Construct validity

Refer to Construct-Related Evidence, means an instrument does not correlate significantly with variables from which it should be different(namely discriminate validity), in the same time it correlates highly with other variables with which it should theoretically correlate(namely convergent validity). Factor analysis can be used to identify underlying variables, or factors, that explain the pattern of correlations within a set of observed variables. It is often used in data reduction to identify a small number of factors that explain most of the variance that is observed in a much larger number of manifest variables. So the factor analysis can be used to analysis content related evidence involves the degree to which the content of the test matches a content domain associated with the construct.

Factor analysis usually used to analysis the construct validity of an instrument.

Kaiser-Meyer-Olkin(KMO) measure of sampling adequacy. If KMO test P is over 0.7, then factor analysis can be used in these data. Otherwise, factor analysis should not be used in the data analysis. The KMO and Bartlett's Test P is 0.789 at sub-standard level(13 domains) in this research survey, and is 0.754 at standards level(five standards). These results show that factor

analysis can be used for analysis the data at the standard and substandard level. Principle analysis model was used to extract principal factors.

What are the true attitudes lead people to respond to the questions on a self-assessment survey as they really do? Whether or not the investigation result can reflect the theory model and conception? If yes, then the instrument has content validity. Examining the correlations among the survey items reveals that there is significant overlap among various subgroups of items--questions about the health promotion conception tend to correlate with each other. For instance, the questions (items) about standard management policy should correlate with each other, and so on for questions (items) about standard patients` assessment, about standard patients’ information, about standard healthy workplace, and about standard continuity and cooperation. So with factor analysis, the number of underlying factors which were investigated can identify what the factors represent conceptually. If the data analysis result matches the original theory model, this instrument could be regarded as validity. The source instrument includes management policy with 6 sub-standards domains and 17 items, patient assessment with 5 sub-standards domains and 8 items, patient information and intervention with 5 sub-standards and 8 items, promoting a healthy workplace with 4 facets 16 items, and continuity and cooperation with 5 sub-standards and 19items . Chinese Vision WHOSATHPH completely keeps the same structure and items of source instrument.

The five standards were used as the analysis variables, principal component extracted method to do the factor analysis, the results show that the correlations effectives between each standard are very high. Except standard 1 is only 0.562, others standards correlation effectives are 0.876, 0.956, 0.879 and 0.841 (see table24).

Table24 Factor Analysis for Validity Test at Standards level Comp

onent

Initial Eigenvalues Extraction Sums of Squared Loadings Total % of Variance Cumulative % Total % of Variance Cumulative %

1 3.478 69.562 69.562 3.478 69.562 69.562

2 .858 17.158 86.720

3 .356 7.111 93.831

4 .222 4.433 98.264

5 .087 1.736 100.000

The abscissa in Figure15 shows there are five component numbers were abstracted from data, but only one Eigenvalues (see figure 18). The cumulative rate of the principle factor is 69.6%, the validity coefficient is 0.704. Result indicated that these standards have high relation and they had well cumulative feature and expressed one conception. These results match the original theory

model. So Chinese Vision WHOSATHPH was proved to have general structure validity in this survey but not high. Limited by the number of cases, the valide test for this Chinese version WHOSATHPH could not be generize.

Figure18 The principle factor analysis for Validity Test among Five

Standards

Confirmatory factor analysis is a method used to test whether the data fits a hypothetical model.

This conceptual structure is assumed that 13 domains should be abstracted 5 principle components because the original instrument has five standards and 13 domains.

Table 25 Total Variance Explanation

Compo nent

Initial Eigenvalues

Extraction Sums of Squared Loadings

Rotation Sums of Squared Loadings

Total

% of Variance

Cumulative

% Total

% of Variance

Cumulative

% Total

% of Variance

Cumulative

% 1 6.227 47.900 47.900 6.227 47.900 47.900 2.966 22.819 22.819 2 2.263 17.405 65.306 2.263 17.405 65.306 2.282 17.554 40.373 3 1.089 8.378 73.684 1.089 8.378 73.684 2.245 17.270 57.643 4 .724 5.573 79.257 .724 5.573 79.257 1.792 13.787 71.430 5 .595 4.573 83.830 .595 4.573 83.830 1.612 12.400 83.830

The factor analysis result shows that 13 variables were abstracted into 5 principle factors, the values show the principle factor rate of total factors which contribute to the sums. Table 16 results show that 13 domains have high correlation effective with component 1, but domain1.1 and domain 4.1 have high correlation effective with component 2, no domain has high correlation

effective with component 3, 4 and 5(see table 24). The result show that the five standards with its domain don`t have clear conception boundary. However, by method of principle component extraction, 5 main factors which loading cumulative 83.8% of total information (see table 25).

The factor analysis results based on sub-standards of the instrument show that among the 13 variables (13 domains), after principle component extraction, 5 factors were abstracted which loading about 83.8% cumulative information of total factors. The hypothesis assumes that 13 sub-standards belong to five standards, so 5 principle factors explain 83.8% information of health promotion conception. The figure19 displays five principle components contribution rate to total conception of HPH.

The conceptual structure of the Chinese Vision WHOSATHPH assumed that 13 domains belong to five standards, and these five standards contribute to the overall assessment of health promotion. These standards would therefore be expected to load onto only one factor (a hypothetical health promotion construct that matches the original instrument structure). The result shows that about 5 factors were extracted that match the five standards in Chinese Vision WHOSATHPH. Factor analysis results show that Chinese Vision WHOSATHPH has a general construct validity, but the 13 domains with their standards don`t have clear conception boundary.

Figure 19 Factors Analysis for Validity Test among 13 Domains

The validity test result shows that factor analysis for ths Chinese version WHOSATHPH validity test at domain level is not clear. This could be caused by the unvalidy instrument designe, it also may be caused by the small sample size and investigation bias. Although Chinese version

WHOSATHPH shows that the general eigenvalues matches the theory structure model, the cumulative is low, and the domain level engenvalues analysis don’t well match the theory structure model.

This result may indicate the Chinese version WHOSATHPH might have not good validity.

Because this research is small sample size, so the further big sample size research to test the instrument validity is necessary, and it is necessary to test the validity of other language version WHOSATHPH.

Discussion