Deriving Meaningful Aspects of Health Related to Physical Activity in Chronic Disease: Concept Elicitation Using Machine Learning-Assisted Coding of Online Patient Conversations.

OBJECTIVES: Clinical outcome assessment (COA) developers must ensure that measures assess aspects of health that are meaningful to the target patient population. Although the methodology for doing this is well understood for certain COAs, such as patient-reported outcome measures, there are fewer examples of this practice in the development of digital endpoints using mobile sensor technology such as physical activity monitors. This study explored the utility of social media data, specifically, posts on online health boards, in understanding meaningful aspects of health related to physical activity in 3 different chronic diseases: fibromyalgia, chronic obstructive pulmonary disease, and chronic heart failure. METHODS: We used machine learning and manual coding to summarize the content of posts extracted from 4 online health boards. Where available, patient age and sex were retrieved from post content or user profiles. We utilized analytical approaches to assess the robustness of findings to differences in the characteristics of online samples compared to the true patient population. Finally, we assessed concept saturation by measuring the convergence of autocorrelations. RESULTS: We identify a number of aspects of health described as important by patients in our samples, and summarize these into concepts for measurement. For chronic heart failure, these included purposeful walking duration and speed, fatigue, difficulty going upstairs, standing, and aspects of physical exercise. Overall and age-adjusted results did not differ considerably for each disease group. CONCLUSIONS: This study illustrates the potential of performing concept elicitation research using social media data, which may provide valuable insight to inform COA development.

Updated Recommendations on Evidence Needed to Support Measurement Comparability Among Modes of Data Collection for Patient-Reported Outcome Measures: A Good Practices Report of an ISPOR Task Force.

The ISPOR Task Force on measurement comparability between modes of data collection for patient-reported outcome measures (PROMs) has updated the good practice recommendations from the 2009 ISPOR electronic patient-reported outcome and 2014 patient-reported outcome mixed modes Good Research Practices Task Force reports in light of accumulated evidence of measurement comparability among different modes of PROM data collection. Furthermore, with the increasing use of electronic formats of clinical outcome assessments in clinical trials and the US Food and Drug Administration's encouragement of electronic data collection, this new task force report provides stakeholders with best practice recommendations reflecting the current body of evidence and enables them to respond to future developments in research and technology. This task force recommends an evidence-based approach to determine whether new research is needed to evaluate measurement comparability for a given questionnaire or technology. The suitability of existing evidence depends upon whether it satisfactorily demonstrates that the change in data collection mode has not affected the PROM's measurement properties. In cases where sufficient evidence of measurement comparability exists and best practices for faithful migration are followed, this task force concludes that further testing of measurement comparability among the data collection modes is unnecessary, including cases of "mixing modes" within clinical trials such as bring your own device designs.

Recommendations on the Selection, Development, and Modification of Performance Outcome Assessments: A Good Practices Report of an ISPOR Task Force.

In evaluating the clinical benefit of new therapeutic interventions, it is critical that the treatment outcomes assessed reflect aspects of health that are clinically important and meaningful to patients. Performance outcome (PerfO) assessments are measurements based on standardized tasks actively undertaken by a patient that reflect physical, cognitive, sensory, and other functional skills that bring meaning to people's lives. PerfO assessments can have substantial value as drug development tools when the concepts of interest being measured best suit task performance and in cases where patients may be limited in their capacity for self-report. In their development, selection, and modification, including the evaluation and documentation of validity, reliability, usability, and interpretability, the good practice recommendations established for other clinical outcome assessment types should continue to be followed, with concept elicitation as a critical foundation. In addition, the importance of standardization, and the need to ensure feasibility and safety, as well as their utility in patient groups, such as pediatric populations, or those with cognitive and psychiatric challenges, may enhance the need for structured pilot evaluations, additional cognitive interviewing, and evaluation of quantitative data, such as that which would support concept confirmation or provide ecological evidence and other forms of construct evidence within a unitary approach to validity. The opportunity for PerfO assessments to inform key areas of clinical benefit is substantial and establishing good practices in their selection or development, validation, and implementation, as well as how they reflect meaningful aspects of health is critical to ensuring high standards and in furthering patient-focused drug development.

Comparative Effectiveness of eConsent: Systematic Review.

BACKGROUND: Providing informed consent means agreeing to participate in a clinical trial and having understood what is involved. Flawed informed consent processes, including missing dates and signatures, are common regulatory audit findings. Electronic consent (eConsent) uses digital technologies to enable the consenting process. It aims to improve participant comprehension and engagement with study information and to address data quality concerns. OBJECTIVE: This systematic literature review aimed to assess the effectiveness of eConsent in terms of patient comprehension, acceptability, usability, and study enrollment and retention rates, as well as the effects of eConsent on the time patients took to perform the consenting process ("cycle time") and on-site workload in comparison with traditional paper-based consenting. METHODS: The systematic review was conducted and reported in accordance with the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) guidelines. Ovid Embase and Ovid MEDLINE were systematically searched for publications reporting original, comparative data on the effectiveness of eConsent in terms of patient comprehension, acceptability, usability, enrollment and retention rates, cycle time, and site workload. The methodological validity of the studies that compared outcomes for comprehension, acceptability, and usability across paper consent and eConsent was assessed. Study methodologies were categorized as having "high" validity if comprehensive assessments were performed using established instruments. RESULTS: Overall, 37 publications describing 35 studies (13,281 participants) were included. All studies comparing eConsenting and paper-based consenting for comprehension (20/35, 57% of the studies; 10 with "high" validity), acceptability (8/35, 23% of the studies; 1 with "high" validity), and usability (5/35, 14% of the studies; 1 with "high" validity) reported significantly better results with eConsent, better results but without significance testing, or no significant differences in overall results. None of the studies reported better results with paper than with eConsent. Among the "high" validity studies, 6 studies on comprehension reported significantly better understanding of at least some concepts, the study on acceptability reported statistically significant higher satisfaction scores, and the study on usability reported statistically significant higher usability scores with eConsent than with paper (P<.05 for all). Cycle times were increased with eConsent, potentially reflecting greater patient engagement with the content. Data on enrollment and retention were limited. Comparative data from site staff and other study researchers indicated the potential for reduced workload and lower administrative burden with eConsent. CONCLUSIONS: This systematic review showed that compared with patients using paper-based consenting, patients using eConsent had a better understanding of the clinical trial information, showed greater engagement with content, and rated the consenting process as more acceptable and usable. eConsent solutions thus have the potential to enhance understanding, acceptability, and usability of the consenting process while inherently being able to address data quality concerns, including those related to flawed consenting processes.

Proof-of-Concept Study: a Mobile Application to Derive Clinical Outcome Measures from Expression and Speech for Mental Health Status Evaluation.

This proof-of-concept study aimed to assess the ability of a mobile application and cloud analytics software solution to extract facial expression information from participant selfie videos. This is one component of a solution aimed at extracting possible health outcome measures based on expression, voice acoustics and speech sentiment from video diary data provided by patients. Forty healthy volunteers viewed 21 validated images from the International Affective Picture System database through a mobile app which simultaneously captured video footage of their face using the selfie camera. Images were intended to be associated with the following emotional responses: anger, disgust, sadness, contempt, fear, surprise and happiness. Both valence and arousal scores estimated from the video footage associated with each image were adequate predictors of the IAPS image scores (p < 0.001 and p = 0.04 respectively). 12.2% of images were categorised as containing a positive expression response in line with the target expression; with happiness and sadness responses providing the greatest frequency of responders: 41.0% and 21.4% respectively. 71.2% of images were associated with no change in expression. This proof-of-concept study provides early encouraging findings that changes in facial expression can be detected when they exist. Combined with voice acoustical measures and speech sentiment analysis, this may lead to novel measures of health status in patients using a video diary in indications including depression, schizophrenia, autism spectrum disorder and PTSD amongst other conditions.

Standards for Instrument Migration When Implementing Paper Patient-Reported Outcome Instruments Electronically: Recommendations from a Qualitative Synthesis of Cognitive Interview and Usability Studies.

OBJECTIVES: To synthesize the findings of cognitive interview and usability studies performed to assess the measurement equivalence of patient-reported outcome (PRO) instruments migrated from paper to electronic formats (ePRO), and make recommendations regarding future migration validation requirements and ePRO design best practice. METHODS: We synthesized findings from all cognitive interview and usability studies performed by a contract research organization between 2012 and 2015: 53 studies comprising 68 unique instruments and 101 instrument evaluations. We summarized study findings to make recommendations for best practice and future validation requirements. RESULTS: Five studies (9%) identified minor findings during cognitive interview that may possibly affect instrument measurement properties. All findings could be addressed by application of ePRO best practice, such as eliminating scrolling, ensuring appropriate font size, ensuring suitable thickness of visual analogue scale lines, and providing suitable instructions. Similarly, regarding solution usability, 49 of the 53 studies (92%) recommended no changes in display clarity, navigation, operation, and completion without help. Reported usability findings could be eliminated by following good product design such as the size, location, and responsiveness of navigation buttons. CONCLUSIONS: With the benefit of accumulating evidence, it is possible to relax the need to routinely conduct cognitive interview and usability studies when implementing minor changes during instrument migration. Application of design best practice and selecting vendor solutions with good user interface and user experience properties that have been assessed in a representative group may enable many instrument migrations to be accepted without formal validation studies by instead conducting a structured expert screen review.

Selection of and Evidentiary Considerations for Wearable Devices and Their Measurements for Use in Regulatory Decision Making: Recommendations from the ePRO Consortium.

BACKGROUND: Wearable devices offer huge potential to collect rich sources of data to provide insights into the effects of treatment interventions. Despite this, at the time of writing this report, limited regulatory guidance on the use of wearables in clinical trial programs has been published. OBJECTIVES: To present recommendations from the Critical Path Institute's Electronic Patient-Reported Outcome Consortium regarding the selection and evaluation of wearable devices and their measurements for use in regulatory trials and to support labeling claims. METHODS: The evaluation group was composed of Critical Path Institute's clinical outcome assessment (COA) scientists and COA specialists from pharmaceutical trial eCOA solution providers, including COA development and validation specialists. The resulting recommendations were drawn from a broad range of backgrounds, perspectives, and expertise that enriched the development of this report. Recommendations were developed through analysis of existing regulatory guidance relating to COA development and use in clinical trials, medical device certification/clearance regulations, literature-reported best practice, and practical experience of wearable technology application in clinical trials. RESULTS: We identify the essential properties of fit-for-purpose wearables and propose evidence needed to support their use. In addition, we overview the activities required to establish clinical endpoints derived from wearables data. CONCLUSIONS: Using this framework, we believe there is enough current understanding to promote the appropriate use of wearables in study protocols. We hope this will provide a basis for discussion among clinical trial stakeholders and catalyze the development of more robust regulatory guidance.

Measurement Equivalence of Patient-Reported Outcome Measure Response Scale Types Collected Using Bring Your Own Device Compared to Paper and a Provisioned Device: Results of a Randomized Equivalence Trial.

OBJECTIVES: The aim of this study was to assess the measurement equivalence of individual response scale types by using a patient reported outcome measure (PROM) collected on paper and migrated into electronic format for use on the subject's own mobile device (BYOD) and on a provisioned device (site device). METHODS: Subjects suffering from chronic health conditions causing daily pain or discomfort were invited to participate in this single-site, single visit, three-way crossover study. Association between individual item and instrument subscale scores was assessed by using the intraclass correlation coefficient (ICC) and its CI. Participant attitudes toward the use of BYOD in a clinical trial were assessed through use of a questionnaire. RESULTS: In this study, 155 subjects (females 83 [54%]; males 72 [46%]) ages 19 to 69 years (mean ± SD: 48.6 ± 13.1) were recruited. High association between the modes of administration (paper, BYOD, site device) was shown with analysis of ICCs (0.79-0.98) for each response scale type, including visual analogue scale, numeric rating scale, verbal response scale, and Likert scale. Of the subjects, 94% (146 of 155) stated that they would definitely or probably be willing to download an app onto their own mobile device for a forthcoming clinical trial. Forty-five percent of subjects felt BYOD would be more convenient compared with 15% preferring a provisioned device (40% had no preference). CONCLUSIONS: This study provides strong evidence supporting the use of BYOD for PROM collection in terms of the conservation of instrument measurement equivalence across the most widely used response scale types, and high patient acceptance of the approach.

The Burden of a Remote Trial in a Nursing Home Setting: Qualitative Study.

BACKGROUND: Despite an aging population, older adults are typically underrecruited in clinical trials, often because of the perceived burden associated with participation, particularly travel associated with clinic visits. Conducting a clinical trial remotely presents an opportunity to leverage mobile and wearable technologies to bring the research to the patient. However, the burden associated with shifting clinical research to a remote site requires exploration. While a remote trial may reduce patient burden, the extent to which this shifts burden on the other stakeholders needs to be investigated. OBJECTIVE: The aim of this study was to explore the burden associated with a remote trial in a nursing home setting on both staff and residents. METHODS: Using results from a grounded analysis of qualitative data, this study explored and characterized the burden associated with a remote trial conducted in a nursing home in Dublin, Ireland. A total of 11 residents were recruited to participate in this trial (mean age: 80 years; age range: 67-93 years). To support research activities, we also recruited 10 nursing home staff members, including health care assistants, an activities co-ordinator, and senior nurses. This study captured the lived experience of this remote trial among staff and residents and explored the burden associated with participation. At the end of the trial, a total of 6 residents and 8 members of staff participated in semistructured interviews (n=14). They reviewed clinical data generated by mobile and wearable devices and reflected upon their trial-related experiences. RESULTS: Staff reported extensive burden in fulfilling their roles and responsibilities to support activities of the trial. Among staff, we found eight key characteristics of burden: (1) comprehension, (2) time, (3) communication, (4) emotional load, (5) cognitive load, (6) research engagement, (7) logistical burden, and (8) product accountability. Residents reported comparatively less burden. Among residents, we found only four key characteristics of burden: (1) comprehension, (2) adherence, (3) emotional load, and (4) personal space. CONCLUSIONS: A remote trial in a nursing home setting can minimize the burden on residents and enable inclusive participation. However, it arguably creates additional burden on staff, particularly where they have a role to play in locally supporting and maintaining technology as part of data collection. Future research should examine how to measure and minimize the burden associated with data collection in remote trials.

Utilising the Intel RealSense Camera for Measuring Health Outcomes in Clinical Research.

Applications utilising 3D Camera technologies for the measurement of health outcomes in the health and wellness sector continues to expand. The Intel® RealSense™ is one of the leading 3D depth sensing cameras currently available on the market and aligns itself for use in many applications, including robotics, automation, and medical systems. One of the most prominent areas is the production of interactive solutions for rehabilitation which includes gait analysis and facial tracking. Advancements in depth camera technology has resulted in a noticeable increase in the integration of these technologies into portable platforms, suggesting significant future potential for pervasive in-clinic and field based health assessment solutions. This paper reviews the Intel RealSense technology's technical capabilities and discusses its application to clinical research and includes examples where the Intel RealSense camera range has been used for the measurement of health outcomes. This review supports the use of the technology to develop robust, objective movement and mobility-based endpoints to enable accurate tracking of the effects of treatment interventions in clinical trials.

Leveraging sensor-based functional outcomes to enhance understanding of the patient experience: challenges and opportunities.

INTRODUCTION: Sensor-based digital health technology (DHT) has emerged as a promising means to assess patient functioning within and outside clinical trials. Sensor-based functional outcomes (SBFOs) provide valuable insights that complement other measures of how a patient feels or functions to enhance understanding of the patient experience to inform medical product development. AREAS COVERED: This perspective paper provides recommendations for defining SBFOs, discusses the core evidence required to support SBFOs to inform decision-making, and considers future directions for the field. EXPERT COMMENTARY: The clinical outcome assessment (COA) development process provides an important starting point for developing patient-centered SBFOs; however, given the infancy of the field, SBFO development may benefit from a hybrid approach to evidence generation by merging exploratory data analysis with patient engagement in measure development. Effective SBFO development requires combining unique expertise in patient engagement, measurement and regulatory science, and digital health and analytics. Challenges specific to SBFO development include identifying concepts of interest, ensuring measurement of meaningful aspects of health, and identifying thresholds for meaningful change. SBFOs are complementary to other COAs and, as part of an integrated evidence strategy, offer great promise in fostering a holistic understanding of patient experience and treatment benefits, particularly in real-world settings.

Deriving stair-climbing performance outcome measures using the smartphone barometer: Results of an algorithm development study.

As we seek to gain richer insights to understand intervention effects, and increasingly decentralise aspects of clinical trials to simplify participation, there is a growing interest in leveraging wearables and sensors to generate novel and informative clinical outcome measures for at-home assessment. The sensors embedded within smartphone technology provide one approach to capture of this data, and may be particularly useful when patients are already using mobile devices for at-home capture of other clinical trials data, such as patient-reported outcomes. We describe the results of an initial algorithm development study to determine whether the atmospheric pressure data provided by an onboard smartphone sensor is sufficiently informative to enable detection of a small height gain, such as that achieved during a short stair climb performance test. We were able to sufficiently distinguish height changes of 0.6 m in indoor conditions, representing around 4 stairs on an average staircase. This suggests that the smartphone barometer may indeed be suitable for inclusion within future work developing a stair-climbing performance outcome test instrumented using a mobile application.

Considerations to address missing data when deriving clinical trial endpoints from digital health technologies.

Digital health technologies (DHTs) enable us to measure human physiology and behavior remotely, objectively and continuously. With the accelerated adoption of DHTs in clinical trials, there is an unmet need to identify statistical approaches to address missing data to ensure that the derived endpoints are valid, accurate, and reliable. It is not obvious how commonly used statistical methods to handle missing data in clinical trials can be directly applied to the complex data collected by DHTs. Meanwhile, current approaches used to address missing data from DHTs are of limited sophistication and focus on the exclusion of data where the quantity of missing data exceeds a given threshold. High-frequency time series data collected by DHTs are often summarized to derive epoch-level data, which are then processed to compute daily summary measures. In this article, we discuss characteristics of missing data collected by DHT, review emerging statistical approaches for addressing missingness in epoch-level data including within-patient imputations across common time periods, functional data analysis, and deep learning methods, as well as imputation approaches and robust modeling appropriate for handling missing data in daily summary measures. We discuss strategies for minimizing missing data by optimizing DHT deployment and by including the patients' perspectives in the study design. We believe that these approaches provide more insight into preventing missing data when deriving digital endpoints. We hope this article can serve as a starting point for further discussion among clinical trial stakeholders.

Measurement Comparability of Electronic and Paper Administration of Visual Analogue Scales: A Review of Published Studies.

BACKGROUND: Visual analogue scales (VASs) are used in a variety of patient-, observer- and clinician-reported outcome measures. While typically included in measures originally developed for pen-and-paper completion, a greater number of clinical trials currently use electronic approaches to their collection. This leads researchers to question whether the measurement properties of the scale have been conserved during the migration to an electronic format, particularly because electronic formats often use a different scale length than the 100 mm paper standard. METHODS: We performed a review of published studies investigating the measurement comparability of paper and electronic formats of the VAS. RESULTS: Our literature search yielded 26 studies published between 1997 and 2018 that reported comparison of paper and electronic formats using the VAS. After excluding 2 publications, 23 of the remaining 24 studies included in this review reported electronic formats of the VAS (eVAS) and paper formats (pVAS) to be equivalent. A further study concluded that eVAS and pVAS were both acceptable but should not be interchanged. eVAS length varied from 21 to 200 mm, indicating that 100 mm length is not a requirement. CONCLUSIONS: The literature supports the hypothesis that eVAS and pVAS provide comparable results regardless of the VAS length. When implementing a VAS on a screen-based electronic mode, we recommend following industry best practices for faithful migration to minimise the likelihood of non-comparability with pVAS.

Comparability of a provisioned device versus bring your own device for completion of patient-reported outcome measures by participants with chronic obstructive pulmonary disease: qualitative interview findings.

BACKGROUND: There is interest in participants using their own smartphones or tablets ("bring your own device"; BYOD) to complete patient-reported outcome (PRO) measures in clinical studies. Our study aimed to qualitatively evaluate participants' experience using a provisioned device (PD) versus their own smartphone (BYOD) for this purpose. METHODS: Participants with chronic obstructive pulmonary disease (COPD) were recruited for this observational, cross-over study and completed PRO measures daily on one device type for 15 days, then switched to the other device type to complete the same measures for another 15 days. After each 15-day period, semi-structured interviews were conducted about their experience with the device. RESULTS: Of 64 participants enrolled, the final qualitative analysis populations comprised those who participated in an interview without protocol violations. Thus, the qualitative longitudinal population (LP) included n = 57 (89%), while the qualitative cross-sectional population (CSP) included n = 60 (94%). CSP participants found both device types easy to use. Twenty CSP participants (33%) reported missing data entry on at least one day when using PD, and 24 (40%) reported missing at least one day when using BYOD. In the LP, preference for one of the device types was somewhat evenly split; 45.6% (n = 26) preferred PD and 50.9% (n = 29) preferred BYOD. The most common reason for preferring PD was that it was "dedicated" to the study; the "convenience" of carrying a single device was the main reason for preferring BYOD. CONCLUSION: The findings from the interviews demonstrated few differences in participants' experience completing PRO measures on a PD versus BYOD. Our study supports the use of BYOD as a potential addition to PD for collecting PRO data and contributes evidence that BYOD may be employed to collect PRO data in demographically diverse patient populations.

Comparability of a provisioned device versus bring your own device for completion of patient-reported outcome measures by participants with chronic obstructive pulmonary disease: quantitative study findings.

OBJECTIVE: To quantitatively compare equivalence and compliance of patient-reported outcome (PRO) data collected via provisioned device (PD) versus bring your own device (BYOD). METHODS: Participants with stable chronic obstructive pulmonary disease (COPD) completed the EXAcerbations of Chronic Pulmonary Disease Tool (EXACT®) daily and COPD Assessment Test™ (CAT) and Patient Global Impression of Severity (PGIS) of COPD weekly on either PD or BYOD for 15 days, then switched device types for 15 days. EXACT was scored using the Evaluating Respiratory Symptoms in COPD (E-RS®: COPD) algorithm and equivalence assessed using intraclass correlation coefficients (ICCs) adjusting for cross-over sequence, period, and time. Two one-sided tests (TOSTs) used ICC adjusted means with 10%, 20%, and 40% of total score tested as equivalence margins. Compliance and comfort with technology were assessed. Equivalence across 3 device screen sizes was assessed following the second completion period. RESULTS: Participants (N = 64) reported high comfort with technology, with 79.7% reporting being "quite a bit" or "very" comfortable. Weekly compliance was high (BYOD = 89.7-100%; PD = 76.9-100%). CAT and E-RS: COPD scores correlated well with PGIS (r > 0.50) and demonstrated equivalence between PD and BYOD completion (ICC = 0.863-0.908). TOST equivalence was achieved within 10% of the total score (p > 0.05). PRO measure scores were equivalent across 3 different screen sizes (ICC = 0.972-0.989). CONCLUSIONS: Measure completion was high and scores equivalent between PD and BYOD, supporting use of BYOD in addition to PD for collecting PRO data in COPD studies and in demographically diverse patient populations.

Determining Minimum Wear Time for Mobile Sensor Technology.

Part 1 in the DIA Study Endpoint Community Working Group on Mobile Sensor Technology (MST) series addresses considerations that may be useful when determining the minimum wear time associated with mobile sensor use to ensure reliable estimation of the clinical endpoint under consideration. What constitutes a minimum valid data set is a dilemma facing those using MSTs in clinical studies. If this alignment does not occur, the integrity of the data collected and conclusions drawn from these data may be in incorrect. While study participants should consent to engage with MSTs as defined in a protocol, participant behavior or technology lapses may result in capturing incomplete data. Drawing from the literature, we review what constitutes a minimum data set, the risks associated with missing data, alignment with the clinical endpoint(s) and goals of a study, as well as managing patient burden.

Does scrolling affect measurement equivalence of electronic patient-reported outcome measures (ePROM)? Results of a quantitative equivalence study.

BACKGROUND: Scrolling is a perceived barrier in the use of bring your own device (BYOD) to capture electronic patient reported outcomes (ePROs). This study explored the impact of scrolling on the measurement equivalence of electronic patient-reported outcome measures (ePROMs) in the presence and absence of scrolling. METHODS: Adult participants with a chronic condition involving daily pain completed ePROMs on four devices with different scrolling properties: a large provisioned device not requiring scrolling; two provisioned devices requiring scrolling - one with a "smart-scrolling" feature that disabled the "next" button until all information was viewed, and a second without this feature; and BYOD with smart-scrolling. The ePROMs included were the SF-12, EQ-5D-5L, and three pain measures: a visual analogue scale, a numeric response scale and a Likert scale. Participants completed English or Spanish versions according to their first language. Associations between ePROM scores were assessed using intraclass correlation coefficients (ICCs), with lower bound of 95% confidence interval (CI) > 0.7 indicating comparability. RESULTS: One hundred fifteen English- or Spanish-speaking participants (21-75y) completed all four administrations. High associations between scrolling and non-scrolling were observed (ICCs: 0.71-0.96). The equivalence threshold was met for all but one SF-12 domain score (bodily pain; lower 95% CI: 0.65) and two EQ-5D-5L item scores (pain/discomfort, usual activities; lower 95% CI: 0.64/0.67). Age, language, and device size produced insignificant differences in scores. CONCLUSIONS: The measurement properties of PROMs are preserved even in the presence of scrolling on a handheld device. Further studies that assess scrolling impact over long-term, repeated use are recommended.

Attitudes of older people/seniors to completion of electronic patient-reported outcome measures and use of mobile applications in clinical trials: results of a qualitative research study.

Aim: We undertook qualitative research to understand more about older people and their interactions with technology, specifically to evidence the question "can older people (seniors) manage electronic patient-reported outcomes solutions in clinical trials?". Methods: We undertook qualitative research interviews with older people and investigated the findings. Results: Seven of the ten participants had a smartphone and 3/10 had a feature phone (a mobile phone with buttons and no touchscreen). There was a shift from smartphone use by the younger participants to feature phone use by the oldest participants. Conclusion: The younger group of older individuals had similar experiences and attitudes toward touchscreen devices as the rest of the population. While the older participants expressed some reluctance toward unfamiliar technology, all participants were using technology and accepting of it.

Optimizing electronic capture of patient-reported outcome measures in oncology clinical trials: lessons learned from a qualitative study.

Aim: To understand the impact of anticancer treatment on oncology patients' ability to use electronic solutions for completing patient-reported outcomes (ePRO). Materials & methods: Semi-structured interviews were conducted with seven individuals who had experienced a cancer diagnosis and treatment. Results: Participants reported that the following would impact the ability to interact with an ePRO solution: peripheral neuropathy of the hands (4/7), fatigue and/or concentration and memory issues (6/7), where they are in a treatment cycle (5/7). Approaches to improve usability included: larger, well-spaced buttons to deal with finger numbness, the ability to pause a survey and complete at a later point and presenting the recall period with every question to reduce reliance on memory. Conclusion: Symptoms associated with cancers and anticancer treatments can impact the use of technologies. The recommendations for optimizing the electronic implementation of patient-reported outcome instruments in this population provides the potential to improve data quality in oncology trials and places patient needs at the forefront to ensure 'fit-for-purpose' solutions.