Measuring outcomes for temple hollowing treatment: Content validity of new and existing FACE‐Q scales

2021 ◽  
Author(s):  
Manraj Kaur ◽  
Sarah Baradaran ◽  
Vaishali Patel ◽  
Anne F. Klassen
Keyword(s):  
Content Validity ◽  
Measuring Outcomes

Measuring Outcomes in Audiology

2003 ◽  
Vol 11 (2) ◽  
pp. 2-5
Author(s):  
Harvey B. Abrams ◽  
Theresa Hnath Chisolm
Keyword(s):  
Measuring Outcomes

Further Validity of the Japanese Version of the Ten Item Personality Inventory (TIPI-J)

2014 ◽  
Vol 35 (4) ◽  
pp. 236-244 ◽  
Author(s):  
Atsushi Oshio ◽  
Shingo Abe ◽  
Pino Cutrone ◽  
Samuel D. Gosling
Keyword(s):  
Big Five ◽  
Content Validity ◽  
Structural Equation ◽  
English Language ◽  
Full Range ◽  
Reliability And Validity ◽  
Japanese Version ◽  
Personality Inventory ◽  
Equation Modeling ◽  
Big Five Personality

The Ten Item Personality Inventory (TIPI; Gosling, Rentfrow, & Swann, 2003 ) is a widely used very brief measure of the Big Five personality dimensions. Oshio, Abe, and Cutrone (2012) have developed a Japanese version of the TIPI (TIPI-J), which demonstrated acceptable levels of reliability and validity. Until now, all studies examining the validity of the TIPI-J have been conducted in the Japanese language; this reliance on a single language raises concerns about the instrument’s content validity because the instrument could demonstrate reliability (e.g., retest) and some forms of validity (e.g., convergent) but still not capture the full range of the dimensions as originally conceptualized in English. Therefore, to test the content validity of the Japanese TIPI with respect to the original Big Five formulation, we examine the convergence between scores on the TIPI-J and scores on the English-language Big Five Inventory (i.e., the BFI-E), an instrument specifically designed to optimize Big Five content coverage. Two-hundred and twenty-eight Japanese undergraduate students, who were all learning English, completed the two instruments. The results of correlation analyses and structural equation modeling demonstrate the theorized congruence between the TIPI-J and the BFI-E, supporting the content validity of the TIPI-J.

Content Validity Is Little Help When Choosing Among Selection Tests

2011 ◽  
Author(s):  
Kevin R. Murphy ◽  
Paige J. Deckert ◽  
Ted B. Kinney ◽  
Mei-Chuan Kung
Keyword(s):  
Content Validity

Towards a Customized¬ Awareness Campaign to Educate the Public about COVID-19: Development and Validation of a Messaging Campaign to Promote Precautionary Behavior Using Geospatial Intelligence in Saudi Arabia (Preprint)

2020 ◽  
Author(s):  
Mayda Alrige ◽  
Hind Bitar Bitar ◽  
Maram Meccawi ◽  
Balakrishnan Mullachery
Keyword(s):  
Artificial Intelligence ◽  
Saudi Arabia ◽  
Content Validity ◽  
Awareness Campaign ◽  
Artificial Intelligence Technique ◽  
The Public ◽  
High Infection ◽  
Local Map ◽  
The City ◽  
Intelligence Technique

BACKGROUND Designing a health promotion campaign is never an easy task, especially during a pandemic of a highly infectious disease, such as Covid-19. In Saudi Arabia, many attempts have been made toward raising the public awareness about Covid-19 infection-level and its precautionary health measures that have to be taken. Although this is useful, most of the health information delivered through the national dashboard and the awareness campaign are very generic and not necessarily make the impact we like to see on individuals’ behavior. OBJECTIVE The objective of this study is to build and validate a customized awareness campaign to promote precautionary health behavior during the COVID-19 pandemic. The customization is realized by utilizing a geospatial artificial intelligence technique called Space-Time Cube (STC) technique. METHODS This research has been conducted in two sequential phases. In the first phase, an initial library of thirty-two messages was developed and validated to promote precautionary messages during the COVID-19 pandemic. This phase was guided by the Fogg Behavior Model (FBM) for behavior change. In phase 2, we applied STC as a Geospatial Artificial Intelligence technique to create a local map for one city representing three different profiles for the city districts. The model was built using COVID-19 clinical data. RESULTS Thirty-two messages were developed based on resources from the World Health Organization and the Ministry of Health in Saudi Arabia. The enumerated content validity of the messages was established through the utilization of Content Validity Index (CVI). Thirty-two messages were found to have acceptable content validity (I-CVI=.87). The geospatial intelligence technique that we used showed three profiles for the districts of Jeddah city: one for high infection, another for moderate infection, and the third for low infection. Combining the results from the first and second phases, a customized awareness campaign was created. This awareness campaign would be used to educate the public regarding the precautionary health behaviors that should be taken, and hence help in reducing the number of positive cases in the city of Jeddah. CONCLUSIONS This research delineates the two main phases to developing a health awareness messaging campaign. The messaging campaign, grounded in FBM, was customized by utilizing Geospatial Artificial Intelligence to create a local map with three district profiles: high-infection, moderate-infection, and low-infection. Locals of each district will be targeted by the campaign based on the level of infection in their district as well as other shared characteristics. Customizing health messages is very prominent in health communication research. This research provides a legitimate approach to customize health messages during the pandemic of COVID-19.

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