METHODS: The development of the MUAPHQ C-19 was conducted in two stages. Stage I resulted in the generation of the instrument's items (development), and stage II resulted in the performance of the instrument's items (judgement and quantification). Six-panel experts related to the study field and ten general public participated to evaluate the validity of the MUAPHQ C-19. The content validity index (CVI), content validity ratio (CVR) and face validity index (FVI) were analysed using Microsoft Excel.
RESULTS: There were 54 items and four domains, namely the understanding, attitude, practice and health literacy towards COVID-19, identified in the MUAPHQ C-19 (Version 1.0). The scale-level CVI (S-CVI/Ave) for every domain was above 0.9, which is considered acceptable. The CVR for all items was above 0.7, except for one item in the health literacy domain. Ten items were revised to improve the item's clarity, and two items were deleted due to the low CVR value and redundancy, respectively. The I-FVI exceeded the cut-off value of 0.83 except for five items from the attitude domain and four from the practice domains. Thus, seven of these items were revised to increase the clarity of items, while another two were deleted due to low I-FVI scores. Otherwise, the S-FVI/Ave for every domain exceeded the cut-off point of 0.9, which is considered acceptable. Thus, 50-item MUAPHQ C-19 (Version 3.0) was generated following the content and face validity analysis.
CONCLUSIONS: The questionnaire development, content validity, and face validity process are lengthy and iterative. The assessment of the instruments' items by the content experts and the respondents is essential to guarantee the instrument's validity. Our content and face validity study has finalised the MUAPHQ C-19 version that is ready for the next phase of questionnaire validation, using Exploratory and Confirmatory Factor Analysis.
METHODS: Structural Equation Modeling (SEM) is utilized for analysis, enabling the creation of a metric set to explore intangibles such as perfectionism, learning self-efficacy, motivation, study habits, cultural influences, and introspection. The research utilizes a diverse sample from multiple universities across different regions of China, incorporating demographic factors to encompass the varied characteristics within the EFL learner community.
RESULTS: Results reveal that perfectionism (β = 0.30, p
METHOD: The primary data source of the study consists of excerpts of verbal expressions within the familial context. The provenance of the locational data can be traced to a familial unit with a cultural legacy deeply embedded in Javanese customs. The data were collected using observation and participation methodologies, employing advanced techniques of recording and note taking. The data were categorized and characterized to identify the various data types and formats. The tabulated results of classification and typification are presented to triangulate theory through expert validation and justification of theories. The method of contextual analysis was utilized to conduct the data analysis that relies on the pragmatic context.
RESULTS: The study's findings indicate the following: The Javanese language encompasses various modes of pseudo-directive utterances, such as commanding, ordering, suggesting, insinuating, and recommending. In addition, the Javanese language encompasses pseudo-directive pragmatics such as warning, prohibiting, reminding, suggesting, and commanding.
CONCLUSION: This research will significantly assist in formulating a pragmatic framework that considers cultural factors, as other linguistic phenomena in various regional languages remain unresolved.
METHODS: Data were collected from undergraduate students at all campuses of the Universiti Sains Malaysia. A total of 1,605 students completed the SEE-M (female: 71.5%, male: 28.5%), with the mean age of 20.3 years (SD = 1.5). Perceived self-efficacy was assessed with the 18-item SEE-M. Standard forward-backward translation was performed to translate the English version of the Efficacy for Exercise Scale (SEE) into the Malay version (SEE-M).
RESULTS: The 2 initial measurement models tested (1-factor and 3-factor models) did not result in a good fit to the data. Subsequent investigation of the CFA results recommended some modifications, including adding correlations between the item residuals within the same latent variable. These modifications resulted in good fit indices for the 1-factor model (RMSEA = .059, CFI = .939, TLI = .922, SRMR = .049) and the 3-factor model (RMSEA = .066, CFI = .924, TLI = .903, SRMR = .051). The final measurement models comprised all 18 SEE-M items, which had significant factor loadings of more than .40. The test-retest results indicated that the SEE-M was stable, with an intra-class correlation of .99. The composite reliability was .886 for the 1-factor model and .670-.854 for the 3-factor model.
CONCLUSIONS: The translated version of the SEE-M was valid and reliable for assessing the level of self-efficacy for exercise among university students in Malaysia.
PERSPECTIVE: This study examining the psychometric properties of the SEE scale based on CFA was the first to assess 2 proposed models (1-factor and 3-factor models) simultaneously and to translate the original, English-language SEE into Malay.