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Introduction: Ecological momentary assessment (EMA) is a methodological approach to studying intraindividual variation over time. This study aimed to use EMA to determine the variability of cognition in individuals with chronic stroke, identify the latent classes of cognitive variability, and examine any differences in daily activities, social functioning, and neuropsychological performance between these latent classes., Methods: Participants ( N  = 202) with mild-to-moderate stroke and over 3-month post-stroke completed a study protocol, including smartphone-based EMA and two lab visits. Participants responded to five EMA surveys daily for 14 days to assess cognition. They completed patient-reported measures and neuropsychological assessments during lab visits. Using latent class analysis, we derived four indicators to quantify cognitive variability and identified latent classes among participants. We used ANOVA and Chi-square to test differences between these latent classes in daily activities, social functioning, and neuropsychological performance., Results: The latent class analysis converged on a three-class model. The moderate and high variability classes demonstrated significantly greater problems in daily activities and social functioning than the low class. They had significantly higher proportions of participants with problems in daily activities and social functioning than the low class. Neuropsychological performance was not statistically different between the three classes, although a trend approaching statistically significant difference was observed in working memory and executive function domains., Discussion: EMA could capture intraindividual cognitive variability in stroke survivors. It offers a new approach to understanding the impact and mechanism of post-stroke cognitive problems in daily life and identifying individuals benefiting from self-regulation interventions.

Objective: To assess contemporaneous and temporal dynamics of perceived social isolation (PSI), secondary conditions, and daily activity patterns in individuals post-stroke., Design: Longitudinal observational study using ecological momentary assessment (EMA) as a real-time assessment of an individual's lived experiences. We conducted dynamic network analyses to examine longitudinal associations among EMA variables., Settings: Home and Community., Participants: 202 individuals with mild-to-moderate chronic stroke (median age=60 years; 45% women; 44% black; 90% ischemic stroke; median NIHSS score=2; N=202)., Intervention: Not applicable., Main Outcome Measures: EMA questions measured PSI, secondary conditions (pain, tiredness, stress, anxiety, worthlessness, difficulty concentrating, and cheerfulness), and daily activity patterns (being at home, being alone, and participating in productive activities)., Results: The median EMA response rate was 84%. The contemporaneous model showed that PSI was associated with being home, alone, and all symptoms except pain. The temporal model revealed a pathway indicating that feelings of worthlessness predicted PSI (regression coefficient=0.06, P=.019), followed by stress (regression coefficient=0.06, P=.024), and then by being not at home (regression coefficient=-0.04, P=.013)., Conclusion: Implementing dynamic network analyses on EMA data can uncover dynamic connections among PSI, secondary conditions, and daily activity patterns after stroke. This study found a significant temporal association between PSI and negative emotions. Feeling isolated was followed by feeling stressed, which was followed by a tendency to be out of home, indicating adaptive behaviors in individuals with stroke. These findings highlight the importance of engaging in out-of-home or outdoor activities to mitigate PSI and negative emotions., (Copyright © 2024 American Congress of Rehabilitation Medicine. Published by Elsevier Inc. All rights reserved.)

Introduction: The impact of depressed mood in daily life is difficult to investigate using traditional retrospective assessments, given daily or even within-day mood fluctuations in various contexts. This study aimed to use a smartphone-based ambulatory assessment to examine real-time relationships between depressed mood and functional behaviors among individuals with stroke., Methods: A total of 202 participants with mild-to-moderate stroke (90% ischemic, 45% female, 44% Black) completed an ecological momentary assessment five times per day for 2 weeks by reporting their depressed mood and functional behaviors regarding where, with whom, and what activity was spent., Results: Participants spent 28% of their wake-up time participating in passive leisure activities but spent the least time in physical (4%) and vocational (9%) activities. Depressed mood was concurrently lower when participants engaged in social activities (β = -0.023 ± 0.011) and instrumental activities of daily living (β = -0.061 ± 0.013); spent time with family members (β = -0.061 ± 0.014), spouses (β = -0.043, ± 0.016), friends (β = -0.094, ± 0.021), and coworkers (β = -0.050 ± 0.021); and were located in restaurants (β = -0.068 ± 0.029), and homes of family members (β = -0.039 ± 0.020) or friends (β = -0.069 ± 0.031). Greater depressed mood was associated with worse ratings in satisfaction, performance, and engagement of activities in concurrent (βs = -0.036 ± 0.003, -0.053 ± 0.003, -0.044 ± 0.003) and time-lagged models (βs = -0.011 ± 0.004, -0.012 ± 0.004, -0.013 ± 0.004)., Discussion: Smartphone-based ambulatory assessment can elucidate functional behaviors and associated mood after stroke. Findings support behavioral activation treatments to schedule social and instrumental activities for stroke survivors to reduce their depressed mood., Competing Interests: Declaration of conflicting interestsThe author(s) declared the following potential conflicts of interest with respect to the research, authorship, and/or publication of this article: Dr Lenze reported research support from the National Institutes of Health (NIH), Patient-Centered Outcomes Research Institute, and Mercatus Center Emergent Ventures outside the submitted work. He also received grant support (loaned equipment for research) from MagStim. He has served as a consultant for Prodeo, Janssen Pharmaceuticals, and Boehringer Ingelheim. Dr Lee reported research support from the NIH, Barnes-Jewish Foundation, Biogen and consulting fees from Regenera outside the submitted work. Dr Mohr reported research support from the NIH, personal fees from Apple and other support from Actualize Therapy and Otsuka Pharmaceuticals. Dr Mohr has an ownership interest in Adaptive Health and had a patent to US Patent 15/654,245, 2018 pending. Dr Metts has an ownership interest in Infinite Arms. Dr Wong reported research support from the NIH, National Institute on Disability, Independence, and Rehabilitation Research, American Occupational Therapy Foundation, and Craig H. Neilsen Foundation. No other disclosures were reported.

Objective: To examine the relationships between post-stroke depression and cognition using network analysis. In particular, we identified central depressive symptoms, central cognitive performances, and bridge components that connect these 2 constructs., Design: An observational study. We applied network analysis to analyze baseline data to visualize and quantify the relationships between depression and cognition., Setting: Home and Community., Participants: 202 participants with mild-to-moderate stroke (N=202; mean age: 59.7 years; 55% men; 55% Whites; 90% ischemic stroke)., Intervention: Not applicable., Main Outcome Measures: Patient Health Questionnaire (PHQ-8) for depressive symptoms and the NIH Toolbox Cognitive Battery for cognitive performances., Results: Depressive symptoms were positively intercorrelated with the network, with symptoms from similar domains clustered together. Mood (expected influence=1.58), concentration (expected influence=0.67), and guilt (expected influence=0.63) were the top 3 central depressive symptoms. Cognitive performances also showed similar network patterns, with executive function (expected influence=0.89), expressive language (expected influence=0.68), and processing speed (expected influence=0.48) identified as the top 3 central cognitive performances. Psychomotor functioning (bridge expected influence=2.49) and attention (bridge expected influence=1.10) were the components connecting depression and cognition., Conclusions: The central and bridge components identified in this study might serve as targets for interventions against these deficits. Future trials are needed to compare the effectiveness of interventions targeting the central and bridge components vs general interventions treating depression and cognitive impairment as a homogenous clinical syndrome., (Copyright © 2023 American Congress of Rehabilitation Medicine. Published by Elsevier Inc. All rights reserved.)

Background: Digital interventions provided through smartphones or the internet that are guided by a coach have been proposed as promising solutions to support the self-management of chronic conditions. However, digital intervention for poststroke self-management is limited; we developed the interactive Self-Management Augmented by Rehabilitation Technologies (iSMART) intervention to address this gap., Objective: This study aimed to examine the feasibility and initial effects of the iSMART intervention to improve self-management self-efficacy in people with stroke., Methods: A parallel, 2-arm, nonblinded, randomized controlled trial of 12-week duration was conducted. A total of 24 participants with mild-to-moderate chronic stroke were randomized to receive either the iSMART intervention or a manual of stroke rehabilitation (attention control). iSMART was a coach-guided, technology-supported self-management intervention designed to support people managing chronic conditions and maintaining active participation in daily life after stroke. Feasibility measures included retention and engagement rates in the iSMART group. For both the iSMART intervention and active control groups, we used the Feasibility of Intervention Measure, Acceptability of Intervention Measure, and Intervention Appropriateness Measure to assess the feasibility, acceptability, and appropriateness, respectively. Health measures included the Participation Strategies Self-Efficacy Scale and the Patient-Reported Outcomes Measurement Information System's Self-Efficacy for Managing Chronic Conditions., Results: The retention rate was 82% (9/11), and the engagement (SMS text message response) rate was 78% for the iSMART group. Mean scores of the Feasibility of Intervention Measure, Acceptability of Intervention Measure, and Intervention Appropriateness Measure were 4.11 (SD 0.61), 4.44 (SD 0.73), and 4.36 (SD 0.70), respectively, which exceeded our benchmark (4 out of 5), suggesting high feasibility, acceptability, and appropriateness of iSMART. The iSMART group showed moderate-to-large effects in improving self-efficacy in managing emotions (r=0.494), symptoms (r=0.514), daily activities (r=0.593), and treatments and medications (r=0.870), but the control group showed negligible-to-small effects in decreasing self-efficacy in managing emotions (r=0.252), symptoms (r=0.262), daily activities (r=0.136), and treatments and medications (r=0.049). In addition, the iSMART group showed moderate-to-large effects of increasing the use of participation strategies for management in the home (r=0.554), work (r=0.633), community (r=0.673), and communication activities (r=0.476). In contrast, the control group showed small-to-large effects of decreasing the use of participation strategies for management in the home (r=0.567), work (r=0.342, community (r=0.215), and communication activities (r=0.379)., Conclusions: Our findings support the idea that iSMART was feasible to improve poststroke self-management self-efficacy. Our results also support using a low-cost solution, such as SMS text messaging, to supplement traditional therapeutic patient education interventions. Further evaluation with a larger sample of participants is still needed., Trial Registration: ClinicalTrials.gov 202004137; https://clinicaltrials.gov/study/NCT04743037?id=202004137&rank=1., (©Zhaoying Li, Yating Lei, Quoc Bui, Olivia DePaul, Ginger E Nicol, David C Mohr, Sunghoon I Lee, Mandy W M Fong, Christopher L Metts, Stephanie E Tomazin, Alex W K Wong. Originally published in JMIR Rehabilitation and Assistive Technology (https://rehab.jmir.org), 19.02.2024.)

Background: Digital therapeutics, such as interventions provided via smartphones or the internet, have been proposed as promising solutions to support self-management in persons with chronic conditions. However, the evidence supporting self-management interventions through technology in stroke is scarce, and the intervention development processes are often not well described, creating challenges in explaining why and how the intervention would work., Objective: This study describes a specific use case of using intervention mapping (IM) and the taxonomy of behavior change techniques (BCTs) in designing a digital intervention to manage chronic symptoms and support daily life participation in people after stroke. IM is an implementation science framework used to bridge the gap between theories and practice to ensure that the intervention can be implemented in real-world settings. The taxonomy of BCTs consists of a set of active ingredients designed to change self-management behaviors., Methods: We used the first 4 steps of the IM process to develop a technology-supported self-management intervention, interactive Self-Management Augmented by Rehabilitation Technologies (iSMART), adapted from a face-to-face stroke-focused psychoeducation program. Planning group members were involved in adapting the intervention. They also completed 3 implementation measures to assess the acceptability, appropriateness, and feasibility of iSMART., Results: In step 1, we completed a needs assessment consisting of assembling a planning group to codevelop the intervention, conducting telephone surveys of people after stroke (n=125) to identify service needs, and performing a systematic review of randomized controlled trials to examine evidence of the effectiveness of digital self-management interventions to improve patient outcomes. We identified activity scheduling, symptom management, stroke prevention, access to care resources, and cognitive enhancement training as key service needs after a stroke. The review suggested that digital self-management interventions, especially those using cognitive behavioral theory, effectively reduce depression, anxiety, and fatigue and enhance self-efficacy in neurological disorders. Step 2 identified key determinants, objectives, and strategies for self-management in iSMART, including knowledge, behavioral regulation, skills, self-efficacy, motivation, negative and positive affect, and social and environmental support. In step 3, we generated the intervention components underpinned by appropriate BCTs. In step 4, we developed iSMART with the planning group members. Especially, iSMART simplified the original psychoeducation program and added 2 new components: SMS text messaging and behavioral coaching, intending to increase the uptake by people after stroke. iSMART was found to be acceptable (mean score 4.63, SD 0.38 out of 5), appropriate (mean score 4.63, SD 0.38 out of 5), and feasible (mean score 4.58, SD 0.34 out of 5)., Conclusions: We describe a detailed example of using IM and the taxonomy of BCTs for designing and developing a digital intervention to support people after stroke in managing chronic symptoms and maintaining active participation in daily life., (©Alex W K Wong, Mandy W M Fong, Elizabeth G S Munsell, Christopher L Metts, Sunghoon I Lee, Ginger E Nicol, Olivia DePaul, Stephanie E Tomazin, Katherine J Kaufman, David C Mohr. Originally published in JMIR Human Factors (https://humanfactors.jmir.org), 24.07.2023.)

The co-occurrence of posttraumatic stress disorder (PTSD) and alcohol use disorder (AUD) is common following sexual assault and associated with more severe symptomology and increased likelihood of sexual revictimization. Integrated interventions aimed at reducing PTSD and AUD symptoms following recent sexual assault are needed and should address barriers to care and early treatment termination. The proposed study will test a novel, brief (5 to 7 sessions) intervention that integrates Written Exposure Therapy for PTSD and Cognitive Behavioral Therapy for AUD, and is initiated within the first six weeks post-assault. In Phase 1, qualitative analysis of content gathered during focus groups with treatment providers will be conducted to inform intervention development. In Phase 2, a proof-of-concept pilot study (n = 10) of the intervention, Substance Use Skills Training and Exposure Post-Sexual Assault (STEPS), will be conducted. In Phase 3, a pilot randomized controlled trial (RCT) among 54 recent sexual assault survivors will be implemented using the updated manualized STEPS intervention to evaluate feasibility and preliminary efficacy in reducing PTSD and AUD symptoms. Ecological momentary assessments will be used to assess daily alcohol use, craving, affect, intrusions and avoidance. The effects of STEPS on commonly associated symptoms (e.g., depression, substance use) will be examined. The proposed study has the potential to make a significant public health impact by advancing knowledge on the link between sexual assault and co-occurring PTSD and AUD and informing early intervention efforts for this high-risk population., Competing Interests: Declaration of Competing Interest The authors declare the following financial interests/personal relationships which may be considered as potential competing interests: Dr. Brian Marx receives royalties from the American Psychological Association for publishing the Written Exposure Therapy manual., (Copyright © 2022 Elsevier Inc. All rights reserved.)

Objective: The integration of an artificial intelligence tool into pathologists' workflow may lead to a more accurate and timely diagnosis of melanocytic lesions, directly patient care. The objective of this study was to create and evaluate the performance of such a model in achieving clinical-grade diagnoses of Spitz nevi, dermal and junctional melanocytic nevi, and melanomas., Methods: We created a beginner-level training environment by teaching our algorithm to perform cytologic inferences on 136,216 manually annotated tiles of hematoxylin and eosin-stained slides consisting of unequivocal melanocytic nevi, Spitz nevi, and invasive melanoma cases. We sequentially trained and tested our network to provide a final diagnosis-classification on 39 cases in total. Positive predictive value (precision) and sensitivity (recall) were used to measure our performance., Results: The tile-classification algorithm predicted the 136,216 irrelevant, melanoma, melanocytic nevi, and Spitz nevi tiles at sensitivities of 96%, 93%, 94% and 73%, respectively. The final trained model was able to correctly classify and predict the correct diagnosis in 85.7% of unseen cases (n = 28), reporting at or near screening-level performances for precision and recall of melanoma (76.2%, 100.0%), melanocytic nevi (100.0%, 75.0%), and Spitz nevi (100.0%, 75.0%)., Conclusions: Our pilot study proves that convolutional networks trained on cellular morphology to classify melanocytic proliferations can be used as a powerful tool to assist pathologists in screening for melanoma versus other benign lesions., Competing Interests: The authors declare no conflicts of interest., (Copyright © 2022 Wolters Kluwer Health, Inc. All rights reserved.)

Objective: To validate and characterize real-world functional behaviors in individuals after stroke., Design: Longitudinal observational study using ecological momentary assessment (EMA) as a real-time assessment of functional behaviors in natural contexts. Wilcoxon rank-sum tests, Fisher exact tests, and Spearman correlations were used to analyze data., Setting: Community., Participants: Individuals with mild to moderate stroke (N=212)., Interventions: Not applicable., Main Outcome Measures: Individuals were assessed 5 times daily for 14 days with EMA surveys to determine what, with whom, and where individuals were doing activities and appraise mental, somatic, and cognitive symptoms. Individuals also completed standardized assessments during laboratory visits, including Lawton Instrumental Activities of Daily Living Scale, Activity Card Sort, Patient-Reported Outcome Measurement Information System, and Quality of Life in Neurological Disorders., Results: Most individuals (median age, 60 years; 55% male) were ischemic stroke (90%) and had mild stroke severity (median National Institutes of Health Stroke Scale, 2). A total of 14,140 EMA surveys were analyzed. Individuals were home 78% of the time; primarily participated in passive, unproductive activities (27%), especially watching television and resting; and participated least in physical activities (4%). EMA was sensitive to indicators of poststroke disability; unemployed individuals reported fewer vocational activities but more activities of daily living (ADL) and passive activities than employed counterparts. Users of mobility devices and individuals with cognitive problems spent significantly less time on vocational activities and more on ADL than nonusers and those without cognitive problems. Our data supported the validity of EMA methods in stroke, with small to moderate correlations of EMA with in-laboratory measures of daily functioning (r=-0.30 to 0.35, P<.05) and very large correlations between EMA and in-laboratory measures of symptoms, especially those measuring same constructs (r=-0.64 to 0.79, P<.0001)., Conclusions: Our findings reveal that EMA tracked poststroke functioning precisely. EMA may be beneficial in examining poststroke functional recovery, in monitoring patients for home-based interventions, and for longitudinal research., (Copyright © 2022 American Congress of Rehabilitation Medicine. Published by Elsevier Inc. All rights reserved.)

Background: Falls are a common problem among older adults that lead to injury, emergency department (ED) visits, and institutionalization. The Apple Watch can detect falls and alert caregivers and clinicians that help is needed; the device could also be used to objectively collect data on gait, fitness, and falls as part of clinical trials. However, little is known about the ease of use of this technology among older adult ED patients, a population at high risk of recurrent falls., Objective: The goal of this study-the Geriatric Acute and Post-Acute Fall Prevention Intervention (GAPcare) II-is to examine the feasibility, acceptability, and usability of the Apple Watch Series 4 paired with the iPhone and our research app Rhode Island FitTest (RIFitTest) among older adult ED patients seeking care for falls., Methods: We will conduct field-testing with older adult ED patients (n=25) who sustained a fall and their caregivers (n=5) to determine whether they can use the Apple Watch, iPhone, and app either (1) continuously or (2) periodically, with or without telephone assistance from the research staff, to assess gait, fitness, and/or falls over time. During the initial encounter, participants will receive training in the Apple Watch, iPhone, and our research app. They will receive an illustrated training manual and a number to call if they have questions about the research protocol or device usage. Participants will complete surveys and cognitive and motor assessments on the app during the study period. At the conclusion of the study, we will solicit participant feedback through semistructured interviews. Qualitative data will be summarized using framework matrix analyses. Sensor and survey response data will be analyzed using descriptive statistics., Results: Recruitment began in December 2019 and was on pause from April 2020 until September 2020 due to the COVID-19 pandemic. Study recruitment will continue until 30 participants are enrolled. This study has been approved by the Rhode Island Hospital Institutional Review Board (approval 1400781-16)., Conclusions: GAPcare II will provide insights into the feasibility, acceptability, and usability of the Apple Watch, iPhone, and the RIFitTest app in the population most likely to benefit from the technology: older adults at high risk of recurrent falls. In the future, wearables could be used as part of fall prevention interventions to prevent injury before it occurs., Trial Registration: ClinicalTrials.gov NCT04304495; https://clinicaltrials.gov/ct2/show/NCT04304495., International Registered Report Identifier (irrid): DERR1-10.2196/24455., (©Daniel H Strauss, Natalie M Davoodi, Margaret Healy, Christopher L Metts, Roland C Merchant, Swechya Banskota, Elizabeth M Goldberg. Originally published in JMIR Research Protocols (http://www.researchprotocols.org), 01.04.2021.)

Objectives: To examine real-time relationships between social interactions and poststroke mood and somatic symptoms in participants' daily environments., Design: Prospective observational study using smartphone-based ecological momentary assessment (EMA) surveys 5 times a day for 2 weeks. Multilevel models were used to analyze data for concurrent and lagged associations., Setting: Community., Participants: Adults (N=48) with mild stroke., Interventions: Not applicable., Main Outcome Measures: EMA measures of self-appraisal of social interactions (confidence, satisfaction, and success), as well as mood (depression and anxiety) and somatic (pain and fatigue) symptoms., Results: In concurrent associations, increased depressed mood was associated with reduced ratings of all aspects of social interactions. Fatigue was associated with reduced ratings of social satisfaction and success. In lagged associations, increased anxious mood preceded increased subsequent social confidence. Higher average social satisfaction, confidence, and success were related to lower momentary fatigue, anxious mood, and depressed mood at the next time point. Regarding clinicodemographic factors, being employed was concurrently related to increased social interactions. An increased number of comorbidities predicted higher somatic, but not mood, symptoms at the next time point., Conclusions: This study provides preliminary evidence of dynamic relationships between social interactions and somatic and mood symptoms in individuals with mild stroke. Interventions to not only address the sequelae of symptoms, but also to promote participation in social activities in poststroke life should be explored., (Copyright © 2020 American Congress of Rehabilitation Medicine. Published by Elsevier Inc. All rights reserved.)

The ability to analyze human specimens is the pillar of modern-day translational research. To enhance the research availability of relevant clinical specimens, we developed the Living BioBank (LBB) solution, which allows for just-in-time capture and delivery of phenotyped surplus laboratory medicine specimens. The LBB is a system-of-systems integrating research feasibility databases in i2b2, a real-time clinical data warehouse, and an informatics system for institutional research services management (SPARC). LBB delivers deidentified clinical data and laboratory specimens. We further present an extension to our solution, the Living µBiome Bank, that allows the user to request and receive phenotyped specimen microbiome data. We discuss the details of the implementation of the LBB system and the necessary regulatory oversight for this solution. The conducted institutional focus group of translational investigators indicates an overall positive sentiment towards potential scientific results generated with the use of LBB. Reference implementation of LBB is available at https://LivingBioBank.musc.edu., (© The Author(s) 2020. Published by Oxford University Press on behalf of the American Medical Informatics Association.)

Background: Mobile health apps are promising vehicles for delivering scalable health behavior change interventions to populations that are otherwise difficult to reach and engage, such as young adults with psychiatric conditions. To improve uptake and sustain consumer engagement, mobile health interventions need to be responsive to individuals' needs and preferences, which may change over time. We previously created an ecological daily needs assessment to capture microprocesses influencing user needs and preferences for mobile health treatment adaptation., Objective: The objective of our study was to test the utility of a needs assessment anchored within a mobile app to capture individualized, contextually relevant user needs and preferences within the framework of a weight management mobile health app., Methods: Participants with an iOS device could download the study app via the study website or links from social media. In this fully remote study, we screened, obtained informed consent from, and enrolled participants through the mobile app. The mobile health framework included daily health goal setting and self-monitoring, with up to 6 daily prompts to determine in-the-moment needs and preferences for mobile health-assisted health behavior change., Results: A total of 24 participants downloaded the app and provided e-consent (22 female; 2 male), with 23 participants responding to at least one prompt over 2 weeks. The mean length of engagement was 5.6 (SD 4.7) days, with a mean of 2.8 (1.1) responses per day. We observed individually dynamic needs and preferences, illustrating daily variability within and between individuals. Qualitative feedback indicated preferences for self-adapting features, simplified self-monitoring, and the ability to personalize app-generated message timing and content., Conclusions: The technique provided an individually dynamic and contextually relevant alternative and complement to traditional needs assessment for assessing individually dynamic user needs and preferences during treatment development or adaptation. The results of this utility study suggest the importance of personalization and learning algorithms for sustaining app engagement in young adults with psychiatric conditions. Further study in broader user populations is needed., (©Ginger E Nicol, Amanda R Ricchio, Christopher L Metts, Michael D Yingling, Alex T Ramsey, Julia A Schweiger, J Philip Miller, Eric J Lenze. Originally published in JMIR mHealth and uHealth (http://mhealth.jmir.org), 13.11.2020.)

Introduction: Some evidence suggests that female smokers may show more context-dependent smoking and that males may show more stereotyped smoking (regardless of stress or cue exposure). The goal of this study was to characterize sex differences in response to stressful and smoking cues ecologically presented in daily life and variability in day-to-day smoking behavior., Methods: Adult smokers (N = 177) provided ratings of mood and cigarette craving before and after stress and smoking cues were presented four times daily for 14 days via a mobile device. Linear mixed models tested whether (1) female smokers exhibited greater reactivity to stressful cues than male smokers; (2) pre-cue negative affect increased reactivity to smoking cues more in female smokers than male smokers; (3) across both sexes, greater reactivity to stressful and smoking cues correlated with greater quantity of smoking within a day; and (4) female smokers exhibited greater variability in cigarettes per day (CPD) relative to males., Results: Relative to male smokers, female smokers reported greater negative affect, stress, and craving in response to stressful cues, but not smoking cues, after accounting for time since last cigarette and pre-cue responding. No sex differences in CPD or variability in CPD were detected. Days with higher subjective reactivity to cues were not associated with increased smoking, in either males or females., Conclusions: Sex differences were observed in response to stress but not smoking cues in the natural environment of regular cigarette smokers. Further research is necessary to evaluate whether stress reactivity in female smokers is associated with reduced latency to smoke following stress exposure in daily life., Implications: This study provides naturalistic evidence that female smokers may not be more reactive to smoking cues than males, but experience heightened stress and craving following stress exposure. There was no evidence to support the hypothesis that amount smoked per day varied more for females, relative to males, as a result of more context-driven smoking for females., (© The Author(s) 2018. Published by Oxford University Press on behalf of the Society for Research on Nicotine and Tobacco. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.)