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Aim <p>Patient involvement in shared decision-making (SDM) is known to improve patient-reported outcomes. However, the patient-perceived level of SDM varies, and this experience is crucial for enacting policies. Evidence suggests that suitable measurement tools are lacking in low- and middle-income countries (LMICs). This study aimed to develop and validate a tool for measuring patient involvement in SDM in LMICs.</p> Subject and methods <p>The study was conducted among cancer patients undergoing chemotherapy. Item generation involved a literature review and focus group discussions, followed by content validation with experts. Item characteristics were initially evaluated, and the tool’s validity was assessed using factor analysis. Scientific rigor was ensured through the Bartlett test of sphericity (<i>p</i> &lt; 0.05) and the Kaiser–Meyer–Olkin (KMO) test for sample adequacy. Exploratory factor analysis (EFA) with varimax rotation was used for factor extraction, considering factor loadings above 0.5. Confirmatory factor analysis (CFA) was used to assess model fit, with data analysis performed using IBM SPSS v.29 and AMOS v.29 software.</p> Results <p>Six items were included in the final tool, validated with 73 cancer patients. The tool showed excellent content validity (scale content validity index [S-CVI] = 1.00, universal agreement [UA] = 1.00), a Bartlett sphericity test result of <i>p</i> &lt; 0.01, and a KMO score of 0.76. EFA identified a single construct explaining 55.4% of the variance. The CFA indicated a good model fit (comparative fit index [CFI] = 0.97, goodness-of-fit index [GFI] = 0.95, Tucker–Lewis index [TLI] = 0.92, standardized root mean square residual [SRMR] = &lt; 0.01).</p> Conclusion <p>The PSDMQ demonstrated strong validity and reliability for measuring patient involvement in SDM in LMICs. Further evaluation with larger samples and diverse disease areas is recommended to enhance its applicability.</p>

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Development and psychometric validation of the patient-reported involvement in shared decision-making questionnaire (PSDMQ) for healthcare systems of low- and middle-income countries (LMICs)

  • 期刊论文

  • 发表日期：

    2025年7月17日

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  • Pavan Kumar Narapaka,
  • Manisha Singh,
  • Sameer Dhingra

摘要

Aim

Patient involvement in shared decision-making (SDM) is known to improve patient-reported outcomes. However, the patient-perceived level of SDM varies, and this experience is crucial for enacting policies. Evidence suggests that suitable measurement tools are lacking in low- and middle-income countries (LMICs). This study aimed to develop and validate a tool for measuring patient involvement in SDM in LMICs.

Subject and methods

The study was conducted among cancer patients undergoing chemotherapy. Item generation involved a literature review and focus group discussions, followed by content validation with experts. Item characteristics were initially evaluated, and the tool’s validity was assessed using factor analysis. Scientific rigor was ensured through the Bartlett test of sphericity (p < 0.05) and the Kaiser–Meyer–Olkin (KMO) test for sample adequacy. Exploratory factor analysis (EFA) with varimax rotation was used for factor extraction, considering factor loadings above 0.5. Confirmatory factor analysis (CFA) was used to assess model fit, with data analysis performed using IBM SPSS v.29 and AMOS v.29 software.

Results

Six items were included in the final tool, validated with 73 cancer patients. The tool showed excellent content validity (scale content validity index [S-CVI] = 1.00, universal agreement [UA] = 1.00), a Bartlett sphericity test result of p < 0.01, and a KMO score of 0.76. EFA identified a single construct explaining 55.4% of the variance. The CFA indicated a good model fit (comparative fit index [CFI] = 0.97, goodness-of-fit index [GFI] = 0.95, Tucker–Lewis index [TLI] = 0.92, standardized root mean square residual [SRMR] = < 0.01).

Conclusion

The PSDMQ demonstrated strong validity and reliability for measuring patient involvement in SDM in LMICs. Further evaluation with larger samples and diverse disease areas is recommended to enhance its applicability.