Publication date: Aug 01, 2025
To test the reliability and construct validity of the Mask Usability Scale in healthcare students and staff. A methodological study involving repeated measures. The study included two batches of participants: (1) 283 university nursing students and (2) 1753 participants composed of students (61%) and clinical staff (39%). All participants underwent N95 respirator fit tests and user seal checks. They also responded to the Mask Usability Scale, which comprises 11 items evaluated using Likert scales. The internal consistency was assessed using Cronbach’s alpha and item-total correlation test. Test-retest reliability was evaluated by the intraclass correlation coefficient (ICC). The factor structure was initially identified through exploratory factor analysis (EFA), laying the groundwork for the model. This approach was followed by confirmatory factor analysis (CFA) to ensure the model fits with the standardised solution. Excluding items 9, 10 and 11, the study showed satisfactory internal consistency, evidenced by a Cronbach’s alpha of 0. 842 for the eight-item scale from the combined samples. Factors, such as ‘Heat’, ‘Breathability’, ‘Tightness’ and ‘Ease in talking’ showed moderate to strong correlations. The test-retest reliability in the batch one sample was acceptable with ICCs ranging between 0. 69 and 0. 71 for different models. The EFA and fit indices supported a two-factor structure. The first factor ‘Comfort and Usage’ included ‘Heat’, ‘Breathability’, ‘Tightness’, ‘Ease in talking’ and ‘Prolonged use’, which were keys for the usability of N95 respirators. The second factor ‘Suitability’ encompassed ‘Itchy’, ‘Easily displaced’ and ‘Ear soreness’. The variance explained by the first and second factors was 49% and 12%, respectively, with a strong inter-factor correlation. The CFA results were satisfactory with fit metrics (NFI = 0. 967, IFI = 0. 969, TLI = 0. 952, CFI = 0. 969, RMSEA = 0. 078 with 90% CI [0. 069, 0. 086] and p

Semantics
| Type | Source | Name |
|---|---|---|
| drug | DRUGBANK | Etoperidone |
| disease | MESH | COVID-19 |