The Impact of Digital Self-Monitoring of Weight on Improving Diabetes Clinical Outcomes: Quasi-Randomized Study

BACKGROUND

The management of type 2 diabetes (T2D) and obesity, particularly in the context of self-monitoring, remains a critical challenge in health care. As nearly 80% to 90% of patients with T2D have overweight or obesity, there is a compelling need for interventions that can effectively manage both conditions simultaneously. One of the goals in managing chronic conditions is to increase awareness and generate behavioral change to improve outcomes in diabetes and related comorbidities, such as overweight or obesity. There is a lack of real-life evidence to test the impact of self-monitoring of weight on glycemic outcomes and its underlying mechanisms.

OBJECTIVE

This study aims to assess the efficacy of digital self-monitoring of weight on blood glucose (BG) levels during diabetes management, investigating whether the weight changes may drive glucose fluctuations.

METHODS

In this retrospective, real-world quasi-randomized study, 50% of the individuals who regularly used the weight monitoring (WM) feature were propensity score matched with 50% of the users who did not use the weight monitoring feature (NWM) based on demographic and clinical characteristics. All the patients were diagnosed with T2D and tracked their BG levels. We analyzed monthly aggregated data 6 months before and after starting their weight monitoring. A piecewise mixed model was used for analyzing the time trajectories of BG and weight as well as exploring the disaggregation effect of between- and within-patient lagged effects of weight on BG.

RESULTS

The WM group exhibited a significant reduction in BG levels post intervention (P<.001), whereas the nonmonitoring group showed no significant changes (P=.59), and both groups showed no differences in BG pattern before the intervention (P=.59). Furthermore, the WM group achieved a meaningful decrease in BMI (P<.001). Finally, both within-patient (P<.001) and between-patient (P=.008) weight variability was positively associated with BG levels. However, 1-month lagged back BMI was not associated with BG levels (P=.36).

CONCLUSIONS

This study highlights the substantial benefits of self-monitoring of weight in managing BG levels in patients with diabetes, facilitated by a digital health platform, and advocates for the integration of digital self-monitoring tools in chronic disease management. We also provide initial evidence of testing the underlying mechanisms associated with BG management, underscoring the potential role of patient empowerment.

Defining suffering in pain. A systematic review on pain-related suffering using natural language processing

ABSTRACT

Understanding, measuring, and mitigating pain-related suffering is a key challenge for both clinical care and pain research. However, there is no consensus on what exactly the concept of pain-related suffering includes, and it is often not precisely operationalized in empirical studies. Here, we (1) systematically review the conceptualization of pain-related suffering in the existing literature, (2) develop a definition and a conceptual framework, and (3) use machine learning to cross-validate the results. We identified 111 articles in a systematic search of Web of Science, PubMed, PsychINFO, and PhilPapers for peer-reviewed articles containing conceptual contributions about the experience of pain-related suffering. We developed a new procedure for extracting and synthesizing study information based on the cross-validation of qualitative analysis with an artificial intelligence-based approach grounded in large language models and topic modeling. We derived a definition from the literature that is representative of current theoretical views and describes pain-related suffering as a severely negative, complex, and dynamic experience in response to a perceived threat to an individual's integrity as a self and identity as a person. We also offer a conceptual framework of pain-related suffering distinguishing 8 dimensions: social, physical, personal, spiritual, existential, cultural, cognitive, and affective. Our data show that pain-related suffering is a multidimensional phenomenon that is closely related to but distinct from pain itself. The present analysis provides a roadmap for further theoretical and empirical development.

Integrating exploration and prediction in computational psychotherapy science: proof of concept

Introduction

Psychotherapy research has long preferred explanatory over predictive models. As a result, psychotherapy research is currently limited in the variability that can be accounted for in the process and outcome of treatment. The present study is a proof-of-concept approach to psychotherapy science that uses a datadriven approach to achieve robust predictions of the process and outcome of treatment.

Methods

A trial including 65 therapeutic dyads was designed to enable an adequate level of variability in therapist characteristics, overcoming the common problem of restricted range. A mixed-model, data-driven approach with cross-validation machine learning algorithms was used to predict treatment outcome and alliance (within- and between-clients; client- and therapist-rated alliance).

Results and discussion

Based on baseline predictors only, the models explained 52.8% of the variance for out-of-sample prediction in treatment outcome, and 24.1-52.8% in therapeutic alliance. The identified predictors were consistent with previous findings and point to directions for future investigation. Although limited by its sample size, this study serves as proof of the great potential of the presented approach to produce robust predictions regarding the process and outcome of treatment, offering a potential solution to problems such as p-hacking and lack of replicability. Findings should be replicated using larger samples and distinct populations and settings.

The prognostic role of emotion regulation dynamics in the treatment of major depressive disorder

OBJECTIVE

The potential prognostic role of emotion regulation in the treatment of major depressive disorder (MDD) has been highlighted by transtheoretical literature and supported by promising empirical findings. The majority of the literature is based on self-report observations at a single snapshot, thus little is known about the prognostic value of moment-to-moment dynamic evolvement of emotion. The present study is the first to examine the prognostic value of both intra- and interpersonal, moment-to-moment emotion regulation dynamics, and the potential moderating effect of the type of treatment.

METHOD

To assess the prognostic value of emotion regulation dynamics, we focused on the first session, using 6,780 talk-turns within 52 patient-therapist dyads. Emotion regulation dynamics were measured using fundamental frequencies of the voice and were calculated using empirical Bayes residuals of the actor-partner interdependence model. Symptomatic change was measured using the Hamilton Rating Scale for Depression across 16 weeks of supportive treatment (ST) or supportive-expressive treatment (SET).

RESULTS

Findings suggest that patients who show less regulated intrapersonal dynamics during the first session show less reduction of symptoms throughout treatment (β = .26, p = .019). Findings further suggest that this association is mitigated when these patients receive SET, as opposed to ST (β = .72, p = .020).

CONCLUSIONS

The findings demonstrate the ability of first-session emotion regulation dynamics to serve as a prognostic variable. The findings further suggest that the adverse effect of emotion regulation dynamics on the patient's prognosis can be mitigated by explicit work on changing maladaptive emotional patterns. (PsycInfo Database Record (c) 2023 APA, all rights reserved).

Specifying the Efficacy of Digital Therapeutic Tools for Depression and Anxiety: Retrospective, 2-Cohort, Real-World Analysis

BACKGROUND

Depression and anxiety are the main sources of work and social disabilities as well as health-related problems around the world. Digital therapeutic solutions using cognitive behavioral therapy have demonstrated efficacy in depression and anxiety. A common goal of digital health apps is to increase user digital engagement to improve outcomes. However, there is a limited understanding of the association between digital platform components and clinical outcomes.

OBJECTIVE

The aim of the study is to investigate the contribution of specific digital engagement tools to mental health conditions. We hypothesized that participation in coaching sessions and breathing exercises would be associated with a reduction in depression and anxiety.

METHODS

Depression and general anxiety symptoms were evaluated in real-world data cohorts using the digital health platform for digital intervention and monitoring change. This retrospective real-world analysis of users on a mobile platform-based treatment followed two cohorts of people: (1) users who started with moderate levels of depression and completed at least 2 depression assessments (n=519) and (2) users who started with moderate levels of anxiety and completed at least 2 anxiety assessments (n=474). Levels of depression (Patient Health Questionnaire-9) and anxiety (Generalized Anxiety Disorder-7) were tracked throughout the first 16 weeks. A piecewise mixed-effects model was applied to model the trajectories of the Patient Health Questionnaire-9 and the Generalized Anxiety Disorder-7 mean scores in 2 segments (1-6 weeks and 7-16 weeks). Finally, simple slope analysis was used for the interpretation of the interactions probing the moderators: coaching sessions and breathing exercises in both depression and anxiety cohorts.

RESULTS

Analysis revealed a significant decrease in depression symptoms (β=-.37, 95% CI -0.46 to 0.28; P≤.001) during the period of weeks 1-6 of app use, which was maintained during the period of 7-16 weeks. Coach interaction significantly moderated the reduction in depression symptoms during the period of weeks 1-6 (β=-.03, 95% CI -0.05 to -0.001; P=.02). A significant decrease in anxiety symptoms (β=-.41, 95% CI -0.50 to -0.33; P≤.001) was revealed during the period of 1-6 weeks, which was maintained during the period of 7-16 weeks. Breathing exercises significantly moderated the reduction in anxiety symptoms during the period of 1-6 weeks (β=-.07, 95% CI -0.14 to -0.01; P=.04).

CONCLUSIONS

This study demonstrated general improvement followed by a period of stability of depression and anxiety symptoms associated with cognitive behavioral therapy-based digital intervention. Interestingly, engagement with a coaching session but not a breathing exercise was associated with a reduction in depression symptoms. Moreover, breathing exercise but not engagement with a coaching session was associated with a reduction of anxiety symptoms. These findings emphasize the importance of using a personalized approach to behavioral health during digital health interventions.

Noninvasive Detection of Stress by Biochemical Profiles from the Skin

Stress is a leading cause of several disease types, yet it is underdiagnosed as current diagnostic methods are mainly based on self-reporting and interviews that are highly subjective, inaccurate, and unsuitable for monitoring. Although some physiological measurements exist (e.g., heart rate variability and cortisol), there are no reliable biological tests that quantify the amount of stress and monitor it in real time. In this article, we report a novel way to measure stress quickly, noninvasively, and accurately. The overall detection approach is based on measuring volatile organic compounds (VOCs) emitted from the skin in response to stress. Sprague Dawley male rats (n = 16) were exposed to underwater trauma. Sixteen naive rats served as a control group (n = 16). VOCs were measured before, during, and after induction of the traumatic event, by gas chromatography linked with mass spectrometry determination and quantification, and an artificially intelligent nanoarray for easy, inexpensive, and portable sensing of the VOCs. An elevated plus maze during and after the induction of stress was used to evaluate the stress response of the rats, and machine learning was used for the development and validation of a computational stress model at each time point. A logistic model classifier with stepwise selection yielded a 66-88% accuracy in detecting stress with a single VOC (2-hydroxy-2-methyl-propanoic acid), and an SVM (support vector machine) model showed a 66-72% accuracy in detecting stress with the artificially intelligent nanoarray. The current study highlights the potential of VOCs as a noninvasive, automatic, and real-time stress predictor for mental health.

Personalizing digital pain management with adapted machine learning approach

Introduction

Digital therapeutics (DT) emerged and has been expanding rapidly for pain management. However, the efficacy of such approaches demonstrates substantial heterogeneity. Machine learning (ML) approaches provide a great opportunity for personalizing the efficacy of DT. However, the ML model accuracy is mainly associated with reduced clinical interpretability. Moreover, classical ML models are not adapted for the longitudinal nature of the DT follow-up data, which may also include nonlinear fluctuations.

Objectives

This study presents an analytical framework for personalized pain management using piecewise mixed-effects model trees, considering the data dependencies, nonlinear trajectories, and boosting model interpretability.

Methods

We demonstrated the implementation of the model with posture biofeedback training data of 3610 users collected during 8 weeks. The users reported their pain levels and posture quality. We developed personalized models for nonlinear time-related fluctuations of pain levels, posture quality, and weekly training duration using age, gender, and body mass index as potential moderating factors.

Results

Pain levels and posture quality demonstrated strong improvement during the first 3 weeks of the training, followed by a sustained pattern. The age of the users moderated the time fluctuations in pain levels, whereas age and gender interactively moderated the trajectories in the posture quality. Train duration increased during the first 3 weeks only for older users, whereas all the users decreased the training duration during the next 5 weeks.

Conclusions

This analytical framework offers an opportunity for investigating the personalized efficacy of digital therapeutics for pain management, taking into account users' characteristics and boosting interpretability and can benefit from including more users' characteristics.

The two-stage therapeutic effect of posture biofeedback training on back pain and the associated mechanism: A retrospective cohort study

Introduction: Back pain is an extremely common symptom experienced by people of all ages and the number one cause of disability worldwide.² Poor posture has been identified as one of the factors leading to back pain. Digital biofeedback technology demonstrates the promising therapeutic ability in pain management through posture training. One common goal of such an approach is to increase users' posture awareness with associated movement correction. However, we lack a deep understanding of the biofeedback therapeutic mechanisms and the temporal dynamics of efficacy. Objective: This study investigates the temporal dynamics of the biofeedback learning process and associated outcomes in daily life settings, testing the mechanism of the biofeedback-associated pain reduction. Methods: This retrospective real-world evidence study followed 981 users who used the UpRight posture biofeedback platform. Piecewise mixed models were used for modeling the two-stage trajectory of pain levels, perceived posture quality, and weekly training duration following an 8-week biofeedback training. Also, the mediation effect of perceived posture quality on the analgesic effect of training duration was tested using Monte Carlo simulations based on lagged effect mixed models. Results: The analysis revealed significant pain level reduction (p <.0001) and posture quality improvement (p <.0001) during the first 4 weeks of the training, maintaining similar pain levels and perceived posture quality during the next 4 weeks. In addition, weekly training duration demonstrated an increase during the first 3 weeks (p <.001) and decreased during the next 5 weeks (p <.001). Moreover, training duration predicted following-week perceived posture quality (p <.001) and in turn perceived posture quality predicted following-week pain (p <.001) (p = 0.30). Finally, perceived posture quality mediated the effect of weekly training duration on the pain levels in 2 weeks (p <.0001). Conclusion: Our findings provide a better understanding of the therapeutic dynamic during digital biofeedback intervention targeting pain, modeling the associated two-stage process. Moreover, the study sheds light on the biofeedback mechanism and may assist in developing a better therapeutic approach targeting perceived posture quality.

Multi-trajectory analysis uncovers latent associations between psychological and physiological acute stress response patterns

Encounter with an acute stressor elicits multiple physiological and psychological response trajectories that spread at different times-scales and directions. Associating a single physiological response trajectory with a specific psychological response has remained a challenge, due to putative interactions between the different stress response pathways. Hence, multidimensional analysis of stress response trajectories may be better suited to account for response variability. To test this, 96 healthy female participants underwent a robust acute laboratory stress induction procedure while their psychological [positive and negative affect (PANAS)] and physiological [heart rate (HR), heart rate variability (HRV), saliva cortisol (CORT)] responses were recorded before, during and after stress. Combining these data using unsupervised group-based multi-trajectory modelling uncovered three latent classes that best accounted for variability across psychological and physiological stress response trajectories. These classes were labelled based on their psychological response patterns as: A prototypical response group that depict a moderate increase in negative and decrease in positive affect during stress, with both patterns recovering after stress offset (n = 55); A heightened response group that depict excessive affective responses during stress that recover after stress offset (n = 24); and a lack of recovery group that depict a moderate increase in negative and decrease in positive affect during stress, with both patterns not recovering after stress offset (n = 17). With respect to physiological acute stress trajectories, all three groups exhibited comparable increases in HR and CORT during stress that recovered after stress offset, yet only the prototypical group expressed the expected stress-induced reduction in HRV, while the other two groups exhibited blunted HRV response. Critically, focusing on a single physiological stress response trajectory, including HRV, did not account for psychological response variability and vice versa. Taken together, a multi-trajectory approach may better account for the multidimensionality of acute stress response and uncover latent associations between psychological and physiological response patterns. Compared to the other two groups, the prototypical group also exhibited significantly lower overall stress scores based on the DASS-21 scale. This, alongside the uncovered response patterns, suggest that latent psycho-physiological associations may shed light on stress response adaptivity or lack thereof.

Instructor-learner body coupling reflects instruction and learning

It is widely accepted that nonverbal communication is crucial for learning, but the exact functions of interpersonal coordination between instructors and learners remain unclear. Specifically, it is unknown what role instructional approaches play in the coupling of physical motion between instructors and learners, and crucially, how such instruction-mediated Body-to-Body Coupling (BtBC) might affect learning. We used a video-based, computer-vision Motion Energy Analysis (MEA) to quantify BtBC between learners and instructors who used two different instructional approaches to teach psychological concepts. BtBC was significantly greater when the instructor employed a scaffolding approach than when an explanation approach was used. The importance of the instructional approach was further underscored by the fact that an increase in motion in the instructor was associated with boosted BtBC, but only during scaffolding; no such relationship between the instructor movements and BtBC was found during explanation interactions. Finally, leveraging machine learning approaches (i.e., support vector and logistic regression models), we demonstrated that both learning outcome and instructional approaches could be decoded based on BtBC. Collectively, these results show that the real-time interaction of teaching and learning bodies is important for learning and that the instructional approach matters, with possible implications for both in-person and online learning.

Blood Pressure Monitoring as a Digital Health Tool for Improving Diabetes Clinical Outcomes: Retrospective Real-world Study

Background

Remote data capture for blood glucose (BG) or blood pressure (BP) monitoring and the use of a supportive digital app are becoming the model in diabetes and hypertension chronic care. One of the goals in chronic condition management is to increase awareness and generate behavioral change in order to improve outcomes in diabetes and related comorbidities, such as hypertension. In addition, there is a lack of understanding of the association between BG and BP levels when using digital health tools.

Objective

By applying a rigorous study framework to digital health data, this study investigated the relationship between BP monitoring and BG and BP levels, as well as a lagged association between BP and BG. We hypothesized that during the first 6 months of BP monitoring, BG and BP levels would decrease. Finally, we suggested a positive association between BP levels and the following month’s BG levels.

Methods

In this retrospective, real-world case-control study, we extracted the data of 269 people with type 2 diabetes (T2D) who tracked their BG levels using the Dario digital platform for a chronic condition. We analyzed the digital data of the users who, in addition to BG, monitored their BP using the same app (BP-monitoring [BPM] group, n=137) 6 months before and after starting their BP monitoring. Propensity score matching established a control group, no blood pressure monitoring (NBPM, n=132), matched on demographic and baseline clinical measures to the BPM group. A piecewise mixed model was used for analyzing the time trajectories of BG, BP, and their lagged association.

Results

Analysis revealed a significant difference in BG time trajectories associated with BP monitoring in BPM and NBPM groups (t=–2.12, P=.03). The BPM group demonstrated BG reduction improvement in the monthly average BG levels during the first 6 months (t=–3.57, P<.001), while BG did not change for the NBPM group (t=0.39, P=.70). Both groups showed similarly stable BG time trajectories (B=0.98, t=1.16, P=.25) before starting the use of the BP-monitoring system. In addition, the BPM group showed a significant reduction in systolic (t=–6.42, P<.001) and diastolic (t=–4.80, P<.001) BP during the first 6 months of BP monitoring. Finally, BG levels were positively associated with systolic (B=0.24, t=2.77, P=.001) and diastolic (B=0.30, t=2.41, P=.02) BP.

Conclusions

The results of this study shed light on the association between BG and BP levels and on the role of BP self-monitoring in diabetes management. Our findings also underscore the need and provide a basis for a comprehensive approach to understanding the mechanism of BP regulation associated with BG.

A randomized controlled trial for identifying the most suitable treatment for depression based on patients' attachment orientation

OBJECTIVE

Many active treatments exist for major depressive disorder (MDD), but little is known about their differential effects for various subpopulations of patients to guide precision medicine. This is the first randomized controlled trial (RCT) designed to identify differential treatment effects based on patients' attachment orientations. We tested an a priori preregistered hypothesis of the potential moderating effect of patients' attachment orientation on the outcome of supportive therapy (ST) versus supportive-expressive therapy (SET).

METHODS

The RCT was conducted between 2015 and 2021. Individuals with MDD were randomly assigned to 16-week ST or SET. The predefined primary outcome measure was the Hamilton Rating Scale for Depression. Hypotheses were formulated and preregistered before data collection.

RESULTS

One hundred patients with MDD were enrolled, 57% women, average age 31.2 (SD = 8.25). Data were analyzed using the intention-to-treat approach. Our hypothesis that attachment anxiety is a significant moderator of treatment outcome was supported (B = -0.09, p = .016): Patients with higher levels of attachment anxiety showed greater treatment efficacy following SET than ST. Although the hypothesis regarding a potential moderating effect of avoidant attachment was not supported, sensitivity analyses revealed that individuals with disorganized attachment orientation (higher scores on both anxious and avoidant attachment) benefited more from SET than from ST (B = -0.07, p = .04).

CONCLUSION

The findings support the clinical utility of patients' attachment orientation in selecting the most suitable treatment for individuals and demonstrate the methodological utility of RCTs predesigned to test theoretically based models of personalized treatment. (PsycInfo Database Record (c) 2022 APA, all rights reserved).

Predicting Chronic Stress among Healthy Females Using Daily-Life Physiological and Lifestyle Features from Wearable Sensors

Background

Chronic stress is a highly prevalent condition that may stem from different sources and can substantially impact physiology and behavior, potentially leading to impaired mental and physical health. Multiple physiological and behavioral lifestyle features can now be recorded unobtrusively in daily-life using wearable sensors. The aim of the current study was to identify a distinct set of physiological and behavioral lifestyle features that are associated with elevated levels of chronic stress across different stress sources.

Methods

For that, 140 healthy female participants completed the Trier inventory for chronic stress (TICS) before wearing the Fitbit Charge3 sensor for seven consecutive days while maintaining their daily routine. Physiological and lifestyle features that were extracted from sensor data, alongside demographic features, were used to predict high versus low chronic stress with support vector machine classifiers, applying out-of-sample model testing.

Results

The model achieved 79% classification accuracy for chronic stress from a social tension source. A mixture of physiological (resting heart-rate, heart-rate circadian characteristics), lifestyle (steps count, sleep onset and sleep regularity) and non-sensor demographic features (smoking status) contributed to this classification.

Conclusion

As wearable technologies continue to rapidly evolve, integration of daily-life indicators could improve our understanding of chronic stress and its impact of physiology and behavior.

Post-Induction High Adalimumab Drug Levels Predict Biological Remission at Week 24 in Patients With Crohn's Disease

INTRODUCTION

We investigated whether early adalimumab drug levels (ADL) at week 4 predicted biological remission at week 24.

METHODS

In a prospective study, we assessed clinical and biological remission at weeks 0, 4, 12, and 24 after induction of adalimumab in 33 patients with Crohn's disease. Disease activity was determined by the Harvey-Bradshaw Index, ileocolonoscopy reports, cross-sectional imaging, C-reactive protein (CRP), and fecal calprotectin (FC) levels. Clinical remission was defined as Harvey-Bradshaw Index <5. Biological remission was defined as a combination of FC < 200 μg/g and CRP <5 μg/mL. ADL trough levels were tested using a liquid phase, mobility shift assay.

RESULTS

At 24 weeks, 18/33 (55%) of the patients were with biological remission. Ten (30%) patients required dose escalation or withdrawal from adalimumab by week 24 because of lack of response and exhibited significantly higher FC (P = 0.003) and CRP (P = 0.002). ADL levels at week 4 (19.8 μg/mL vs 10.2 μg/mL, P = 0.001) were significantly higher in patients with biological remission vs nonresponders at week 24. ADL levels at week 4 were a good predictor of biological remission at week 24, with area under the curve 0.86, 95% confidence interval (1.1; 1.67) and for combined biological and clinical remission, with area under the curve 0.8. The best ADL cutoff at week 4 that predicted biological remission at week 24 was 13.9 μg/mL (sensitivity 94.4% and specificity 73.3%).

DISCUSSION

In individuals with Crohn's disease, higher adalimumab drug levels at week 4 (>13.9 μg/mL) were significantly associated with biological remission at week 24.

Role of Digital Engagement in Diabetes Care Beyond Measurement: Retrospective Cohort Study

BACKGROUND

The use of remote data capture for monitoring blood glucose and supporting digital apps is becoming the norm in diabetes care. One common goal of such apps is to increase user awareness and engagement with their day-to-day health-related behaviors (digital engagement) in order to improve diabetes outcomes. However, we lack a deep understanding of the complicated association between digital engagement and diabetes outcomes.

OBJECTIVE

This study investigated the association between digital engagement (operationalized as tagging of behaviors alongside glucose measurements) and the monthly average blood glucose level in persons with type 2 diabetes during the first year of managing their diabetes with a digital chronic disease management platform. We hypothesize that during the first 6 months, blood glucose levels will drop faster and further in patients with increased digital engagement and that difference in outcomes will persist for the remainder of the year. Finally, we hypothesize that disaggregated between- and within-person variabilities in digital engagement will predict individual-level changes in blood glucose levels.

METHODS

This retrospective real-world analysis followed 998 people with type 2 diabetes who regularly tracked their blood glucose levels with the Dario digital therapeutics platform for chronic diseases. Subjects included "nontaggers" (users who rarely or never used app features to notice and track mealtime, food, exercise, mood, and location, n=585) and "taggers" (users who used these features, n=413) representing increased digital engagement. Within- and between-person variabilities in tagging behavior were disaggregated to reveal the association between tagging behavior and blood glucose levels. The associations between an individual's tagging behavior in a given month and the monthly average blood glucose level in the following month were analyzed for quasicausal effects. A generalized mixed piecewise statistical framework was applied throughout.

RESULTS

Analysis revealed significant improvement in the monthly average blood glucose level during the first 6 months (t=-10.01, P<.001), which was maintained during the following 6 months (t=-1.54, P=.12). Moreover, taggers demonstrated a significantly steeper improvement in the initial period relative to nontaggers (t=2.15, P=.03). Additional findings included a within-user quasicausal nonlinear link between tagging behavior and glucose control improvement with a 1-month lag. More specifically, increased tagging behavior in any given month resulted in a 43% improvement in glucose levels in the next month up to a person-specific average in tagging intensity (t=-11.02, P<.001). Above that within-person mean level of digital engagement, glucose levels remained stable but did not show additional improvement with increased tagging (t=0.82, P=.41). When assessed alongside within-person effects, between-person changes in tagging behavior were not associated with changes in monthly average glucose levels (t=1.30, P=.20).

CONCLUSIONS

This study sheds light on the source of the association between user engagement with a diabetes tracking app and the clinical condition, highlighting the importance of within-person changes versus between-person differences. Our findings underscore the need for and provide a basis for a personalized approach to digital health.

Oxytocin synchrony between patients and therapists as a mechanism underlying effective psychotherapy for depression

OBJECTIVE

Oxytocin (OT) synchrony has been suggested as a key mechanism by which bonds are formed and strengthened in various species, including those between mother and infant and between romantic partners. It is unknown whether such biological synchrony also plays a role in psychotherapy efficacy, where it may underlie the adverse effect of social impairment on the efficacy of treatment of depression.

METHOD

Five hundred eighty OT saliva samples were collected from 37 patient-therapist dyads on a fixed schedule over a 16-session ongoing randomized controlled trial for psychotherapy for depression. Biological synchrony was operationalized as the correlation between changes occurring repeatedly over treatment in patient and therapist OT levels pre- to postsession.

RESULTS

OT synchrony between patients and therapists was found to be associated with effective treatment. The findings support the proposed mediation model: (a) poorer social functioning at baseline predicted lower levels of patient-therapist synchrony in OT changes from pre- to postsession over the course of treatment; (b) lower levels of therapist-patient OT synchrony, in turn, predicted less reduction in depressive symptoms during treatment; and (c) based on quasi-Bayesian Monte Carlo simulations, the levels of therapist-patient synchrony significantly mediated the association between social impairment and reduction in depressive symptoms. Findings were replicated using robust inferential methods.

CONCLUSIONS

The findings suggest that OT synchrony between patient and therapist may be a biological mechanism by which impaired interpersonal functioning undermines treatment outcome. (PsycInfo Database Record (c) 2021 APA, all rights reserved).

What do these sounds tell us about the therapeutic alliance: Acoustic markers as predictors of alliance

Predicting the trajectories of alliance formation that the patient is likely to establish with the therapist during treatment, even before their first meeting, can help prevent the potentially harmful consequences of deterioration in alliance, such as poor outcome and premature dropout. The present study aimed to examine the ability of four pretreatment acoustic markers to predict the alliance that is likely to be formed in the course of treatment: F0 span, speech rate, pause proportion and jitter. Data from 560 observations of 38 patients were collected as part of an ongoing randomized clinical trial of short-term psychotherapy for major depressive disorder. The acoustic markers were measured using high-quality recordings at baseline, before the patient and therapist ever met or had any type of communication. A multilevel model was used to examine the ability of the four acoustic markers to predict the slopes of alliance formation in the course of treatment, all markers being introduced in the same model. The clinical utility of the acoustic markers was explored in two case studies. The model explained 22% of the variance in alliance formation. Higher levels of both jitter and pause proportion at baseline predicted less strengthening of the alliance in the course of treatment. The findings, which should be replicated in larger samples, suggest that much of the therapeutic alliance can be predicted based on the acoustic characteristics of the patient's voice in the first 3 min of their intake, before they even meet their therapist.

Clinician-Patient Movement Synchrony Mediates Social Group Effects on Interpersonal Trust and Perceived Pain

Pain is an unfortunate consequence of many medical procedures, which in some patients becomes chronic and debilitating. Among the factors affecting medical pain, clinician-patient (C-P) similarity and nonverbal communication are particularly important for pain diagnosis and treatment. Participants (N = 66) were randomly assigned to clinician and patient roles and were grouped into C-P dyads. Clinicians administered painful stimuli to patients as an analogue of a painful medical procedure. We manipulated the perceived C-P similarity of each dyad using groups ostensibly based on shared beliefs and values, and each patient was tested twice: Once with a same group clinician (concordant, CC) and once with a clinician from the other group (discordant, DC). Movement synchrony was calculated as a marker of nonverbal communication. We tested whether movement synchrony mediated the effects of group concordance on patients' pain and trust in the clinician. Movement synchrony was higher in CC than DC dyads. Higher movement synchrony predicted reduced pain and increased trust in the clinician. Movement synchrony also formally mediated the group concordance effects on pain and trust. These findings increase our understanding of the role of nonverbal C-P communication on pain and related outcomes. Interpersonal synchrony may be associated with better pain outcomes, independent of the specific treatment provided. PERSPECTIVE: This article demonstrates that movement synchrony in C-P interactions is an unobtrusive measure related to their relationship quality, trust toward the clinician, and pain. These findings suggest that interpersonal synchrony may be associated with better patient outcomes, independent of the specific treatment provided.

Emerging Clinical Technology: Application of Machine Learning to Chronic Pain Assessments Based on Emotional Body Maps

Depression and anxiety co-occur with chronic pain, and all three are thought to be caused by dysregulation of shared brain systems related to emotional processing associated with body sensations. Understanding the connection between emotional states, pain, and bodily sensations may help understand chronic pain conditions. We developed a mobile platform for measuring pain, emotions, and associated bodily feelings in chronic pain patients in their daily life conditions. Sixty-five chronic back pain patients reported the intensity of their pain, 11 emotional states, and the corresponding body locations. These variables were used to predict pain 2 weeks later. Applying machine learning, we developed two predictive models of future pain, emphasizing interpretability. One model excluded pain-related features as predictors of future pain, and the other included pain-related predictors. The best predictors of future pain were interactive effects of (a) body maps of fatigue with negative affect and (b) positive affect with past pain. Our findings emphasize the contribution of emotions, especially emotional experience felt in the body, to understanding chronic pain above and beyond the mere tracking of pain levels. The results may contribute to the generation of a novel artificial intelligence framework to help in the development of better diagnostic and therapeutic approaches to chronic pain.

Blood pressure reaction to negative stimuli: Insights from continuous recording and analysis

Individuals with a tendency toward abnormally enhanced cardiovascular responses to stress are at greater risk of developing essential hypertension later in life. Accurate profiling of continuous blood pressure (BP) reactions in healthy populations is crucial for understanding normal and abnormal emotional reaction patterns. To this end, we examined the continuous time course of BP reactions to aversive pictures among healthy participants. In two experiments, we showed participants negative and neutral pictures while simultaneously measuring their continuous BP and heart rate (HR) reactions. In this study, BP reactions were analyzed continuously, in contrast to previous studies, in which BP responses were averaged across blocks. To compare time points along a temporal continuum, we applied a multi-level B-spline model, which is innovative in the context of BP analysis. Additionally, HR was similarly analyzed in order to examine its correlation with BP. Both experiments revealed a similar pattern of BP reactivity and association with HR. In line with previous studies, a decline in BP and HR levels was found in response to negative pictures compared to neutral pictures. In addition, in both conditions, we found an unexpected elevation of BP toward the end of the stimuli exposure period. These findings may be explained by the recruitment of attention resources in the presence of negative stimuli, which is alleviated toward the end of the stimulation. This study highlights the importance of continuous measurement and analysis for characterizing the time course of BP reactivity to emotional stimuli.

Pain-Evoked Reorganization in Functional Brain Networks

Recent studies indicate that a significant reorganization of cerebral networks may occur in patients with chronic pain, but how immediate pain experience influences the organization of large-scale functional networks is not yet well characterized. To investigate this question, we used functional magnetic resonance imaging in 106 participants experiencing both noxious and innocuous heat. Painful stimulation caused network-level reorganization of cerebral connectivity that differed substantially from organization during innocuous stimulation and standard resting-state networks. Noxious stimuli increased somatosensory network connectivity with (a) frontoparietal networks involved in context representation, (b) "ventral attention network" regions involved in motivated action selection, and (c) basal ganglia and brainstem regions. This resulted in reduced "small-worldness," modularity (fewer networks), and global network efficiency and in the emergence of an integrated "pain supersystem" (PS) whose activity predicted individual differences in pain sensitivity across 5 participant cohorts. Network hubs were reorganized ("hub disruption") so that more hubs were localized in PS, and there was a shift from "connector" hubs linking disparate networks to "provincial" hubs connecting regions within PS. Our findings suggest that pain reorganizes the network structure of large-scale brain systems. These changes may prioritize responses to painful events and provide nociceptive systems privileged access to central control of cognition and action during pain.

Access to mechanical thrombectomy for cerebral ischaemia: A population-based study in the North-of-France

BACKGROUND AND PURPOSE

Hospitals admitting acute strokes should offer access to mechanical thrombectomy (MT), but local organisations are still based on facilities available before MT was proven effective. MT rates and outcomes at population levels are needed to adapt organisations. We evaluated rates of MT and outcomes in inhabitants from the North-of-France (NoF) area.

METHOD

We prospectively evaluated rates of MT and outcomes of patients at 3 months, good outcomes being defined as a modified Rankin scale (mRS) 0 to 2 or like the pre-stroke mRS.

RESULTS

During the study period (2016-2017), 666 patients underwent MT (454, 68.1% associated with intravenous thrombolysis [IVT]). Besides, 1595 other patients received IVT alone. The rate of MT was 81 (95% confidence interval [CI] 72-90) per million inhabitants-year, ranging from 36 to 108 between districts. The rate of IVT was 249 (95% CI 234-264) per million inhabitants-year, ranging from 155 to 268. After 3 months, 279 (41.9%) patients who underwent MT had good outcomes, and 167 (25.1%) had died. Patients living outside the district of Lille where the only MT centre is, were less likely to have good outcomes at 3 months, after adjustment on age, sex, baseline severity, and delay.

CONCLUSION

The rate of MT is one of the highest reported up to now, even in low-rate districts, but outcomes were significantly worse in patients living outside the district of Lille, and this is not only explained by the delay.

French lyophilized plasma versus fresh frozen plasma for the initial management of trauma-induced coagulopathy: a randomized open-label trial

Essentials An immediate supply of plasma in case of trauma-induced coagulopathy is required. The Traucc trial compared French Lyophilised Plasma (FLyP) and Fresh Frozen Plasma (FFP). FLyP achieved higher fibrinogen concentrations compared with FFP. FLyP led to a more rapid coagulopathy improvement than FFP.

SUMMARY

Background Guidelines recommend beginning hemostatic resuscitation immediately in trauma patients. We aimed to investigate if French lyophilized plasma (FLyP) was more effective than fresh frozen plasma (FFP) for the initial management of trauma-induced coagulopathy. Methods In an open-label, phase 3, randomized trial (NCT02750150), we enrolled adult trauma patients requiring an emergency pack of 4 plasma units within 6 h of injury. We randomly assigned patients to receive 4-FLyP units or 4-FFP units. The primary endpoint was fibrinogen concentration at 45 min after randomization. Secondary outcomes included time to transfusion, changes in hemostatic parameters at different time-points, blood product requirements and 30-day in-hospital mortality. Results Forty-eight patients were randomized (FLyP, n = 24; FFP, n = 24). FLyP reduced the time from randomization to transfusion of first plasma unit compared with FFP (median[IQR],14[5-30] vs. 77[64-90] min). FLyP achieved a higher fibrinogen concentration 45 min after randomization compared with FFP (baseline-adjusted mean difference, 0.29 g L-1 ; 95% confidence interval [CI], 0.08-0.49) and a greater improvement in prothrombin time ratio, factor V and factor II. The between-group differences in coagulation parameters remained significant at 6 h. FLyP reduced fibrinogen concentrate requirements. Thirty-day in-hospital mortality rate was 22% with FLyP and 29% with FFP. Conclusion FLyP led to a more rapid, pronounced and extended increase in fibrinogen concentrations and coagulopathy improvement compared with FFP in the initial management of trauma patients. FLyP represents an attractive option for trauma management, especially when facing logistical issues such as combat casualties or mass casualties related to terror attacks or disasters.

The role of touch in regulating inter-partner physiological coupling during empathy for pain

The human ability to synchronize with other individuals is critical for the development of social behavior. Recent research has shown that physiological inter-personal synchronization may underlie behavioral synchrony. Nevertheless, the factors that modulate physiological coupling are still largely unknown. Here we suggest that social touch and empathy for pain may enhance interpersonal physiological coupling. Twenty-two romantic couples were assigned the roles of target (pain receiver) and observer (pain observer) under pain/no-pain and touch/no-touch conditions, and their ECG and respiration rates were recorded. The results indicate that the partner touch increased interpersonal respiration coupling under both pain and no-pain conditions and increased heart rate coupling under pain conditions. In addition, physiological coupling was diminished by pain in the absence of the partner’s touch. Critically, we found that high partner’s empathy and high levels of analgesia enhanced coupling during the partner’s touch. Collectively, the evidence indicates that social touch increases interpersonal physiological coupling during pain. Furthermore, the effects of touch on cardio-respiratory inter-partner coupling may contribute to the analgesic effects of touch via the autonomic nervous system.

Are the results of intravenous thrombolysis trials reproduced in clinical practice? Comparison of observed and expected outcomes with the stroke-thrombolytic predictive instrument (STPI)

AIM

In patients with cerebral ischemia, intravenous (i.v.) recombinant tissue plasminogen activator (rt-PA) increases survival without handicap or dependency despite an increased risk of bleeding. This study evaluated whether the results of randomized controlled trials are reproduced in clinical practice.

METHOD

Data from a registry of consecutive patients treated by rt-PA at Lille University Hospital were retrospectively analyzed for outcomes, using modified Rankin Scale (mRS) scores, at 3 months. The observed outcomes were then compared with the probability of good (mRS 0-1) and of catastrophic (mRS 5-6) outcomes, as predicted by the stroke-thrombolytic predictive instrument (STPI).

RESULTS

Of the 1000 consecutive patients (469 male, median age 74 years, median baseline National Institutes of Health Stroke Scale 11, median onset-to-needle time 143min), 438 (43.8%) had a good outcome, 565 (56.5%) had an mRS score 0-2 or similar to their pre-stroke mRS, 155 (15.5%) died within 3 months and 74 (7.4%) developed symptomatic intracerebral hemorrhage according to ECASS-II (Second European-Australasian Acute Stroke Study) criteria. Of the 613 patients (61.3%) eligible for evaluation by the s-TPI, the observed rate of good outcomes was 41.3% (95% CI: 37.5-45.3%), while expected rates with and without rt-PA were 48.8% (95% CI: 44.8-52.7%) and 32.5% (95% CI: 28.8-36.2%), respectively; the observed rate of catastrophic outcomes was 17.0% (95% CI: 14.0-19.9%), while the expected rate was 19.2% (95% CI: 16.1-22.4%) with or without rt-PA.

CONCLUSION

In clinical practice, the rate of good outcomes is slightly lower than expected, according to the s-TPI, except for the most severe cases, whereas the rate of catastrophic outcomes is roughly similar. However, the rate of good outcomes is higher than predicted without treatment. This finding suggests that rt-PA is effective for improving outcomes in clinical practice.

Empathy during consoling touch is modulated by mu-rhythm: An EEG study

The aim of the present study was to examine the mechanisms of empathy for pain that contribute to consoling touch, a distress-alleviating contact behavior carried out by an observer in response to the suffering of a target. We tested romantic couples in a paradigm that involves consoling touch and examined the attenuation of the mu/alpha rhythm (8-13Hz) in the consoling partner. During the task, the toucher either held the consoled partner's right hand (human touch) or held onto the armrest of the chair (non-human touch), while the consoled partner experienced inflicted pain (pain condition) or did not experience any pain (no-pain condition). In accordance with our hypotheses, the results revealed an interaction between touch and pain at in mu/alpha rhythms in all central sites (C3, C4, Cz). Specifically, we found that the toucher's mu suppression was higher in the consoling touch condition, i.e., while touching the partner who is in pain, compared to the three control conditions. Additionally, we found that in the consoling touch condition, mu suppression at electrode C4 of the toucher correlated with a measure of situational empathy. Our findings suggest that electrophysiological and behavioral measures that have been associated with empathy for pain are modulated during consoling touch.

Patient and provider perspectives on home telecare: Preliminary results from a randomized controlled trial

A randomized controlled trial of home telecare for the management of acute exacerbations of chronic obstructive pulmonary disease has been undertaken in the north-west of England. A videophone was used that communicates via the ordinary telephone network. The intervention period for each participant was two weeks. Participants in the telecare arm of the trial were asked to complete logbooks to record their experiences of each telecare encounter. A simple, self-completed, 10–item questionnaire was used that consisted of a Likert scale, ranging from 1 (totally disagree) to 5 (totally agree). Fourteen nurses completed 150 logbooks and 22 patients completed 145 logbooks. These results demonstrate significant differences in perception between patients and their health-care providers with regard to telecare encounters across all the domains addressed. Participating patients consistently demonstrated more positive views of the telecare encounters than their health-care providers.

Recruitment difficulties in a home telecare trial

We analysed the difficulties encountered in recruiting predominantly older patients, suffering from an acute exacerbation of a chronic illness, to a randomized controlled trial of home telecare. Of 653 patients approached for study participation, after full assessment, 80% (519) met the trial eligibility criteria. Of these, 104 (20%) consented to study participation and 415 (80%) refused. A logistic regression model was constructed to examine independent effects of patient factors on probability of trial participation. Only two independent variables were associated with decreased likelihood of consent: increasing age (1 year older: odds ratio [OR] = 0.96); and being on inhaled steroid medication (OR = 0.60). The most common reason for refusal to participate, accounting for almost one-third of respondents, was a stated preference for a face-to-face nurse visiting service rather than a telecare service. Perhaps home telecare services should continue to be targeted at the more stable chronically ill population and not at those suffering from acute illness.

Empathy Predicts an Experimental Pain Reduction During Touch

Previous studies have provided evidence for pain-alleviating effects of segmental tactile stimulation, yet the effect of social touch and its underlying mechanism is still unexplored. Considering that the soma affects the way we think, feel, and interact with others, it has been proposed that touch may communicate emotions, including empathy, interacting with the identity of the toucher. Thus, the goal of the current study was to examine the analgesic effects of social touch, and to test the moderating role of the toucher's empathy in analgesia using an ecological paradigm. Tonic heat stimuli were administered to women. Concurrently, their partners either watched or touched their hands, a stranger touched their hands, or no one interacted with them. The results revealed diminished levels of pain during partners' touch compared with all other control conditions. Furthermore, taking into account the dyadic interaction, only during the touch condition we found 1) a significant relationship between the partners' pain ratings, and 2) a significant negative relationship between the male touchers' empathy and the pain experience of their female partners. The findings highlight the powerful analgesic effect of social touch and suggest that empathy between romantic partners may explain the pain-alleviating effects of social touch.

PERSPECTIVE

Pain research mostly concentrates on different factors around a single pain target, without taking into account various social interactions with the observers. Our findings support the idea that pain perception models should be extended, taking into account some psychological characteristics of observers. Our conclusions are on the basis of advanced statistical methods.

Two-stage genome-wide search for epistasis with implementation to Recombinant Inbred Lines (RIL) populations

OBJECTIVE AND METHODS

This paper proposes an inegrative two-stage genome-wide search for pairwise epistasis on expression quantitative trait loci (eQTL). The traits are clustered into multi-trait complexes that account for correlations between them that may result from common epistasis effects. The search is done by first screening for epistatic regions and then using dense markers within the identified regions, resulting in substantial reduction in the number of tests for epistasis. The FDR is controlled using a hierarchical procedure that accounts for the search structure. Each combination of trait and marker-pair is tested using a model that accounts for both statistical and functional interpretations of epistasis and considers orthogonal effects, such that their contributions to heritability can be estimated individually. We examine the impact of using multi-trait complexes rather than single traits, and of using a hierarchical search for epistasis rather than skipping the initial screen for epistatic regions. We apply the proposed algorithm on Arabidopsis transcription data.

PRINCIPAL FINDINGS

Both epistasis detection power and heritability contributed by epistasis increased when using multi-trait complexes rather than single traits. Epistatic effects common to the eQTLs included in the complexes have higher chance of being identified by analysis of multi-trait complexes, particularly when epistatic effects on individual traits are small. Compared to direct testing for all potential epistatic effects, the hierarchical search was substantially more powerful in detecting epistasis, while controlling the FDR at the desired level. Association in functional roles within genomic regions was observed, supporting an initial screen for epistatic QTLs.

Face or body? Oxytocin improves perception of emotions from facial expressions in incongruent emotional body context

The neuropeptide oxytocin (OT) has been repeatedly reported to play an essential role in the regulation of social cognition in humans in general, and specifically in enhancing the recognition of emotions from facial expressions. The later was assessed in different paradigms that rely primarily on isolated and decontextualized emotional faces. However, recent evidence has indicated that the perception of basic facial expressions is not context invariant and can be categorically altered by context, especially body context, at early perceptual levels. Body context has a strong effect on our perception of emotional expressions, especially when the actual target face and the contextually expected face are perceptually similar. To examine whether and how OT affects emotion recognition, we investigated the role of OT in categorizing facial expressions in incongruent body contexts. Our results show that in the combined process of deciphering emotions from facial expressions and from context, OT gives an advantage to the face. This advantage is most evident when the target face and the contextually expected face are perceptually similar.

[Fever and jaundice... and if it was a leptospirosis. About a case of L. interrogans icterohaemorrhagiae in Northern France]

Leptospirosis is an anthropozoonose, an animal disease transmissible to humans, caused by a spirochete of the genus Leptospira that lives mainly among rodents but also in wetlands. It occurs worldwide, particularly in Asia, Latin America and Africa. In Europe, the incidence is small (except in France and Great Britain, where its frequency has increased in recent years) but the frequency may be underestimated. Some areas overseas are particularly affected. In France, the potential epidemic of leptospirosis is subject to climatic variations, justifying a constant monitoring of the disease provided by the National Reference Centre (CNR) of leptospires. Transmission to humans primarily occurs through contact with environments contaminated by the urine of infected animals. The disease can affect the liver and kidneys (hepatonephritis) as cytolysis, cholestasis and renal failure associated with fever. A coagulopathy usually accompanies the clinical table. Its diagnosis is difficult because of the clinical polymorphism. Early diagnosis of leptospirosis allows effective medical care, improving patient outcomes. This is currently based on gene amplification (PCR) or serology positive by the microscopic agglutination test (MAT), which is the reference method. Its evolution is usually favorable with appropriate antibiotic treatment (aminopenicillin). However 5-10% of symptomatic patients have a severe multisystem defaillance. Nearly a century after the discovery of the causative agent, this zoonosis remains a public health problem, zoonosis priority in terms of virulence, its reporting is mandatory in our country. We report the case of a severe form of hepatonephritis due to water contaminated with Leptospira observed in Northern France.