User experiences with digital future-self interventions in the contexts of smoking and physical activity: A mixed methods multi-study exploration - Data and analysis code

This repository contains data and analysis code underlying the paper "User experiences with digital future-self interventions in the contexts of smoking and physical activity: A mixed methods multi-study exploration" by Kristell M. Penfornis, Nele Albers, Willem-Paul Brinkman, Mark A. Neerincx, Andrea W.M. Evers, Winifred A. Gebhardt, and Eline Meijer. This includes 1) the data underlying the analysis for study 2, 2) scripts for data preprocessing and for computing the mean effort per activity for study 2, and 3) the SPSS syntaxes used for the analyses for all three studies.<br><strong>Data underlying analysis for study 2</strong>The folder "Study_2/Raw_Data" contains the data underlying the analysis for study 2. This includes:Data from participants' Prolific profiles (e.g., age, gender).Data from the prescreening questionnaire (e.g., smoking frequency).Data from the conversational sessions with the text-based virtual coach Kai (e.g., effort spent on activities).This data is derived from the data published in this repository: https://doi.org/10.4121/1d9aa8eb-9e63-4bf5-98a3-f359dbc932a4.<br><strong>Scripts for data preprocessing and mean effort computation for study 2</strong>The folder "Study_2" further contains scripts for data preprocessing and for computing the mean effort per activity for study 2.<br><strong>SPSS syntaxes</strong>The folder "Analysis_Syntax_SPSS" contains the SPSS syntaxes used for the analyses for all three studies.<br><strong>Additional resources</strong>The implementation of the text-based virtual coach Kai used in study 2 can be found here: https://doi.org/10.5281/zenodo.11102861.The preregistration of the study used to collected the data for study 2 in the Open Science Framework (OSF) can be found here: https://doi.org/10.17605/OSF.IO/78CNR.

本仓库包含Kristell M. Penfornis、Nele Albers、Willem-Paul Brinkman、Mark A. Neerincx、Andrea W.M. Evers、Winifred A. Gebhardt与Eline Meijer合著的论文《吸烟与身体活动场景下的数字未来自我干预用户体验：一项混合方法多研究探索》所依托的数据与分析代码。本仓库涵盖以下内容：1) 研究2的分析所用原始数据；2) 研究2的数据预处理脚本与单活动平均努力度计算脚本；3) 三项研究分析所用的SPSS语法文件。
<strong>研究2的分析数据</strong> 文件夹“Study_2/Raw_Data”中存放了研究2的分析所用数据，具体包括：参与者的Prolific平台档案数据（如年龄、性别）、预筛查问卷数据（如吸烟频率）、与文本型虚拟教练Kai的对话会话数据（如活动所投入的努力程度）。本数据集源自下述仓库已发布的数据：https://doi.org/10.4121/1d9aa8eb-9e63-4bf5-98a3-f359dbc932a4。
<strong>研究2的数据预处理与平均努力度计算脚本</strong> 文件夹“Study_2”中还包含研究2的数据预处理脚本与单活动平均努力度计算脚本。
<strong>SPSS语法文件</strong> 文件夹“Analysis_Syntax_SPSS”中存放了三项研究分析所用的SPSS语法文件。
<strong>附加资源</strong> 研究2中使用的文本型虚拟教练Kai的实现代码可从下述地址获取：https://doi.org/10.5281/zenodo.11102861。本研究2数据采集所依托的研究预注册信息已发布于开放科学框架（Open Science Framework, OSF），详情见：https://doi.org/10.17605/OSF.IO/78CNR。