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Data and Analysis Underlying Study of Factors Affecting User's Behavioral Intention and Use of a Mobile-Phone-Delivered Cognitive Behavioral Therapy for Insomnia
Siska Fitrianie, Corine Horsch, Robbert Jan Beun, Fiemke Griffioen-Both, Willem-Paul Brinkman
Corresponding author: Siska Fitrianie, s.fitrianie@gmail.com
https://doi.org/10.4121/16825843
This document provides links to files underlying the analysis presented in the article:
Siska Fitrianie, Corine Horsch, Robbert Jan Beun, Fiemke Griffioen-Both and Willem-Paul Brinkman. Factors Affecting User’s Behavioral Intention and Use of a Mobile-Phone-Delivered Cognitive Behavioral Therapy for Insomnia: A Small-Scale UTAUT Analysis. Journal of Medical Systems 45, 110 (2021). https://doi.org/10.1007/s10916-021-01785-w.
The analysis was carried out on data gathered from a field trial involving people (n = 89) with relatively mild insomnia using a Cognitive Behavioral Therapy of-Insomnia (CBT-I) app. It studied an extended version of the Unified Theory of Acceptance and Use of Technology (UTAUT2) model to examine factors influencing users' behavioral intention to use a CBT-I app and their app-use behavior. The Partial Least Squares-Structural Equation Modeling method was applied.
Below is the table of content (TOC) of the article. Within this TOC, links to codes, data and the output(s) of the executed codes are presented. These codes and data are necessary for calculations or analyses that are presented in the paper. The outputs of the calculations or analyses are presented in tables, figures or within the text of the corresponding sections.
Requirements
- SmartPLS to run smartpls codes
- Ms Excel 2003 or higher to open the xlxs files of the smartpls results
- R version 3.3.3 or higher to run R codes
Table of Content:
- Method
- Participant
- Table 3 Demographic characteristics of participants participated in the Sleep App Acceptance Questionnaire
- System Description
- Measurement
- Questionnaire Measures
- Behavioral Measures
- Procedure
- Data Analysis
- Minimum Sample Size
- Data Characteristics
- Variability of Constructs
- Missing Values
- The imputation of Missing Values
- Latent Variable Assessment
- Results
- Single-Path Tests
- Table 6 The bootstrapping results of the single-path analyses (n = 89)
- Behavioral Intention (BI) as dependent variable
- Use Behavior (UB) as dependent variable
Individual outputs:
- H9: Behavioral Intention (BI)
- H10: Facilitating Condition (FC)
Multiple-Path Test
- Figure 3 The bootstrapping results of the multiple-path analysis (n = 89).
Mediation Analysis
- Figure 4 Effects of the relationship between Hedonic Motivation and Use Behavior with mediation (n = 89)
- Compliance with Ethical Standards
Funding
Etchical Approval
Informed Consent
Conflict of Interest
- Appendix A Sleep App Acceptance Questionnaire
- Appendix B Data, Analysis, and Results of the Multi-Path Analysis
- Description Analysis of Preprocessed Data
- Summary of Variability and Assessment Results
- Variability of Constructs
- Missing Values
- The imputation of Missing Values
- Assessment Result
- See PLS Algorithm Results of the Multiple-Path Analysis (below)
- PLS Algorithm Results of the Multiple-Path Analysis
- Bootsrapping Results of the Multiple-Path Analysis (Figure 3)
- Bootstrapping Results of the Mediation Analysis (Figure 4)