Ecological Momentary Assessment in Behavioral Research: Addressing Technological and Human Participant Challenges

Temporal Associations of Physical Activity With Subsequent Knee Pain in Individuals With Knee Osteoarthritis: An Ecological Momentary Assessment Study

BACKGROUND

Physical activity (PA) is a first-line treatment for knee osteoarthritis and provides benefits for functional improvement and pain relief. However, movement-evoked pain often hinders PA participation and long-term adherence. The relationship between PA and pain is not fully understood and may vary across individuals. We examined the temporal associations between PA and subsequent knee pain in individuals with knee osteoarthritis.

METHODS

In a 10-day ecological momentary assessment (EMA) cohort study, PA was recorded using an Actigraph accelerometer; momentary knee pain intensity was rated on a numeric rating scale in responses to four daily text prompts. Linear mixed-effects models examined within-day and between-day associations between PA and knee pain, adjusting for age, sex and BMI.

RESULTS

The sample included up to 454 observations across 10 days from 17 participants (age = 64 ± 7 years, BMI = 27 ± 4 kg/m2, 61% women), each consisting of a temporal pair of PA minutes and subsequent momentary pain. Within-day, greater moderate-to-vigorous PA (MVPA) minutes were associated with a subsequent increase in knee pain (adjusted β = 0.112, 95% CI: 0.023, 0.201, p = 0.014); while light-intensity PA showed no association with subsequent pain (adjusted β = -0.003, 95% CI: -0.011, 0.005, p = 0.461). Current-day MVPA and light-intensity PA minutes were not associated with next-day knee pain.

CONCLUSIONS

While MVPA may temporarily increase knee pain, its impact was transient. Light-intensity PA showed no association with pain, suggesting it may be a suitable alternative for those with movement-evoked pain. Understanding these temporal patterns can help guide tailored pain management and PA adherence strategies. Further research is needed to confirm these preliminary findings.

SIGNIFICANCE STATEMENT

Understanding the dynamic relationship between PA and knee pain is crucial for optimising the management of knee OA. This exploratory study offers new insights by leveraging high-frequency data to examine the intra- and inter-day associations of MVPA and light-intensity PA with subsequent knee pain. The preliminary findings demonstrate that MVPA may lead to transient pain increases, while light-intensity PA is not associated with pain intensity. Identifying these PA-pain temporal patterns can inform personalised strategies for pain management and improving long-term activity adherence.

Protocol for project MHISS: Mental Health and Immunodynamics of Social Stress

Background

Growing evidence suggests that immune alterations may mediate the impact of stress on a plethora of negative psychological and somatic health outcomes. In particular, social stress has been demonstrated to be a particularly potent type of stress that modulates immune activity. Typically, this effect has been tested in the lab with acute social stressors. To build upon this research with greater external validity, we used the transition to college campuses for 1st year undergraduates as an ecologically valid social stressor in this novel, intensive longitudinal psychoneuroimmunology study.

Method

This NIMH-funded study collected data from 173 incoming 1st year students at a large public university in California, USA. Eligible participants were recruited using an online screener disseminated by the University registrar's office and had to be 17-19 years old, fluent in English, living on campus, not have self-selected any roommates, and have moved at least 100 miles to campus. Enrolled participants completed a baseline survey, daily self-report measures (3589 reports total), and blood draws every three days for 22 days (656 assayed samples), as well as an additional survey on the 22nd day. The start of the daily surveys was timed so that students' 7th survey was their first full day on campus (i.e., the day after move-in). We also describe sub-studies involving (a) diagnostic interviews at the end of students' 1st academic year, (b) extending the daily surveys to capture a full month for participants with a menstrual cycle, and (c) piloting a college transition resilience program.

Discussion

Consistent with recent calls from the NIMH Director, this study uses the transition to college as an ecologically valid stress paradigm, in combination with novel intensive longitudinal assessment of immunology, to characterize social stress-related changes in biopsychosocial functioning over time. Studies resulting from this project will shed light on the dynamic interplay between key psychoneuroimmunological processes, advance the methodological standards of this field, and help identify intervention opportunities to improve mental health on college campuses and beyond.

A "people-like-me" approach to predict individual recovery following lumbar microdiscectomy and physical therapy for lumbar radiculopathy

BACKGROUND CONTEXT

Lumbar microdiscectomy is an effective treatment for short-term pain relief and improvements in disability in patients with lumbar radiculopathy, however, many patients experience residual pain and long-term disability. The 'people like me' approach seeks to enhance personalized prognosis and treatment effectiveness, utilizing historical data from similar patients to forecast individual outcomes.

PURPOSE

The primary objective was to develop and test the "people-like-me" approach for leg pain intensity and disability at 12 month follow-up after lumbar microdiscectomy and postoperative physical therapy. The secondary objective was to verify the clinical utility of the prediction tool via case vignettes.

STUDY DESIGN/SETTING

A 12 month prospective cohort study.

PATIENT SAMPLE

Patients (N=618, mean age: 44.7) with lumbar radiculopathy who undergo a lumbar microdiscectomy and postoperative physical therapy.

OUTCOME MEASURES

Leg pain intensity (Visual Analogue Scale) and disability (Roland-Morris Disability Questionnaire) were measured at 12 months following surgery.

METHODS

Predictors were selected from data collected in routine practice before and 3 months after lumbar microdiscectomy. Predictive mean matching was used to select matches. Predictions were developed using preoperative data alone or combined with 3 month postoperative data. The prediction performance was evaluated for bias (difference between predicted and actual outcomes), coverage (proportion of actual outcomes within prediction intervals), and precision (accuracy of predictions) using leave-one-out cross-validation.

RESULTS

Overall, the 'people-like-me' approach using preoperative data showed accurate coverage and minimal average bias. However, precision based on preoperative data alone was limited. Incorporating 3 month postoperative data alongside preoperative predictors significantly enhanced prognostic precision for both leg pain and disability. Including postoperative data, leg pain prediction accuracy improved by 43% and disability by 23% compared to the sample mean. Adjusted R2 values improved from 0.04 to 0.21 for leg pain, and from 0.07 to 0.34 for disability, enhancing model precision. The effectiveness of this method was highlighted in two case vignettes, illustrating its application in similar patient scenarios.

CONCLUSION

The "people-like-me" approach generated an accurate prognosis of 12 month outcomes following lumbar discectomy and physical therapy. Scheduling a three month postoperative follow-up to evaluate the course, and refine therapy plans and expectations for patients undergoing lumbar microdiscectomy would be recommended to assist clinicians and patients in more personalized healthcare planning and expectation setting.

Innovative and ecological: integrating ecological momentary assessment into environmental science research

Ecological momentary assessment (EMA) is a widely used methodology in psychological sciences; however, more broadly, environmental scientists have yet to fully capitalize on the benefits this method offers for gaining a critical understanding of subjective and behavioral responses to environmental factors. EMA enables the collection of experiences and actions occurring in one's natural environment as they unfold over time, allowing researchers to gain contextually informed, dynamic, and longitudinal insights. EMA can provide an accurate understanding of experiences and behaviors relevant to environmental science. To share this perspective, first, we describe current limitations in environmental research that could be addressed through the integration of EMA. Second, we discuss several benefits of adopting EMA in environmental sciences. Finally, we highlight the challenges and considerations involved in integrating EMA. The overarching implication of this work is to foster the interdisciplinary potential and promise of EMA methodology in advancing environmental science research.

Real-time monitoring to predict depressive symptoms: study protocol

Introduction

According to the World Health Organization, Depression is the fourth leading cause of global disease burden. However, traditional clinical and self-report assessments of depression have limitations in providing timely diagnosis and intervention. Recently, digital phenotyping studies have found the possibility of overcoming these limitations through the use of wearable-devices and smartphones. The present study aims to identify the digital phenotype that significantly predicts depressive symptoms.

Methods and analysis

The study will recruit a total of 150 participants in their 20s who have experienced depression for the past two weeks in Korea. The study will collect passive (eg., active energy, exercise minutes, heart rate, heart rate variability, resting energy, resting heart rate, sleep patterns, steps, walking pace) data and Ecological Momentary Assessment (EMA) through smartphone and wearable-device for two weeks. This study will be conducted longitudinally, with two repeated measurements over three months. Passive data will be collected through sensors on the wearable-device, while EMA data will be collected four times a day through a smartphone app. A machine learning algorithm and multilevel model will be used to construct a predictive model for depressive symptoms using the collected data.

Discussion

This study explores the potential of wearable devices and smartphones to improve the understanding and treatment of depression in young adults. By collecting continuous, real-time data on physiological and behavioral patterns, the research uncovers subtle changes in heart rate, activity levels and sleep that correlate with depressive symptoms, providing a deeper understanding of the disorder. The findings provide a foundation for further research and contribute to the advancement of digital mental health. Advances in these areas of research may have implications for the detection and prevention of early warning signs of depression through the use of digital markers.

Association between parental stress, coping, mood, and subsequent child physical activity and screen-time: an ecological momentary assessment study

BACKGROUND

Few children meet physical activity and screen-time guidelines. Parents play a key role in supporting children's physical activity and limiting child screen-time, but their own stress, management of stress (i.e., coping), and mood may impact their ability to do so. Ecological momentary assessment (EMA) is a methodology that can be used to assess the temporality of parental state (i.e., stress, mood) and subsequent child behavior. This study aimed to examine the relationship between parental stress, coping, and mood with child physical activity and screen-time, and whether there were differences by child sex.

METHODS

Parents and their children (n = 436, 5-9 y) participated in an EMA study that used signal-contingent and end-of-day surveys. Parents received three signal-contingent surveys during fixed 3-hour windows and one end-of-day survey over 7-days via smartphone notifications. Parents reported their current stress, ability to manage stress, and depressive mood at the first signal-contingent survey. Parents also reported the frequency of their child's physical activity and screen-time across the day during the end-of-day survey. Conditional fixed effects regression was fitted to examine current and lagged day stress, coping, and mood relationships on change in child physical activity and screen-time.

RESULTS

Children were girls (53.7%), mainly non-white (64.3%), and with a household income of less than $50,000 USD (54.1%). Overall, parent's current day stress was negatively related to the frequency of child physical activity (p = 0.001), but not screen-time. Among girls, higher parent current-day stress and lower coping were related to less frequent girl's physical activity (ps < 0.05). Parent's lagged day stress was then associated with more frequent girl physical activity the next day (p = 0.018). There were no associations among parent mood or in models with only boys.

CONCLUSIONS

This study found parent's stress may negatively impact child's physical activity that day, but may positively impact physical activity the next day, namely girls. Findings suggest that reducing parental stress and improving coping abilities may improve girl's physical activity, but other approaches are needed to reduce child screen-time at this age.

From Steps to Context: Optimizing Digital Phenotyping for Physical Activity Monitoring in Older Adults by Integrating Wearable Data and Ecological Momentary Assessment

Physical activity (PA) is essential for healthy aging, but its accurate assessment in older adults remains challenging due to the limitations and biases of traditional clinical assessment. Mobile technologies and wearable sensors offer a more ecological, less biased alternative for evaluating PA in this population. This study aimed to optimize digital phenotyping strategies for assessing PA patterns in older adults, by integrating ecological momentary assessment (EMA) and continuous wearable sensor data collection. Over two weeks, 108 community-dwelling older adults provided real-time EMA responses while their PA was continuously monitored using Garmin Vivo 5 sensors. The combined approach proved feasible, with 67.2% adherence to EMA prompts, consistent across time points (morning: 68.1%; evening: 65.4%). PA predominantly occurred at low (51.4%) and moderate (46.2%) intensities, with midday activity peaks. Motivation and self-efficacy were significantly associated with low-intensity PA (R = 0.20 and 0.14 respectively), particularly in the morning. However, discrepancies between objective step counts and self-reported PA measures, which showed no correlation (R = -0.026, p = 0.65), highlight the complementary value of subjective and objective data sources. These findings support integrating EMA, wearable sensors, and temporal frameworks to enhance PA assessment, offering precise insights for personalized, time-sensitive interventions to promote PA.

Affective dynamics surrounding craving, non-heavy alcohol use and binge drinking in female patients with alcohol use disorder and controls: An experience sampling method study

BACKGROUND AND AIMS

Studies show that higher levels of positive affect (PA) and lower levels of negative affect (NA) are related to craving and alcohol consumption at a daily level in men, but little is known on these associations at a momentary level, and whether they are present in women. This study measured the dynamics of within-person NA and PA surrounding craving, non-heavy alcohol use and binge drinking in women with alcohol use disorder (AUD) and female controls without AUD.

METHODS

53 female patients with AUD and 75 female controls, all recruited in Belgium, were included in an experience sampling study where they reported on momentary NA, PA, craving and alcohol use in daily life over a period of 12 months. Assessments occurred eight times a day on Thursdays, Fridays and Saturdays in seven bursts of three weeks.

RESULTS

Within-person NA at a previous assessment (t-1) predicted craving at the current assessment (t0) in patients with AUD in a positive linear [β = 0.043; 95% confidence interval (CI) = 0.002, 0.057; P = 0.041] and quadratic fashion (β = 0.034; CI = 0.011, 0.057; P = 0.004). Within-person PA at t-1 predicted craving at t0 in patients with AUD with a positive quadratic relation (β = 0.042; CI = 0.08, 0.065; P < 0.001). Within-person NA at t-1 negatively predicted non-heavy alcohol use at t0 in a linear fashion in controls (β = -0.495; CI = -0.677, -0.312; P < 0.001) and patients with AUD (β = -0.276; CI = -0.421, -0.132; P < 0.001). Within-person PA at t-1 significantly predicted non-heavy alcohol use at t0 with a positive linear term (β = 0.470; CI = 0.329, 0.610; P < 0.001) in controls, but with a positive linear term (β = 0.399; CI = 0.260, 0.454; P < 0.001) and a positive quadratic term (β = 0.203; CI = 0.060, 0.347; P = 0.003) in patients with AUD. Within-person NA at t-1 predicted binge drinking at t0 in patients with AUD with a significant quadratic term (β = 0.236; CI = 0.060, 0.412; P = 0.008), but not for controls. Within-person PA at t-1 predicted binge drinking at t0 in patients with AUD with a significant quadratic term (β = 0.378; CI = 0.215, 0.542; P < 0.001), and this was also the case for controls (β = 0.487; CI = 0.158, 0.770; P < 0.001). Non-heavy alcohol use at t0 predicted lower levels of NA at t+1 in both patients with AUD (β = -0.161; SE = 0.044; CI = -0.248, 0.074; P = 0.001) and controls (β = -0.114; CI = -0.198, -0.029; P = 0.010). Non-heavy alcohol use at t0 also predicted higher levels of PA at t+1 in both patients with AUD (β = 0.181; CI = 0.088, 0.274; P < 0.001) and controls (β = 0.189; CI = 0.101, 0.278; P < 0.001).

CONCLUSIONS

The momentary relation between affect and craving or alcohol use seems to be non-linear in female patients with alcohol use disorder, whereby a worse mood predicts subsequent alcohol use, though more for binge drinking than for non-heavy alcohol use.

Psychological Determinants of Health Behavior

This review provides a critical overview of current evidence on psychological health behavior determinants and its value in informing intervention and future determinants research. The review begins with work labeling and classifying the myriad of determinants available in the extant research to arrive at core groups of determinants. Next, the conceptual bases of these determinant groups are identified, and the weight of the evidence for their purported effects on health behavior, including belief-based determinants (e.g., outcome expectancies, capacity beliefs), determinants representing self-regulatory capacity (e.g., planning, action control) and nonconscious processes (e.g., habit, implicit cognition), and dispositional determinants (e.g., personality, regulatory control), is critically evaluated. The review also focuses on the theory-based mechanisms underpinning determinant effects and moderating conditions that magnify or diminish them. Finally, the review recommends a shift away from research on determinants as correlates, outlines how determinants can inform intervention development and mechanisms of action tests, suggests alternatives to predominant individualist approaches, and proposes future research directions.

Ecological Momentary Assessment of Mental Health Problems Among University Students: Data Quality Evaluation Study

BACKGROUND

The use of ecological momentary assessment (EMA) designs has been on the rise in mental health epidemiology. However, there is a lack of knowledge of the determinants of participation in and compliance with EMA studies, reliability of measures, and underreporting of methodological details and data quality indicators.

OBJECTIVE

This study aims to evaluate the quality of EMA data in a large sample of university students by estimating participation rate and mean compliance, identifying predictors of individual-level participation and compliance, evaluating between- and within-person reliability of measures of negative and positive affect, and identifying potential careless responding.

METHODS

A total of 1259 university students were invited to participate in a 15-day EMA study on mental health problems. Logistic and Poisson regressions were used to investigate the associations between sociodemographic factors, lifetime adverse experiences, stressful events in the previous 12 months, and mental disorder screens and EMA participation and compliance. Multilevel reliability and intraclass correlation coefficients were obtained for positive and negative affect measures. Careless responders were identified based on low compliance or individual reliability coefficients.

RESULTS

Of those invited, 62.1% (782/1259) participated in the EMA study, with a mean compliance of 76.9% (SD 27.7%). Participation was higher among female individuals (odds ratio [OR] 1.41, 95% CI 1.06-1.87) and lower among those aged ≥30 years (OR 0.20, 95% CI 0.08-0.43 vs those aged 18-21 years) and those who had experienced the death of a friend or family member in the previous 12 months (OR 0.73, 95% CI 0.57-0.94) or had a suicide attempt in the previous 12 months (OR 0.26, 95% CI 0.10-0.64). Compliance was particularly low among those exposed to sexual abuse before the age of 18 years (exponential of β=0.87) or to sexual assault or rape in the previous year (exponential of β=0.80) and among those with 12-month positive alcohol use disorder screens (exponential of β=0.89). Between-person reliability of negative and positive affect was strong (RkRn>0.97), whereas within-person reliability was fair to moderate (Rcn>0.43). Of all answered assessments, 0.86% (291/33,626) were flagged as careless responses because the response time per item was <1 second or the participants gave the same response to all items. Of the participants, 17.5% (137/782) could be considered careless responders due to low compliance (<25/56, 45%) or very low to null individual reliability (raw Cronbach α<0.11) for either negative or positive affect.

CONCLUSIONS

Data quality assessments should be carried out in EMA studies in a standardized manner to provide robust conclusions to advance the field. Future EMA research should implement strategies to mitigate nonresponse bias as well as conduct sensitivity analyses to assess possible exclusion of careless responders.

Exploring emotions beyond the laboratory: A review of emotional and physiological ecological momentary assessment methods in children and youth

Recent advancements in methodologies such as ecological momentary assessment (EMA) and ambulatory physiology devices have enhanced our ability to measure emotions experienced in daily life. Despite the feasibility of EMA for assessing children's and youth's emotional self-reports, the feasibility of combining it with physiological measurements in a real-life context has yet to be established. Our scoping review evaluates the feasibility and usability of implementing emotional and physiological EMA in children and youth. Due to the complexities of physiological EMA data, this review also synthesized existing methodological and statistical practices of existing studies. Following the PRISMA-ScR guidelines, we searched and screened PsycINFO, PubMed, and Web of Science electronic databases for studies that assessed children's and youth's subjective emotions and cardiac or electrodermal physiological responses outside the laboratory. Our initial search resulted in 4174 studies, 13 of which were included in our review. Findings showed significant variability in the feasibility of physiological EMA, with physiology device wear-time averaging 58.77% of study periods and data loss due to quality issues ranging from 0.2% to 77% across signals. Compliance for emotional EMA was approximately 60% of study periods when combined with physiological EMA. The review points to a lack of standardized procedures in physiological EMA and suggests a need for guidelines in designing, processing, and analyzing such data collected in real-life contexts. We offer recommendations to enhance participant engagement and develop standard practices for employing physiological EMA with children and youth for emotion, developmental, and psychophysiology researchers.

Hybrid mHealth care: Patient perspectives of blended treatments for psychosis. A systematic review

BACKGROUND

mHealth interventions use mobile and wireless technologies to deliver aspects of healthcare, and have been extensively employed in mental health research, showcasing their potential to address the significant treatment gap. While numerous studies underscore the advantages and functionalities of mHealth, challenges persist regarding patient uptake and sustained engagement among individuals with psychosis spectrum disorder. This review aims to explore individual-level barriers and facilitators to engagement with hybrid digital systems, which involves the integration of digital tools alongside in-person care.

METHOD

Four electronic databases (Medline, Web of Science, CINAHL, and PsychINFO) were systematically searched to identify hybrid digital interventions for psychosis spectrum disorders. Studies that only reported the efficacy of the interventions were excluded. 16 studies were included in the final review.

RESULTS

Six themes were identified in this review, including mHealth as a tool to aid communication, the central role of the therapist, an increased sense of support through the provision of digital support, allowing greater insight into auditory hallucinations, enabling technologies and barriers to engagement.

CONCLUSIONS

This review demonstrated the factors impacting engagement in hybrid interventions for psychosis spectrum disorder. By identifying barriers and facilitators, the findings could offer valuable guidance for the design of innovative digital interventions. These findings also underscore the importance of prioritising trustworthiness in digital systems. Future research should focus on establishing and implementing trustworthy digital systems to enhance engagement and effectively integrate mobile health into conventional healthcare practices.

Sleep health, its intraindividuality, and perceived stress in college students during the COVID-19 pandemic

Objective: To describe the changes in sleep health domains and examine the associations between the repeated measures and intraindividual variability (IIV) of these domains and perceived stress. Participants: A diverse racial and ethnic group of first-year college students (N = 23, 78.3% female, aged 17-18) attending in-person classes during the COVID-19 pandemic. Methods: Sleep health domains were determined using 7-day wrist actigraph and daily sleep diaries, and perceived stress scale was completed at 1-month intervals across 3 months. Results: Sleep timing, regularity, and alertness during daytime demonstrated statistically significant changes between three timepoints. Greater stress was associated with more irregularity (B = 2.25 [.87-3.62], p < .001), more dissatisfaction in sleep (B = .04 [.02-.19], p < .01), alertness during daytime (B = .18 [.05-.31], p < .001), and greater IIV (ie, fluctuations) in sleep satisfaction (B = .083 [.02, .15], p < .01). Conclusion: These findings offer insights for future researchers to facilitate intervention development to promote mental and sleep health among college students.

Process mining in mHealth data analysis

This perspective article explores how process mining can extract clinical insights from mobile health data and complement data-driven techniques like machine learning. Despite technological advances, challenges such as selection bias and the complex dynamics of health data require advanced approaches. Process mining focuses on analyzing temporal process patterns and provides complementary insights into health condition variability. The article highlights the potential of process mining for analyzing mHealth data and beyond.

Leveraging A Digital Pill System to Understand Prevention-Effective Adherence to Oral Hiv Pre-Exposure Prophylaxis Among Men Who Have Sex with Men with Substance Use

Daily oral pre-exposure prophylaxis (PrEP) is highly effective for HIV prevention, though efficacy depends on adherence. Digital pill systems (DPS) can enable direct, real-time adherence measurement. HIV-negative men who have sex with men (MSM) with substance use (excluding alcohol) utilized a DPS over 90 days and completed weekly surveys reporting sexual activity, condom use, and substance use. Responses indicating (1) any sexual activity and substance use or (2) condomless anal intercourse (CAI) in the prior week were categorized as high risk for HIV acquisition. PrEP adherence data for the 7-day period preceding each response was dichotomized as ≤ 3 and ≥ 4 doses/week, indicating prevention-effective adherence, and compared by HIV risk level. Thirteen MSM were analyzed (median age: 32). Of 113 surveys, 48.7% indicated high HIV risk, with 12.4% reporting CAI alone, 16.8% any sexual activity and substance use, and 19.5% both CAI and substance use. Weekly mean PrEP adherence was 90.3% (6.3 of 7 doses/week), with ≥ 4 doses/week recorded during 92.0% of weeks. The proportion of participants with ≥ 4 recorded doses/week was 88.9% during weeks with CAI alone, 89.5% during weeks with any sexual activity and substance use, 92.0% during weeks with both CAI and substance use, and 92.8% during lower risk weeks. Participants ingested ≥ 4 doses/week during 89.1% of all high-risk weeks and 94.8% of low-risk weeks. Overall, participants maintained high levels of PrEP adherence while engaging in HIV risk behaviors. DPS can be deployed concurrently with data collection tools to assess ingestion patterns during periods of elevated risk.

Feasibility and Acceptability of Ecological Momentary Assessment to Assess Suicide Risk among Young People with Mood Disorder in China

Suicidal thoughts and behaviors (STBs) are increasing among young people (aged 12-24 years) in China. Although Ecological Momentary Assessment (EMA) has been increasingly used to study STBs worldwide, no study has been conducted on young people with mood disorders (MD) in China. This mixed-method study aimed to evaluate the feasibility and acceptability of suicide risk monitoring in 75 young people with MD. Participants completed five to eight daily EMA surveys and wore smart bands for the EMA study. Semi-structured interviews were used to collect feedback. High adherence to EMA surveys (73.0 %) and smart bands (87.4 %) indicated feasibility. Participants reported an overall positive experience with the EMA study (helpful, friendly, and acceptable). Additionally, the reasons they were willing to comply with the EMA study were: (1) seeing the possibility of returning to "normal," and (2) experiencing the process of returning. However, a small proportion of participants had negative experiences (e.g., annoyance and missing prompts). The results of this mixed-methods study provide preliminary support for the feasibility and acceptability of using EMA (combined smartphones and wearable sensor devices) to assess suicidality among young people with MD in the Chinese cultural and social context.

Examining missingness at the momentary level in clinical research using ecological momentary assessment: Implications for suicide research

The use of intensive time sampling methods, such as ecological momentary assessment (EMA), has increased in clinical, and specifically suicide, research during the past decade. While EMA can capture dynamic intraindividual processes, repeated assessments increase participant burden, potentially resulting in low compliance. This study aimed to shed light on study-level and psychological variables, including suicidal ideation (SI), that may predict momentary prompt (i.e., prompt-to-prompt) completion. We combined data from three EMA studies examining mental health difficulties (N = 103; 10,656 prompts; 7144 completed), using multilevel models and machine learning to determine how well we can predict prompt-to-prompt completion and which variables are most important. The two most important variables in prompt-to-prompt completion were hours since the last prompt and time in study. Psychological variables added little predictive validity; similarly, trait-level SI demonstrated a small effect on prompt-to-prompt completion. Our study showed how study-level characteristics can be used to explain prompt-to-prompt compliance rates in EMA research, highlighting the potential for developing adaptive assessment schedules to improve compliance.

Predicting Completion of Ecological Momentary Assessments Among Substance-Using Women Experiencing Intimate Partner Violence

Noncompletion of ecological momentary assessment (EMA) surveys is a common issue and may yield bias in results if not properly handled. Using data observed at scheduled times as well as data retrieved later to fill missing responses, this study aims to investigate predictors of EMA completion, including demographic characteristics, time-related factors, and momentary experiences/behaviors. Data were from a 30-day EMA study including 145 women currently experiencing intimate partner violence (IPV) and using substances. The average rate of EMA completion was initially 51.4% at the scheduled times and increased to 72.6% after incorporating data from later-retrieved surveys. Participants who were younger, had more children, or had lower mean levels of negative affect dysregulation showed lower completion rates. At the momentary survey level, more days into the study and afternoon/evening reports (vs. morning reports) were associated with lower completion; lower levels of negative affect dysregulation, less smoking or alcohol use, and experiencing IPV were linked to lower momentary completion. Implications of the results for handling missing data in EMA are discussed and have important ramifications for future research, practice, and theory.

Using Large Language Models to Detect Depression From User-Generated Diary Text Data as a Novel Approach in Digital Mental Health Screening: Instrument Validation Study

BACKGROUND

Depressive disorders have substantial global implications, leading to various social consequences, including decreased occupational productivity and a high disability burden. Early detection and intervention for clinically significant depression have gained attention; however, the existing depression screening tools, such as the Center for Epidemiologic Studies Depression Scale, have limitations in objectivity and accuracy. Therefore, researchers are identifying objective indicators of depression, including image analysis, blood biomarkers, and ecological momentary assessments (EMAs). Among EMAs, user-generated text data, particularly from diary writing, have emerged as a clinically significant and analyzable source for detecting or diagnosing depression, leveraging advancements in large language models such as ChatGPT.

OBJECTIVE

We aimed to detect depression based on user-generated diary text through an emotional diary writing app using a large language model (LLM). We aimed to validate the value of the semistructured diary text data as an EMA data source.

METHODS

Participants were assessed for depression using the Patient Health Questionnaire and suicide risk was evaluated using the Beck Scale for Suicide Ideation before starting and after completing the 2-week diary writing period. The text data from the daily diaries were also used in the analysis. The performance of leading LLMs, such as ChatGPT with GPT-3.5 and GPT-4, was assessed with and without GPT-3.5 fine-tuning on the training data set. The model performance comparison involved the use of chain-of-thought and zero-shot prompting to analyze the text structure and content.

RESULTS

We used 428 diaries from 91 participants; GPT-3.5 fine-tuning demonstrated superior performance in depression detection, achieving an accuracy of 0.902 and a specificity of 0.955. However, the balanced accuracy was the highest (0.844) for GPT-3.5 without fine-tuning and prompt techniques; it displayed a recall of 0.929.

CONCLUSIONS

Both GPT-3.5 and GPT-4.0 demonstrated relatively reasonable performance in recognizing the risk of depression based on diaries. Our findings highlight the potential clinical usefulness of user-generated text data for detecting depression. In addition to measurable indicators, such as step count and physical activity, future research should increasingly emphasize qualitative digital expression.

Implementing Ecological Momentary Assessment in Audiological Research: Opportunities and Challenges

Ecological momentary assessment (EMA) is a way to evaluate experiences in everyday life. It is a powerful research tool but can be complex and challenging for beginners. Application of EMA in audiological research brings with it opportunities and challenges that differ from other research disciplines. This tutorial discusses important considerations when conducting EMA studies in hearing care. While more research is needed to develop specific guidelines for the various potential applications of EMA in hearing research, we hope this article can alert hearing researchers new to EMA to pitfalls when using EMA and help strengthen their study design. The current article elaborates study design details, such as choice of participants, representativeness of the study period for participants' lives, and balancing participant burden with data requirements. Mobile devices and sensors to collect objective data on the acoustic situation are reviewed alongside different possibilities for EMA setups ranging from online questionnaires paired with a timer to proprietary apps that also have access to parameters of a hearing device. In addition to considerations for survey design, a list of questionnaire items from previous studies is provided. For each item, an example and a list of references are given. EMA typically provides data sets that are rich but also challenging in that they are noisy, and there is often unequal amount of data between participants. After recommendations on how to check the data for compliance, reactivity, and careless responses, methods for statistical analysis on the individual level and on the group level are discussed including special methods for direct comparison of hearing device programs.

Examining early adherence measures as predictors of subsequent adherence in an intensive longitudinal study of individuals in mutual help groups: One day at a time

BACKGROUND

Individuals with a substance use disorder complete ecological momentary assessments (EMA) at lower rates than community samples. Previous research in tobacco users indicates that early log-in counts to smoking cessation websites predicted subsequent smoking cessation website usage. We extended this line of research to examine individuals who are seeking to change their drinking behaviors through mutual support groups. We examined whether adherence in the first 7 days (1487 observations) of an intensive longitudinal study design could predict subsequent EMA protocol adherence (50% and 80% adherence separately) at 30 (5700 observations) and 60 days (10,750 observations).

METHODS

Participants (n = 132) attending mutual-help groups for alcohol use completed two assessments per day for 6 months. We trained four classification models (logistic regression, recursive partitioning, support vector machines, and neural networks) using a training dataset (80% of the data) with each of the first 7 days' cumulative EMA assessment completion. We then tested these models to predict the remaining 20% of the data and evaluated model classification accuracy. We also used univariate receiver operating characteristic curves to examine the minimal combination of days and completion percentage to best predict subsequent adherence.

RESULTS

Different modeling techniques can be used with early assessment completion as predictors to accurately classify individuals that will meet minimal and optimal adherence rates later in the study. Models ranged in their performance from poor to outstanding classification, with no single model clearly outperforming other models.

CONCLUSIONS

Traditional and machine learning approaches can be used concurrently to examine several methods of predicting EMA adherence based on early assessment completion. Future studies could investigate the use of several algorithms in real time to help improve participant adherence rates by monitoring early adherence and using early assessment completion as features in predictive modeling.

Leveraging Experience Sampling/Ecological Momentary Assessment for Sociological Investigations of Everyday Life

Experience sampling (ES) - also referred to as ecological momentary assessment (EMA) - is a data collection method that involves asking study participants to report on their thoughts, feelings, behaviors, activities, and environments in (or near) real time. ES/EMA is typically administered using an intensive longitudinal design (repeated assessments within and across days). Although use of ES/EMA is widespread in psychology and health sciences, uptake of the method among sociologists has been limited. We argue that ES/EMA offers key advantages for the investigation of sociologically relevant phenomena, particularly in light of recent disciplinary emphasis on investigating the everyday mechanisms through which social structures and micro (individual and relational) processes are mutually constitutive. We describe extant and potential research applications illustrating advantages of ES/EMA regarding enhanced validity, disentangling short-term dynamics, and the potential for linkage with spatially and temporally referenced data sources. We also consider methodological challenges facing sociological research using ES/EMA.

Choosing Health: acceptability and feasibility of a theory-based, online-delivered, tailored weight loss, and weight loss maintenance intervention

Few weight loss and weight loss maintenance interventions are tailored to include factors demonstrated to predict the user's behavior. Establishing the feasibility and acceptability of such interventions is crucial. The aim of this study was to assess the acceptability and feasibility of a theory-based, tailored, online-delivered weight loss and weight loss maintenance intervention (Choosing Health). We conducted a mixed methods process evaluation of the Choosing Health tailored intervention, nested in a randomized controlled trial (N = 288) with an embedded N-of-1 study, investigating participants' and implementers' experiences related to intervention context, implementation, and mechanisms of impact. Measures included: (i) surveys, (ii) data-prompted interviews (DPIs) with study participants, (iii) semi-structured interviews with implementers, and (iv) intervention access and engagement data. Five themes described the acceptability of the intervention to participants: (i) monitoring behavior change and personal progress to better understand the weight management process, (ii) working collaboratively with the intervention implementers to achieve participants' goals, (iii) perceived benefits of non-judgmental and problem-solving tone of the intervention, (iv) changes in personal perception of the weight management process due to intervention tailoring, and (v) insufficient intervention content tailoring. The intervention delivery was feasible, however, emails and text messages differed in terms of accessibility and resources required to deliver the content. The use of Ecological Momentary Assessment as a technique to gather personal data for further tailoring was acceptable, and facilitated behavior change monitoring. Personalization of the intervention content above and beyond domain-specific issues, for example, by addressing participants' social roles may better match their needs. Support from the implementers and feedback on body composition changes may increase participants' engagement.

Recruitment and retention of adolescents for an ecological momentary assessment measurement burst mental health study: The MHIM engagement strategy

INTRODUCTION

Recruitment and long-term retention of adolescent participants in longitudinal research are challenging and may be especially so in studies involving remote measurement and biosampling components. The ability to effectively recruit and retain participants can be supported by the use of specific evidence-based engagement strategies that are built in from the earliest stages.

METHODS

Informed by a review of the evidence on effective engagement strategies and consultations with adolescents (via two Young Person Advisory Groups [YPAGs]; ages 11-13 and 14-17), the current protocol describes the planned participant engagement strategy for the Mental Health in the Moment Study: a multimodal measurement burst study of adolescent mental health across ages 11-19.

RESULTS

The protocol incorporates engagement strategies in four key domains: consultations/co-design with the target population, incentives, relationship-building and burden/barrier reduction. In addition to describing general engagement strategies in longitudinal studies, we also discuss specific concerns regarding engagement in data collection methods such as biosampling and ecological momentary assessment where a paucity of evidence exists.

CONCLUSION

Engagement strategies for adolescent mental health studies should be based on existing evidence and consultations with adolescents. We present our approach in developing the planned engagement strategies and also discuss limitations and future directions in engaging adolescents in longitudinal research.

PATIENT OR PUBLIC CONTRIBUTION

The study design for this project places a strong emphasis on the active engagement of adolescents throughout its development. Specifically, the feedback and suggestions provided by the YPAGs have been instrumental in refining our strategies for maximising the recruitment and retention of participants.

Trajectories and Predictors of Change in Emotion Dysregulation and Deliberate Self-Harm Amongst Adolescents with Borderline Features

BACKGROUND

Deliberate self-harm (DSH) and emotion dysregulation (ED) peaks in adolescence, and is associated with an increased risk of psychopathology, suicide and lower functioning in adulthood. DBT-A has been established as an effective treatment for reducing DSH, however less is known about changes in emotion dysregulation. This study aimed to identify baseline predictors of treatment response in outcome trajectories of DSH and emotion dysregulation.

METHODS

Response trajectories of DSH and ED were investigated using Latent Class Analysis on RCT data comparing DBT-A and EUC for 77 adolescents treated for deliberate self-harm and borderline traits. Logistic regression analysis was used to examine baseline predictors.

RESULTS

Two-class solutions were selected for both indicators, distinguishing between early and late responders in DSH, and responders and non-responders in ED. Higher levels of depression, shorter DSH histories and not receiving DBT-A predicted less favourable response in DSH, while DBT-A was the only predictor of treatment response in ED.

CONCLUSIONS

DBT-A was associated with a significantly faster reduction of deliberate self-harm in the short-term and improved emotion regulation in the long-term.

The use of ecological momentary assessment for family caregivers of adults with chronic conditions: A systematic review

Background

Ecological momentary assessment (EMA) as a real-time data collection method can provide insight into the daily experiences of family caregivers.

Purpose

This systematic review aimed to synthesize studies involving EMA completed by family caregivers of adults with chronic conditions.

Methods

A systematic search was conducted within six databases for articles published from the inception of the database through September 2023. We extracted the characteristics of the included studies and data on EMA-specific methods to determine the quality of the included studies.

Results

A total of 12 studies involving EMA completed by family caregivers of adults with chronic conditions were identified, with almost all studies focused on caregivers of persons with Alzheimer's or dementia-related conditions. The average compliance rate across the included studies was 75%, below the recommended rate. In addition, most of the included studies did not collect the family caregivers' daily activities and care contexts in their responses (i.e., affect, stress, well-being, care demand, and fatigue) to the EMA prompts.

Discussion

This review showed that using EMA to collect information on family caregivers of adults with chronic health conditions appeared feasible and acceptable. However, the methodology or design of using EMA to collect caregiver information in this population is still preliminary. The limited number of existing studies that have used EMA to capture the daily experiences of family caregivers does not provide key information that could improve understanding of caregivers' emotional experiences and well-being in real-life situations. We identified gaps in the literature that warrant additional EMA studies for this population.

Compliance Trends in a 14-Week Ecological Momentary Assessment Study of Undergraduate Alcohol Drinkers

High compliance is a priority for successful ecological momentary assessment (EMA) research, but meta-analyses of between-study differences show that reasons for missed prompts remain unclear. We examined compliance data from a 14-week, 182-survey EMA study of undergraduate alcohol use to test differences over time and across survey types between participants with better and worse compliance rates, and to evaluate the impact of incentives on ongoing participation. Participants were N = 196 students (65.8% female; Mage = 20.6). Overall compliance was 76.5%, declining gradually from 88.9% to 70% over 14 weeks. Declines were faster in participants with lower overall compliance, but we found no demographic, personality, mental health, or substance use differences between participants with better versus worse compliance rates. Compliance varied by survey type, and unannounced bonus incentives did not impact compliance rates. Participants completed fewer surveys the week after winning a gift card. We offer recommendations for designing future EMA studies.

Mobile-based ecological momentary assessment and intervention: bibliometric analysis

Objective

The aim of this article was to review existing documents in the field of mobile-based EMA and EMI, provide an overview of current hot topics, and predict future development trends.

Methods

We conducted a bibliometric study on mobile-based EMA and EMI publications that were collected from the Web of Science Core Collection database. Biblioshiny and CiteSpace were utilized to analyze scientific productions, leading sources, authors, affiliations, documents, research hot topics, keywords, and trend topics.

Results

A total of 2222 documents related to EMA and EMI published between 1992 and 2023 were retrieved. In recent years, scholarly publications have generally increased in mobile-based EMA and EMI research, particularly in the last decade. JMIR mHealth and uHealth (n=86), as well as JMIR (n=73), showed the highest number of publications. The United States (n=1038), Germany (n=218) and Netherlands (n=175) were leading countries. Regarding keyword co-occurrence and trend topics analysis, mental health, health behaviors, and feasibility were hot topics in mobile-based EMA and EMI research. Future research trends included using EMA for tailoring EMI, just-in-time adaptive interventions (JITAI), and digital phenotyping.

Conclusion

This bibliometric study on mobile-based EMA and EMI is a valuable resource for understanding the field's evolution and future trends. Our analysis indicates that EMA and EMI have great potential in health behaviors and mental health, but implementation should consider feasibility and reactivity issues carefully. Emerging trends include EMA-tailored EMI, JITAI, and digital phenotyping. In the future, strengthening multidisciplinary cooperation will be necessary to promote the continued development of the field.

Personalized Deep Learning for Substance Use in Hawaii: Protocol for a Passive Sensing and Ecological Momentary Assessment Study

BACKGROUND

Artificial intelligence (AI)-powered digital therapies that detect methamphetamine cravings via consumer devices have the potential to reduce health care disparities by providing remote and accessible care solutions to communities with limited care solutions, such as Native Hawaiian, Filipino, and Pacific Islander communities. However, Native Hawaiian, Filipino, and Pacific Islander communities are understudied with respect to digital therapeutics and AI health sensing despite using technology at the same rates as other racial groups.

OBJECTIVE

In this study, we aimed to understand the feasibility of continuous remote digital monitoring and ecological momentary assessments in Native Hawaiian, Filipino, and Pacific Islander communities in Hawaii by curating a novel data set of longitudinal Fitbit (Fitbit Inc) biosignals with the corresponding craving and substance use labels. We also aimed to develop personalized AI models that predict methamphetamine craving events in real time using wearable sensor data.

METHODS

We will develop personalized AI and machine learning models for methamphetamine use and craving prediction in 40 individuals from Native Hawaiian, Filipino, and Pacific Islander communities by curating a novel data set of real-time Fitbit biosensor readings and the corresponding participant annotations (ie, raw self-reported substance use data) of their methamphetamine use and cravings. In the process of collecting this data set, we will gain insights into cultural and other human factors that can challenge the proper acquisition of precise annotations. With the resulting data set, we will use self-supervised learning AI approaches, which are a new family of machine learning methods that allows a neural network to be trained without labels by being optimized to make predictions about the data. The inputs to the proposed AI models are Fitbit biosensor readings, and the outputs are predictions of methamphetamine use or craving. This paradigm is gaining increased attention in AI for health care.

RESULTS

To date, more than 40 individuals have expressed interest in participating in the study, and we have successfully recruited our first 5 participants with minimal logistical challenges and proper compliance. Several logistical challenges that the research team has encountered so far and the related implications are discussed.

CONCLUSIONS

We expect to develop models that significantly outperform traditional supervised methods by finetuning according to the data of a participant. Such methods will enable AI solutions that work with the limited data available from Native Hawaiian, Filipino, and Pacific Islander populations and that are inherently unbiased owing to their personalized nature. Such models can support future AI-powered digital therapeutics for substance abuse.

INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID)

DERR1-10.2196/46493.

Implementing ecological momentary assessments to measure violence and adolescent HIV transmission risk: Lessons from Johannesburg, South Africa

Ecological Momentary Assessment (EMA) is an important methodology to understand risky behaviour and holds promise for HIV research. EMA is still novel in sub-Saharan Africa. We describe challenges and lessons learned on a novel study implementing mobile phone EMAs with adolescent boys in South Africa. The Tsamaisano study was a longitudinal study from 2020-2023 to recruit adolescent boys aged 15-19 years; including those without HIV and those perinatally infected and living with HIV. Participants were prompted to complete 52 weekly mobile phone survey on emotional state, exposure to and perpetration of violence, and sexual risk behaviour. Surveys were delivered using a random algorithm to choose the day. We incorporated mechanisms to assess challenges and optimize survey completion: weekly team meetings with youth representation and real-time data monitoring. Additionally, 20 frequent vs infrequent survey submitters participated in qualitative interviews about barriers and recommendations. Real-time monitoring indicated low (defined as <50%) survey completion in the first months of study implementation. To ensure that both the adolescent participant and their caregiver understood the commitment required for successful EMA, we created and implemented a guided discussion around mobile phone access during the enrolment visit. We identified a need for increased and ongoing technical support; addressed by creating technical guides, implementing a standard two-week check-in call after enrolment, adding an automated request button for call-back assistance, creating a WhatsApp messaging stream, and reaching out to all participants failing to submit two sequential surveys. Entry-level smartphones, including those initially distributed by the study, did not have capacity for certain updates and had to be replaced with more expensive models. Participants struggled with randomly allocated survey days; completion improved with set completion days and targeted reminder messages. Together, these steps improved survey completion from 40% in December 2020 to 65% in April 2022. We describe key lessons learned to inform future study designs with mobile phone EMAs, drawing on our experience implementing such among adolescent boys, including persons living with HIV, in a low-and-middle income setting. The key lessons learned through the Tsamaisano study are important to inform future study designs with EMA utilizing mobile phone, electronic data collection among adolescent boys in low-and-middle-income settings.

Resilience and Disaster: Flexible Adaptation in the Face of Uncertain Threat

Disasters cause sweeping damage, hardship, and loss of life. In this article, we first consider the dominant psychological approach to disasters and its narrow focus on psychopathology (e.g., posttraumatic stress disorder). We then review research on a broader approach that has identified heterogeneous, highly replicable trajectories of outcome, the most common being stable mental health or resilience. We review trajectory research for different types of disasters, including the COVID-19 pandemic. Next, we consider correlates of the resilience trajectory and note their paradoxically limited ability to predict future resilient outcomes. Research using machine learning algorithms improved prediction but has not yet illuminated the mechanism behind resilient adaptation. To that end, we propose a more direct psychological explanation for resilience based on research on the motivational and mechanistic components of regulatory flexibility. Finally, we consider how future research might leverage new computational approaches to better capture regulatory flexibility in real time.

Selecting an Ecological Momentary Assessment Platform: Tutorial for Researchers

BACKGROUND

Although ecological momentary assessment (EMA) has been applied in psychological research for decades, delivery methods have evolved with the proliferation of digital technology. Technological advances have engendered opportunities for enhanced accessibility, convenience, measurement precision, and integration with wearable sensors. Notwithstanding, researchers must navigate novel complexities in EMA research design and implementation.

OBJECTIVE

In this paper, we aimed to provide guidance on platform selection for clinical scientists launching EMA studies.

METHODS

Our team includes diverse specialties in child and adolescent behavioral and mental health with varying expertise on EMA platforms (eg, users and developers). We (2 research sites) evaluated EMA platforms with the goal of identifying the platform or platforms with the best fit for our research. We created a list of extant EMA platforms; conducted a web-based review; considered institutional security, privacy, and data management requirements; met with developers; and evaluated each of the candidate EMA platforms for 1 week.

RESULTS

We selected 2 different EMA platforms, rather than a single platform, for use at our 2 research sites. Our results underscore the importance of platform selection driven by individualized and prioritized laboratory needs; there is no single, ideal platform for EMA researchers. In addition, our project generated 11 considerations for researchers in selecting an EMA platform: (1) location; (2) developer involvement; (3) sample characteristics; (4) onboarding; (5) survey design features; (6) sampling scheme and scheduling; (7) viewing results; (8) dashboards; (9) security, privacy, and data management; (10) pricing and cost structure; and (11) future directions. Furthermore, our project yielded a suggested timeline for the EMA platform selection process.

CONCLUSIONS

This study will guide scientists initiating studies using EMA, an in vivo, real-time research tool with tremendous promise for facilitating advances in psychological assessment and intervention.

Intervening on high-risk responses during ecological momentary assessment of suicidal thoughts: Is there an effect on study data?

Ecological momentary assessment (EMA) is increasingly used to study suicidal thoughts and behaviors (STBs). There is a potential ethical obligation for researchers to intervene when receiving information about suicidal thoughts in real time. A possible concern, however, is that intervening when receiving responses that indicate high risk for suicide during EMA research may impact how participants respond to questions about suicidal thoughts and thus affect the validity and integrity of collected data. We leveraged data from a study of adults and adolescents (N = 434) recruited during a hospital visit for STBs to examine whether monitoring and intervening on high-risk responses affects subsequent participant responding. Overall, we found mixed support for the notion that intervening on high-risk responses influences participants' ratings. Although we observed some evidence of discontinuity in subsequent responses at the threshold used to trigger response-contingent interventions, it was not clear that such discontinuity was caused by the interventions; lower subsequent responses could be due to effective intervention, participant desire to not be contacted again, or regression to the mean. Importantly, the likelihood of completing surveys did not change from before to after response-contingent intervention. Adolescents were significantly more likely than adults, however, to change their initial suicidal intent ratings from above to below the high-risk threshold after viewing automated response-contingent pop-up messages. Studies explicitly designed to assess the potential impact of intervening on high-risk responses in real-time monitoring research are needed, as this will inform effective, scalable strategies for intervening during moments of high suicide risk. (PsycInfo Database Record (c) 2024 APA, all rights reserved).

Mind Your Heart: A Mindful Eating and Diet Education eHealth Program

OBJECTIVE

Examine user perceptions of the Mind Your Heart (MYH) program, a mindful eating and nutrition education program delivered via an eHealth system.

METHODS

Sixteen participants (41.5 ± 13.1 years) completed sample MYH lessons over 3 weeks. We examined changes in mindfulness from the State Mindfulness Scale via text messages sent 3 times per week. We assessed MYH user perceptions in a semistructured interview after 3 weeks. Analyses included Spearman's correlation, repeated measures ANOVA, and thematic analysis.

RESULTS

State Mindfulness Scale scores were significantly improved (F[1,15] = 5.35, P = 0.01) from week 1 (M = 2.28 ± 0.80) to week 3 (M = 2.75 ± 1.04). Four themes emerged: (1) MYH is supportive of health goals, (2) text messages act as an intervention, (3) facilitators or inhibitors of use, and (4) enhancing engagement.

CONCLUSIONS AND IMPLICATIONS

Based on participant feedback, the final version of MYH should include example-based learning to translate abstract concepts like mindful eating into action.

Rapid, reliable mobile assessment of affect-related motor processing

Mobile technologies can be used for behavioral assessments to associate changes in behavior with environmental context and its influence on mental health and disease. Research on real-time motor control with a joystick, analyzed using a computational proportion-derivative (PD) modeling approach, has shown that model parameters can be estimated with high reliability and are related both to self-reported fear and to brain structures important for affective regulation, such as the anterior cingulate cortex. Here we introduce a mobile version of this paradigm, the rapid assessment of motor processing (RAMP) paradigm, and show that it provides robust, reliable, and accessible behavioral measurements relevant to mental health. A smartphone version of a previous joystick sensorimotor task was developed in which participants control a virtual car to a stop sign and stop. A sample of 89 adults performed the task, with 66 completing a second retest session. A PD modeling approach was applied to compute Kp (drive) and Kd (damping) parameters. Both Kp and Kd exhibited high test-retest reliabilities (ICC .81 and .78, respectively). Replicating a previous finding from a different sample with the joystick version of the task, both Kp and Kd were negatively associated with self-reported fear. The RAMP paradigm, a mobile sensorimotor assessment, can be used to assess drive and damping during motor control, which is robustly associated with subjective affect. This paradigm could be useful for examining dynamic contextual modulation of affect-related processing, which could improve assessment of the effects of interventions for psychiatric disorders in a real-world context.

Daily self-weighing compared with an active control causes greater negative affective lability in emerging adult women: A randomized trial

Age-related weight gain prevention may reduce population overweight/obesity. Emerging adulthood is a crucial time to act, as rate of gain accelerates and health habits develop. Evidence supports self-weighing (SW) for preventing weight gain; however, how SW impacts psychological states and behaviors in vulnerable groups is unclear. This study assessed daily SW effects on affective lability, stress, weight-related stress, body satisfaction, and weight-control behaviors. Sixty-nine university females (aged 18-22) were randomized to daily SW or temperature-taking (TT) control. Over 2 weeks, participants completed five daily ecological momentary assessments with their intervention behavior. A graph of their data with a trendline was emailed daily, with no other intervention components. Multilevel mixed models with random effect for day assessed variability in positive/negative affect. Generalized linear mixed models assessed outcomes pre- and post-SW or TT and generalized estimating equations assessed weight-control behaviors. Negative affective lability was significantly greater for SW versus TT. While general stress did not differ between groups, weight-related stress was significantly higher and body satisfaction was significantly lower post-behavior for SW but not TT. Groups did not significantly differ in the number or probability of weight-control behaviors. Caution is advised when recommending self-weighing to prevent weight gain for emerging adults.

Refining an ecological momentary assessment study of binge eating among sexual minority and heterosexual young women: a mixed methods pilot study

Background

Ecological momentary assessment (EMA) is used to capture daily lived experiences, states, and environments. Although EMA is commonly used in behavioral health research, there remains a dearth of literature on how researchers account for design considerations of EMA techniques when designing studies. The goal of this formative mixed methods study was to elicit feedback on EMA study procedures and materials from the target populations for a larger study about binge eating among sexual minority and heterosexual young women, in which data are collected entirely remotely.

Methods

Sexual minority (n=12) and heterosexual (n=9) women ages 18-30 who binge ate took part in a pilot EMA study and exit interview and survey. As part of the consent and orientation process, participants reviewed video and written materials describing the study purpose and procedures. Using a smartphone app, for seven consecutive days they completed a survey each morning, 5 random surveys per day, and self-initiated a survey each time they binge ate. Participants then provided feedback on the study via a 1-hour virtual interview and online survey. Interviews were transcribed and reviewed by two coders to identify themes on the acceptability and feasibility of the EMA procedures with a focus on: (I) the training and study description materials; (II) general smartphone app and survey preferences; and (III) specific EMA survey question content and wording.

Results

The qualitative and quantitative data converged to suggest participants were able to easily download and use the app to complete surveys and report on binge eating events. Participants provided feedback that was incorporated into revisions on general study procedures, the training video content, and EMA question content for binge eating, identity-related stressors, and appearance-related pressures. No systematic themes in the quantitative or qualitative data emerged to suggest questions were perceived differently by sexual minority and heterosexual young women.

Conclusions

These findings provide evidence for the feasibility of conducting a remote EMA study to assess young women's experiences around binge eating. This formative study provides an example of how a mixed methods approach can be used to refine EMA study methods and questions to improve study design.

Risk stratification by sex and menopausal status in the multivariable apnea prediction index

STUDY OBJECTIVES

To determine the sensitivity of the Multivariable Apnea Prediction (MAP) index for obstructive sleep apnea (OSA) in pre- and post-menopausal women with the goal of developing a tailored scoring classification approach.

METHODS

Data from two studies (N = 386); the diabetes sleep treatment trial (N = 236) and EMPOWER (N = 150) were used to assess the sensitivity and specificity of the MAP index by comparing men (n = 129) to women (n = 257), and premenopausal (n = 100) to post-menopausal women (n = 136). We evaluated participants at two cut points, apnea-hypopnea index (AHI) values of ≥ 5 and ≥ 10, using 0.5 as a predicted probability cut point to establish baseline sensitivity and specificity. Contingency tables and receiver operating characteristic (ROC) analysis were conducted to evaluate the accuracy of the MAP index in predicting OSA in men versus women, and in pre-versus post-menopausal women. To select optimal predicted probabilities for classification by sex and menopausal status, Youden's J statistic was generated from ROC coordinates.

RESULTS

The MAP index was more sensitive to women in the AHI ≥ 5 group (76%) compared to AHI ≥ 10 group (30%). Among post-menopausal women with AHI ≥ 5, sensitivity was similar to men (98%), but less than men when AHI ≥ 10 (32%). Suggested probability cut points for women with an AHI ≥ 10 are 0.24 overall; 0.15 for premenopausal, and 0.38 for postmenopausal women.

CONCLUSIONS

Because women's risk for OSA (AHI ≥ 10) was underestimated by the MAP index, we suggest the use of tailored cut points based on sex and menopausal status or assessing for OSA risk with an AHI of ≥ 5.

Traditional surveys versus ecological momentary assessments: Digital citizen science approaches to improve ethical physical activity surveillance among youth

The role of physical activity (PA) in minimizing non-communicable diseases is well established. Measurement bias can be reduced via ecological momentary assessments (EMAs) deployed via citizen-owned smartphones. This study aims to engage citizen scientists to understand how PA reported digitally by retrospective and prospective measures varies within the same cohort. This study used the digital citizen science approach to collaborate with citizen scientists, aged 13-21 years over eight consecutive days via a custom-built app. Citizen scientists were recruited through schools in Regina, Saskatchewan, Canada in 2018 (August 31-December 31). Retrospective PA was assessed through a survey, which was adapted from three validated PA surveys to suit smartphone-based data collection, and prospective PA was assessed through time-triggered EMAs deployed consecutively every day, from day 1 to day 8, including weekdays and weekends. Data analyses included paired t-tests to understand the difference in PA reported retrospectively and prospectively, and linear regressions to assess contextual and demographic factors associated with PA reported retrospectively and prospectively. Findings showed a significant difference between PA reported retrospectively and prospectively (p = 0.001). Ethnicity (visible minorities: β = - 0.911, 95% C.I. = -1.677, -0.146), parental education (university: β = 0.978, 95% C.I. = 0.308, 1.649), and strength training (at least one day: β = 0.932, 95% C.I. = 0.108, 1.755) were associated with PA reported prospectively. In contrast, the number of active friends (at least one friend: β = 0.741, 95% C.I. = 0.026, 1.458) was associated with retrospective PA. Physical inactivity is the fourth leading cause of mortality globally, which requires accurate monitoring to inform population health interventions. In this digital age, where ubiquitous devices provide real-time engagement capabilities, digital citizen science can transform how we measure behaviours using citizen-owned ubiquitous digital tools to support prevention and treatment of non-communicable diseases.

Personalized Machine Learning using Passive Sensing and Ecological Momentary Assessments for Meth Users in Hawaii: A Research Protocol

Background

Artificial intelligence (AI)-powered digital therapies which detect meth cravings delivered on consumer devices have the potential to reduce these disparities by providing remote and accessible care solutions to Native Hawaiians, Filipinos, and Pacific Islanders (NHFPI) communities with limited care solutions. However, NHFPI are fully understudied with respect to digital therapeutics and AI health sensing despite using technology at the same rates as other races.

Objective

We seek to fulfill two research aims: (1) Understand the feasibility of continuous remote digital monitoring and ecological momentary assessments (EMAs) in NHFPI in Hawaii by curating a novel dataset of longitudinal FitBit biosignals with corresponding craving and substance use labels. (2) Develop personalized AI models which predict meth craving events in real time using wearable sensor data.

Methods

We will develop personalized AI/ML (artificial intelligence/machine learning) models for meth use and craving prediction in 40 NHFPI individuals by curating a novel dataset of real-time FitBit biosensor readings and corresponding participant annotations (i.e., raw self-reported substance use data) of their meth use and cravings. In the process of collecting this dataset, we will glean insights about cultural and other human factors which can challenge the proper acquisition of precise annotations. With the resulting dataset, we will employ self-supervised learning (SSL) AI approaches, which are a new family of ML methods that allow a neural network to be trained without labels by being optimized to make predictions about the data itself. The inputs to the proposed AI models are FitBit biosensor readings and the outputs are predictions of meth use or craving. This paradigm is gaining increased attention in AI for healthcare.

Conclusions

We expect to develop models which significantly outperform traditional supervised methods by fine-tuning to an individual subject's data. Such methods will enable AI solutions which work with the limited data available from NHFPI populations and which are inherently unbiased due to their personalized nature. Such models can support future AI-powered digital therapeutics for substance abuse.

Neighborhood Walkability Is Associated with Physical Activity and Prediabetes in a Behavioral Weight Loss Study: a Secondary Analysis

BACKGROUND

Socio-environmental factors may affect uptake and utility of behavioral interventions targeting weight loss and cardiometabolic health. To evaluate the relation of neighborhood walkability to physical activity (PA) and glucose control in a sample of adults with overweight/obesity participating in a weight loss study.

METHODS

Secondary analysis of a 12-month behavioral weight loss intervention (2011-2015) using one-group pretest-posttest design. Neighborhood walkability was assessed via residential Walk Score (0-100) at study entry. Fasting plasma glucose (FPG) via phlebotomy and PA via waist-worn ActiGraph GT3X were assessed at baseline and end of study. Study variables included neighborhood walkability (car-dependent: Walk Score < 50 vs. walkable: Walk Score ≥ 50), prediabetes (FPG 100-125 mg/dL), and recommended PA (moderate to vigorous PA [MVPA] > 22 min/day). Generalized linear model with logit link results were reported as adjusted odds ratios (AOR) with 95% confidence intervals (CI).

RESULTS

The sample (N = 114) was mostly female (88.6%), white (83.3%), college educated (73.7%), and on average 51.4 ± 1.0 years of age. At baseline, persons residing in car-dependent neighborhoods tended to have higher income than those in walkable neighborhoods. Neighborhood walkability interacted with household income at study entry to predict participants' ability to meet the MVPA goal at 12 months (AOR = 13.52, 95% CI: 1.86-119.20). Those from walkable neighborhoods had 67% lower odds of having prediabetes compared to those from car-dependent neighborhoods (AOR = 0.33, 95% CI: 0.10-0.87) at 12 months.

CONCLUSION

Our findings corroborate previous research characterizing the relationship between neighborhood walkability, PA, and prediabetes status. Key drivers of this impact warrant further investigation in a study with a larger, more diverse sample.

Application of machine learning to discover interactions predictive of dietary lapses

The purpose of this study it to build a machine learning model to predict dietary lapses with comparable accuracy, sensitivity, and specificity to previous literature while recovering predictor interactions. The sample for the current study consisted of merged data from two separate studies of individuals with obesity/overweight (total N = 87). Participants completed six ecological momentary assessment surveys per day where they were asked about 16 risk factors of lapse and if they had lapsed from their dietary prescriptions since the previous survey. Alcohol consumption and self-efficacy were the most prevalent in the top 10 stable interactions. Alcohol consumption decreased the protective effect of self-efficacy, motivation, and planning. Higher planning predicted higher risk for lapse only when consuming alcohol. Low motivation, hunger, cravings, and lack of healthy food availability increased the protective effect of self-efficacy. Higher self-efficacy increased risk effect of positive mood and having recently eaten a meal on lapse. For individuals with lower levels of self-efficacy, planning increased the risk of lapse. Alcohol intake and self-efficacy interact with several variables to predict dietary lapses, and these interactions should be targeted in just-in-time adaptive interventions that deliver interventions for lapses.

Compliance with ecological momentary assessment programmes in the elderly: a systematic review and meta-analysis

OBJECTIVE

Ecological momentary assessment (EMA) refers to the repeated sampling of information about an individual's symptoms and behaviours, enabling the capture of ecologically meaningful real-time information in a timely manner. Compliance with EMA is critical in determining the validity of an assessment. However, there is limited evidence related to how the elderly comply with EMA programmes or the factors that are associated with compliance.

DESIGN

Systematic review and meta-analysis.

DATA SOURCES

PubMed, Embase, the Cochrane Library and Web of Science were searched up to 17 July 2022.

ELIGIBILITY CRITERIA

We included observational studies on EMA in the elderly reported in English.

DATA EXTRACTION AND SYNTHESIS

Two investigators independently performed screening and data extraction. Discrepancies were resolved by discussion or a third investigator. A systematic review was carried out to characterise the basic characteristics of the participants and EMA programmes. Random-effects meta-analysis was conducted to assess overall compliance and to explore factors associated with differences in compliance among the elderly.

RESULTS

A total of 20 studies with 2047 participants were included in the systematic review and meta-analysis. Meta-analysis showed that the combined compliance rate was 86.41% (95% CI: 77.38% to 92.20%; I²=96.4%; p<0.001). Subgroup analysis revealed high levels of heterogeneity in terms of the methods used to assess population classification, assessment method and assessment frequency, although these may not be the sources of heterogeneity. Meta-regression analysis showed that population classification and assessment period might have a significant impact on heterogeneity (p<0.05). Egger's test indicated significant publication bias (p<0.001).

CONCLUSIONS

Compliance with EMA programmes is high in the elderly. It is recommended that scholars design reasonable EMA programmes according to the health status of the elderly in the future.

Parameters of EMA Compliance and Self-Reported Reactivity in a Longitudinal Study of Young Adult Cannabis and Tobacco Co-Users

Background

Co-use of cannabis and tobacco has become increasingly popular among young adults. Interactive voice response (IVR) based ecological momentary assessment (EMA) allows for measurement of behavior in or near real-time, but has limitations including non-compliance, missing data, and potential for reactivity (e.g., behavior change) from frequent assessments.

Methods

This study examined tobacco and cannabis use characteristics and factors associated with IVR compliance and self-reported reactivity in 97 young adults who reported cannabis and tobacco co-use at baseline and completed daily IVR surveys of co-use behavior at three random times per day for 28 days.

Results

Overall IVR compliance was 55%, with a modal compliance of 60%. Compliance rates did not differ across morning, midday, and evening surveys, but significantly declined over time. The sample was divided into high frequency responders (>70% calls completed, n=35) and low frequency responders (<70%, calls completed n=62). There were no differences between high and low frequency responders on any baseline demographic, tobacco use (nicotine dependence severity), alcohol, or cannabis use characteristics (past 30-day frequency of use). Participants were receptive to IVR-based EMA monitoring and, 16.5% reported purposely decreasing nicotine/tobacco use due to monitoring, while 19.6% reported purposely decreasing cannabis use, which predicted lower cannabis use post-EMA monitoring.

Conclusions

Real-time assessment of co-use behavior among young adults does not appear to be impacted by specific demographics or substance use severity (nicotine dependence, heavy drinking). Data suggest some predictive utility of IVR-based EMA monitoring on short-term behavior change. More intensive approaches are needed to improve compliance among young adult cannabis and tobacco co-users.

Assessment of Traumatic Stress Symptoms During the Acute Posttrauma Period

A substantial majority of adults in the United States will experience a potentially traumatic event (PTE) in their lifetime. A considerable proportion of those individuals will go on to develop posttraumatic stress disorder (PTSD). Distinguishing between those who will develop PTSD and those who will recover, however, remains as a challenge to the field. Recent work has pointed to the increased potential of identifying individuals at greatest risk for PTSD through repeated assessment during the acute posttrauma period, the 30-day period after the PTE. Obtaining the necessary data during this period, however, has proven to be a challenge. Technological innovations such as personal mobile devices and wearable passive sensors have given the field new tools to capture nuanced in vivo changes indicative of recovery or nonrecovery. Despite their potential, there are numerous points for clinicians and research teams to consider when implementing these technologies into acute posttrauma care. The limitations of this work and considerations for future research in the use of technology during the acute posttrauma period are discussed.

A Randomized Trial of Incentivization to Maximize Retention for Real-Time Symptom and Activity Monitoring Using Ecological Momentary Assessment in Pediatric Concussion

OBJECTIVE

The aims of this study were to determine the incentivization strategy that maximizes patient adherence to report symptoms and activity via ecological momentary assessment (EMA) after pediatric concussion, and assess the feasibility of tracking concussed youth using EMA from the emergency department (ED) setting.

METHODS

This study was a randomized controlled trial of participants ages 13 to 18 years with concussion presenting to an urban, academic pediatric ED within 5 days of injury. Participants were randomized to 1 of 4 incentive arms: 2 dynamic (loss-based and streak) and 2 control flat-rate (monetary and electronic device). Participants reported symptoms 3 times per day and cognitive activity once each evening for 3 weeks. Physical activity (step count) and sleep were monitored using a Fitbit (kept by participants in the device flat-rate arm). The primary outcome was proportion of prompts to which participants responded. Secondary outcomes included differential response rates by demographics, and comparison of outcome determination between EMA and subsequent clinical visits.

RESULTS

Thirty participants were enrolled, with a median age of 15.5 years and 60% female. Median cumulative proportion of prompts responded to was 68.3% (interquartile range, 47.6%-82.5%) in the dynamic arms versus 54.0% (interquartile range. 20.6%-68.3%) in the flat-rate arms, P = 0.065. There were nonsignificant differences in median response by sex (65.9% for female vs 40.0% for male, P = 0.072), race/ethnicity (61.9% for non-Hispanic White vs 43.7% for non-Hispanic Black participants, P = 0.097), and insurance (61.9% for private insurance vs 47.6% for public insurance, P = 0.305). Recovery at 3 weeks was discernible for all but 2 participants (93.3%) using EMA data, compared with only 9 participants (30.0%) ( P < 0.001) from clinical visits.

CONCLUSIONS

Dynamic incentivization showed higher rates of response to tridaily symptom prompts compared with flat-rate incentivization. These data show tracking concussed youth using EMA from the ED is feasible using a dynamic incentivization strategy, with improved ability to discern outcomes compared with prospective monitoring using follow-up clinical visits.

Evaluating Declines in Compliance With Ecological Momentary Assessment in Longitudinal Health Behavior Research: Analyses From a Clinical Trial

BACKGROUND

Ecological momentary assessment (EMA) is increasingly used to evaluate behavioral health processes over extended time periods. The validity of EMA for providing representative, real-world data with high temporal precision is threatened to the extent that EMA compliance drops over time.

OBJECTIVE

This research builds on prior short-term studies by evaluating the time course of EMA compliance over 9 weeks and examines predictors of weekly compliance rates among cigarette-using adults.

METHODS

A total of 257 daily cigarette-using adults participating in a randomized controlled trial for smoking cessation completed daily smartphone EMA assessments, including 1 scheduled morning assessment and 4 random assessments per day. Weekly EMA compliance was calculated and multilevel modeling assessed the rate of change in compliance over the 9-week assessment period. Participant and study characteristics were examined as predictors of overall compliance and changes in compliance rates over time.

RESULTS

Compliance was higher for scheduled morning assessments (86%) than for random assessments (58%) at the beginning of the EMA period (P<.001). EMA compliance declined linearly across weeks, and the rate of decline was greater for morning assessments (2% per week) than for random assessments (1% per week; P<.001). Declines in compliance were stronger for younger participants (P<.001), participants who were employed full-time (P=.03), and participants who subsequently dropped out of the study (P<.001). Overall compliance was higher among White participants compared to Black or African American participants (P=.001).

CONCLUSIONS

This study suggests that EMA compliance declines linearly but modestly across lengthy EMA protocols. In general, these data support the validity of EMA for tracking health behavior and hypothesized treatment mechanisms over the course of several months. Future work should target improving compliance among subgroups of participants and investigate the extent to which rapid declines in EMA compliance might prove useful for triggering interventions to prevent study dropout.

TRIAL REGISTRATION

ClinicalTrials.gov NCT03262662; https://clinicaltrials.gov/ct2/show/NCT03262662.

Feasibility and Acceptability of Using Ecological Momentary Assessment to Evaluate Alcohol Use with American Indian Women

BACKGROUND

Ecological momentary assessments (EMA) are one way to collect timely and accurate alcohol use data, as they involve signaling participants via cell phones to report on daily behaviors in real-time and in a participant's natural environment. EMA has never been used with American Indian populations to evaluate alcohol consumption. The purpose of this project was to determine the feasibility and acceptability of EMA for American Indian women.

METHODS

Eligible participants were American Indian women between the ages of 18 and 44 who were not pregnant and had consumed more than one drink within the past month. All participants received a TracFone and weekly automated messages. Self-reported measures of daily quantity and frequency of alcohol consumption, alcohol type, and context were assessed once per week for four weeks. Baseline measurements also included the Drinking Motives Questionnaire-Revised (DMQ-R) and the Interpersonal Support Evaluation List (ISEL).

RESULTS

Fifteen participants were enrolled in the study. All but one participant completed all data collection time points, and drinking patterns were consistent across the study period. A total of 420 records were completed across 86 drinking days and 334 non-drinking days. Participants reported drinking an average of 5.7 days over the 30-day period and typically consumed 3.99 drinks per drinking occasion. Sixty-six percent of participants met gender-specific cut-points for heavy episodic drinking, with an average of 2.46 binge drinking occasions across the four week study period.

CONCLUSIONS

This proof-of-concept project showed that EMA was both feasible and acceptable for collecting alcohol data from American Indian women. Additional studies are necessary to fully implement EMA with American Indian women to better understand the drinking motives, contexts, patterns, and risk factors in this population.

Time-varying model of engagement with digital self reporting: Evidence from smoking cessation longitudinal studies

Objective

Insufficient engagement is a critical barrier impacting the utility of digital interventions and mobile health assessments. As a result, engagement itself is increasingly becoming a target of studies and interventions. The purpose of this study is to investigate the dynamics of engagement in mobile health data collection by exploring whether, how, and why response to digital self-report prompts change over time in smoking cessation studies.

Method

Data from two ecological momentary assessment (EMA) studies of smoking cessation among diverse smokers attempting to quit (N = 573) with a total of 65,974 digital self-report prompts. We operationalize engagement with self-reporting in term of prompts delivered and prompt response to capture both broad and more granular engagement in self-reporting, respectively. The data were analyzed to describe trends in prompt delivered and prompt response over time. Time-varying effect modeling (TVEM) was employed to investigate the time-varying effects of response to previous prompt and the average response rate on the likelihood of current prompt response.

Results

Although prompt response rates were relatively stable over days in both studies, the proportion of participants with prompts delivered declined steadily over time in one of the studies, indicating that over time, fewer participants charged the device and kept it turned on (necessary to receive at least one prompt per day). Among those who did receive prompts, response rates were relatively stable. In both studies, there is a significant, positive and stable relationship between response to previous prompt and the likelihood of response to current prompt throughout all days of the study. The relationship between the average response rate prior to current prompt and the likelihood of responding to the current prompt was also positive, and increasing with time.

Conclusion

Our study highlights the importance of integrating various indicators to measure engagement in digital self-reporting. Both average response rate and response to previous prompt were highly predictive of response to the next prompt across days in the study. Dynamic patterns of engagement in digital self-reporting can inform the design of new strategies to promote and optimize engagement in digital interventions and mobile health studies.

Discontinuation versus continuation of hypertonic saline or dornase alfa in modulator treated people with cystic fibrosis (SIMPLIFY): results from two parallel, multicentre, open-label, randomised, controlled, non-inferiority trials

BACKGROUND

Reducing treatment burden is a priority for people with cystic fibrosis, whose health has benefited from using new modulators that substantially increase CFTR protein function. The SIMPLIFY study aimed to assess the effects of discontinuing nebulised hypertonic saline or dornase alfa in individuals using the CFTR modulator elexacaftor plus tezacaftor plus ivacaftor (ETI).

METHODS

The SIMPLIFY study included two parallel, multicentre, open-label, randomised, controlled, non-inferiority trials at 80 participating clinics across the USA in the Cystic Fibrosis Therapeutics Development Network. We included individuals with cystic fibrosis aged 12-17 years with percent predicted FEV1 (ppFEV1) of 70% or more, or those aged 18 years or older with ppFEV1 of 60% or more, if they had been taking ETI and either (or both) mucoactive therapies (≥3% hypertonic saline or dornase alfa) for at least 90 days before screening. Participants on both hypertonic saline and dornase alfa were randomly assigned to one of the two trials, and those on a single therapy were assigned to the applicable trial. All participants were then randomly assigned 1:1 to continue or discontinue therapy for 6 weeks using permuted blocks of varying size, stratified by baseline ppFEV1 (week 0; ≥90% or <90%), single or concurrent use of hypertonic saline and dornase alfa, previous SIMPLIFY study participation (yes or no), and age (≥18 or <18 years). For participants randomly assigned to continue their therapy during a given trial, this therapy was instructed to be taken at least once daily according to each participant's pre-existing, clinically prescribed regimen. Hypertonic saline concentration was required to be at least 3%. The primary objective for each trial was to determine whether discontinuing was non-inferior to continuing, measured by the 6-week change in ppFEV1 in the per-protocol population. We established a non-inferiority margin of -3% for the difference between groups in the 6-week change in ppFEV1. Safety outcomes were analysed in the intention-to-treat population. This study is registered with ClinicalTrials.gov, NCT04378153.

FINDINGS

From Aug 25, 2020, to May 25, 2022, a total of 672 unique participants were screened for eligibility for one or both trials, resulting in 847 total random assignments across both trials with 594 unique participants. 370 participants were randomly assigned in the hypertonic saline trial and 477 in the dornase alfa trial. Participants across both trials had an average ppFEV1 of 96·9%. Discontinuing treatment was non-inferior to continuing treatment with respect to the absolute 6-week change in ppFEV1 in both the hypertonic saline trial (-0·19% [95% CI -0·85 to 0·48] in the discontinuation group [n=133] vs 0·14% [-0·51 to 0·78] in the continuation group [n=140]; between-group difference -0·32% [-1·25 to 0·60]) and dornase alfa trial (0·18% [-0·38 to 0·74] in the discontinuation group [n=199] vs -0·16% [-0·73 to 0·41] in the continuation group [n=193]; between-group difference 0·35% [-0·45 to 1·14]), with consistent results in the intention-to-treat populations. In the hypertonic saline trial, 64 (35%) of 184 in the discontinuation group versus 44 (24%) of 186 participants in the continuation group and, in the dornase alfa trial, 89 (37%) of 240 in the discontinuation group versus 55 (23%) of 237 in the continuation group had at least one adverse event.

INTERPRETATION

In individuals with cystic fibrosis on ETI with relatively well preserved pulmonary function, discontinuing daily hypertonic saline or dornase alfa for 6 weeks did not result in clinically meaningful differences in pulmonary function when compared with continuing treatment.