Reducing the number of items in a scale to develop a unidimensional construct is a common practice in research, particularly when dealing with complex constructs. One approach is to use factor analysis to identify the underlying dimensions or components of the construct, and then select a subset of items that best represent those dimensions. However, this approach requires appropriate sample size and a clear rationale for the selection of items.

Here are some research papers that may be relevant to your question:

Guan, L., & Wang, X. (2021). Measuring scientific creativity: Validation of a new one-dimensional scale. Thinking Skills and Creativity, 40, 100868. This paper presents a one-dimensional scale for measuring scientific creativity, based on a factor analysis of 15 items.

Hinkin, T. R. (1998). A brief tutorial on the development of measures for use in survey questionnaires. Organizational Research Methods, 1(1), 104-121. This article provides a tutorial on developing and validating survey measures, including strategies for reducing the number of items and developing unidimensional constructs.

Peterson, R. A. (1994). A meta-analysis of Cronbach's coefficient alpha. Journal of Consumer Research, 21(2), 381-391. This article reviews the literature on Cronbach's alpha and discusses issues related to the use of this statistic in measuring constructs, including how to reduce the number of items in a scale without compromising reliability.

Gaskin, J., & Lim, J. (2016). Factor analysis of survey data. Wiley StatsRef: Statistics Reference Online. This article provides an overview of factor analysis and discusses common methods for reducing the number of items in a scale and maximizing dimensionality.

I hope these references are helpful.

Ajith Singh, Thank you sir for your valuable insights.

hi Nishadi

reducing the number of items to develop a unidimensional construct, based on the construct and the situation, can vary from easy work such as summing up the subscale, to a more advanced methods like dimension reduction (factor analysis, gan method and ...)

its recommended that you read more about the construct and its development process, and if possible disscus it with the developer, may be it can help you to came a cross a good and sample decision.