New Ten-Item Scale Captures Surgical Anxiety with Strong Psychometric Credentials

For millions of patients each year, the hours before an operation are defined not by physical pain but by a quieter, grinding dread. Surgery-related anxiety is one of the most common psychological responses in hospital medicine, and clinicians have long lacked a brief, purpose-built instrument to detect it. A research team based at Leshan People’s Hospital in Sichuan Province, China, has now reported the development and validation of a new measure, the Surgical Patient’s Anxious Condition Assessment Scale, abbreviated as SPAC. Writing in the journal Discover Psychology, the team led by Li Wei and colleagues describes a ten-item scale whose statistical performance suggests it could become a practical screening tool for identifying surgical inpatients whose worry about their operation deserves attention.

The study’s rationale rests on a familiar clinical dilemma. General-purpose anxiety questionnaires exist, but they are not tailored to the specific cognitive and emotional concerns that arise in the days surrounding an operation, such as fear of anesthesia, fear of complications, or worry about waking during surgery. Without a focused instrument, nurses and physicians may miss patients whose distress is severe enough to warrant non-pharmacological interventions, such as reassurance, structured information-giving, relaxation training, or psychological support. The researchers set out explicitly to build a scale that could provide the evidentiary foundation for such non-drug interventions, and their design followed a deliberately rigorous, multi-stage pipeline that has become the gold standard in psychometric instrument development.

The first stage was qualitative. At Leshan People’s Hospital, the team conducted semi-structured interviews with eleven surgical patients, using open-ended conversation to surface the language and themes patients themselves use to describe preoperative and postoperative worry. From these interviews the researchers generated an initial pool of candidate items. They then convened a Delphi expert inquiry, a structured consensus method in which sixteen experts independently rated and commented on the items across successive rounds, refining the wording and pruning redundancies. A pilot test with thirty patients followed, allowing the team to adjust the scale in response to real patient feedback about clarity and relevance before any formal statistical testing began.

The psychometric heart of the study involved two large, independent samples of surgical inpatients from the same hospital. The researchers administered the draft scale to all surveyed patients and then split the data into two groups for separate analyses. A randomly selected sample of 376 patients was used for exploratory factor analysis, a statistical technique that asks whether the patterns of correlation among items reveal an underlying structure. A second, separate sample of 386 patients was used for confirmatory factor analysis, which tests whether a predefined structure fits the new data. Splitting the samples in this way is considered best practice, because a structure discovered in one dataset is only convincing if it replicates in another.

The exploratory analysis was conducted with technical care. Because the scale uses a three-point Likert response format, the item responses are ordinal categories rather than continuous measurements, and the researchers therefore based their analysis on a polychoric correlation matrix, which estimates the latent correlation between items more accurately than a standard Pearson matrix when response options are few. Principal axis factoring was used to extract the common factors, and the suitability of the data was confirmed by two standard tests. The Kaiser-Meyer-Olkin measure of sampling adequacy reached 0.937, far above the conventional threshold of 0.60, indicating that the items shared substantial common variance. Bartlett’s test of sphericity produced an approximate chi-square of 2144.652 with 45 degrees of freedom, a result statistically significant at p less than 0.001, showing the correlation matrix was far from identity.

What the exploratory analysis found was striking in its simplicity. Applying the standard criterion of eigenvalues greater than one, the analysis extracted a single common factor accounting for 62.3 percent of the cumulative variance. In plain terms, all ten items appeared to be measuring the same underlying construct, surgery-related anxious condition, rather than several distinct subdimensions. Factor loadings for each individual item ranged from 0.71 to 0.82, all comfortably exceeding the 0.40 acceptance criterion, meaning every item correlated strongly with the common factor and none needed to be discarded. A unidimensional scale is attractive in clinical practice because a single total score can be computed and interpreted quickly at the bedside.

The confirmatory factor analysis on the second sample then tested whether this one-factor structure held up independently. The results met all widely accepted benchmarks. The chi-square to degrees-of-freedom ratio was 4.080, within the commonly cited acceptable range of below five. The Comparative Fit Index reached 0.942 and the Tucker-Lewis Index 0.926, both above the 0.90 threshold that signals good fit, and approaching the stricter 0.95 standard. The Root Mean Square Error of Approximation was 0.058 and the Standardized Root Mean Square Residual 0.067, both below the 0.08 cutoff typically treated as evidence of reasonable model fit. Together, these indices indicate that the single-factor model reproduced the observed data well in a completely new group of patients.

Reliability and convergent validity added further support. The Cronbach’s alpha coefficient for the total scale was 0.893, indicating excellent internal consistency, which means the items respond coherently and patients who score high on one item tend to score high on the others. To examine convergent validity, the researchers administered the SPAC alongside the State portion of the State-Trait Anxiety Inventory, a well-established measure, in a subgroup of 57 patients. The correlation between the two instruments was 0.424 with a p-value of 0.001, a statistically significant positive association demonstrating that the new scale tracks anxiety as expected. The moderate rather than very high correlation is also informative, since it suggests the SPAC captures content specific to the surgical context that a generic state anxiety measure does not fully overlap.

The authors are careful, and rightly so, about the limits of their work. They conclude that the SPAC shows satisfactory psychometric properties and may serve as a screening measure for surgery-related cognitive worry, but they emphasize that its clinical utility remains preliminary. Predictive validity, the demonstration that scale scores actually forecast clinically meaningful outcomes such as anesthetic requirements, postoperative pain, length of stay, or recovery trajectories, has not yet been established. Neither have cut-off scores, the threshold values clinicians would need to decide who counts as a high-anxiety case requiring intervention. Until those studies are done, the researchers recommend the scale be used mainly for research purposes rather than as a decision-making tool in routine care.

Even with those caveats, the study offers a template for how new clinical instruments should be built: grounded in patient interviews, refined through expert consensus, piloted with the target population, and then validated on two independent samples with both exploratory and confirmatory analysis. The work was funded by a Specialised Nursing Research Funding Grant from the Leshan Nursing Association and approved by the hospital’s ethics committee, with written informed consent from all participants. For the surgical teams on the front lines, the promise is tangible. A brief, ten-item questionnaire that reliably flags surgical patients experiencing significant anxiety could make non-pharmacological care more systematic, ensuring that reassurance, education, and psychological support reach the patients who need them most, before the anesthesia ever begins.

Subject of Research: Development and psychometric validation of the Surgical Patient's Anxious Condition Assessment Scale for measuring surgery-related anxiety

Article Title: The Surgical Patient’s Anxious Condition Assessment Scale demonstrates good factorial structure

Article References: WEI, L., JIE, Y., LI JUN, W., LI, Z., FENG JIAO, X., HUI, X., XIN, Z., GUO JUN, Z., & ZE HUA, L. (2026). The Surgical Patient’s Anxious Condition Assessment Scale demonstrates good factorial structure. Discover Psychology. https://doi.org/10.1007/s44202-026-00929-8

Image Credits: AI Generated

DOI: 10.1007/s44202-026-00929-8

Keywords: psychometrics, anxiety, surgical patients, scale validation, factor analysis, Cronbach's alpha, confirmatory factor analysis, nursing research, screening tool, preoperative care, China, non-pharmacological intervention