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. 2017 Jul 25;27(1):e1574. doi: 10.1002/mpr.1574

Psychometric investigation of the specific phobia of vomiting inventory: A new factor model

Danielle J Maack 1,✉, Chad Ebesutani 2, Todd A Smitherman 1
PMCID: PMC6877170  PMID: 28745033

Abstract

Well‐validated, standardized measures are lacking for the assessment of emetophobia, the specific phobia of vomiting. The Specific Phobia of Vomiting Inventory (SPOVI) was recently developed and shows promise as a useful measure of emetophobia. The goal of the present study was to further examine and investigate the psychometric properties of the SPOVI in a large student sample (n = 1626), specifically focusing on its factor structure, measurement invariance across gender, and convergent/divergent validity. Confirmatory factor analysis results provide support for a one‐factor model of the SPOVI, in contrast to the previously proposed two‐factor model. Internal consistency of the SPOVI was good (α = 0.89) and measurement invariance across gender invariance was supported. The SPOVI also demonstrated good psychometric properties with respect to convergent and divergent validity. The present study's demonstration of the reliability and validity of the SPOVI suggests that the instrument may be a valuable tool for assessing emetophobia symptoms based on its one‐factor structure.

Keywords: CFA, emetophobia, measure invariance, specific phobia of vomiting

1. INTRODUCTION

Emetophobia, a specific phobia of vomiting, is a relatively under‐researched anxiety disorder that has recently begun to attract increased attention (Boschen, 2007; Marks, 1987; van Hout & Bouman, 2012; Veale & Lambrou, 2006). As a specific phobia, emetophobia is currently subsumed under the “other” category of specific phobias (DSM‐V; American Psychiatric Association [APA], 2013; ICD‐10; World Health Organization [WHO], 1992). As a basic definition, emetophobia is the excessive fear of and preoccupation with vomiting. The presentation of this disorder is largely diverse and poorly understood (Boschen, 2007). From what has been assessed, emetophobia appears to be characterized by an early age of onset (Lipsitz, Fyer, Paterniti, & Klein, 2001), a chronic course (Lipsitz et al., 2001; Maack, Deacon, & Zhao, 2013) without successful treatment, and few (if any) periods of remittance (Lipsitz et al., 2001). Emetophobic symptoms can be triggered by both internal stimuli (i.e. catastrophic cognitions, physiological sensations) and external stimuli (i.e. sights/sounds related to the experience of vomiting; Maack et al., 2013). Although previously considered a rare phobia, prevalence estimates range between 1.7 and 3.1% for men and 6 and 7% for women (Hunter & Antony, 2009; Phillips, 1985), and these numbers are likely underestimates as emetophobia symptoms may mistakenly be attributed to other anxiety disorders such as panic disorder, social phobia, obsessive–compulsive disorder, and health anxiety (see Boschen, 2007, for a review). Emetophobia can cause significant distress (e.g. panic attacks; fear of somatic symptoms related to vomiting; Lipsitz et al., 2001) and functional impairment (avoiding social situations; being significantly underweight from dieting restrictions; Veale et al., 2013; Boschen, 2007), particularly among women, some of whom delay pregnancy (Lipsitz et al., 2001; Maack et al., 2013; Veale & Lambrou, 2006) for fear of morning sickness and/or fear of the baby vomiting.

Despite a growing body of research examining emetophobia, only recently have two measures been developed to scientifically assess and standardize evaluation of symptoms. The Emetophobia Questionnaire‐13 (EmetQ‐13; Boschen, Veale, Ellison, & Reddell, 2013) and the Specific Phobia of Vomiting Inventory (SPOVI; Veale et al., 2013) have been presented as promising measures of severity of emetophobia symptoms. The initial measure development paper of the SPOVI assessed its psychometric properties among a clinical sample and included a control group with no known vomiting fears; however, the control group was noted to have insufficient variance in item responses to allow for factor analysis (Veale et al., 2013). In this initial study, the authors proposed a two‐factor structure underlying the SPOVI representing (1) avoidance behavior (i.e. avoiding/trying to control stimuli due to a fear of vomiting), and (2) threat monitoring (i.e. worry/self‐focus on monitoring symptoms of being ill) based on Horn's parallel factor analysis. Of note, the initial study did not provide the correlation between the two proposed factors or provide an ethnic breakdown of participants.

The SPOVI has been implemented in several studies as a measure of emetophobic symptoms, including two case studies detailing emetophobia treatment where SPOVI scores were the main clinical outcome (Fix, Proctor, & Gray, 2016; Paulus & Norton, 2016), a group design pilot study of a cognitive behavioral intervention for emetophobia (Riddle‐Walker et al., 2016), and as an analogue measure to assess clinical correlates of emetophobia in a college sample (Wu, Rudy, Arnold, & Storch, 2015). Additionally, it has been used to distinguish between individuals who restricted food on the basis of fear of vomiting and those exhibiting similar eating pathology who did not endorse such fear (Veale, Costa, Murphy, & Ellison, 2012).

To date, however, the only study of the SPOVI assessing its psychometrics is the original scale development paper (Veale et al., 2013). Further psychometric investigation of the instrument in a normative sample would enhance research in this specific area. In particular, the distinction between “normal” and “abnormal” is a fundamental element of understanding the psychometric validity and clinical utility of psychological measures (Nunnally & Bernstein, 1994). For example, establishing normative values through rigorous research facilitates comparison of subsequent findings across settings (i.e. community versus clinical versus university samples) in terms of symptom intensity, frequency, duration, and resultant functional impairment. A nuanced view of these distinctions can, in turn, lead to greater understanding of etiology, course, and treatment, particularly to the degree programmatic research establishes instruments that are sensitive to treatment change.

As such, the present study aimed to further examine and investigate the psychometric properties of the SPOVI among a student sample, focusing specifically on factor structure, gender invariance (as most anxiety disorders disproportionately affect women; Seedat et al., 2009), and convergent/divergent validity. Given the SPOVI's iterative development based on interviews with individuals seeking emetophobia treatment (Veale et al., 2013), the transdiagnostic nature of anxiety disorders more generally, and the limited research to suggest otherwise, a priori hypotheses suggested that the factor structure in a normative sample would emulate that shown in the initial instrument development study. Similarly, given a lack of evidence for differential responses to items across genders, and inclusion of both men and women in iterative interviews conducted in the original study (Veale et al., 2013), it was also hypothesized that the instrument would exhibit gender invariance in the current sample. Finally, to assess convergent and divergent validity for the SPOVI, the anxiety and depression subscales of the 21‐item Depression, Anxiety and Stress Scale (DASS‐21) and the Anxiety Sensitivity Index‐3 (ASI‐3) were used. Theoretically, and in line with the initial development study, these measures were selected to help determine if the SPOVI is able to assess and discern symptomatology related to emetophobia, and distinguish such symptoms beyond general duress (anxiety and depressive symptoms) and/or sensitivity to such (anxiety sensitivity).

2. METHOD

2.1. Participants

Participants were 1626 students recruited from a large south‐eastern University. The mean age of the sample was 19.04 years (standard deviation [SD] = 2.12, range = 18–48), and the group consisted of 1038 females (63.8%) and 588 males (36.2%). The ethnic makeup of the sample was 77% Caucasian, 17.2% Black, 1.8% Asian, 1.8% Multiracial, 1.7% Hispanic or Latino, 0.2% Pacific Islander, and 0.2% Native American or Alaskan Native. Informed consent was obtained from all individual participants included in the study.

2.2. Measures

2.2.1. Specific phobia of vomiting inventory (SPOVI; Veale et al., 2013)

The SPOVI is a 14‐item, self report questionnaire of emetophobia symptom severity. Each item is scored on a Likert‐type scale ranging from 0 (not at all) to 4 (all the time). Total score ranges from 0 to 56, with higher scores reflecting greater endorsement of symptoms/severity. A cutoff score of 10 is considered a positive screen of emetophobia (Veale et al., 2013). From the initial development study, internal consistency of the overall scale ranged from α = 0.81 (community sample) to α = 0.91 (clinical sample), with subscale consistencies (only assessed previously in the clinical sample) of α = 0.85 (avoidance) and α = 0.88 (threat monitoring; Veale et al., 2013). In the present sample the overall internal consistency was α = 0.89 (avoidance subscale α = 0.85; threat monitoring subscale α = 0.78).

2.2.2. Anxiety sensitivity index‐3 (ASI‐3; Taylor et al., 2007)

The ASI‐3 (Taylor et al., 2007) is an 18‐item measure that assesses the degree to which participants fear perceived negative consequences of anxiety symptoms. Items are rated on a 5‐point Likert‐type scale from 0 (very little) to 4 (very much) with total scores ranging from 0 to 72. The ASI‐3 measures three theoretically derived facets of anxiety sensitivity: physical (e.g. “It scares me when my heart beats rapidly”), cognitive (e.g. “When I feel ‘spacey’ or spaced out, I worry that I may be mentally ill”), and social concerns (e.g. “It is important not to appear nervous”). Initial validation demonstrated that the ASI‐3 possessed sound psychometric properties as examined across a number of sites using diverse participants (Taylor et al., 2007). However, the total ASI‐3 score was used in the present analysis as it has been found to be a better predictor (accounting for 50% of the variance) of anxiety sensitivity than use of the separate subscales (Ebesutani, McLeish, Luberto, Young, & Maack, 2014; Osman et al., 2010). In the present sample, overall internal consistency was good (α = 0.89).

2.2.3. Depression, anxiety and stress Scales – 21‐item version (DASS‐21; Lovibond & Lovibond, 1995a)

The DASS‐21 is a 21‐item self‐ report questionnaire designed to assess the core symptoms of depression, anxiety, and stress. Items are measured on a Likert‐type scale ranging from 0 “Did not apply to me at all” to 3 “Applied to me very much, or most of the time” with subscale scores ranging from 0 to 21. The DASS‐21 has demonstrated adequate test–retest reliability (Brown, Chorpita, Korotitisch, & Barlow, 1997), and there is extensive evidence for its construct and discriminant validity (Antony, Bieling, Cox, Enns, & Swinson, 1998; Brown et al., 1997; Clara, Cox, & Enns, 2001; Lovibond & Lovibond, 1995a; Lovibond & Lovibond, 1995b). Both the anxiety and depression symptom severity subscales of the DASS‐21 were examined in this study for assessment of convergent/divergent validity. Internal consistency estimates (α) in this sample were acceptable for the anxiety subscale = 0.78 and good for both the depression = 0.83 and stress subscales = 0.82.

2.3. Procedure

The current study was part of a larger psychology research screening. All procedures performed in studies involving human participants were in accordance with the ethical standards of the institutional and/or national research committee and with the 1964 Helsinki declaration and its later amendments or comparable ethical standards. After informed consent was obtained, participants completed all measures via an online survey system. Students received research or course credit for participation.

2.4. Data analytic strategy

2.4.1. Confirmatory factor analysis (CFA)

Using confirmatory factor analysis (CFA) via Mplus version 7.11 (Muthen & Muthen, 2010), the fit of competing factor structures of the SPOVI was examined. Polychoric correlations and the robust weighted least‐squares with mean and variance adjustment (WLSMV) estimator were used because the analyses were based on Likert‐response options that produce categorical (ordinal) data. The WLSMV estimator is one of the most recommended estimators to use when conducting CFA with categorical data (Flora & Curran, 2004; Holgado‐Tello, Chacon‐Moscoso, Barbero‐Garcia, & Vila‐Abad, 2010; Muthen, du Toit, & Spisic, 1997). The following fit indices and cutoffs were used to examine model fit of the tested structures: the root mean square error of approximation (RMSEA; Steiger, 1990); Comparative Fit Index (CFI; Bentler, 1990), and Tucker–Lewis Index (TLI; Tucker & Lewis, 1973). CFI values greater than 0.90 (Bentler, 1990) and 0.95 (Hu & Bentler, 1999) indicated acceptable and good model fit, respectively. RMSEA values lower than 0.08, and 0.05 indicated acceptable and good fit, respectively (Browne & Cudeck, 1993).

2.4.2. Missing data

Relatively few participants had missing data on the SPOVI: 1578 (97.0%) had no missing data, 44 (2.7%) had only one missing item, three (0.2%) had two missing items, and one (0.1%) had four missing items. Missing data were addressed using pairwise present procedures available in Mplus, which is recommended when using the WLSMV estimator (see http://www.statmodel.com/discussion/messages/11/1535.html).

2.4.3. Model comparisons

To compare nested models, the chi‐square (χ 2) difference test (Bentler & Bonett, 1980) was performed. The “difftest” function in Mplus was used to compute the χ 2 difference test (as opposed to hand calculating the χ 2 difference test). This method was chosen because limited information estimators (such as the WLSMV estimator) necessitate estimation of degrees of freedom and because the differences between χ 2 values are not distributed as χ 2 values when limited estimators are employed. The Mplus Technical Appendices (at http://www.statmodel.com/ download/webnotes/webnote10.pdf; Asparouhov & Muthen, 2006) and the Mplus User's Guide (Muthen & Muthen, 2010) outline how to execute the difftest function in Mplus and indicate how degrees of freedom are estimated.

2.4.4. Haberman analyses

The relative reliability and utility of the subscales compared to the total score (when appropriate) was examined via Haberman analyses (Haberman, 2008). Haberman Analyses examine whether a subscale score is a better predictor of an individual's “true score” of the trait targeted by that subscale compared to using the total score. The Haberman procedures involve computing the proportional reduction in mean squared error based on the total score (PRMSEtotal) and comparing that value to the proportional reduction in mean squared error based on the subscale score (PRMSEsubscale), the latter of which is typically estimated by the reliability alpha coefficient (see Reise, Bonifay, & Haviland, 2013). If PRMSEsubscale > PRMSEtotal, then the subscale provides a more reliable indicator of the subscale's true score relative to the total score. If, however, PRMSEtotal > PRMSEsubscale, then the total score captures at least the same amount of variance as the subscale, and thus scoring and interpreting subscales is not necessary (see Reise et al., 2013).

2.4.5. Measurement invariance across gender

Multi‐group CFA (MG‐CFA) and the MG‐CFA procedures outlined by Brown (2006) were employed to examine the measurement invariance of the best‐fitting model across gender. First, single‐sample solutions were examined for good fit within each of the male‐only (n = 588) and female‐only (n = 1038) subsamples separately. The tested model should fit well (based on the aforementioned fit indices and cutoffs) in each sample separately before proceeding to further MG‐CFA invariance tests. Following the examination of single‐sample solutions, configural invariance (also known as the test of “equal form”) was examined. This test is conducted on the full sample and tests whether the overall number of factors and the item‐to‐factor grouping patterns across all factors are the same across genders. Support for configural invariance is based on whether the fit indices achieve the aforementioned benchmarks for good model fit (cf. Brown, 2006).

If configural invariance is supported, metric invariance can then be tested. Metric invariance (also referred to as the test of “equal factor loadings”) refers to whether the factors have the same meaning (and thus the same factor loading strengths) across groups. This is tested by imposing the equality constraint for factor loadings between subgroups (e.g. across males and females). Support for metric invariance was determined using the recommended ΔCFI difference test (Chen, 2007). If the difference in the CFI fit index of the metric invariance and configural invariance model is less than 0.01 (i.e. ΔCFI <0.01), then the model is associated with metric invariance (Chen, 2007; Cheung & Rensvold, 2002).

If metric invariance is supported, then the test of scalar invariance (i.e. “equal thresholds” or the test of “differential item functioning”; McDonald, 1999) can be conducted. This involved constraining thresholds (and factor loadings) to be equivalent across groups. The presence of differential item functioning suggests that individuals who fall on the same level of the latent trait report systematically different on the observed items. In other words, scalar invariance tests whether the comparison of group scores is meaningfully interpretable. Scalar invariance is examined in a similar way as metric invariance, with the ΔCFI difference test relative to the metric invariance model.

3. RESULTS

3.1. Confirmatory factor analysis (CFA)

First, the fit of a 1‐factor model was examined. The 1‐factor model was associated with good model fit (RMSEA = 0.069; CFI = 0.961, TLI = 0.953; WRMR = 1.717). All factor loadings were also significant (p < 0.001), ranging from 0.65 to 0.95. Examination of modification indices did not reveal the need to correlate any error terms between items. All loadings and standard errors are presented in Table 1.

Table 1.

Factor loadings and standard errors for the 1‐factor confirmatory factor analysis model

Item Factor loading Standard errors
SPOVI1 .76 .019
SPOVI2 .95 .015
SPOVI3 .93 .011
SPOVI4 .84 .018
SPOVI5 .85 .02
SPOVI6 .89 .016
SPOVI7 .88 .018
SPOVI8 .65 .024
SPOVI9 .82 .018
SPOVI10 .75 .021
SPOVI11 .75 .021
SPOVI12 .87 .015
SPOVI13 .91 .016
SPOVI14 .87 .016
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Note: SPOVI, Specific Phobia of Vomiting Inventory.

Next, the fit of the proposed 2‐factor model, which was based on results of the initial factor analyses from the scale development (Veale et al., 2013), was examined. The two factors were termed Threat Monitoring and Avoidance. The 2‐factor model was also associated with good model fit (RMSEA = 0.068; CFI = 0.962, TLI = 0.955; WRMR = 1.674). The fit indices relative to the 1‐factor model (RMSEA = 0.069; CFI = 0.961, TLI = 0.953; WRMR = 1.717) were not substantially different. All factor loadings of the 2‐factor model were significant (p < 0.001), ranging from 0.65 to 0.96. When compared to the 1‐factor model using the χ 2 difference test, the 2‐factor model fit significantly better (χ 2 diff (1) = 31.73, p < 0.001). Notably, however, the two factors were correlated at 0.96, which suggests a lack of distinct factors.

3.2. Haberman analyses

Given that the high intercorrelation between the two factors questions the distinctiveness of these two factors, Haberman analyses were conducted to examine the relative reliability of each of these two subfactors (i.e. the subscales of the 2‐factor model) in relation to the total score (i.e. the 1‐factor model). PRMSEtotal (0.881) was greater than PRMSEsubscale for both the Avoidance subscale (0.845) and the Threat Monitoring subscale (0.778). These results suggest that the subscales of the 2‐factor model do not allow a better prediction of subscale true scores as opposed to simply knowing the total scale score (i.e. the 1‐factor model). These results, together with the high correlation between the two factors, suggest that the 1‐factor model appears to be a more viable and supported model. Subsequent analyses thus proceeded with measurement invariance tests of the 1‐factor model via MG‐CFA.

3.3. Measurement invariance across gender

The fit indices associated with the measurement invariance tests may be seen in Table 2. The single‐sample solutions revealed good model fit in each of the male‐only (RMSEA = 0.055; CFI = 0.986) and female‐only (RMSEA = 0.073; CFI = 0.958) subsamples. The configural invariance (“equal form”) model was also associated with good model fit (RMSEA = 0.068; CFI = 0.968), suggesting that the general factor structure was the same across males and females. The metric invariance (“equal factor loading”) model also fit the data well (RMSEA = 0.065; CFI = 0.970), and the ΔCFI difference test between the configural and metric invariance model suggested that the 1‐factor model is associated with metric invariance across males and females, ΔCFI <0.01. The scalar invariance (“equal thresholds”) model also fit the data well (RMSEA = 0.051; CFI = 0.978), and the ΔCFI difference test between the metric and scalar invariance models suggested that the 1‐factor model is associated with scalar invariance across genders, ΔCFI <0.01.

Table 2.

Fit statistics for the confirmatory factor analysis (CFA) models

Models χ2 Df RMSEA (90% ci) TLI CFI ΔCFI
1‐factor model 665.49 77 .069 (.064–.074) .961 .953 —
2‐factor model 639.81 76 .068 (.063–.073) .955 .962 31.73
Single‐group solutions (1‐factor model)
Males (n = 588) 21.047 76 .055 (.046–.064) .983 .986 —
Females (n = 1038) 494.98 76 .073 (.067–.079) .950 .958 —
Configural invariance (equal form) 730.91 154 .068 (.063–.073) .970 .968 —
Metric invariance (equal factor loadings) 736.72 167 .065 (.060–.070) .968 .970 .002
Scalar invariance (equal thresholds) 615.28 201 .051 (.046–.055) .981 .978 .008
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Note: RMSEA, root mean square error of approximation; CI, confidence interval; CFI, comparative fit index; TLI, Tucker–Lewis Index.

3.4. Convergent/divergent validity

To assess the relation of the SPOVI to other self‐report instruments, correlations with the DASS‐21 and ASI‐3 were calculated. Means and intercorrelations among variables of interest are provided in Table 3. Several notable, theoretically consistent results emerged when comparing scores on the SPOVI to the ASI‐3 and DASS‐anxiety, constructs typically associated with phobias. Moderate positive correlations were found between the SPOVI and DASS‐anxiety, r = 0.31 (p < 0.01) and between the SPOVI and anxiety sensitivity (r = 0.36; p < 0.01). By comparison, SPOVI scores were only weakly associated with constructs divergent to phobias: depression (DASS‐depression: r = 0.18, p < 0.01) and general stress (DASS‐stress: r = 0.24, p < 0.01).

Table 3.

Intercorrelations among variables of interest

M SD (2) (3) (4)
(1) SPOVI total 2.70 5.29 .36** .31** .18**
(2) ASI‐3 51.75 16.58 — .57** .47**
(3) DASS‐anxiety 5.35 6.07 — .63**
(4) DASS‐depression 5.67 7.15 —
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Note: SPOVI, Specific Phobia of Vomiting Inventory; ASI‐3, Anxiety Sensitivity Index‐3; DASS, Depression, Anxiety and Stress Scale; M, mean; SD, standard deviation.

*

p < 0.05,

**

p < 0.01.

3.5. Frequencies and clinical elevations

As a final check to ensure adequate variability in the data set, the percentage of respondents with various scores on the SPOVI was examined (Table 4). Approximately half of the respondents endorsed no items at a level above 0, indicating no fear of vomiting. Among the other half of respondents, scores were between 1 and 52, representing the full range of possible data. Additionally, it was notable that 8.5% (n = 134) of the sample scored 10 or higher on the SPOVI, which was consistent with the cutoff for clinically elevated fear established in the original psychometric paper (Veale et al., 2013). Taken together, although the data were highly positively skewed, sufficient variability existed to apply the factor model comparisons described earlier and establish normative values for the instrument in a community sample.

Table 4.

Frequency of scores on specific phobia of vomiting inventory (SPOVI) as percentage of sample

Score Percentage
0 49.5
1 12.2
2 9.7
3 6.4
4 4.4
5 3.8
6 1.8
7 1.2
8 1.5
9 1.1
10 0.9
11 0.6
12 0.9
13 0.6
14 1.2
15 0.7
≥16 3.6
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Note: Percentages derived from participants with no missing data (n = 1578).

4. DISCUSSION

The goal of the present study was to contribute to the body of research on emetophobia by psychometrically investigating a newly published measure of the construct, the SPOVI. Confirmatory factor analyses indicated the structure of the SPOVI is best represented by a 1‐factor model, as opposed to the previously asserted 2‐factor model (Veale et al., 2013). In the present study, the 2‐factor model evidenced good model fit; however, the factors were correlated just under 1.0, suggesting that they are not distinct factors. In the original study, the correlation between the two factors was not presented which hinders the ability to compare herein. Nevertheless, the finding of a single factor structure suggests that the SPOVI is best conceptualized as a unidimensional measure.

The SPOVI also demonstrated good psychometric properties, including good internal consistency, and appropriate convergent and divergent validity. Specifically, the results of convergent validity analyses suggest that scores on the SPOVI are associated with variables often associated with phobias and other anxiety disorders (i.e. anxiety sensitivity, anxiety symptoms). Additionally, although these associations are meaningful and provide supporting evidence for the validity of the SPOVI as an instrument, correlations were not so high as to suggest overlapping constructs of measurement. In short, the pattern of results indicated that the SPOVI is measuring a construct different from the other instruments implemented in this study for comparative purposes in a way that is theoretically cogent. Moreover, the tests of measurement invariance on the 1‐factor structure supported scalar invariance across genders, indicating that the SPOVI reliably assesses emetophobic symptoms across gender. Establishing this property of a measure confers considerable advantages to consolidating findings from multiple studies, in that measureable differences in scores can be ascribed to true differences in latent levels of the construct across males and females (rather than a potential confounding influence of gender).

A relative strength of the present study was its large sample size. The substantial number of students who reported any symptoms of emetophobia provides evidence of the pervasive nature of symptoms related to the fear of vomiting. This is especially important because in the initial development of the scale, comparisons with a non‐clinical sample were not feasible because of very limited symptom endorsement; Veale et al., 2013). As emetophobia is a relatively new focus in the domain of anxiety disorders research, assessment is less standardized as compared with other more established areas. Until the development of the SPOVI, no standardized instrument of emetophobia symptoms existed; previous instruments were based on qualitative designs and questionnaires created for a specific study question. This state of affairs has caused difficulty in making generalizations about the overall conceptualization of emetophobia across studies and samples. The present study's demonstration of the reliability and validity of the SPOVI suggests that the instrument may be a valuable tool for assessing emetophobic symptoms across various samples.

Although the current study provides further psychometric support for the SPOVI, limitations should be noted. First, participants were university students, not a clinical sample. As articulated previously, this sample was chosen due to the initial validation's study inability to complete factor analyses among the non‐clinical sample, and the present sample provided adequate power to complete such analyses. The establishment of the current factor structure in a normative population, however, does not obviate previous findings in clinical samples (where variability is likely higher and a different factor structure could be viable). Time and more research are thus necessary to understand more about the psychometric properties of the SPOVI. Another limitation is that test–retest reliability and sensitivity to change analyses were not conducted, but these were reported in the Veale et al. (2013) paper. Despite the noted limitations, the present study contributed to furthering the study of emetophobia by providing additional psychometric validation of the SPOVI. Future research will benefit from examination of the SPOVI in a greater range of contexts (e.g. in other communities, other languages), investigation with a wider range of ages, and additional psychometric investigation to confirm the findings of the present study. Additionally, further use of the instrument in clinical samples as a part of a more comprehensive diagnostic strategy including case history, structured interview, and assessment of functional impairment will support advances in research and clinical application.

DECLARATION OF INTEREST STATEMENT

The authors have no conflicts of interest to declare.

Maack DJ, Ebesutani C, Smitherman TA. Psychometric investigation of the specific phobia of vomiting inventory: A new factor model. Int J Methods Psychiatr Res. 2018;27:e1574 10.1002/mpr.1574

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