The Specific Phobia Questionnaire (SPQ): A robust DSM-5-TR Aligned Validation and Clinical Cut-Offs for Spanish Adults

Ansiedad y Estrés, (2026), 32(2), 85-92
https://doi.org/10.5093/anyes2026a10
https://www.ansiedadyestres.es
Bibliography reference

The Specific Phobia Questionnaire (SPQ): A robust DSM-5-TR Aligned Validation and Clinical Cut-Offs for Spanish Adults

INFO ARTICLE

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Received 2 March 2026
Accepted 12 June 2026

 

ABSTRACT

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Background: Specific phobias represent a clinically significant category of anxiety disorders. The present study adapted the Specific Phobia Questionnaire (SPQ; Fairbrother & Antony, 2012; Ovanessian et al., 2019) for Spanish populations, providing a comprehensive assessment tool for both fear severity and associated life interference. Method: A total of 867 participants were included (56% female; mean age = 33 years). Psychometric evaluation against established measures (STAI, FQ, DASS-21) demonstrated excellent reliability for both anxiety (a = .94) and interference (a = .95). Results: Convergent validity was supported by significant correlations with other instruments. In contrast, discriminant validity was evidenced through clear differentiation between clinical and non-clinical groups. Temporal stability was excellent, and the confirmatory factorial analysis successfully replicated the original five-factor structure, aligning with the DSM-5-TR classifications. Conclusions: These robust psychometric properties support the clinical utility of established cut-off scores for diagnosing and evaluating specific phobias in Spanish-speaking populations.

 

KEYWORDS

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specific phobia
questionnaire
SPQ
validation
CFA
Spanish populations

Ansiedad y Estrés, (2026), 32(2), 85-92
https://doi.org/10.5093/anyes2026a10
https://www.ansiedadyestres.es
Bibliography reference

 

RESUMEN

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Introducción: Las fobias específicas representan una categoría clínicamente significativa de los trastornos de ansiedad. El presente estudio adaptó el Cuestionario de Fobias Específicas (SPQ; Fairbrother y Antony, 2012; Ovanessian et al., 2019) para población española, proporcionando una herramienta de evaluación integral tanto de la gravedad del miedo como de la interferencia en la vida diaria. Método: Se incluyó un total de 867 participantes (56% mujeres; edad media = 33 años). La evaluación psicométrica frente a medidas consolidadas (STAI, FQ, DASS-21) demostró una excelente fiabilidad tanto para la ansiedad (a = .94) como para la interferencia (a = .95). Resultados: La validez convergente se calculó con correlaciones significativas con otros instrumentos. En contraste, la validez discriminante se evidenció mediante una diferenciación estadísticamente significativa entre grupos clínicos y no clínicos. La estabilidad temporal fue excelente, y el análisis factorial confirmatorio replicó con éxito la estructura original de cinco factores, en línea con las clasificaciones del DSM-5-TR. Conclusiones: Estas sólidas propiedades psicométricas respaldan la utilidad clínica de los puntos de corte establecidos para el diagnóstico y la evaluación del tratamiento de las fobias específicas en población española.

 

PALABRAS CLAVE

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fobia específica
cuestionario
SPQ
validación
AFC
población española
 

Introduction

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Phobias are among the most common anxiety disorders. Specific phobias are characterised by persistent and irrational fear or anxiety towards discrete objects or situations. This provokes clinically significant interference in daily functioning and results in active avoidance or escape behaviours. Phobic stimuli may be actual or imagined. The Diagnostic and Statistical Manual of Mental Disorders (DSM-5-TR; APA, 2022) classifies five specific phobia subtypes: animal (e.g., spiders, insects, dogs); natural environment (e.g., heights, storms, water); blood-injection-injury (e.g., needles, invasive medical procedures); situational (e.g., aeroplanes, lifts, enclosed places); and other (e.g., situations that may lead to choking or vomiting).

Epidemiological studies have demonstrated lifetime prevalence rates of 3-15% in the general population (Domínguez-Domínguez et al., 2024; Eaton et al., 2018), with cross-national data indicating 7.4% lifetime and 5.5% 12-month prevalence rates. Gender disparities are marked, with women exhibiting twice the prevalence of men (9.8% vs. 4.9% lifetime) and 12-month prevalence (7.7% vs. 3.3%) (Wardenaar et al., 2017). Longitudinal data reveal chronicity, with 6-20% persistence at one year, 12-19% at three years, and 6-28% after twelve years (Eaton et al., 2018). Comorbidity is substantial also: 60% of affected individuals develop secondary mental health conditions, predominantly anxiety or mood disorders (Wardenaar et al., 2017). Early-onset cases particularly predict subsequent psychological disorders, including depression, bipolar disorder, and eating disorders (Lieb et al., 2016), alongside somatic conditions such as cardiovascular diseases, gastrointestinal disturbances, and chronic cephalalgia (Witthauer et al., 2016).

Specific phobias are routinely assessed through standardised diagnostic instruments and self-report measures. Clinicians frequently employ structured interviews, including the Anxiety and Related Disorders Interview Schedule for DSM-5 (ADIS-5; Brown & Barlow, 2014); the Structured Clinical Interview for DSM-5 (SCID; First et al., 2015); and the Semi-structured Interview for the Behavioural Assessment of Specific Phobias (BISP; Ruiz-García & Valero-Aguayo, 2020, 2021). Self-report questionnaires provide complementary assessment tools, such as the Fear Survey Schedule (FSS; Geer, 1965; Wolpe & Lang, 1977); the Phobic Stimuli Response Scales (PSRS; Cutshall & Watson, 2004); and the Fear Questionnaire (FQ; Marks & Mathews, 1979; Ruiz-García et al., 2025). More specifically, the Severity Measure for Specific Phobia (SMSP; Craske et al., 2013; MacLeod et al., 2022) holds particular clinical utility, quantifying problem severity while differentiating diagnostic subgroups through empirically derived dimensions.

The Specific Phobia Questionnaire (SPQ, Fairbrother & Antony, 2012; Ovanessian et al., 2019) was developed to evaluate fear severity and associated functional impairment across diverse phobic stimuli. This 43-item questionnaire employs a 5-point Likert scale to assess two core dimensions: subjective fear intensity and the degree of life interference caused by avoidance behaviours. The SPQ aligns with the DSM-5-TR classification, effectively distinguishing between individuals with and without specific phobias. The psychometric evaluation of the SPQ was conducted using two sample types: university students and clinical populations (Ovanessian et al., 2019). The questionnaire demonstrated excellent internal consistency (Cronbach’s a = .95 for total score), with subscale reliability ranging from Cronbach's a = 72 to .93). Confirmatory factor analysis identified five distinct subscales, each showing adequate-to-strong internal consistency (from a = .53 to .99). Temporal reliability was exceptional, with two-week test-retest reliability coefficients of .95 for the total scale, .92 for fear, and .95 for interference. The SPQ also showed strong convergent validity, with established measures of worry, depression, and other specific phobias. Its discriminant validity was equally supported, effectively differentiating clinical and non-clinical populations while aligning with DSM-5-TR diagnostic criteria.

The SPQ has demonstrated cross-cultural applicability, having been validated in Australian (Matthews et al., 2025), Canadian (Mathews et al., 2022), and Caucasian populations (Zsido et al., 2023). In the Canadian sample, internal consistency ranged from a = .85 to .96 across the subscales of animal, blood-injection-injury, natural environment, situational, and other scales (Mathews et al., 2022). Confirmatory factor analyses supported the five-factor DMS-5 model in both the Australian and Caucasian populations. This study reported excellent reliability for the total fear (a = .95) and interference scales (a = .94), with subscale coefficients ranging from a = .59 to .92. In the study by Zsido et al. (2023) the McDonald’s omegas for the fear and interference scales were .78, and for the subscale’s values between .77 and .93. Their analysis identified key phobia predictors including female gender, trauma history, emotional distress, and worry tendencies.

Also, a shortened version of the questionnaire with 12 items has recently been trialled in Malaysia (Nka et al., 2023), incorporating modified items and demonstrating acceptable reliability (from a = .72 to .86). This adaptation yielded three primary factors (animals, blood-injection-injury, and situational phobias) due to item reduction.

Despite the high prevalence of specific phobias, few validated instruments exist for the Spanish population, such as the Escala de Temores (FSS; Matesanz, 2009) or the Cuestionario de Miedos (FQ; Ruiz-García et al., 2025). However, there is no instrument adapted to Spanish (such as the SPQ) that can be used to evaluate and diagnose specific phobias according to the DSM-5-TR categories.

Consequently, this study has four main objectives: (1) to examine the SPQ’s factorial structure, where it is expected to replicate the five-factor structure proposed in the original questionnaire and studies in other countries; (2) to evaluate its psychometric properties in the Spanish adults, including internal consistency and temporal stability; (3) to establish convergent and discriminant validity, through comparison with other questionnaires; and (4) to determine an a preliminary optimal clinical cut-off score for detecting potential phobia cases, so it can be used for diagnostic purposes. (5) In line with previous validations conducted in English-speaking and Caucasian populations (Matthews et al., 2025; Ovanessian et al., 2019; Zsido et al., 2023), the five-factor structure proposed by the DSM-5-TR is expected to be replicated, as well as reliability indices and convergent and discriminant validity comparable to those reported for the international versions of the instrument.

Method

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Participants

To calculate the sample size for the research, the instructions of Cohen (1988) and Westland (2010) have been followed. When performing a power analysis, we compute the sample size required for the study, given the number of observed and latent variables in the model and the minimum sample size required given the structural complexity of the model (N = 848). The sample comprised 863 individuals from the general Spanish population. Of these, 43.22% were men, 56.78% were women. Participants` ages ranged from 18 to 92 years (M = 33.86; SD = 15.15). Most participants were single. Most were students (43.25%) or employed (40.6%). Only 7.96% reported a diagnosed mental disorder (e.g., anxiety, depression, obsessive-compulsive disorder). Additionally, 4.73% had been diagnosed with a specific phobia disorder and had received treatment for it. However, 46.37% of the sample reported negative experiences related to closed spaces, insects, driving, heights, flying, animals, blood, or similar situations. Table 1 summarises the socio-demographic characteristics of the sample. The retest sample consisted of 35 participants. Of these, 42.86% were men and 57.14% were women. Participants’ ages ranged from 20 to 59 years (M = 29.60, SD = 12.07). Most participants were single. Most were students (54.29%) or employed (31.43%). Only 3.86% reported having a diagnosed mental disorder and having received treatment for it. However, 40% of the sample reported negative experiences. The time interval between test administrations showed a mean of 17.74 days (SD = 4.29).

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Instruments

The study used several questionnaires to collect data and assess reliability and validity:

Sociodemographic and Health Questionnaire. It assesses age, gender, marital status, socioeconomic status, educational level, presence of treatments, diagnosis with specific phobia, treatment for phobia, and negative experiences (e.g., insects, blood, heights, and others).

Specific Phobia Questionnaire (SPQ; Fairbrother & Antony, 2012; Ovanessian et al., 2019). This is a screening tool for fear or anxiety across a range of phobic stimuli. It also evaluates the extent to which the fear interferes with daily life. The questionnaire consists of 43 items with a Likert-type response scale across two dimensions: fear, ranging from 0 (no fear) to 4 (extreme fear), and interference, ranging from 0 (no interference) to 4 (extreme interference). The 43-item SPQ was translated into Spanish by two researchers and reviewed by other experts on anxiety assessment. The original validation study (Ovanessian et al., 2019) reported Cronbach’s a ranging from .53 to .99, good test-retest reliability (r = .95), and good convergent and discriminant validity with related constructs.

State-Trait Anxiety Inventory (STAI; Spielberger et al., 1970; Spanish version by Buela et al., 2015). It measures state and trait anxiety through 40 items (20 per subscale), rated on a Likert-type scale ranging from 0 (not at all) to 3 (very much). The Spanish adaptation (Buela et al., 2015) showed high internal consistency (a =.83 to .92). In the present study, the alpha coefficient was .93 for the STAI-State, and .91 for STAI-Trait subscales.

Fear Questionnaire (FQ; Marks & Mathews, 1979; Spanish adaptation by Ruiz-García et al., 2025). It includes 23 items assessing avoidance, anxious and depressive responses, as well as the resulting impairment for the individual. This instrument measures the degree to which the person avoids each situation on a Likert-type scale ranging from 0 (I do not avoid it) to 8 (I always avoid it). Original reliability ranged from a = .83 to .86. The Spanish adaptation ranged from a = .71 to .83, and the current study achieved a =.89. The first item of the questionnaire asks the participants about their main phobia, and rates avoidance on the same scale. Participants could also indicate if they had any phobias and describe the feared stimulus or situation.

Depression, Anxiety and Stress Scale (DASS-21; Lovibond & Lovibond, 1995; adapted into Spanish by Daza et al., 2002). It evaluates symptoms of depression, anxiety, and stress over the past week using 21 items, rated on a 4-point frequency scale for the past week (0 = Did not apply to me at all, 1 = Applied to me to some degree, or some of the time, 2 = Applied to me to a considerable degree or a good part of the time, 3 = Applied to me very much or most of the time). Total scores for each subscale are calculated by summing the corresponding items. The Spanish adaptation (Daza et al., 2002) showed a high internal consistency (a = .96). In the present study, Cronbach’s alpha coefficient was .95. Also, DASS-21 has demonstrated convergent validity with other anxiety measures.

Procedure

The adaptation of the SPQ was carried out from the original English study. The original items are those that appear in the results tables, but the participants used them in Spanish. International Test Commission (ITC; Muñiz et al., 2013) recommendations were followed. The team was composed of experts in clinical evaluation, the evaluation and treatment of specific phobias, and statistical methodology for questionnaire adaptation. Firstly, the direct translation of the items was carried out, and then it was reviewed by two independent researchers, different from the team, and by consensus, some words were changed for a Spanish cultural context. A reverse translation was then performed using the DeepL program, and the translated English version was contrasted with the original. A small test was carried out with 10 students to answer and review the items.

Data were collected via an online survey hosted on Google Forms, which managed participation acceptance and ethical/legal requirements. The homepage of the questionnaire outlined the study’s objectives, emphasised anonymity and voluntary participation, and included an informed consent section. All participants provided consent before proceeding. Socio-demographic data were collected without personal identifiers, and responses were linked to an alphanumeric code. Questionnaire items appeared on subsequent pages, with no names recorded. The survey took approximately 15 minutes to complete. Data were stored in a password-protected Excel file using coded identifiers.

Inclusion criteria required participants to be adults (>18 years), hold Spanish nationality, and understand Spanish. A non-probabilistic snowball sampling method was used. One of the authors recruited university students, inviting five additional contacts. In addition, study advertisements were also shared on social media (e.g., Twitter, Facebook, Instagram).

For test-retest reliability, a subset of participants repeated the survey after 15 days. Only those completing both rounds were included in this analysis. University students received grade incentives; other participants received no compensation.

The study protocol was approved by the Human Research Ethics Committee of the University of Córdoba (Spain, Ref. CEIH-21-21). Procedures adhered to APA ethical guides and the Helsinki Declaration (WMA, 2013). Personal data were processed in compliance with the Spanish Organic Law on the Protection of Personal Data and Guarantee of Digital Rights 3/2018. All data were used exclusively for research purposes.

Data analysis

First, an item analysis of the original SPQ scale was conducted. Mean scores, standard deviations, skewness, kurtosis, minimum, and maximum for each item were calculated. Second, internal consistency was assessed for the full 43-item scale using both McDonald's ? and Cronbach’s a. Test-retest reliability was evaluated using two-week test-retest data from 36 participants to examine the scale’s temporal stability. Third, convergent validity was analysed through Pearson’s correlations between SPQ and related measures (STAI, FQ, and DASS). The correlation between the SPQ-fear and SPQ-interference scales was also analysed.

Discriminant validity was assessed by comparing SPQ scores across three groups: the general population, individuals diagnosed with a specific phobia disorder, and individuals receiving specific phobia treatment. This was done using Student’s t-test. Finally, data suitability for factor analysis was verified through the Kaiser-Meyer-Olkin test (KMO) and Bartlett’s test of sphericity.

Exploratory Factor Analysis (EFA) was conducted to identify the SPQ’s factor structure, and oblique rotation was used. Then, Confirmatory Factor Analysis (CFA) was conducted using the Diagonally Weighted Least Squares (DWLS). Regarding the factor-analytic strategy, we adopted a two-phase procedure to address the methodological concerns associated with conducting an EFA and a CFA on the same sample. To overcome this limitation, the adult sample (N = 865) was divided into two independent subsamples using a Solomon split. The resulting calibration subsample (Sample A; n = 407) was used for the EFA, and the independent validation subsample (Sample B; n = 412) was used for the CFA. Equivalence between the two subsamples was verified prior to analysis using independent-samples t-tests for continuous variables and Fisher's exact test confirming full demographic comparability. In a second phase, the CFA model was additionally fitted to the full sample (N = 865). This decision follows the recommendation of simulation research demonstrating that parameter estimates and goodness-of-fit indices are more precise and statistically powerful when derived from the full available sample than from split subsamples (Yang et al., 2023).

Three competing models were tested: (1) EFA-derived structure model; 2) DSM-5-TR theoretical model; and (3) unidimensional model. To evaluate the goodness of fit between the observed data and the model, the Chi-square test (?²), comparative fit index (CFI), the Tucker-Lewis index (TLI), and the root mean square error of approximation (RMSEA) were used. It is indicative of acceptable fit CFI and TLI > .90 (McDonald & Ho, 2002), RMSEA < .08 (Hu & Bentler, 1999). All analyses were performed using IBM SPSS and JASP software.

Results

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Item analysis

Table 2 displays the item analysis results of the original version of SPQ-fear. The 43 items of the SPQ were answered using the entire 4-point Likert-type response scale (from a minimum of 0 to a maximum of 4), confirming the appropriateness of the response options. The highest mean scores or most extreme fear were observed for items 12 (Choking; M = 1.79) and 41 (Developing an illness; M = 1.77), while items 14 (Swimming in a swimming pool; M = .27) and 6 (Cats; M = .29) obtained the lowest mean scores or absence of fear. All items demonstrated satisfactory correlations with the total SPQ score, indicating good internal consistency (see Table 2). The standard deviations ranged from 0.66 to 1.36, suggesting appropriate variability in response across items.

The SPQ-Interference scale showed a mean score of 26.82 (SD = 27.80; range = 0–172). The correlation between the SPQ-Fear scale and the SPQ-Interference scale was high (r = .817, p < .001), confirming the close association between perceived fear intensity and related functional interference, consistent with findings reported in validations conducted in English-speaking samples (Matthews et al., 2025; Ovanessian et al., 2019). Due to the high correlation between the two dimensions, the factor analyses were conducted using only the fear scale as the primary variable.

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Exploratory Factor Analysis

The Kaiser-Meyer-Olkin (KMO) measure of sampling adequacy yielded an excellent value of .93, and Bartlett’s test of sphericity was statistically significant (?2 = 4989.38, p < .001), confirming the suitability of the data for factor analysis. The initial Exploratory Factor Analysis (EFA) revealed a five-factor structure, accounting for 55.84% of the total variance (eigenvalues: 13.83; 4.18; 2.33; 2.09 and 1.55 for each respective dimension).

Confirmatory Factor Analysis

The five-factor DSM-5-TR model of the SPQ shows a good fit for the data (?2 = 1197.71, p < .001; CFI = .98; TLI = .98; RMSEA = .032 (.027-.036). CFA demonstrated that the five-factor DSM-5-TR model exhibited good model fit, while the unidimensional model showed poorer fit indices (?2 = 2610.99, p < .001; CFI = .93; TLI = .93; RMSEA = .071 (.068-.074).

The analysis of the degree of relationship (standardized lambda) of each item with its factor showed that most items loaded strongly on their respective factors (? > .70), with only item 1 having loadings below .60 (see Table 3).

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All fit indices indicate that this model fits the data of the groups studied reasonably well. The CFI index of the single-group model (total sample) equals the CFI indices of the multigroup analysis. According to the criteria of Cheung and Rensvold (2002), this allows us to conclude that the SPQ scores show total invariance (configural, factor loadings, measurement errors, intercepts, variances, and covariances) between men and women. Traditional thresholds of ?CFI < .01 and ?RMSEA < .01 were used to confirm invariance (see Table 4).

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Reliability

The SPQ demonstrated excellent reliability values (McDonald's ? = .95; Cronbach’s a = .95) for the full scale. Reliability coefficients for the subscales were similarly strong: Animals (? = .87; a = .87), Nature (? = .84; a = .84), Blood/Injections (? = .94; a = .94) and Situational (? = .84; a = .83). The Others subscale showed moderate internal consistency (? = .54; a = .52), attributable to its composition of only two items. The results showed that the scale's reliability would not increase if some items were dropped (a-i). Test-retest reliability analysis revealed exceptionally high stability, with Pearson’s r = 97 (p < .001) between time points and an intraclass correlation coefficient of ICC = .987 [.985-.989] in the subsample of 36 participants who completed both assessments.

Convergent and Discriminant Validity

Regarding validity, the SPQ-total fear score showed significant but low correlations with STAI-state (r = .32; p < .001), moderate correlations with STAI-trait (r = .40; p < .001) and DASS-21 (r = .49; p < .001), and a strong correlation with FQ-avoidance (r = .72; p < .001). SPQ subscales exhibited low correlations with STAI-state (r = .24 to .31), and with STAI-trait (r = .28 to .37), while demonstrating low-to-moderate association with DASS-21 and its subscales (r = .29 to .47). Correlations between SPQ and FQ subscales ranged from low to moderate (r = .27 to .60), except for the Blood subscale with showed a robust association (r = .77). Complete convergent validity results, including all subscale comparisons, are presented in Table 5.

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The SPQ-fear scores for the total sample ranged from 0 to 136 (M = 34.06; SD = 26.16). There were significant differences in SPQ-fear between participants with and those without specific phobia disorder diagnoses. Participants diagnosed with a specific phobia disorder scores significantly higher (n = 41; M = 50.07, SD = 27.77) than those without diagnoses (n = 826; M = 33.26, SD = 25.84 t = -4.05; p < .001, d = -.65). Similarly, significant differences in SPQ-fear were observed between participants who had received treatment for specific phobia (n = 41; M = 47.88, SD = 28.71) compared to untreated participants (n = 826; M = 33.37, SD = 25.85; t = -3.49, p < .001, d = -.56). Finally, significant differences in SPQ-fear were observed between participants reporting negative experiences with higher fear levels (n = 402; M = 39.59, SD = 26.67) than participants without such experiences (n = 465; M = 29.36, SD = 24.86; t = -5.82, p < .001, d = -.39). These consistent between-group differences provide strong evidence for the discriminant validity of the SPQ-fear.

Also, there were significant differences in SPQ-fear between women (n = 490; M = 39.62, SD = 26.20) and men (n = 373; M = 26.83, SD = 24.39; t = -7.32, p < .001, d = -.50). Women always obtained higher SPQ-fear scores. In all analyses, the effect sizes ranged between 0.39 and 0.65, corresponding to a low-to-moderate magnitude according to Cohen’s (1988) criteria.

Clinical criteria

To provide an empirically grounded reference, a receiver operating characteristic (ROC) curve analysis was performed using self-reported specific phobia diagnosis as the criterion variable (n_clinical = 41; n_non-clinical = 826). The area under the curve (AUC) was .686 (95% bootstrap CI = [.599, .764]), indicating moderate discrimination. The statistically optimal cutoff point according to Youden's index was 34 (sensitivity = .732; specificity = .604; J = .336). The range 47–50—corresponding approximately one standard deviation above the mean of the non-clinical group—shows greater specificity (.743–.767) at the expense of lower sensitivity (.415–.463), and may be more conservative for clinical assessment contexts where minimizing false positives is the goal. Given the small size of the clinical group and the self-reported nature of the diagnosis, all proposed cut-off points should be considered preliminary and replicated with larger confirmed clinical samples (see Table 6).

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Discussion

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The Spanish adaptation of the SPQ has demonstrated robust psychometric properties in a large sample, with results comparable to those from the original English version. The scale showed excellent reliability, exceeding both the original study and subsequent English-language validations, with an alpha and omega reliability of .95 and .95 for the total scale. For the subscales, the alpha ranged from .52 to .94, and the omega ranged from .54 to .94. The instrument demonstrated high temporal stability (test-retest r = .97) and strong convergent validity, particularly with specific phobia measures, such as the FQ.

For the validation of the instrument, the SPQ-fear scale was used, due to its near-perfect correlation with the interference scales, making it indifferent to use one scale over the other. Although anxiety scores consistently exceeded interference scores, the relevance of this study is to demonstrate that different factors may appear in a factor analysis using only anxiety scores. Factor analysis replicated the original five-factor structure. Those factors are similar to the original (Ovanessian et al., 2019) and other subsequent studies (Matthews et al., 2025) following the DSM-5-TR classification: animals, nature, blood/injections, situational, and other specifics. These results were also found in the study of Zsido et al. (2023), which found five similar factors for both the measurement of anxiety and interference. However, some abbreviated versions (e.g., Nka et al., 2023) with Malaysian people only found three factors: blood-injection-injury, animals, and situational, likely due to reduced item content and sample limitations. Perhaps this abbreviated version can better summarize the factors, since the elements included in "situational" and "natural environments" are comparable. In addition, the problem of the "other" factor would be eliminated, since it only has two items (both in the original and in replications in other countries). Actually, the authors only added two items of this type, but there can be as many as there are names of phobias, since they can be very specific (e.g., clowns, balloons, striped figures, touching or being touched, nomophobia, etc.). In that case, the scale SPQ should include a multitude of items and would not serve for an evaluation of the factors already determined by the DSM-5-TR.

The study revealed significant gender differences, with women scoring higher than men, a finding consistent with epidemiological data on specific phobia (APA, 2022; Ruiz-García & Valero-Aguayo, 2021; Wardenaar et al., 2017). Also, participants with negative experiences showed greater fear than those who had no experience. Finally, those who had a diagnosis of phobia and treatments for specific phobia obtained higher scores than those who had neither diagnosis nor treatment. All of this supports the scale’s discriminant validity.

Despite all this, this work has several limitations. Firstly, limited clinical subsample availability, because a larger sample of the clinical population with specific phobias, either diagnosed or under treatment, was not accessible. In addition, other anxiety measures, without specific phobia content, could have been included to test the discriminant validity of the instruments, and a random sampling method could have been used to allow generalisation of the results, although the snowball sampling methodology is appropriate due to the difficulty of accessing this type of population. Additionally, the sample included in this study could have greater homogeneity in some socio-demographic variables, such as marital status, occupation, educational level, or types of treatment, potentially affecting generalisability. Finally, there is no diagnostic confirmation through a structured clinical interview. These limitations should be addressed in future SPQ research.

Notwithstanding these limitations, the Spanish adaptation of the SPQ demonstrates sufficient reliability and validity to be used to assess specific phobias. The established cut-off scores (47-50 points) provide practitioners with empirically derived benchmarks for diagnosing and evaluating treatment. Therefore, this adaptation serves as a valuable tool for assessing specific phobias in Spanish adult population, always considering using a complementary clinical evaluation to obtain a specific diagnosis.

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