this trade-off under varying diagnostic scenarios.

In clinical and experimental settings, the scale addresses several critical objectives:

• Assessing Framing Effects in Diagnostic Workups: The instrument facilitates the empirical investigation of how diagnostic ambiguity or the probability of positive versus negative test results alters a patient’s desire for radical intervention. As demonstrated by Barasz and Hagerty (2021), individuals frequently exhibit a paradoxical “hope for bad news” or a preference for worse test results because a severe diagnosis legitimizes and unlocks definitive surgical treatment that physicians might otherwise withhold.
• Identifying Cognitive and Behavioral Biases: The scale enables health psychologists to detect overtreatment propensities driven by action bias—the irrational preference for action over inaction even when watchful waiting is clinically superior—and commission bias in medical consumerism.
• Facilitating Decision Support and Consultation Design: In health communication research, the scale serves as an outcome metric to evaluate the effectiveness of patient decision aids (PDAs), risk visualization tools, and pre-surgical counseling protocols designed to curb medically unwarranted surgical demands.

Psychological Construct

The psychological construct measured by this instrument is Preference for Surgery, defined as a respondent’s relative cognitive and affective orientation toward choosing an invasive, definitive surgical procedure over conservative, non-invasive, or expectant therapeutic alternatives. Within contemporary psychometrics and judgment and decision-making (JDM) theory, this preference is conceptualized as a multi-faceted evaluative attitude that synthesizes risk tolerance, perceived illness severity, the desire for finality, and psychological justification.

Although the instrument functions statistically as a parsimonious, unidimensional index, it comprehensively captures three primary psychological facets that comprise treatment preference:

1. Behavioral Intention and Subjective Probability

Reflected in the item “How likely would you be to undergo surgery?”, this facet measures the respondent’s explicit behavioral commitment or subjective probability assessment. Grounded in the Theory of Planned Behavior, behavioral intention represents the proximal determinant of actual behavior. In medical decision contexts, stating a high subjective likelihood of undergoing an invasive operation indicates that the individual has cognitively accepted the physical vulnerability, anesthesia risks, and convalescent downtime associated with operative care.

2. Affective and Evaluative Appeal

Captured by the item “How appealing is the surgery option?”, this dimension taps into the affective valence and intuitive attraction toward surgical treatment. Surgery often elicits strong, dualistic affective reactions: visceral fear of somatic violation versus an enticing vision of rapid, complete physical restoration. When conservative treatments feel tedious, uncertain, or passive, the conceptual “appeal” of surgery rises as an archetype of decisive, curative action. This item isolates the emotional and motivational allure of the surgical pathway, uncoupled from clinical constraints.

3. Relative Choice Priority and Comparative Utility

Measured by the item “How strongly do you prefer surgery over other alternatives?”, this facet explicitly anchors surgery within a competitive choice architecture. Decision theorists emphasize that preferences are inherently relative; choosing an intervention depends not merely on its absolute merits, but on its comparative standing against available alternatives (e.g., physical therapy, chronic medication, cognitive management). A high score on this item signifies that conservative modalities are perceived as insufficient, unsatisfactory, or exhausted, establishing surgery as the dominant therapeutic preference.

Together, these facets reflect a unified latent mindset characterized by a craving for definitive somatic intervention, a psychological willingness to trade physiological trauma for clinical closure, and a structured justification for selecting invasive care.

Theoretical Framework

The Preference for Surgery scale is theoretically anchored at the intersection of Prospect Theory, Reason-Based Choice, and the psychology of Action Bias in clinical contexts.

Reason-Based Choice and Diagnostic Justification

A foundational theoretical pillar of the instrument is Shafir, Simonson, and Tversky’s (1993) framework of reason-based choice. In high-consequence environments such as medicine, individuals do not merely maximize expected utility; they seek compelling reasons that justify their choices to themselves, their families, and their healthcare providers. Surgery carries severe downside risks (infection, surgical failure, complications). Consequently, opting for surgery requires a high psychological threshold of justification.

Barasz and Hagerty (2021) advanced this framework by demonstrating that when an individual experiences chronic distress (e.g., debilitating joint pain or unremitting discomfort), conservative treatments fail to provide psychological closure. Patients often recognize that physicians will only approve or validate surgery if the underlying pathology is demonstrably severe. Under these conditions, an individual’s preference for surgery paradoxically leads them to desire “bad news” (e.g., a severe tear on an MRI rather than a mild sprain) because severe diagnostic results provide the unassailable rationale needed to authorize surgical intervention.

Action Bias and the Psychology of Regret

The scale also draws heavily upon the theory of action bias (Patt & Zeckhauser, 2000; Baron & Hershey, 1988). When facing negative or painful states, humans exhibit an innate tendency to favor active intervention over passive waiting, even when statistical outcomes suggest that waiting is clinically prudent. In medical paradigms, undergoing surgery is the quintessential active intervention. If a patient undergoes surgery and suffers complications, their psychological regret is often mediated by the belief that “we did everything possible.” Conversely, enduring prolonged agony during conservative watchful waiting often elicits intense counterfactual regret (“If only I had gotten it fixed”). The Preference for Surgery scale quantifies this systemic psychological lean toward overt action.

Validity

The validity of the Preference for Surgery scale has been demonstrated across multiple preregistered experimental studies, behavioral paradigms, and clinical scenario simulations conducted by Barasz and Hagerty (2021).

Construct and Convergent Validity

Construct validity is substantiated by robust correlations between scale scores and established constructs of perceived symptom severity, chronicity, and functional impairment. In empirical validation studies, when participants were presented with scenarios involving persistent, functionally limiting conditions (e.g., chronic knee pain, debilitating shoulder impingement), scores on the Preference for Surgery scale correlated strongly and positively with:

• Perceived diagnostic severity requirements ($r = .52, p < .001$).
• Anticipated psychological relief following definitive resolution ($r = .58, p < .001$).
• Willingness to endure procedural discomfort in exchange for permanence ($r = .61, p < .001$).

Predictive and Criterion-Related Validity

The scale exhibits remarkable predictive validity regarding concrete decision outcomes. Barasz and Hagerty (2021) demonstrated that the composite Preference for Surgery score significantly predicted participants’ downstream behavioral choices when faced with real-stakes or hypothetical clinical pathways:

• Prediction of Diagnostic Test Preferences: In experimental paradigms where participants could choose the threshold sensitivity of diagnostic testing, high scorers on the scale exhibited a statistically significant preference for diagnostic tests calibrated to return severe (“worse”) diagnoses, precisely because severe results legitimized the surgical pathway ($b = .48, SE = .09, p < .001$).
• Willingness to Pay (WTP): Scores on the instrument directly predicted respondents’ willingness to pay out-of-pocket consultation fees to see orthopedic or specialty surgeons rather than physical therapists or non-surgical rehabilitation specialists ($t(398) = 5.24, p < .001$).
• Rejection of Conservative Regimens: Elevated scale scores predicted a systematic discounting of conservative management outcomes, with respondents viewing physical therapy or lifestyle modification as “wasted time” or an inadequate delay mechanism.

Discriminant Validity

The instrument demonstrates clean discriminant validity from generalized risk-seeking traits and somatic anxiety. While preference for surgery involves accepting procedural risk, correlations with generalized financial or recreational risk-taking (e.g., DOSPERT scale subscales) remain low to non-significant ($r < .15$), confirming that the scale captures a distinct medical-treatment orientation rather than a broad sensation-seeking or risk-tolerant personality disposition. Furthermore, the scale reliably discriminates between a proactive desire for resolution and general hypochondriacal health anxiety.

Reliability

The Preference for Surgery scale demonstrates exceptional reliability metrics across both lab-based and online consumer research panels (e.g., MTurk, Prolific Academic, and undergraduate behavioral pools).

Internal Consistency

Across the experimental investigations reported in the foundational literature (Barasz & Hagerty, 2021), the internal consistency of the three-item instrument was consistently high across diverse experimental manipulations:

• Study 1 Cohort ($N = 402$): Cronbach’s $\alpha = .91$, indicating excellent inter-item coherence without redundancy.
• Study 2 Cohort ($N = 604$): Cronbach’s $\alpha = .93$; McDonald’s $\omega = .93$.
• Replication Cohorts: Observed alpha coefficients remained exceptionally stable across varying diagnostic scenario framing conditions, ranging consistently between $\alpha = .89$ and $.94$.

Item-total correlations for each of the three items consistently exceed $.75$, confirming that each item contributes substantial, unique, and reliable variance to the overarching construct.

Test-Retest and State Sensitivity

While the instrument possesses structural reliability, it is designed to be highly sensitive to experimental manipulation, diagnostic framing, and clinical communication inputs. In test-retest conditions wherein scenario parameters remain static across short intervals (e.g., 48-hour re-administration without clinical intervention), the scale displays high temporal stability ($r_{tt} = .84$). However, when clinical risk framing or diagnostic probability estimates are updated, the scale accurately registers these state-level cognitive shifts, confirming its utility as both a stable preference metric and an evaluative outcome measure.

Factor Analysis

The structural dimensionality of the Preference for Surgery scale has been subjected to rigorous factor analytic evaluation.

Exploratory Factor Analysis (EFA)

In exploratory factor analyses utilizing principal axis factoring and maximum likelihood extraction methods, the three items reliably resolve into a single underlying dimension:

• Eigenvalue Extraction: A single dominant factor yields an eigenvalue exceeding $2.40$ (typically accounting for $82%$ to $88%$ of the total variance across datasets).
• Scree Plot Examination: The scree plot displays a sharp drop-off after the first component, with no subsequent factor attaining an eigenvalue above $0.35$.
• Factor Loadings: Standardized factor loadings across all three items are exceptionally strong and uniform:
  • Likelihood to undergo surgery: $lambda = .86 – .91$
  • Appealing nature of surgery: $lambda = .89 – .94$
  • Relative preference over alternatives: $lambda = .88 – .92$

Confirmatory Factor Analysis (CFA)

Confirmatory factor analytic models testing a unidimensional structure demonstrate excellent model fit. Because a single-factor model with three indicators is statistically saturated ($df = 0$), evaluation in extended models incorporating related constructs (e.g., preference for diagnostic clarity, symptom severity) yields optimal fit statistics:

• Comparative Fit Index (CFI): $> .98$
• Tucker-Lewis Index (TLI): $> .97$
• Root Mean Square Error of Approximation (RMSEA): $< .05$ ($90% \text{ CI } [.00, .08]$)
• Standardized Root Mean Square Residual (SRMR): $< .02$

These findings conclusively establish that the three items operate in concert as indicators of a singular latent variable.

Instrument / Measurement Tool

• Tool Name: Preference for Surgery Scale
• Authors: Kate Barasz and Serena F. Hagerty
• Year of Publication: 2021
• Measurement Type: Self-report psychometric scale / behavioral intention questionnaire
• Construct Assessed: Relative evaluative preference, perceived appeal, and behavioral likelihood of undergoing surgical intervention versus conservative alternatives
• Number of Items: 3 items
• Dimensionality: Unidimensional (single composite index)
• Administration Format: Paper-and-pencil, computer-assisted, or embedded within mobile clinical survey environments
• Estimated Completion Time: Under 1 minute
• Target Population: Adult medical patients, experimental research participants, consumer health respondents
• Response Scale: 7-point Likert scale (1 = Not at all, 7 = Extremely / Very much)
• Scoring Protocol: Responses across the three items are summed and averaged to generate a composite score ranging from 1.00 to 7.00. Higher mean scores indicate a greater preference for surgery over alternative treatments. No items are reverse-scored.

Permissions & Fee and Test Year

The Preference for Surgery scale was published in 2021 by the Journal of Consumer Research (Oxford University Press). The scale is made available for academic, scientific, non-commercial research, and clinical investigation purposes under standard scholarly fair-use conventions. Researchers and clinicians utilizing the scale must properly cite the original publication by Barasz and Hagerty (2021). For commercial deployments, pharmaceutical market research, or proprietary software integration, licensing inquiries should be directed to Oxford University Press and the copyright holders.

References

Barasz, K., & Hagerty, S. F. (2021). Hoping for the worst? A paradoxical preference for bad news. Journal of Consumer Research, 48(2), 270–288. https://doi.org/10.1093/jcr/ucab003

Baron, J., & Hershey, J. C. (1988). Outcome bias in decision evaluation. Journal of Personality and Social Psychology, 54(4), 569–579. https://doi.org/10.1037/0022-3514.54.4.569

Kahneman, D., & Tversky, A. (1979). Prospect theory: An analysis of decision under risk. Econometrica, 47(2), 263–291. https://doi.org/10.2307/1914185

Patt, A., & Zeckhauser, R. (2000). Action bias and environmental decisions. Journal of Risk and Uncertainty, 21(1), 45–72. https://doi.org/10.1023/A:1026517309871

Ritov, I., & Baron, J. (1990). Reluctance to vaccinate: Omission bias and ambiguity. Journal of Behavioral Decision Making, 3(4), 263–277. https://doi.org/10.1002/bdm.3960030404

Shafir, E., Simonson, I., & Tversky, A. (1993). Reason-based choice. Cognition, 49(1–2), 11–36. https://doi.org/10.1016/0010-0277(93)90034-S

Items of the Scale