Reliability and validity test
The research conducted a reliability and validity analysis of the
questionnaire in the study, using the Cronbach’s Alpha coefficient to
verify the reliability of the questionnaire and questions on SPSS25.0
software, and then using factor analysis to verify the content validity
of the questionnaire tools and questions. Researchers often use the
Cronbach’s alpha coefficient to examine the internal consistency of
measurement tools (Kaplan, 2009), in consequence of the Cronbach’s alpha
was above 0.7, means the tools are acceptable, 0.8 means good
reliability, and 0.9 means preferable (Kline, 2011; George & Mallery,
2003). Thus, if the reliability of the questionnaire item is greater
than 0.8, it can be judged that the questionnaire tool has high
reliability and stability. If the reliability of the questionnaire item
is greater than 0.7, it can be judged that the reliability of the
questionnaire is average and within the acceptable range.
Through internal consistency analysis, the Cronbach’s Alpha coefficient
of the web-based learning tool scale (13 items in WBLTs) is
0.954>0.9, which is highly reliable. The Chinese version of
the general self-efficacy scale (10 items in GSES-C) has Cronbach’s The
Alpha coefficient is 0.939>0.9, which has a high
reliability. The Cronbach’s Alpha coefficient of the
depression-anxiety-stress scale (21 items of DASS) is
0.959>0.9, which has high reliability. The Cronbach’s Alpha
coefficient of the family quality of life scale (FQLS) (25 items) is
0.961>0.9, which has high reliability. the Cronbach’s Alpha
coefficient of the general health questionnaire (12 items of GHQ) is
0.702>0.7, and its reliability was within an acceptable
range.
Also, factor analysis and Kaiser-Meyer-Olkin (KMO) test were always used
to confirm the construct validity, and the content validity was examined
by literature review and expert appraisal (Catalano, 2018). This study
conducted an exploratory factor analysis on five questionnaires to test
the structural validity of the questionnaire, selecting the maximum
variance orthogonal rotation method, KMO and Bartletts’ test, and
principal component analysis (extract factor if the characteristic value
is greater than 1, the absolute value of the factor load is greater than
0.5, and the results are shown in the table). Utilizing factor analysis,
the KMO value of the web-based learning tool scale is
0.940>0.9 (p<0.000, satisfied with the Bartletts’
test), the factor loading is between 0.647~0.848, and the cumulative
variance contribution rate of three common factors is 79.046%. Its
validity is relatively high. The KMO value of the Chinese version of the
self-efficacy scale (10 items of GSES-C) is 0.928>0.9
(p<0.000, satisfied with the Bartletts’ test), the factor
loading is 0.487~0.795. The cumulative variance contribution rate of
the co-factors is 73.502%, and its validity is very high. The KMO value
of the depression, anxiety and stress scale (21 items of DASS) is
0.947>0.9 (p<0.000, satisfied with the Bartletts’
test, the factor loading is 0.625~0.809, and the cumulative variance
contribution rate of 3 common factors is 73.244%, and its validity is
high. The KMO value of the Family Quality of Life Scale (FQLS 25 items)
is 0.950>0.9 (p <0.000, satisfied with the
Bartletts’ test), the factor loading is 0.506~0.934, the cumulative
variance contribution rate of 5 common factors is 79.334%, and its
validity is high. The KMO value of general health scale (12 items on
GHQ) is 0.917>0.9 (p<0.000, satisfied with the
Bartletts’ test), the factor loading is 0.660~0.832, and the cumulative
variance contribution rate of extracting 2 common factors is 75.688%,
and its validity is very high.
Finally, confirmatory factor analysis (CFA) was used to verify the
reliability, convergence validity, and discriminate validity of each
questionnaire. As shown in Table 3 and Table 4, four major measurement
tools as follows: web-based learning tool scale,
depression-anxiety-stress scale, general self-efficacy scale, and family
life quality scale, are mainly used in confirmatory factor analysis.
Firstly, after the test of the proposed model, the fitting index of the
proposed model was very unsatisfactory. Therefore, the independent
variable of the general health questionnaire was directly removed.
Furthermore, during the process of confirmatory factor analysis and
structural equation model construction, the general health questionnaire
was excluded from the SEM. In addition, it can be seen from Table 3 and
Table 4 that the reliability and validity of other questionnaires
reached a good level excluding the general health questionnaire.
Table 3 Reliability and Convergence validity