A Reliability Generalization Meta-Analysis of the Padua Inventory-Revised (PI-R) / Meta-análisis de generalización de la fiabilidad del Padua Inventory-Revised (PI-R)

Background/Objective: The Padua Inventory-Revised (PI-R) is a widely applied instrument to measure obsessive-compulsive symptoms in clinical and nonclinical samples. We conducted a reliability generalization meta-analysis on the PI-R. Method: An exhaustive literature search yielded 118 empirical studies that had applied the PI-R, from which 30 studies (33 samples) reported an original reliability estimate. Results: Assuming a random-effects model, the average internal consistency reliability (Cronbach's alpha) was .92 (95% CI [.91, .93]) for the total scores, and ranged from .74 to .89 for the subscales. Assuming mixed-effects models, moderator analyses showed a positive statistically significant association between the standard deviation of the total scores and the reliability coefficients (p = .002; R2 = .38). Conclusions: In terms of reliability, the PI-R scale was found to be adequate for both research and clinical purposes, although exhibiting large heterogeneity across studies. Future empirical studies using the PI-R should be required to provide at least one reliability estimate based on their own data

Antecedentes/Objetivo: El Padua Inventory-Revised (PI-R) es un instrumento ampliamente utilizado para medir los síntomas obsesivo-compulsivos en muestras clínicas y no clínicas. Llevamos a cabo un meta-análisis de generalización de la fiabilidad del PI-R. Método: Una búsqueda exhaustiva de la literatura arrojó 118 estudios empíricos que habían aplicado el PI-R, de los cuales 30 estudios (33 muestras) reportaron una estimación propia de la fiabilidad. Resultados: Asumiendo un modelo de efectos aleatorios, la fiabilidad en términos de consistencia interna promedio (alfa de Cronbach) fue de 0,92 (IC del 95% [0,91, 0,93]) para las puntuaciones totales, y osciló entre 0,74 y 0,89 para las subescalas. Asumiendo modelos de efectos mixtos, los análisis de moderadores mostraron una relación positiva estadísticamente significativa entre la desviación típica de las puntuaciones totales y los coeficientes de fiabilidad (p = 0,002; R2 = 0,38). Conclusiones: En términos de fiabilidad, se encontró que el PI-R es adecuado tanto para fines clínicos como de investigación, aunque con una alta heterogeneidad entre los estudios. Es necesario que los estudios empíricos futuros que apliquen el PI-R proporcionen al menos una estimación de la fiabilidad basada en sus propios datos.

A Reliability Generalization Meta-analysis of the Padua Inventory-Revised (PI-R).

Background/Objective: The Padua Inventory-Revised (PI-R) is a widely applied instrument to measure obsessive-compulsive symptoms in clinical and nonclinical samples. We conducted a reliability generalization meta-analysis on the PI-R. Method: An exhaustive literature search yielded 118 empirical studies that had applied the PI-R, from which 30 studies (33 samples) reported an original reliability estimate. Results: Assuming a random-effects model, the average internal consistency reliability (Cronbach's alpha) was .92 (95% CI [.91, .93]) for the total scores, and ranged from .74 to .89 for the subscales. Assuming mixed-effects models, moderator analyses showed a positive statistically significant association between the standard deviation of the total scores and the reliability coefficients (p = .002; R2  = .38). Conclusions: In terms of reliability, the PI-R scale was found to be adequate for both research and clinical purposes, although exhibiting large heterogeneity across studies. Future empirical studies using the PI-R should be required to provide at least one reliability estimate based on their own data.

Antecedentes/Objetivo: El Padua Inventory-Revised (PI-R) es un instrumento ampliamente utilizado para medir los síntomas obsesivo-compulsivos en muestras clínicas y no clínicas. Llevamos a cabo un meta-análisis de generalización de la fiabilidad del PI-R. Método: Una búsqueda exhaustiva de la literatura arrojó 118 estudios empíricos que habían aplicado el PI-R, de los cuales 30 estudios (33 muestras) reportaron una estimación propia de la fiabilidad. Resultados: Asumiendo un modelo de efectos aleatorios, la fiabilidad en términos de consistencia interna promedio (alfa de Cronbach) fue de 0,92 (IC del 95% [0,91, 0,93]) para las puntuaciones totales, y osciló entre 0,74 y 0,89 para las subescalas. Asumiendo modelos de efectos mixtos, los análisis de moderadores mostraron una relación positiva estadísticamente significativa entre la desviación típica de las puntuaciones totales y los coeficientes de fiabilidad (p = 0,002; R2  = 0,38). Conclusiones: En términos de fiabilidad, se encontró que el PI-R es adecuado tanto para fines clínicos como de investigación, aunque con una alta heterogeneidad entre los estudios. Es necesario que los estudios empíricos futuros que apliquen el PI-R proporcionen al menos una estimación de la fiabilidad basada en sus propios datos.

Improving the reporting quality of reliability generalization meta-analyses: The REGEMA checklist.

Reliability generalization (RG) is a meta-analytic approach that aims to characterize how reliability estimates from the same test vary across different applications of the instrument. With this purpose RG meta-analyses typically focus on a particular test and intend to obtain an overall reliability of test scores and to investigate how the composition and variability of the samples affect reliability. Although several guidelines have been proposed in the meta-analytic literature to help authors improve the reporting quality of meta-analyses, none of them were devised for RG meta-analyses. The purpose of this investigation was to develop REGEMA (REliability GEneralization Meta-Analysis), a 30-item checklist (plus a flow chart) adapted to the specific issues that the reporting of an RG meta-analysis must take into account. Based on previous checklists and guidelines proposed in the meta-analytic arena, a first version was elaborated by applying the nominal group methodology. The resulting instrument was submitted to a list of independent meta-analysis experts and, after discussion, the final version of the REGEMA checklist was reached. In a pilot study, four pairs of coders applied REGEMA to a random sample of 40 RG meta-analyses in Psychology, and results showed satisfactory inter-coder reliability. REGEMA can be used by: (a) meta-analysts conducting or reporting an RG meta-analysis and aiming to improve its reporting quality; (b) consumers of RG meta-analyses who want to make informed critical appraisals of their reporting quality, and (c) reviewers and editors of journals who are considering submissions where an RG meta-analysis was reported for potential publication.

A Reliability Generalization Meta-Analysis of the Padua Inventory of Obsessions and Compulsions.

The Padua Inventory (PI) of obsessions and compulsions is one of the most usually applied tests to assess obsessive-compulsive symptomatology in research contexts as well as for clinical and screening purposes. A reliability generalization meta-analysis was accomplished to estimate the average reliability of the PI scores and to search for characteristics of the samples and studies that can explain the variability among reliability estimates. An exhaustive literature search enabled us to select 39 studies (53 independent samples) that reported alpha and/or test-retest coefficients with the data at hand for the PI total score and subscales. An excellent average coefficient alpha was found for the PI total score (M = .935; 95%CI = .922-.949) and for Impaired Mental Control subscale (M = .911; 95%CI = .897-.924), being good for Contamination (M = .861; 95%CI = .841-.882) and Checking (M = .880; 95%CI = .856-.903), and fair for Urges and Worries (M = .783; 95%CI = .745-.822). The average test-retest reliability for PI total score was also satisfactory (M = .835; 95%CI = .782-.877). Moderator analyses showed larger coefficients alpha for larger standard deviation of the PI total scores (p = .0005; R 2 = .46), for adapted versions of the test (p = .002; R 2 = .32), and for samples composed of clinical participants (p = .066; R 2 = .10). The practical implications of these results are discussed as well as the need for researchers to report reliability estimates with the data at hand.

A reliability generalization meta-analysis of the padua inventory of obsessions and compulsions

The Padua Inventory (PI) of obsessions and compulsions is one of the most usually applied tests to assess obsessive-compulsive symptomatology in research contexts as well as for clinical and screening purposes. A reliability generalization meta-analysis was accomplished to estimate the average reliability of the PI scores and to search for characteristics of the samples and studies that can explain the variability among reliability estimates. An exhaustive literature search enabled us to select 39 studies (53 independent samples) that reported alpha and/or test-retest coefficients with the data at hand for the PI total score and subscales. An excellent average coefficient alpha was found for the PI total score (M = .935; 95%CI = .922-.949) and for Impaired Mental Control subscale (M = .911; 95%CI = .897-.924), being good for Contamination (M = .861; 95%CI = .841-.882) and Checking (M = .880; 95%CI = .856-.903), and fair for Urges and Worries (M = .783; 95%CI = .745-.822). The average test-retest reliability for PI total score was also satisfactory (M = .835; 95%CI = .782-.877). Moderator analyses showed larger coefficients alpha for larger standard deviation of the PI total scores (p = .0005; R2 = .46), for adapted versions of the test (p = .002; R2 = .32), and for samples composed of clinical participants (p = .066; R2 = .10). The practical implications of these results are discussed as well as the need for researchers to report reliability estimates with the data at hand

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The Yale-Brown Obsessive Compulsive Scale: A Reliability Generalization Meta-Analysis.

The Yale-Brown Obsessive Compulsive Scale (Y-BOCS) is the most frequently applied test to assess obsessive compulsive symptoms. We conducted a reliability generalization meta-analysis on the Y-BOCS to estimate the average reliability, examine the variability among the reliability estimates, search for moderators, and propose a predictive model that researchers and clinicians can use to estimate the expected reliability of the Y-BOCS. We included studies where the Y-BOCS was applied to a sample of adults and reliability estimate was reported. Out of the 11,490 references located, 144 studies met the selection criteria. For the total scale, the mean reliability was 0.866 for coefficients alpha, 0.848 for test-retest correlations, and 0.922 for intraclass correlations. The moderator analyses led to a predictive model where the standard deviation of the total test and the target population (clinical vs. nonclinical) explained 38.6% of the total variability among coefficients alpha. Finally, clinical implications of the results are discussed.