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This paper aims to present a systematic performance-oriented procedure to predict structural responses of composite layered structures. The procedure has a direct application in the preliminary design of aerospace composite structures evaluating the right and most effective material.

The aforementioned procedure is based upon the definition of stiffness invariants. In the paper, the authors briefly recall the definition and the physical explanation of the invariants, i.e. the trace; then they present the scaling procedure for the selection of the best material for a fixed geometrical shape.

The authors report the basic principles of the scaling procedure and several examples pertaining typical responses sought in the preliminary design of aeronautic structures

Typically, during early stages, engineers had to perform the daunting task of balancing among functional requirements and constraints and give the optimum solution in terms of structural concept and material selection. Moreover, preliminary design activities require evaluating different responses as a function of as less as possible parameters, ensuring medium to high fidelity. The importance of incorporating as much physics and understanding of the problem as early as possible in the preliminary design stages is therefore fundamental. A robust and systematic procedure is necessary.

The time/effort reduction in the preliminary design of composite structures can increase the overall quality of the configuration chosen.

Reduction in design costs and time.

In spite of the well-known invariant properties of composites, the application and extension to the preliminary design of composite structures by means of a scaling rule is new and original.

The purpose of this paper is to investigate user satisfaction with digital health solutions by identifying and prioritizing different service attributes on the basis of their impact on improving user satisfaction.

Through a literature review and interviews with health professionals and patients, 20 attributes of digital health services provided in Italy have been identified. User satisfaction with these attributes has been evaluated by adopting the Kano model’s continuous and discrete analyses.

The findings reveal the essential attributes of digital health services that meet users' expectations, identify the attributes that users appreciate or dislike having and highlight unexpected attributes that lead to a significant boost in satisfaction when provided.

This study demonstrates the efficacy of the Kano model in assessing the nonlinear correlation between user satisfaction and the quality of digital health services, thus contributing to fill a gap in the literature in this area. The main limitation of this work is the use of a non-probabilistic sampling method.

This research suggests healthcare institutions and organizations consider user preferences when designing digital health solutions to increase their satisfaction. The results indicate different effects on user satisfaction and dissatisfaction for different categories of attributes in the Italian context.

Previous works studied customer satisfaction with digital health, assuming a linear relationship with service quality, or investigated consumer adoption intentions focusing on the technological factors. This work advances available knowledge by analyzing the nonlinear relationship between digital health attributes and users’ satisfaction and dissatisfaction.