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Introduction <p>The growing complexity of clinical trials, particularly in oncology, has significantly increased the operational burden on research staff. However, standardized and validated instruments to measure trial-related workload remain scarce. This study aimed to adapt and validate the Italian version of Ontario Protocol Assessment Level (I-OPAL) tool for the Italian context, providing a reliable framework for workload planning and feasibility assessment.</p> Methods <p>A cross-sectional, multicenter study was conducted across Italian research institutions. The OPAL tool was translated and culturally adapted following established validation procedures. Content validity was assessed using the Content Validity Ratio (CVR), while inter-rater reliability was evaluated with the intraclass correlation coefficient (ICC). Discriminant validity was examined through non-parametric tests, effect size measures, and multiple correspondence analysis.</p> Results <p>A total of 513 clinical trials were included. The OPAL tool showed excellent inter-rater reliability (ICC = 0.93) and all items met the minimum CVR threshold (0.78–1.00). Significant differences in OPAL scores were observed across study type, clinical setting, sample size, and duration (all <i>p</i> &lt; 0.001), with large effect sizes (ε<sup>2</sup> up to 0.645). Higher OPAL scores were positively correlated with greater allocation of research staff, particularly nurses and data managers. Sensitivity analyses confirmed the robustness of findings, and internal consistency checks revealed full alignment with the model’s classification rules.</p> Conclusions <p>The Italian validation of OPAL confirmed its reliability, validity, and practical relevance as a tool for standardized workload assessment in clinical research. Its integration into feasibility analyses and trial planning could enhance resource allocation, regulatory compliance, and sustainability of research activities in Italy.</p>

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Validation of the Ontario Protocol Assessment Level (OPAL) Tool for Assessing Clinical Trial Complexity and Supporting Workforce Planning in the Italian Clinical Research Context

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2026年6月30日

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  • Daniele Napolitano,
  • Mattia Bozzetti,
  • Rosario Caruso,
  • Monica Guberti,
  • Ileana Frau,
  • Bobbi Smuck,
  • Gionata Fiorino,
  • Franco Scaldaferri,
  • Lucrezia Laterza,
  • Antonio Gasbarrini,
  • Vincenzina Mora

摘要

Introduction

The growing complexity of clinical trials, particularly in oncology, has significantly increased the operational burden on research staff. However, standardized and validated instruments to measure trial-related workload remain scarce. This study aimed to adapt and validate the Italian version of Ontario Protocol Assessment Level (I-OPAL) tool for the Italian context, providing a reliable framework for workload planning and feasibility assessment.

Methods

A cross-sectional, multicenter study was conducted across Italian research institutions. The OPAL tool was translated and culturally adapted following established validation procedures. Content validity was assessed using the Content Validity Ratio (CVR), while inter-rater reliability was evaluated with the intraclass correlation coefficient (ICC). Discriminant validity was examined through non-parametric tests, effect size measures, and multiple correspondence analysis.

Results

A total of 513 clinical trials were included. The OPAL tool showed excellent inter-rater reliability (ICC = 0.93) and all items met the minimum CVR threshold (0.78–1.00). Significant differences in OPAL scores were observed across study type, clinical setting, sample size, and duration (all p < 0.001), with large effect sizes (ε2 up to 0.645). Higher OPAL scores were positively correlated with greater allocation of research staff, particularly nurses and data managers. Sensitivity analyses confirmed the robustness of findings, and internal consistency checks revealed full alignment with the model’s classification rules.

Conclusions

The Italian validation of OPAL confirmed its reliability, validity, and practical relevance as a tool for standardized workload assessment in clinical research. Its integration into feasibility analyses and trial planning could enhance resource allocation, regulatory compliance, and sustainability of research activities in Italy.