Evaluating the Acceptability, Feasibility and Usability of Various Digital Biopsychosocial Conversational Data Collection Software in a Patient Population With Chronic Pain
试验速览
- 阶段
- 不适用
- 状态
- 招募中
- 发起方
- 入组人数
- 100
- 试验地点
- 1
- 主要终点
- Acceptability
研究概览
简要总结
This research study is being conducted to evaluate digital software tools that collect health information through conversations. The study will test how acceptable, feasible, and usable these conversational software programs are for patients with chronic pain.
Purpose of the Study:
The goal is to understand whether digital conversational tools can effectively gather biopsychosocial information (biological, psychological, and social factors related to health) from patients experiencing chronic pain. Biopsychosocial information includes details about your physical symptoms, emotional well-being, social circumstances, and how these factors interact to affect your health. These digital tools are designed to have conversation-like interactions with patients to collect this comprehensive health data in a more natural and engaging way.
What Participation Involves:
If you join this study, you will interact with digital conversational software that will ask you questions about your health, pain experience, and related factors. The software is designed to communicate with you in a conversational manner, similar to talking with a healthcare provider, to gather information about your condition. You will be asked about various aspects of your chronic pain experience, including how it affects your daily life, your emotional state, and your social interactions.
Who Can Participate:
This study is looking for participants who have chronic pain conditions. Medical providers who treat patients with chronic pain are encouraged to refer eligible patients to this study. Healthcare providers interested in referring patients or learning more about the study can contact the study sponsor, AugMend Health Inc.
Why This Research Matters:
Chronic pain affects millions of people and understanding the full scope of how it impacts patients requires collecting detailed information about physical, psychological, and social factors. Traditional methods of collecting this information can be time-consuming and may not capture the complete picture. Digital conversational tools offer a potential new approach to gathering comprehensive health information in a more efficient and patient-friendly manner. This research will evaluate whether patients find these tools acceptable to use, whether they work practically in real-world clinical settings, and whether they are user-friendly and accessible for people with chronic pain.
Study Location:
The study is being conducted at AugMend Health in Cambridge, Massachusetts.
Study Sponsor:
This study is sponsored by AugMend Health Inc. Healthcare providers or potential participants who would like more information about the study or wish to make a referral can contact AugMend Health Inc.
Participation in this study is voluntary, and you can choose to stop participating at any time without affecting your regular medical care.
详细描述
Study Design and Methodology:
This is a research study designed to systematically evaluate various digital biopsychosocial data collection software platforms in a population of patients with chronic pain. The study will assess three key dimensions: acceptability (whether patients find the tools appropriate and are willing to use them), feasibility (whether the tools can be practically implemented in real-world clinical settings), and usability (how easy and intuitive the tools are for patients to interact with).
The study employs a comparative design to rigorously evaluate different approaches to collecting biopsychosocial information from patients with chronic pain. Participants will be assigned to use different data collection methods, allowing researchers to compare the effectiveness, user experience, and practical implementation considerations across multiple approaches. This comparative framework is essential for determining which methods work best for patients and healthcare systems.
Background and Rationale:
Chronic pain is a complex, multifaceted condition that requires comprehensive assessment of biological, psychological, and social factors to effectively understand and manage. The biopsychosocial model of pain recognizes that pain experiences cannot be fully understood by examining biological factors alone. Psychological factors such as mood, stress, coping strategies, and pain-related beliefs significantly influence pain perception and disability. Social factors including work status, family support, social isolation, and economic circumstances also play crucial roles in the chronic pain experience.
研究设计
- 研究类型
- Interventional
- 分配方式
- Randomized
- 干预模型
- Parallel
- 主要目的
- Other
- 盲法
- Triple (Participant, Care Provider, Investigator)
入排标准
- 年龄范围
- 18 Years 至 —（Adult, Older Adult）
- 性别
- All
- 接受健康志愿者
- 否
入选标准
- •Adults aged 18 years or older
- •Diagnosis of chronic pain (pain lasting 3 months or longer)
- •Able to read and understand English
- •Able to provide informed consent
- •Willing and able to complete study procedures either at home or at the MIT.nano Immersion Lab
- •Access to necessary technology for home-based participation (if assigned to home-based group), or ability to travel to the MIT.nano Immersion Lab (if assigned to laboratory-based group)
- •Cognitively able to interact with digital data collection software and provide feedback
排除标准
- •Under 18 years of age
- •Unable to provide informed consent
- •Non-English speaking
- •Acute pain only (pain lasting less than 3 months)
- •Cognitive impairment that would prevent meaningful interaction with data collection software or ability to provide valid feedback
- •Unable or unwilling to complete study procedures in assigned setting (home or laboratory)
- •Any condition that, in the opinion of the investigator, would make participation unsafe or interfere with the participant's ability to complete study procedures
研究组 & 干预措施
Experimental Digital Biopsychosocial Data Collection Software
Participants in this arm will use digital software to provide biopsychosocial information about their chronic pain condition. The software will collect data about participants' pain experiences, physical functioning, emotional well-being, social circumstances, and other health-related factors.
Participants may complete study procedures at home or at the MIT.nano Immersion Lab depending on the technical requirements and study protocol. They will interact with the digital platform to provide comprehensive health information and will be asked to provide feedback on their experience with the data collection method.
This arm evaluates the acceptability (whether patients find the tool appropriate and are willing to use it), feasibility (whether it can be practically implemented in real-world settings), and usability (how easy and intuitive the tool is for patients) of the digital data collection approach.
干预措施: Digital Biopsychosocial Conversational Data Collection Software (Other)
Control Standard Data Collection Method
Participants in this arm will use a standard method to provide biopsychosocial information about their chronic pain condition. They will provide data about their pain experiences, physical functioning, emotional well-being, social circumstances, and other health-related factors using conventional data collection approaches.
Participants may complete study procedures at home or at designated study locations depending on the study protocol. They will provide comprehensive health information through the assigned data collection method and will be asked to provide feedback on their experience.
This arm serves as a comparison group to evaluate the acceptability (whether patients find the method appropriate and are willing to use it), feasibility (whether it can be practically implemented in real-world settings), and usability (how easy and intuitive the method is for patients) of standard data collection approaches.
干预措施: Standard Digital Questionnaire Data Collection (Other)
结局指标
主要结局
Acceptability
时间窗: Assessed immediately after completion of data collection procedures (typically within 1-2 weeks of enrollment)
Acceptability will be measured using the Acceptability, Feasibility and Usability Survey (AFUS) - Acceptability Subscale, a researcher-developed instrument. This subscale includes items from Part 1 (Core Assessment Experience), Part 2 (culture), Part 3 (Future Use \& Preference), Part 4 (Privacy \& Trust), and Part 5 (Medical Disclosure Comfort). Items are rated on a 7-point Likert scale (1 = Strongly Disagree to 7 = Strongly Agree). Subscale scores will be calculated as the mean of all acceptability items. Higher scores indicate greater acceptability. Subscale breakdown will be accessible in supplemental figures of publications.
Usability
时间窗: Assessed immediately after completion of data collection procedures (typically within 1-2 weeks of enrollment)
Usability will be measured using the Acceptability, Feasibility and Usability Survey (AFUS) - Usability Subscale (Part 6), a researcher-developed instrument adapted from established usability frameworks. The subscale consists of 10 items rated on a 7-point Likert scale (1 = Strongly Disagree to 7 = Strongly Agree). Negatively-worded items are reverse-scored. The total score is calculated as the mean of all items. Higher scores indicate better usability.
Technical Feasibility
时间窗: Assessed throughout study participation (typically within 1-2 weeks of enrollment)
Technical feasibility will be measured by the proportion of data collection sessions completed without significant technical failures. A significant technical failure is defined as any system error, software malfunction, connectivity interruption, hardware issue, or other technical problem that results in early termination of the session. Technical success rate will be calculated as the number of sessions without significant technical failures divided by total sessions attempted, expressed as a percentage. Higher percentages indicate greater technical feasibility.
Implementation Feasibility
时间窗: Assessed immediately after completion of data collection procedures (typically within 1-2 weeks of enrollment)
Implementation feasibility will be measured using the Acceptability, Feasibility and Usability Survey (AFUS) - Future Use \& Preference Subscale (Part 3). Items assess participant willingness to use the data collection method again, likelihood of recommending it to others, and trust in the method for ongoing health evaluation. Items are rated on a 7-point Likert scale (1 = Strongly Disagree to 7 = Strongly Agree). The subscale score is calculated as the mean of all items. Higher scores indicate greater implementation feasibility.
Data Collection Feasibility
时间窗: Assessed at completion of all data collection procedures (typically within 1-2 weeks of enrollment)
Feasibility of comprehensive data collection will be measured by the proportion of biopsychosocial domains for which data was successfully collected across all sessions. Domain coverage will be calculated as the number of domains with complete data divided by total possible domains, expressed as a percentage. Domains include biological (pain characteristics, sleep, physical function, nutrition), psychological (mood, cognition, coping, trauma, pain catastrophizing), and social (relationships, support, work, identity). Higher percentages indicate more comprehensive data collection.
次要结局
- Participant Experience & Satisfaction(Assessed immediately after completion of data collection procedures (typically within 1-2 weeks of enrollment))
- Patient Engagement - Session Duration(Measured during each data collection session (typically within 1-2 weeks of enrollment))
- Patient Engagement - Response Elaboration(Measured during each data collection session (typically within 1-2 weeks of enrollment))
- Perceived Therapeutic Alliance(Assessed immediately after completion of conversational data collection (typically within 1-2 weeks of enrollment))
- Immersion and Comfort(Assessed immediately after completion of immersive data collection (typically within 1-2 weeks of enrollment))