IntroductionCitizen science for health invites non-professionals into research, but the degree to which individuals control the knowledge-making process varies widely. Personal science—the self-directed, inquiry-driven practice associated with the Quantified Self (QS) community—represents a high-agency form of self-tracking in which the individual is both subject and scientist. Drawing on work on epistemic injustice, we use “epistemic agency” to describe whether a person exercises genuine control over inquiry rather than merely supplying data.AimTo assess the utility of an agency-based framework for characterizing the epistemic dimension of self-tracking, and to examine how personal science has been represented in the scientific literature.MethodsFollowing Jaakkola's theory-synthesis approach, we developed a four-phase analytical framework (questioning, observing, reasoning, discovering) with three levels of individual agency (low agency, mixed agency, high agency). A search of Web of Science and PubMed (April–May 2025) for “quantified self” yielded 721 records; 241 were retained for analysis, of which 46 used self-tracking as the data-collection method and were classified by agency level through independent dual-author review.ResultsThe 46 articles spanned the full agency spectrum: 17 low, 10 mixed, and 19 high. Low-agency studies treated individuals as data sources, whereas high-agency studies displayed the complete self-directed cycle, often with the self-tracker as co-author. Data-sharing dominated low-agency accounts, while sharing of methods and experiences characterized higher-agency work.ConclusionThe framework can meaningfully distinguish merely measurement from self-directed knowledge production, turning on who owns the question. Personal science can be seen as a high-agency dimension of citizen science for health.

Even though citizen and patient engagement in health research has a long tradition, citizen science in health has only recently gained attention and recognition. However, at present, there is no clear overview of the specifics and challenges of citizen science initiatives in the health domain. Such an overview could contribute to highlighting and articulating the different needs of stakeholders engaged in any form of citizen science in the health domain. It may also encourage the input of citizens and patients alike in health research and innovation, policy, and practice. This paper reports on a survey developed by the European Citizen Science Association (ECSA)’s Working Group “Citizen Science for Health,” to highlight the perceived characteristics and enabling factors of citizen science in the health domain, and to formulate a direction for future work and research. The survey was available in six languages and was open between January and August 2022. The majority of the 254 respondents were from European countries, and the largest stakeholder respondent group was researchers. Respondents were asked about their perspectives on the particular characteristics of citizen science performed in health and biomedical research, as well as the challenges and opportunities it affords. Ethics, the complexity of the health domain, and the overlap in roles whereby the researcher is sometimes also the subject of research, were the main issues suggested as being specific to citizen science in health. The top two areas that respondents identified as in need of development were “balanced return on investment” and “ethics.” This publication discusses these and other conditions with references to current literature.

Background Individuals’ self-tracking of subjectively experienced phenomena related to health can be challenging, as current options for instrumentation often involve too much effort in the moment or rely on retrospective self-reporting, which is likely to impair accuracy and compliance. Objective This study aims to assess the usability and perceived usefulness of low-effort, in-the-moment self-tracking using simple instrumentation and to establish the amount of support needed when using this approach. Methods In this exploratory study, the One Button Tracker—a press-button device that records time stamps and durations of button presses—was used for self-tracking. A total of 13 employees of an academic medical center chose a personal research question and used the One Button Tracker to actively track specific subjectively experienced phenomena for 2 to 4 weeks. To assess usability and usefulness, we combined qualitative data from semistructured interviews with quantitative results from the System Usability Scale. Results In total, 29 barriers and 15 facilitators for using the One Button Tracker were found. Ease of use was the most frequently mentioned facilitator. The One Button Tracker’s usability received a median System Usability Scale score of 75.0 (IQR 42.50), which is considered as good usability. Participants experienced effects such as an increased awareness of the tracked phenomenon, a confirmation of personal knowledge, a gain of insight, and behavior change. Support and guidance during all stages of the self-tracking process were judged as valuable. Conclusions The low-effort, in-the-moment self-tracking of subjectively experienced phenomena has been shown to support personal knowledge gain and health behavior change for people with an interest in health promotion. After addressing barriers and formally validating the collected data, self-tracking devices may well be helpful for additional user types or health questions.

Background. During the SARS-CoV-2 pandemic, there was shortage of the standard respiratory protective equipment (RPE). The aim of this study was to develop a procedure to test the performance of alternative RPEs used in the care of COVID-19 patients. Methods. A laboratory-based test was developed to compare RPEs by total inward leakage (TIL). We used a crossflow nebulizer to produce a jet spray of 1–100 µm water droplets with a fluorescent marker. The RPEs were placed on a dummy head and sprayed at distances of 30 and 60 cm. The outcome was determined as the recovery of the fluorescent marker on a membrane filter placed on the mouth of the dummy head. Results. At 30 cm, a type IIR surgical mask gave a 17.7% lower TIL compared with an FFP2 respirator. At 60 cm, this difference was similar, with a 21.7% lower TIL for the surgical mask compared to the respirator. When adding a face shield, the TIL at 30 cm was further reduced by 9.5% for the respirator and 16.6% in the case of the surgical mask. Conclusions. A safe, fast and very sensitive test method was developed to assess the effectiveness of RPE by comparison under controlled conditions.

Using Parkinson's disease as an exemplary chronic condition, this Commentary discusses ethical aspects of using self-tracking for personal science, as compared to using self-tracking in the context of conducting clinical research on groups of study participants. Conventional group-based clinical research aims to find generalisable answers to clinical or public health questions. The aim of personal science is different: to find meaningful answers that matter first and foremost to an individual with a particular health challenge. In the case of personal science, the researcher and the participant are one and the same, which means that specific ethical issues may arise, such as the need to protect the participant against self-harm. To allow patient-led research in the form of personal science in the Parkinson field to evolve further, the development of a specific ethical framework for self-tracking for personal science is needed.

Self-tracking of health may have positive effects on lifestyle behavior and weight loss; however, not much is known about the role of psychological processes in this effect. The purpose of this study was to assess to what extent a change in self-regulation capabilities can explain weight loss after 4 and 12 months of self-tracking physical activity and weight. An explorative cohort study was conducted with measurements at baseline (T0), 4 months (T1), and 12 months (T2). Healthy adult volunteers ( N = 80) were included and provided with a digital weight scale and an activity tracker. Personal characteristics as well as the intention to change weight and physical activity were measured at T0. Self-regulation capabilities (goal orientation, self-direction, decision making, and impulse control) were measured with the Self-Regulation Questionnaire at T0, T1, and T2, together with body weight. At T0, all four dimensions of self-regulation were negatively related to BMI ( p < .01). At T1, weight significantly declined compared to T0 (− 2.0 kg/− 0.64 kg/m 2 , p < .001). At T2, this weight loss was maintained (− 1.8 kg/− 0.57 kg/m 2 , p < .01). At T1, intention to lose weight, self-weighing frequency, and an increase in goal orientation explained weight loss. At T2, an increase in decision making explained weight loss. Incremental self-regulation capabilities may explain weight loss after engaging in self-tracking of physical activity and weight. Future research should focus on exploring effective ways to further enhance self-regulation when using self-tracking technology and to assess the impact of different types of self-regulation stimuli on weight loss.

Background: Standard immunosuppressive therapy (IST) for severe/very severe aplastic anemia (SAA/vSAA) patients not eligible for transplantation is horse antithymocyte globulin (hATG) plus ciclosporin (CsA).We report an open-label, phase III, randomized trial of hATG and CsA with or without EPAG in naive patients with SAA/vSAA (clinicaltrials.gov,NCT02009747).Methods: From July 2015 to April 2019, 197 treatmentnaive patients were enrolled (6 countries and 24 sites), stratified on disease severity, age and center.Patients were randomized to either standard IST (hATG 40 mg/kg x4d and CsA 5 mg/kg/d; arm A) or standard IST + EPAG (experimental arm B) at the dose of 150 mg/d from day +14 until 6 months (m) (or 3m, in case of early complete response (CR)).The primary endpoint was hematological CR at 3m. Secondary endpoints included overall survival (OS), hematological response at 6m, clonal evolution and number and allele burden of somatic myeloid mutations (central laboratory, King's College London, UK).The study was powered to detect an increase in CR from 7% in arm A to 21% in arm B at 3m, requiring at least 96 patients per arm.Results: One-hundred-one and 96 patients were randomized to arm A and arm B, respectively.Baseline characteristics were comparable between the 2 arms, including median age (52 and 55 years in arms A and B), age stratum (age < 40 was 35.6% in arm A and 30.2% in arm B), disease severity (vSAA was 33.7% in arm A and 35.4% in arm B), and presence of a PNH clone (59.2% in arm A and 45.2% in arm B).Median follow-up was 18 months.The primary endpoint was reached with 3m CR rates of 9.9% and 21.9% in arms A and B (pooled Odds Ratio 3.2, p = 0.012).Overall response (OR=CR +PR) rates were 31.7% and 59.4%, respectively.At time of analysis, OR at 6m for patients alive, not being transplanted and without clonal evolution was 50.0% in arm A vs 76.3% in arm B (Odds Ratio: 3.8).SAEs were comparable in both arms.Eight patients came off study prematurely in arm A and 7 in arm B requiring secondline transplantation.Clonal evolution occurred in 1 patient in arm A (karyotype abnormality 6.5m after randomization) and in 3 patients in arm B (2 karyotypic abnormalities and 1 MDS after 6.2, 6.3 and 12.0m after randomization).High sensitivity NGS analysis was performed using a 31 gene target molecular bar coded panel.At time of this analysis, samples were available from 163 patients at baseline, and 132 at 6m follow up with no difference in term of somatic myeloid mutations (baseline: VAF >1% 38.2% in arm A vs 36.6% in arm B).During the study, 22 patients died (14 in arm A, OS of 83.2% at 24m and 8 in arm B, OS 86.3% at 24m) (p = 0.142).Conclusions: This practice changing phase III trial support the combination of hATG, CsA and EPAG as the next first line standard-of-care for SAA/vSAA patients not eligible fortransplantation.RPDL, CD and AMR equally contributed Clinical Trial Registry: clinicaltrials.gov,

This paper introduces a conceptual framework to guide research and education into the practice of personal science, which we define as using empirical methods to pursue personal health questions. Personal science consists of five activities: questioning, designing, observing, reasoning, and discovering. These activities are conceptual abstractions derived from review of self-tracking practices in the Quantified Self community. These practices have been enabled by digital tools to collect personal real-world data. Similarities and differences between personal science, citizen science and single subject (N-of-1) research in medicine are described. Finally, barriers that constrain widespread adoption of personal science and limit the potential benefits to individual wellbeing and clinical and public health discovery are briefly discussed, with perspectives for overcoming these barriers.

The purpose of this study was to determine the efficacy of an online self-tracking program on physical activity, glycated hemoglobin, and other health measures in patients with type 2 diabetes. Seventy-two patients with type 2 diabetes were randomly assigned to an intervention or control group. All participants received usual care. The intervention group received an activity tracker (Fitbit Zip) connected to an online lifestyle program. Physical activity was analyzed in average steps per day from week 0 until 12. Health outcome measurements occurred in both groups at baseline and after 13 weeks. Results indicated that the intervention group significantly increased physical activity with 1.5 ± 3 days per week of engagement in 30 minutes of moderate-vigorous physical activity versus no increase in the control group (P = .047). Intervention participants increased activity with 1255 ± 1500 steps per day compared to their baseline (P < .010). No significant differences were found in glycated hemoglobin A1c, with the intervention group decreasing −0.28% ± 1.03% and the control group showing −0.0% ± 0.69% (P = .206). Responders (56%, increasing minimally 1000 steps/d) had significantly decreased glycated hemoglobin compared with nonresponders (−0.69% ± 1.18% vs 0.22% ± 0.47%, respectively; P = .007). To improve effectiveness of eHealth programs, additional strategies are needed.

BACKGROUND:The Dutch professional nursing standard of 2012 stipulates that Dutch nursing practices are to be evidence-based. Not all practicing nurses can satisfy these requirements, therefore, an educational programme about Evidence-Based Practice (EBP) was developed for a Dutch teaching hospital.OBJECTIVE:The aim of this study was to measure the effects of a six month in-house EBP programme on knowledge, skills, attitudes, and perceived barriers of nurses (four European Credits equals two US Credit Hours).METHODS:A multiple-cohort study was conducted with a pre-post-test design. In the period of 2011-2015, a total of 58 nurses (9 cohorts) followed the programme. Baseline and follow-up assessments consisted of three questionnaires each: the Dutch Modified Fresno, the two subscales of the McColl questionnaire, and the BARRIER scale to assess knowledge and skills, attitudes, and perceived barriers, respectively.RESULTS:Fifty nurses completed both assessments. The results demonstrated that actual knowledge and skills significantly increased by approximately 40%. Self-perceived knowledge increased significantly, while attitudes towards EBP remained (moderately) positive. Perceived barriers did not notably change except for the Research subscale which received many "no opinion" responses prior to the programme but fewer afterwards.CONCLUSIONS:Our multifaceted in-house EBP programme led to a significant improvement of approximately 40% in EBP knowledge and skills of participating nurses. Most nurses who followed the EBP programme are currently applying their knowledge and skills in practice. Managerial support and allocated time for EBP are important facilitators for its implementation. Furthermore, to maintain and expand nurses' EBP knowledge and skills and translate them into practice, follow-up interventions, such as journal clubs, may well be beneficial. Based on the positive results of our programme, we will implement it throughout the hospital with an emphasis on training more groups of nurses.

Single subject research design, also known as N-of-1 research, is a scientific method in which an individual person serves as the research subject. We treat “N-of-1” and “single subject” as synonyms encompassing all scientific practice which focuses on observations made about a single person. Other names for similar and overlapping approaches include: single case experiments [1–3] single case research [4, 5], single case designs [6], and single patient trials [7]. Some authors distinguish between single subject research in general, which may be descriptive and exploratory in character, and single subject experiments that are prospectively planned and use formal methods such as randomization, blinding, or crossover comparisons. Here, we use N-of-1 and single subject research as synonymous, high level general terms for research focused on an individual rather than a group. N-of-1 research is common in applied fields of psychology, education, and human behavior where it has benefited from extensive methodical research and practical guidance for practitioners [8, 9]. However, over a half-century of study and advocacy, including pioneering publications by Guyatt et al., Larson et al., Mahon et al., and others, have failed to establish single subject science as central to research and practice in medicine [10–13]. A systematic review of 122 eligible N-of-1 studies published between 1985 and 2013 showed wide variation in methodology and reporting, reducing the power of these studies to influence practice [14]. Researchers advocating N-of-1 techniques have noted that the practical obstacles to design, conduct, analyze and apply the results for single subjects have simply been too high [15, 16]. Nevertheless the rise of personalized medicine and patient-centered research create new opportunities for using N-of-1 methods [17, 18]. Recent key publications include an extensive and comprehensive user guide for the design and implementation of N-of-1 trials [19], an update of the standard (CONSORT) for reporting N-of-1 trials [20, 21], and a special issue of the Journal of Clinical Epidemiology devoted to individual patients as the primary source and target of clinical research [22]. General public interest in gathering data about health is also growing. A Pew Internet study conducted in 2013 found that 1 in 5 Americans use some form of technology to track their health [23]. In 2016, the number of consumers in the United States who use mobile health apps increased from 16 percent in 2014 to 33 percent and the number of consumers who use health wearables increased from 9 percent to 21 percent [24]. According to data from the International Data Corporation (IDC), 104.3 million wearable devices were shipped in 2016, a number that is likely to be almost doubled by 2021 [25]. The increasing availability of home blood testing kits, wearable glucose monitors, and heart rate monitors, among other consumer health tools and services, suggest a large scale transformation of the measurement context for N-of-1 research. The combination of increased public interest and reliable measurement technologies broadly available may reduce the barriers to application of N-of-1 methodology [16, 26]. These consumer technologies have already attracted research attention. For instance, activity trackers made by Fitbit, Inc, have been deployed as instrumentation in over 450 public scientific studies [27]. Of course, application of wearables for clinical or research practice requires the technology to be valid and reliable. Research has found considerable variation of accuracy in different consumer wearables, including activity trackers [28–30], sleep trackers [31, 32], and wrist worn heart rate monitors [33, 34]. Despite this variation, there have been some notable successes. For instance, in an innovative two year study published in 2017, Li et al. demonstrated that measurement of heart rate and skin temperature using consumer wearables could predict inflammatory response as revealed by laboratory blood work showing elevated hs-CRP and onset of symptoms [35]. In presenting the articles in this focus theme, we aim to encourage attention to single subject research from from both scholars and researchers in health and biomedical informatics who may play a key role in advancing its practical methods and resolving doubts about its power and validity.

Self-tracking and automated persuasive eCoaching combined in a smartphone application may enhance stress management among employees at an early stage. For the application to be persuasive and create impact, we need to achieve a fit between the design and end-users’ and important stakeholders’ values. Semi-structured interviews were conducted among 8 employees and 8 human resource advisors to identify values of self-tracking, persuasive eCoaching, and preconditions (e.g., privacy and implementation) for a stress management application, using the value proposition design by Osterwalder et al. Results suggest essential features and functionalities that the application should possess. In general, respondents see potential in combining self-tracking and persuasive eCoaching for stress management via a smartphone application. Future design of the application should mainly focus on gaining awareness about the level of stress and causes of stress. In addition, the application should possess a positive approach besides solely the focus on negative aspects of stress.

BACKGROUND: A lack of physical activity is considered to cause 6% of deaths globally. Feedback from wearables such as activity trackers has the potential to encourage daily physical activity. To date, little research is available on the natural development of adherence to activity trackers or on potential factors that predict which users manage to keep using their activity tracker during the first year (and thereby increasing the chance of healthy behavior change) and which users discontinue using their trackers after a short time. OBJECTIVE: The aim of this study was to identify the determinants for sustained use in the first year after purchase. Specifically, we look at the relative importance of demographic and socioeconomic, psychological, health-related, goal-related, technological, user experience-related, and social predictors of feedback device use. Furthermore, this study tests the effect of these predictors on physical activity. METHODS: A total of 711 participants from four urban areas in France received an activity tracker (Fitbit Zip) and gave permission to use their logged data. Participants filled out three Web-based questionnaires: at start, after 98 days, and after 232 days to measure the aforementioned determinants. Furthermore, for each participant, we collected activity data tracked by their Fitbit tracker for 320 days. We determined the relative importance of all included predictors by using Random Forest, a machine learning analysis technique. RESULTS: The data showed a slow exponential decay in Fitbit use, with 73.9% (526/711) of participants still tracking after 100 days and 16.0% (114/711) of participants tracking after 320 days. On average, participants used the tracker for 129 days. Most important reasons to quit tracking were technical issues such as empty batteries and broken trackers or lost trackers (21.5% of all Q3 respondents, 130/601). Random Forest analysis of predictors revealed that the most influential determinants were age, user experience-related factors, mobile phone type, household type, perceived effect of the Fitbit tracker, and goal-related factors. We explore the role of those predictors that show meaningful differences in the number of days the tracker was worn. CONCLUSIONS: This study offers an overview of the natural development of the use of an activity tracker, as well as the relative importance of a range of determinants from literature. Decay is exponential but slower than may be expected from existing literature. Many factors have a small contribution to sustained use. The most important determinants are technical condition, age, user experience, and goal-related factors. This finding suggests that activity tracking is potentially beneficial for a broad range of target groups, but more attention should be paid to technical and user experience-related aspects of activity trackers.

This exploratory study aims to obtain a first impression of the wishes and needs of employees on the use of wearables at work for health promotion. 76 employ-ees with a mean age of 40 years old (SD ±11.7) filled in a survey after trying out a wearable. Most employees see the potential of using wearable devices for workplace health promotion. However, according to employees, some negative aspects should be overcome before wearables can effectively contribute to health promotion. The most mentioned negative aspects were poor visualization and un-pleasantness of wearing. Specifically for the workplace, employees were con-cerned about the privacy of data collection.

This exploratory study aims to obtain a first impression of the wishes and needs of employees on the use of wearables at work for health promotion. 76 employ-ees with a mean age of 40 years old (SD ±11.7) filled in a survey after trying out a wearable. Most employees see the potential of using wearable devices for workplace health promotion. However, according to employees, some negative aspects should be overcome before wearables can effectively contribute to health promotion. The most mentioned negative aspects were poor visualization and un-pleasantness of wearing. Specifically for the workplace, employees were con-cerned about the privacy of data collection.

Background The combination of self-tracking and persuasive eCoaching in automated interventions is a new and promising approach for healthy lifestyle management. Objective The aim of this study was to identify key components of self-tracking and persuasive eCoaching in automated healthy lifestyle interventions that contribute to their effectiveness on health outcomes, usability, and adherence. A secondary aim was to identify the way in which these key components should be designed to contribute to improved health outcomes, usability, and adherence. Methods The scoping review methodology proposed by Arskey and O’Malley was applied. Scopus, EMBASE, PsycINFO, and PubMed were searched for publications dated from January 1, 2013 to January 31, 2016 that included (1) self-tracking, (2) persuasive eCoaching, and (3) healthy lifestyle intervention. Results The search resulted in 32 publications, 17 of which provided results regarding the effect on health outcomes, 27 of which provided results regarding usability, and 13 of which provided results regarding adherence. Among the 32 publications, 27 described an intervention. The most commonly applied persuasive eCoaching components in the described interventions were personalization (n=24), suggestion (n=19), goal-setting (n=17), simulation (n=17), and reminders (n=15). As for self-tracking components, most interventions utilized an accelerometer to measure steps (n=11). Furthermore, the medium through which the user could access the intervention was usually a mobile phone (n=10). The following key components and their specific design seem to influence both health outcomes and usability in a positive way: reduction by setting short-term goals to eventually reach long-term goals, personalization of goals, praise messages, reminders to input self-tracking data into the technology, use of validity-tested devices, integration of self-tracking and persuasive eCoaching, and provision of face-to-face instructions during implementation. In addition, health outcomes or usability were not negatively affected when more effort was requested from participants to input data into the technology. The data extracted from the included publications provided limited ability to identify key components for adherence. However, one key component was identified for both usability and adherence, namely the provision of personalized content. Conclusions This scoping review provides a first overview of the key components in automated healthy lifestyle interventions combining self-tracking and persuasive eCoaching that can be utilized during the development of such interventions. Future studies should focus on the identification of key components for effects on adherence, as adherence is a prerequisite for an intervention to be effective.

Self-tracking and Persuasive eCoaching in Healthy Lifestyle Interventions: Work-in-progress Scoping Review of Key Components. This presentation is given during the Workshop Behavior Change Support Systems (BCSS 2016): Epic for Change, the Pillars for Persuasive Technology for Smart Societies. The presentation is about the work-in-progress paper 'Self-tracking and Persuasive eCoaching in Healthy Lifestyle Interventions: Work-in-progress Scoping Review of Key Components.' The combination of self-tracking and persuasive eCoaching in healthy lifestyle interventions is a promising approach. The objective of this study is to map the key components of existing healthy lifestyle interventionscombining self-tracking and persuasive eCoaching using the scoping review methodology in accordance with the York methodological framework by Arksey and O’Malley. Seven studies were included in this preliminary scoping review. Components related to persuasive eCoaching applied only in effective interventions were reduction of complex behavior into small steps, providingpositive motivational feedback by praise and providing reliable information to show expertise. Concerning self-tracking, it did not seem to matter if more action was required by the participant to obtain personal data. The first results of this study indicate the necessity to identify the needs and problems of the specific target group of the interventions, due to differences found between variousgroups of users. In addition to objective data on lifestyle and health behavior, other factors need to be taken into account, such as the context of use, daily experiences, and feelings of the users.

•Preference for low dose axial CT over DR was demonstrated in a human cadaver study.•Forty out of 54 observers (74%) preferred CT over DR.•∼70% dose reduction did not affect CT preference for assessment of zygomatic fractures.