Ecological Momentary Assessment Data Research Articles

Emotional and interpersonal states following dialectical behavioral therapy in adolescent borderline personality disorder: A proof-of-concept ecological momentary assessment outcome study

ABSTRACT Objective: The effects of Dialectical Behavioral Therapy for Adolescents (DBT-A) on emotional and interpersonal instability were explored in adolescents exhibiting Borderline Personality Disorder (BPD) features, using ecological momentary assessment (EMA) to reduce recall bias. Method: N = 28 help-seeking female adolescents were enrolled, meeting ≥ 3 DSM-IV BPD criteria. BPD criteria, non-suicidal self-injury (NSSI), and depressive symptoms were examined pre- and post-DBT-A treatment (mean duration: 42.74 weeks, SD = 7.46). Participants maintained e-diaries pre- and post-treatment, hourly rating momentary affect, attachment to mother and best friend, and self-injury urges. Results: Interview-rated BPD symptoms decreased (χ²(1) = 5.66, p = .017), alongside reduced self-rated depression severity (χ²(1) = 9.61, p = .002). EMA data showed decreased NSSI urges (χ²(1) = 9.05, p = .003) and increased mother attachment (χ²(1) = 6.03, p = .014). However, mean affect, affective instability, mean attachment to the best friend, and attachment instability showed no significant change over time. Conclusion: DBT-A yielded limited evidence for altering momentary affective states and instability in adolescents based on EMA. Nevertheless, significant effects were observed in reducing NSSI urges and enhancing interpersonal dynamics during treatment, as assessed via EMA.

Evidence for mood instability in patients with bipolar disorder: Applying multilevel hidden Markov modeling to intensive longitudinal ecological momentary assessment data.

Bipolar disorder (BD) is a chronic psychiatric condition characterized by large episodic changes in mood and energy. Recently, BD has been proposed to be conceptualized as chronic cyclical mood instability, as opposed to the traditional view of alternating discrete episodes with stable periods in-between. Recognizing this mood instability may improve care and call for high-frequency measures coupled with advanced statistical models. To uncover empirically derived mood states, a multilevel hidden Markov model (HMM) was applied to 4-month ecological momentary assessment data in 20 patients with BD, yielding ∼9,820 assessments in total. Ecological momentary assessment data comprised self-report questionnaires (5 × daily) measuring manic and depressive constructs. Manic and depressive symptoms were also assessed weekly using the Altman Self-Rating Mania Scale and the Quick Inventory for Depressive Symptomatology Self-Report. Alignment between HMM-uncovered momentary mood states and weekly questionnaires was assessed with a multilevel linear model. HMM uncovered four mood states: neutral, elevated, mixed, and lowered, which aligned with weekly symptom scores. On average, patients remained < 25 hr in one state. In almost half of the patients, mood instability was observed. Switching between mood states, three patterns were identified: patients switching predominantly between (a) neutral and lowered states, (b) neutral and elevated states, and (c) mixed, elevated, and lowered states. In all, elevated and lowered mood states were interspersed by mixed states. The results indicate that chronic mood instability is a key feature of BD, even in "relatively" euthymic periods. This should be considered in theoretical and clinical conceptualizations of the disorder. (PsycInfo Database Record (c) 2024 APA, all rights reserved).

Beyond one-size-fits-all suicide prediction: studying idiographic associations of risk factors for suicide in a psychiatric sample using ecological momentary assessment

The Interpersonal Psychological Theory of Suicide (IPTS) states that thwarted belongingness (TB), perceived burdensomeness (PB), and hopelessness are risk factors for suicidal ideation. This ecological momentary assessment (EMA) study aimed to (1) demonstrate that there is substantial between-person variability in the association between IPTS predictors and suicidal ideation, (2) identify clusters of patients for which the predictors differently predict suicidal ideation, and (3) examine whether identified clusters are characterized by specific patient characteristics. EMA data was collected ten times per day for six days in 74 psychiatric inpatients and was analyzed with dynamic structural equation modelling. Idiographic associations were obtained and clustered using k-means clustering. We found substantial between-person variability in associations between IPTS predictors and suicidal ideation. Four distinct clusters were identified and different risk factors were relevant for different clusters. In the largest cluster (n=36), none of the IPTS predictors predicted suicidal ideation. Clusters in which associations between IPTS variables and suicidal ideation were stronger showed higher suicidal ideation, depression, and lower positive affect. These findings suggest that a one-size-fits-all model may not adequately reflect idiosyncratic processes leading to suicidal ideation. A promising avenue might be to use idiographic approaches to personalize prediction and interventions.

A latent variable approach to jointly modeling longitudinal and cumulative event data using a weighted two-stage method.

Ecological momentary assessment (EMA), a data collection method commonly employed in mHealth studies, allows for repeated real-time sampling of individuals' psychological, behavioral, and contextual states. Due to the frequent measurements, data collected using EMA are useful for understanding both the temporal dynamics in individuals' states and how these states relate to adverse health events. Motivated by data from a smoking cessation study, we propose a joint model for analyzing longitudinal EMA data to determine whether certain latent psychological states are associated with repeated cigarette use. Our method consists of a longitudinal submodel-a dynamic factor model-that models changes in the time-varying latent states and a cumulative risk submodel-a Poisson regression model-that connects the latent states with the total number of events. In the motivating data, both the predictors-the underlying psychological states-and the event outcome-the number of cigarettes smoked-are partially unobservable; we account for this incomplete information in our proposed model and estimation method. We take a two-stage approach to estimation that leverages existing software and uses importance sampling-based weights to reduce potential bias. We demonstrate that these weights are effective at reducing bias in the cumulative risk submodel parameters via simulation. We apply our method to a subset of data from a smoking cessation study to assess the association between psychological state and cigarette smoking. The analysis shows that above-average intensities of negative mood are associated with increased cigarette use.

Negative urgency as a state-level process.

Test whether global self-reports of urgency moderated the within-person associations of affect and impulsive behaviors. Negative urgency is a personality trait that is a risk factor for a range of psychopathology. Although it is assumed that global self-reports of urgency measure individual tendencies to act more impulsively in the face of negative emotions, evidence from ecological momentary assessment studies is mixed. In this Registered Report, we used ecological momentary assessment data from a large sample of young adults (n = 496, age 18-22, 5 surveys per day for 40 days). All forms of momentary impulsivity were impaired in moments when people reported more intense negative emotions, but global self-reports of urgency did not explain individual differences in this association. Moreover, averaged affective states, rather than specific dimensions, affective circumplex, or appraisals, best predicted impulsive states. Results suggest that face-valid interpretations of global self-report of urgency are inaccurate, and it may be important to understand how some people come to understand themselves as high on urgency rather than assuming that people's self-reports of their motivations are accurate. Momentary experiences of emotions globally impact multiple weakly to moderately associated impulsive behaviors, and future research should seek to understand both when and for whom these associations are strongest.

Temporal relations between alcohol use, posttraumatic stress disorder, and internalizing symptoms during the COVID-19 pandemic: An ecological momentary assessment investigation.

COVID-19 is a collective stressor associated with both increased mental health symptoms and increased frequency of alcohol use. These increases highlight the need for investigations into the functional relationships between traumatic stress symptoms and alcohol use in the wake of the pandemic. This study sought to use ecological momentary assessment to examine the temporal association of posttraumatic stress disorder (PTSD) with alcohol use during the COVID-19 pandemic. Participants were 21 students (Mage = 21.0; 86% female, 23.9% White) from a large, mid-Atlantic public university. Ecological momentary assessment data on PTSD symptoms, internalizing psychopathology, affect, and alcohol consumption were collected via twice daily surveys for a 14-day period. Increased negative affect predicted an increase in alcohol consumption at the next assessment. Increased alcohol consumption predicted increased subsequent negative affect, anxiety symptoms, and depressive symptoms. Findings did not support a relationship between PTSD symptoms and alcohol consumption in either direction. Results suggest a bidirectional, cyclical relationship between alcohol consumption and internalizing psychopathology broadly, rather than PTSD specifically, during the pandemic. Interventions for alcohol consumption on college campuses may benefit from targeting internalizing symptoms, such as through facilitating the development of adaptive coping strategies. (PsycInfo Database Record (c) 2024 APA, all rights reserved).

Stability and Spread: Transition Metrics that are Robust to Time Interval Misspecification

Intensive longitudinal data collected via ecological momentary assessment (EMA) are often sampled with unequal time spacing between surveys. Given the popularity of EMA data, it is important to understand whether time series methods are robust to such time interval misspecification. The present study demonstrates via simulation that stability and spread—two metrics for quantifying different aspects of transitioning behavior within multivariate binary time series data—are unbiased when applied to data that are collected along an off/on burst sampling schedule, a between-person random sampling schedule, and a within-person random sampling schedule. These results held in randomly generated data with differing numbers of time series variables (k=10 and k=20) and in data simulated based on the proportions of observed data from a prior EMA study. Further, stability and spread demonstrated approximately 95% coverage for all between- and within-person random sampling schedules. However, coverage for stability and spread was poor in the off/on burst sampling schedules (around 67%). We also applied these transition metrics—which measure repetitiveness and diversity of transitions, respectively—to a foundational EMA dataset that was among the first to show that adults regularly use many different emotion regulation strategies throughout their daily life (Heiy &amp; Cheavens, 2014). As hypothesized, we found a stronger positive relation between mood and higher stability/lower spread in emotion regulation among people with fewer depressive symptoms than those with more depressive symptoms. Taken together, stability and spread appear to be appropriate metrics to use with data collected using common unequal time spacing conditions and can be used to uncover theoretically consistent insights in real psychosocial data.

Leveraging Ecological Momentary Assessment Data to Characterize Individual Mobility: Exploratory Pilot Study in Rural Uganda.

The geographical environments within which individuals conduct their daily activities may influence health behaviors, yet little is known about individual-level geographic mobility and specific, linked behaviors in rural low- and middle-income settings. Nested in a 3-month ecological momentary assessment intervention pilot trial, this study aims to leverage mobile health app user GPS data to examine activity space through individual spatial mobility and locations of reported health behaviors in relation to their homes. Pilot trial participants were recruited from the Rakai Community Cohort Study-an ongoing population-based cohort study in rural south-central Uganda. Participants used a smartphone app that logged their GPS coordinates every 1-2 hours for approximately 90 days. They also reported specific health behaviors (alcohol use, cigarette smoking, and having condomless sex with a non-long-term partner) via the app that were both location and time stamped. In this substudy, we characterized participant mobility using 3 measures: average distance (kilometers) traveled per week, number of unique locations visited (deduplicated points within 25 m of one another), and the percentage of GPS points recorded away from home. The latter measure was calculated using home buffer regions of 100 m, 400 m, and 800 m. We also evaluated the number of unique locations visited for each specific health behavior, and whether those locations were within or outside the home buffer regions. Sociodemographic information, mobility measures, and locations of health behaviors were summarized across the sample using descriptive statistics. Of the 46 participants with complete GPS data, 24 (52%) participants were men, 30 (65%) participants were younger than 35 years, and 33 (72%) participants were in the top 2 socioeconomic status quartiles. On median, participants traveled 303 (IQR 152-585) km per week. Over the study period, participants on median recorded 1292 (IQR 963-2137) GPS points-76% (IQR 58%-86%) of which were outside their 400-m home buffer regions. Of the participants reporting drinking alcohol, cigarette smoking, and engaging in condomless sex, respectively, 19 (83%), 8 (89%), and 12 (86%) reported that behavior at least once outside their 400-m home neighborhood and across a median of 3.0 (IQR 1.5-5.5), 3.0 (IQR 1.0-3.0), and 3.5 (IQR 1.0-7.0) unique locations, respectively. Among residents in rural Uganda, an ecological momentary assessment app successfully captured high mobility and health-related behaviors across multiple locations. Our findings suggest that future mobile health interventions in similar settings can benefit from integrating spatial data collection using the GPS technology in mobile phones. Leveraging such individual-level GPS data can inform place-based strategies within these interventions for promoting healthy behavior change.

Be present now, sleep well later: Mindfulness promotes sleep health via emotion regulation.

Despite the popularity of mindfulness in research and interventions, information is missing about how and why mindfulness may benefit employee sleep health. Drawing from emotion regulation theory, we evaluate affective rumination, negative affect, and positive affect as potential mechanisms. We also explore differential effects of trait and state attentional mindfulness on both subjective (e.g., quality and sufficiency) and actigraphy-measured aspects (e.g., duration and wake after sleep onset) of sleep health. Ecological momentary assessment and sleep actigraphy data were collected across two independent samples of health care workers (N1 = 60, N2 = 84). Ecological momentary assessment was also used to collect daily information on state mindfulness, affect, and rumination. Our results support rumination and, to a less consistent extent, negative affect as mediators of the association between mindfulness and sleep health but not positive affect. Trait and state mindfulness demonstrate comparable benefits for employee sleep health, but these benefits largely emerge for subjective sleep dimensions than actigraphy-measured. These findings support emotion regulation as a sound theoretical framework for sleep and mindfulness research and may support more informed workplace mindfulness interventions. (PsycInfo Database Record (c) 2024 APA, all rights reserved).

Supplemental Material for Evidence for Mood Instability in Patients With Bipolar Disorder: Applying Multilevel Hidden Markov Modeling to Intensive Longitudinal Ecological Momentary Assessment Data

Supplemental Material for Evidence for Mood Instability in Patients With Bipolar Disorder: Applying Multilevel Hidden Markov Modeling to Intensive Longitudinal Ecological Momentary Assessment Data

Investigating home-based opioid use among youth with sickle cell disease using ecological momentary assessment.

Opioids are a common and essential treatment for acute sickle cell disease (SCD) pain. However, opioids carry well-known adverse side effects, including potential development of hyperalgesia and nociplastic pain. We characterized opioid use in youth with SCD using ecological momentary assessment (EMA) data, and investigated the relationships between home-based opioid use, pain, and a range of biopsychosocial factors. Eighty-eight youth with SCD (aged 8-17years) completed EMAs assessing home-based opioid use, pain, and related factors. Analyses consisted of descriptive and multilevel logistic regression to predict daily home opioid use. Youth averaged 3.64weeks of EMAs. Approximately 35% of the sample (n=31) took an opioid during the EMA period, and used them on only 24% of reported pain days. Youth who took opioids reported a higher percentage of pain days (t=-2.67, p<.05) and mean pain severity scores (t=-2.30, p<.05) than youth who did not take opioids. Multilevel logistic regression analyses indicated that high daily pain severity (odds ratio [OR]=1.02, p<.01), older age (OR=1.324, p<.01), and low positive affect (OR=0.91, p<.01) were each related to an increased likelihood of opioid use. Youth with SCD take opioids appropriately in response to their pain, based on daily self-report. Beyond daily pain severity, age, and daily variation in positive affect were related to home-based opioid use. This suggests that behavioral interventions that enhance positive affect may promote reduced opioid use among youth with SCD.

Symptoms of a feather flock together? An exploratory secondary dynamic time warp analysis of 11 single case time series of suicidal ideation and related symptoms

Suicidal ideation fluctuates over time, as does its related risk factors. Little is known about the difference or similarities of the temporal patterns. The current exploratory secondary analysis examines which risk symptoms have similar time dynamics using a mathematical algorithm called dynamic time warping (DTW). Ecological momentary assessment data was used of 11 depressed psychiatric outpatients with suicidal ideation who answered three daytime surveys at semi-random sampling points for a period of three to six months. Patients with 45 assessments or more were included. Results revealed significant inter-individual variability in symptom dynamics and clustering, with certain symptoms often clustering due to similar temporal patterns, notably feeling sad, hopelessness, feeling stuck, and worrying.The directed network analyses shed light on the temporal order, highlighting entrapment and worrying as symptoms strongly related to suicide ideation. Still, all patients also showed unique directed networks. While for some patients changes in entrapment directly preceded change in suicide ideation, the reverse temporal ordering was also found. Relatedly, within some patients, perceived burdensomeness played a pivotal role, whereas in others it was unconnected to other symptoms. The study underscores the individualized nature of symptom dynamics and challenges linear models of progression, advocating for personalized treatment strategies.

The temporal order of emotional, cognitive, and behavioral gains in daily life during treatment of depression.

Despite the importance for understanding mechanisms of change, little is known about the order of change in daily life emotions, cognitions, and behaviors during treatment of depression. This study examined the within-person temporal order of emotional, cognitive, and behavioral improvements using ecological momentary assessment data. Thirty-two individuals with diagnosed depression completed ecological momentary assessment questions on emotions (sad mood, happy mood), behaviors (social interaction, number of activities), and cognitive variables (worrying, negative self-thoughts) 5 times a day during a 4-month period in which they underwent psychotherapy for depression. Nonparametric change-point analyses were used to determine the timing of gains (i.e., improvements in the mean of each variable) for each individual. We then established whether the first (i.e., earliest) gains in emotions preceded, followed, or occurred in the same week as cognitive and behavioral gains for each individual. Contrary to our hypotheses, first gains in behaviors did not precede first emotional gains (3 times, 8%) more often than they followed them (26 times, 70%). Cognitive gains often occurred in the same week as first emotional gains (43 times, 58%) and less often preceded (13 times, 18%) or followed emotional gains (18 times, 24%). The first improvements in behaviors did not tend to precede the first improvements in emotions likely because fewer behavioral gains were found. The finding that cognitive variables tend to improve around the same time as sad mood may explain why many studies failed to find that cognitive change predicts later change in depressive symptoms. (PsycInfo Database Record (c) 2024 APA, all rights reserved).

Pleasure and Satisfaction as Predictors of Future Cigarette and E-Cigarette Use: A Novel Two-Stage Modeling Approach.

Subjective experience of e-cigarettes may be an important factor in helping people who use combustible cigarettes switch completely to e-cigarettes to reduce harms from smoking. This paper describes a novel two-stage analysis using pleasure and satisfaction responses from Ecological Momentary Assessments (EMA) of both cigarette and e-cigarette use to predict future cigarette and e-cigarette tobacco use. This observational study included adult users of cigarettes and e-cigarettes who provided 7-days of EMA, capturing cigarette and e-cigarette use, followed by biweekly reports of cigarette and e-cigarette use over one year. Participants were 279 adults who provided both cigarette and e-cigarette responses during the EMA. We employed a two-stage analytic approach in which EMA data were used to predict subsequent levels of cigarette and e-cigarette use. In the first stage, EMA responses of cigarette and e-cigarette events were modeled via a mixed-effects location scale (MELS) model to yield summaries of participants' means and variability on event-related ratings of pleasure and satisfaction. These EMA summaries served as predictors in the second stage analysis of the biweekly post-EMA longitudinal cigarette and e-cigarette use data. EMA pleasure and satisfaction ratings were similar for both products and predicted both longitudinal cigarette and e-cigarette use, even after controlling for baseline cigarette and e-cigarette dependence. Relatively higher levels of satisfaction with e-cigarettes were associated with greater decreases in cigarette use over time. Pleasure and satisfaction are important predictors of subsequent cigarette and e-cigarette use. Experienced subjective pleasure and satisfaction from e-cigarettes relative to cigarettes may be an important factor in helping individuals who smoke to switch completely to e-cigarettes as a harm reduction approach. In order to help sustain complete product switching and reduce dual use or relapse to smoking, e-cigarettes may need to deliver more satisfaction to the user compared to that experienced from cigarettes.

Occurrence and characteristics of suicidal ideation in psychiatrically healthy individuals based on ecological momentary assessment.

Decedents with no known mental disorder comprise 5-40% of suicides, suggesting that suicide ideation (SI) and behavior may occur in the psychiatrically healthy with important implications for suicide risk screening. Healthy Volunteers (HV) and patients with Major Depressive Disorder (MDD) provided 7 days of Ecological Momentary Assessment (EMA) data about SI and stressors. Longitudinal mixed effects logistic regression models compared HV and patient SI and stressors. Mixed effects linear regression models compared HVs' and patients' SI score change from the previous epoch's SI score when each stressor occurred. HVs (n = 42) reported less frequent (p < 0.001) and less intense SI (p < 0.003) than patients (n = 80), yet did endorse SI and/or SI-related items in 44% of EMA epochs, endorsing SI items in 25% of epochs with non-zero SI scores. For 7 of 8 stressors, patients reported stressors more often than HVs (all p < 0.001) responding to them with increased SI (0.0001 < p < 0.0472). HVs were relatively resilient to stressors, reporting SI increases only in response to neglect (p < 0.0147). Although SI and SAs are documented among psychiatrically healthy individuals, scientific attention to these observations has been scant. Real-time SI measurement showed that HVs' SI was less pronounced than MDD patients', but was endorsed, nonetheless. Patients were more likely to report stressors than HVs, perhaps due to greater sensitivity to the environment, and reported SI in response to stressors, which was less common in HVs. Both MDD patients and HVs most often manifested passive SI (viz, "decreased wish to live"). However, passive SI (viz, "desire for death"), may predict suicide, even absent SI per se (thinking about killing yourself). This study validates the utility of real-time SI assessment, showing that HVs endorse SI items in 11% of epochs, which implies that suicide risk screening focused on those with mental disorders may be too narrow an approach.

Person-specific dynamics between negative emotions and suicidal thoughts

IntroductionRecent technology has enabled researchers to collect ecological momentary assessments (EMA) to examine within-person correlates of suicidal thoughts. Prior studies examined generalized temporal dynamics of emotions and suicidal thinking over brief periods, but it is not yet known how variable these processes are across people. MethodWe use data EMA data delivered over two weeks with youth/young adults (N = 60) who reported past year self-injurious thoughts/behaviors. We used group iterative multiple model estimation (GIMME) to model group- and person-specific associations of negative emotions (i.e., fear, sadness, shame, guilt, and anger) and suicidal thoughts. Results29 participants (48.33%) reported at least one instance of a suicidal thought and were included in GIMME models. In group level models, we consistently observed autoregressive effects for suicidal thoughts (e.g., earlier thoughts predicting later thoughts), although the magnitude and direction of this link varied from person-to-person. Among emotions, sadness was most frequently associated with contemporaneous suicidal thoughts, but this was evident for less than half of the sample, while other emotional correlates of suicidal thoughts broadly differed across people. No emotion variable was linked to future suicidal thoughts in >14% of the sample, ConclusionsEmotion-based correlates of suicidal thoughts are heterogeneous across people. Better understanding of the individual-level pathways maintaining suicidal thoughts/behaviors may lead to more effective, personalized interventions.

‘I crave not to feel uncomfortable’ – investigating craving for opioids and cannabis among individuals with chronic pain

Background The assessment of drug craving is common in survey studies, including those using real-time data collection methods, such as Ecological Momentary Assessment (EMA). However, few studies investigate how participants with chronic pain interpret the word ‘craving’ and how interpretations impact survey responses. Methods We conducted a mixed-methods study among 12 individuals with chronic pain who were using prescription opioids and cannabis. Participants completed baseline surveys, cognitive interviews, and 14-day smartphone-based EMA data collection. Analyses included deductive and inductive coding of interviews and t-tests of EMA self-reports of opioid and cannabis craving. Results Four participants had negative reactions to the word ‘craving’, including mentions that these questions offended them. The remaining eight participants mentioned no negative connotation. EMA data showed that participants without negative reactions reported a greater range (opioids), higher standard deviation (opioids), and higher maximum (opioids, cannabis) on Likert-type EMA craving items, compared to those with a negative reaction. Conclusions Some individuals with chronic pain may have a negative reaction to the word ‘craving’ related to opioid and cannabis use and this reaction may impact survey responses. Alternative wording of survey items is recommended, for example focused on ‘wanting’ or ‘needing’.

Preoperative Mobile Health Data Improve Predictions of Recovery From Lumbar Spine Surgery.

Neurosurgeons and hospitals devote tremendous resources to improving recovery from lumbar spine surgery. Current efforts to predict surgical recovery rely on one-time patient report and health record information. However, longitudinal mobile health (mHealth) assessments integrating symptom dynamics from ecological momentary assessment (EMA) and wearable biometric data may capture important influences on recovery. Our objective was to evaluate whether a preoperative mHealth assessment integrating EMA with Fitbit monitoring improved predictions of spine surgery recovery. Patients age 21-85 years undergoing lumbar surgery for degenerative disease between 2021 and 2023 were recruited. For up to 3 weeks preoperatively, participants completed EMAs up to 5 times daily asking about momentary pain, disability, depression, and catastrophizing. At the same time, they were passively monitored using Fitbit trackers. Study outcomes were good/excellent recovery on the Quality of Recovery-15 (QOR-15) and a clinically important change in Patient-Reported Outcomes Measurement Information System Pain Interference 1 month postoperatively. After feature engineering, several machine learning prediction models were tested. Prediction performance was measured using the c-statistic. A total of 133 participants were included, with a median (IQR) age of 62 (53, 68) years, and 56% were female. The median (IQR) number of preoperative EMAs completed was 78 (61, 95), and the median (IQR) number of days with usable Fitbit data was 17 (12, 21). 63 patients (48%) achieved a clinically meaningful improvement in Patient-Reported Outcomes Measurement Information System pain interference. Compared with traditional evaluations alone, mHealth evaluations led to a 34% improvement in predictions for pain interference (c = 0.82 vs c = 0.61). 49 patients (40%) had a good or excellent recovery based on the QOR-15. Including preoperative mHealth data led to a 30% improvement in predictions of QOR-15 (c = 0.70 vs c = 0.54). Multimodal mHealth evaluations improve predictions of lumbar surgery outcomes. These methods may be useful for informing patient selection and perioperative recovery strategies.

Development and Initial Validation of a Momentary Cannabis Craving Scale Within a Homogeneous Sample of U.S. Emerging Adults.

Given the popularity and ease of single-item craving assessments, we developed a multi-item measure and compared it to common single-item assessments in an ecological momentary assessment (EMA) context. Two weeks of EMA data were collected from 48 emerging adults (56.25% female, 85.42% White) who frequently used cannabis. Eight craving items were administered, and multilevel factor analyses were used to identify the best fitting model. The resulting scale's factors represented purposefulness/general desire and emotionality/negative affect craving. Convergent validity was examined using measures of craving, cannabis use disorder symptoms, frequency of use, cannabis cue reactivity, cannabis use, negative affect, and impulsivity. The scale factors were associated with cue-reactivity craving, negative affect, impulsivity, and subfactors of existing craving measures. For researchers interested in using a single item to capture craving, one item performed particularly well. However, the new scale may provide a more nuanced assessment of mechanisms underlying craving.

Daily vitality fluctuations in older adults with depressive symptoms: A multilevel location-scale model

BackgroundExamining the daily experiences of older adults with depression facilitates the development and application of personalized effective treatments for them. In previous clinical research on depression, traditional mean-based approaches have mainly been employed. However, the within-person residual variance as a random effect provides greater insight into the heterogeneity of daily experiences among geriatric samples. ObjectiveThis study aimed to examine the relationship between depression and daily vitality in older adults. Specifically, it focused on the mean and residual variance of daily vitality measured by the Ecological Momentary Assessment (EMA). MethodsData from 64 older adults aged 65 years or more, who participated in community welfare centers or retirees’ associations, were used. Daily vitality was examined using EMA surveys for seven consecutive days (four random surveys per day). The data were analyzed using a location-scale model. ResultsThe intraclass correlation computed from the empty model for the EMA data was 0.488, indicating significant variances in daily vitality across time between individuals. Older adults with higher levels of depressive symptoms showed low mean levels of daily vitality and a large log-residual variance of daily vitality. ConclusionsThe findings from the current study suggest that individuals experiencing depression not only exhibit low vitality in their daily lives but also struggle to maintain stable levels of vitality in their lives. These insights could contribute to the facilitation and advancement of personalized interventions tailored for older adults.