31 Chapter III Research Methodology In this chapter, the author provides details of the research methodology, including discussions about data, research strategy, research instrument development, research variables, and explanations of the several tests used in this study. III.1 Introduction An appropriate and well-formulated research methodology is needed to achieve the objectives and answer the research questions. Sources of data taken must have good quality, as a reflection of the quality of the research outputs. Therefore, as the data source, respondents become a crucial component. Respondents must be able to represent the population; thus, sample selection becomes very important. In addition, a valid and reliable research instrument is a requirement that must be met to produce a good result. However, not only that, the result of the data obtained through research instruments will be decisive if only processed and analyzed with appropriate tests. This chapter will explain the details of the process regarding the research methodology so that the above requirements can be fulfilled in this study. III.2 Research Methods This mixed method study used the convergent parallel design to gain complete and better understanding of the results (Creswell, 2015). Each method has its strengths. Integrating these two methods will result in a comprehensive and richer discovery of what each method can offer. In the quantitative phase, the survey was chosen as the research strategy in this study. The survey strategy allows the researcher to effectively collect quantitative data from a sample of a sizeable population to produce findings that represent the population. Surveys are used when the research objective is to determine the respondents' beliefs, opinions, and behaviors (Lawrence Neuman, 2014; Saunders et al., 2009). With the same goal, questionnaires were distributed to collect the data and study the self-reported behavior of a sample of mobile teledentistry mobile application users in Indonesia. In the qualitative phase, researcher performed interview to gain the explanation how the factors influence the user’s adoption of TMA. 32 III.3 Data Collection and Analysis The primary data for this cross-sectional study were obtained from the target population of TMA users in Indonesia. Adult users (≥18 years old) who have consulted a dentist via TMA at least once are considered part of the inclusion criteria. The confidence level, standard deviation, and margin of error should be considered in determining the sample size. According to the Central Limit Theorem, the sample size should be greater than 30 to provide a normally distributed sampling distribution for the mean (Miladinovic & Hong, 2016; Saunders et al., 2007). Another method to determine the minimum sample size is 10-time rule, which means that the sample size should be ten times the total number of independent variables in the PLS path model's most complex regression. According to this general rule, the minimum sample size should be ten times the greatest number of arrowheads in the PLS path model that point at a latent variable. If adopted in this study, the minimum sample is 80. In addition to the methods already discussed, the inverse square root approach became the updated method proposed by Kock and Hadaya in 2018. The inverse square root approach was introduced by Kock and Hadaya (2018). It takes into account the likelihood that, for a given significance level, the ratio of a path coefficient and its standard error will be larger than the test statistic's crucial value. The minimal sample size (nmin) is determined by the following formulae, respectively, assuming a common power level of 80% and significance levels of 1%, 5%, and 10% (Hair et al., 2021). Assuming, for instance, a minimum path coefficient of 0.2 and a significance level of 5%, the minimal sample size is determined by: (III.1) where: nmin = the minimum sample size required pmin = the value of the path coefficient with the minimum magnitude 33 Chin (1998) states that standardized pathways have to be at least 0.20 to be deemed significant enough for discussion. After entering the numbers into the calculation below, the minimum sample size is 155. Furthermore, for the qualitative study, the sample size is defined by thematic saturation or the point at which new data appears to no longer contribute to the conclusions due to respondents' repeated comments (Morse, 1995; Vasileiou et al., 2018). Aside from determining the number of samples, ethical concerns are another essential issue concerning the data collection process. Ethical issues related to the respondent as one of the stakeholders in the research are things that must be very carefully considered. Researchers must ensure that the research is not influenced by or involves personal interests and will not harm any party, including respondents. Researchers must provide a transparent explanation of the research so that respondents know the purpose of the research, what information will be extracted from them, the outputs of the research, and the effects they may get. Researchers should also guarantee that the data collection process is carried out by considering the respondents' privacy concerns (Kumar, 2011). According to these provisions, respondents in this study have been explained and agreed to the informed consent. III.3.1 Survey Instrument Development Following are some of the processes that were conducted to design the survey instrument for this study: 1. Formulation of the questionnaire items of each construct of the proposed research model. The survey instrument is prepared based on the hypothesis that has been developed. Details regarding the variables/constructs used in preparing the questionnaire items in this study can be seen in Table III.1. 34 Table III. 1 Variables of the study Variable/Construct Concept Operational definition No. Item Measurement Performance expectancy Independent variable The degree of benefits obtained by the user in adopting teledentistry in mobile health application. 1-4 (4) Nominal scale Effort expectancy Independent variable The degree of convenience associated with users’ use of teledentistry in mobile health application. 5-8 (4) Nominal scale Social influence Independent variable The degree which an individual perceives that important other believe he or she should use the teledentistry in mobile health application. 9-11 (3) Nominal scale Facilitating conditions Independent variable The extent to which users perceive that there is an adequate technical infrastructure to support the use of teledentistry in mobile health application and resources that offer the necessary knowledge using teledentistry in mobile health application. 12-14 (3) Nominal scale Price value Independent variable Consumers’ cognitive trade-off between the perceived benefits of teledentistry in mobile health application and the monetary cost for using them. 15-17 (3) Nominal scale 35 Trust in dentist Independent variable The users’ belief in the ability, integrity and benevolence of the dentist in teledentistry in mobile health application. 18-20 (3) Nominal scale Trust in teledentistry platform Independent variable The users’ belief in the ability, integrity and benevolence of teledentistry in mobile health application. 21-23 (3) Nominal scale Perceived Privacy Risk Independent variable The predicted harm related to the disclosure of personal data.