Using Wearable Digital Devices to Screen Children for Mental Health Conditions: Ethical Promises and Challenges.

In response to a burgeoning pediatric mental health epidemic, recent guidelines have instructed pediatricians to regularly screen their patients for mental health disorders with consistency and standardization. Yet, gold-standard screening surveys to evaluate mental health problems in children typically rely solely on reports given by caregivers, who tend to unintentionally under-report, and in some cases over-report, child symptomology. Digital phenotype screening tools (DPSTs), currently being developed in research settings, may help overcome reporting bias by providing objective measures of physiology and behavior to supplement child mental health screening. Prior to their implementation in pediatric practice, however, the ethical dimensions of DPSTs should be explored. Herein, we consider some promises and challenges of DPSTs under three broad categories: accuracy and bias, privacy, and accessibility and implementation. We find that DPSTs have demonstrated accuracy, may eliminate concerns regarding under- and over-reporting, and may be more accessible than gold-standard surveys. However, we also find that if DPSTs are not responsibly developed and deployed, they may be biased, raise privacy concerns, and be cost-prohibitive. To counteract these potential shortcomings, we identify ways to support the responsible and ethical development of DPSTs for clinical practice to improve mental health screening in children.

How Much Data Is Enough? A Reliable Methodology to Examine Long-Term Wearable Data Acquisition in Gait and Postural Sway.

Wearable sensors facilitate the evaluation of gait and balance impairment in the free-living environment, often with observation periods spanning weeks, months, and even years. Data supporting the minimal duration of sensor wear, which is necessary to capture representative variability in impairment measures, are needed to balance patient burden, data quality, and study cost. Prior investigations have examined the duration required for resolving a variety of movement variables (e.g., gait speed, sit-to-stand tests), but these studies use differing methodologies and have only examined a small subset of potential measures of gait and balance impairment. Notably, postural sway measures have not yet been considered in these analyses. Here, we propose a three-level framework for examining this problem. Difference testing and intra-class correlations (ICC) are used to examine the agreement in features computed from potential wear durations (levels one and two). The association between features and established patient reported outcomes at each wear duration is also considered (level three) for determining the necessary wear duration. Utilizing wearable accelerometer data continuously collected from 22 persons with multiple sclerosis (PwMS) for 6 weeks, this framework suggests that 2 to 3 days of monitoring may be sufficient to capture most of the variability in gait and sway; however, longer periods (e.g., 3 to 6 days) may be needed to establish strong correlations to patient-reported clinical measures. Regression analysis indicates that the required wear duration depends on both the observation frequency and variability of the measure being considered. This approach provides a framework for evaluating wear duration as one aspect of the comprehensive assessment, which is necessary to ensure that wearable sensor-based methods for capturing gait and balance impairment in the free-living environment are fit for purpose.

Incorporating single-arm evidence into a network meta-analysis using aggregate level matching: Assessing the impact.

Increasingly, single-armed evidence is included in health technology assessment submissions when companies are seeking reimbursement for new drugs. While it is recognized that randomized controlled trials provide a higher standard of evidence, these are not available for many new agents that have been granted licenses in recent years. Therefore, it is important to examine whether alternative strategies for assessing this evidence may be used. In this work, we examine approaches to incorporating single-armed evidence formally in the evaluation process. We consider matching aggregate level covariates to comparator arms or trials and including this evidence in a network meta-analysis. We consider two methods of matching: (i) we include the chosen matched arm in the data set itself as a comparator for the single-arm trial; (ii) we use the baseline odds of an event in a chosen matched trial to use as a plug-in estimator for the single-arm trial. We illustrate that the synthesis of evidence resulting from such a setup is sensitive to the between-study variability, formulation of the prior for the between-design effect, weight given to the single-arm evidence, and extent of the bias in single-armed evidence. We provide a flowchart for the process involved in such a synthesis and highlight additional sensitivity analyses that should be carried out. This work was motivated by a hepatitis C data set, where many agents have only been examined in single-arm studies. We present the results of our methods applied to this data set.

Health-related quality of life in hepatitis C patients who achieve sustained virological response to direct-acting antivirals: a comparison with the general population.

PURPOSE: To compare health-related quality of life (HRQoL) between hepatitis C patients who achieve sustained virological response (SVR) to direct-acting antivirals and a sex- and age-paired sample of the general population. METHODS: HRQoL was evaluated in patients recruited in Navarre, Spain, from May 2016 to April 2017 at baseline and after SVR, using the EQ-5D-5L questionnaire. Both results were compared to those of general population of the same sex and age obtained from the 2011/12 National Health Survey in Spain. Observed/expected (O/E) ratios for health dimensions and differences between O-E in EQ-5D utility and visual analogical scale (VAS) scores were calculated. RESULTS: 206 patients were studied. Before treatment, patients had more problems than the general population in every domain of EQ-5D-5L, except in self-care dimension (O/E = 1.1). After SVR, patients continued having more limitation, especially for usual activities (O/E = 3.1), anxiety/depression (O/E = 2.8) and EQ-5D utility (- 0.086, p < 0.001); however, differences in VAS score between patients and general population disappeared (74.8 vs 76.5, p = 0.210). F0-F1 patients with SVR had minor differences with the general population in EQ-5D-5L dimensions, utility and VAS score. Although cirrhotic patients also reduced that difference, they still had worse HRQoL, especially in usual activities, self-care, EQ-5D utility (- 0.152, p < 0.001) and VAS score (- 8.5, p = 0.005). CONCLUSIONS: HRQoL of chronic hepatitis C patients remains lower than that of the general population despite viral clearance, with primary problems in usual activities and anxiety/depression. Knowledge of these on-going problems despite cure serves to guide healthcare interventions and patient's follow-up.

Effectiveness of triple therapy with direct-acting antivirals for hepatitis C genotype 1 infection: application of propensity score matching in a national HCV treatment registry.

BACKGROUND: Observational studies are used to measure the effectiveness of an intervention in non-experimental, real world scenarios at the population level and are recognised as an important component of the evidence pyramid. Such data can be accrued through prospective cohort studies and a patient registry is a proven method for this type of study. The national hepatitis C (HCV) registry was established in Ireland in 2012 with the aim of monitoring the clinical and economic outcomes from new, high cost regimens for the treatment of HCV infection. A sustained virological response (SVR) 24 weeks following completion of therapy with interferon-containing regimens is considered a cure. Non-randomisation in these studies can result in confounding or selection bias. Propensity score (PS) matching is one of a number of statistical tools that can be used to mitigate the effects of confounding in observational studies. METHODS: We analysed the data of 309 patients who underwent triple therapy treatment with telaprevir (TPV) in combination with pegylated-interferon and ribavirin (PR) or boceprevir (BOC)/PR between June 2012 and December 2014. The decision to initiate treatment and the selection of the treatment regimen was at the discretion of the physician. To adjust for confounding, three approaches to propensity score matching were assessed Adjusted sustained-virological response rates (SVR), odds ratios, p-values and 95% confidence intervals were calculated from the three PS matched dataset. RESULTS: Prior to matching, the unadjusted sustained virological response rates 24 weeks after treatment complete (SVR24) were 74% (n = 158/215) and 61% (n = 57/94) for telaprevir/PR and boceprevir/PR, respectively. After matching, adjusted SVR24 rates were between 73-74% and 60-61% for telaprevir/PR and boceprevir/PR, respectively. CONCLUSION: Efficacy rates were comparable with those reported in pivotal clinical trials and real world studies. After adjusting for confounding, we conclude that there was no difference in treatment effect after PS matching. The small sample size limits the conclusions that can be made about the effect of PS matching. Propensity score adjustment remains a tool that can be applied to future analysis, however, we suggest, where possible, using a larger sample size in order to reduce the uncertainty around the outcomes.

Determinants of HIV outpatient service utilization: a systematic review.

Demands on HIV services are increasing as a consequence of the increased life-expectancy of HIV patients in the highly active antiretroviral therapy era. Understanding the factors that influence utilization of ambulatory HIV services is useful for planning service provision. This study reviewed factors associated with utilization of hospital based HIV out-patient services. Studies reporting person-based utilization rates of HIV-specific outpatient services broken down by patient or healthcare characteristics were eligible for inclusion. The Andersen Behavioral Model was used to organize the information extracted into pre-disposing, enabling and need components. Ten studies were included in the final review. Older age, private insurance, urban residence, lower CD4 counts, a diagnosis of AIDS, or anti-retroviral treatment were associated with higher utilization rates. The results of this review are consistent with existing knowledge regarding HIV patients' use of health services. Little information was identified on the influence of health service characteristics on utilization of out-patient services.

Hepatitis C in the era of direct-acting antivirals: real-world costs of untreated chronic hepatitis C; a cross-sectional study.

BACKGROUND: Recent advances in Hepatitis C therapeutics offer the possibility of cure but will be expensive. The cost of treatment may be partially offset by the avoidance of advanced liver disease. We performed a micro-costing study of the ambulatory healthcare utilisation of patients with Hepatitis C supplemented with inpatient diagnosis related group costs. METHODS: The staff utilisation costs associated with a Hepatitis C ambulatory visit were measured and combined with the costs of investigations to establish a mean cost per consultation. An annualised estimate of cost was produced by multiplying this by the number of consultations accessed, stratified by degree of liver impairment. Inpatient costs were established by identifying the number of inpatient episodes and multiplying by Irish diagnosis related group costs. Non-parametric bootstrapping was performed to derive mean and 95%CI values. RESULTS: Two hundred and twenty-five patients were identified. The cost of an outpatient medical review was €136 (€3.60 SD). The cost of a Hepatitis C nursing review was €128 (€7.30 SD). The annual mean costs of care were as follows (95%CI): Mild €398 (€336, €482), Moderate €417(€335, €503), Compensated cirrhosis €1790 (€990, €3164), Decompensated cirrhosis €8302 (€3945, €14,637), Transplantation Year 1 €137,176 (€136,024, €138,306), Transplantation after Year 1 €5337 (€4942, €5799), Hepatocellular carcinoma €21,992 (€15,222, €29,467), Sustained virological response €44 (€16, €73). CONCLUSIONS: The direct medical cost associated with Hepatitis C care in Ireland is substantial and increases exponentially with progression of liver disease. The follow-up costs of patients with a sustained virological response in this cohort were low in comparison to patients with chronic infection.

The relative efficacy of boceprevir and telaprevir in the treatment of hepatitis C virus genotype 1.

BACKGROUND: The licensing of direct-acting antivirals heralds a new era in the treatment of hepatitis C virus (HCV) genotype 1. We undertook a mixed treatment comparison to examine the relative efficacy among current treatments for HCV. METHODS: A systematic literature review identified relevant studies. Meta-analyses were planned in treatment-naive and treatment-experienced patients. Study arms that evaluated telaprevir or boceprevir for unlicensed durations or without both pegylated interferon and ribavirin at standard doses were excluded. A Bayesian mixed treatment comparison model was fitted for each patient population. RESULTS: Four hundred ninety-nine studies were identified. Ten met inclusion criteria. In the subgroup of prior treatment "relapsers," telaprevir had greater relative efficacy than boceprevir (odds ratio [OR], 2.61 [95% confidence interval {CI}, 1.24-5.52]). There were no statistically significant differences detected in relative efficacy for other patient categories. Treatment-naive patients: boceprevir vs standard of care (n = 1417) (OR, 3.06 [95% CI, 2.43-3.87]); telaprevir vs standard of care (n = 1309) (OR, 3.24 [95% CI, 2.56-4.10]); telaprevir vs boceprevir (OR, 1.06 [95% CI, 0.75-1.47]). Total treatment-experienced population: boceprevir vs standard of care (n = 604) (OR, 6.53 [95% CI, 4.20-10.32]); telaprevir vs standard of care (n = 891) (OR, 8.32 [5.69-12.36]); telaprevir vs boceprevir (OR, 1.27 [95% CI, .71-2.30]). CONCLUSIONS: Telaprevir had greater relative efficacy than boceprevir in patients who had previously relapsed. There was insufficient evidence to detect a difference in treatment outcomes between the 2 agents in the overall population. It was not possible to determine relative efficacy for subgroups such as patients with cirrhosis owing to small numbers.

Understanding the factors influencing community pharmacist retention - A qualitative study.

Background: Shortages in healthcare workers affects the overall delivery and effectiveness of the provision of healthcare. There are currently insufficient pharmacists working in the community sector in Ireland. While several studies have reported on the factors leading to retention in the medical and nursing profession, there is an absence of robust research examining retention within the pharmacist workforce in Ireland. Objective: To identify and understand the range of factors currently at play in the community pharmacy sector in Ireland which influence the decision-making process for pharmacists deciding whether or not to continue to practice as a community pharmacist. Method: A cross-sectional qualitative descriptive study was used to investigate the factors influencing community pharmacist retention as elicited from the lived experiences of 23 pharmacists. Study recruitment was undertaken using both convenience and purposive sampling. Qualitative content analysis was used to analyze the interview data to identify and explore themes. Results: A broad and diverse range of factors were identified as affecting community pharmacist retention including working conditions, career fulfilment and progression, regulatory and administrative burden, the commercial focus within community practice, lack of representation and their overall health and well-being. Conclusion: The findings show that there are a number of factors which either individually or cumulatively influence a pharmacist's decision to stay in or leave community practice. Various areas for change were identified, which if addressed are considered likely to improve retention in the sector. These include enhanced terms and working conditions, better acknowledgement and resourcing of professional activities, improved opportunities for career progression, reforms to the regulatory model including the personal accountability of a supervising pharmacist for all of the pharmacy's professional activities, a more streamlined model of reimbursement and more effective collective representation.

Economic evaluation of a collaborative model of pharmaceutical care in an Irish hospital: cost-utility analysis.

Background: A complex, collaborative pharmaceutical care intervention including medication review and reconciliation demonstrated a statistically significant reduction in the prevalence of discharge medication error and improved quality of prescribing for hospitalised adults.  This study sought to assess the cost-effectiveness of this intervention. Methods: A cost-utility analysis was undertaken using a decision-analytic framework. The evaluation was undertaken from the Health Service Executive's perspective, the payer for primary and secondary care settings. Direct costs associated with managing hypothetical harm consequent to intercepted discharge medication error and consequences in terms of quality-adjusted life years loss were key input parameters. Analysis was structured within a decision tree model in Microsoft Excel® populated with consequences as utilities, estimated costs using macro- and micro-costing approaches, and event probabilities generated from the original study. Incremental analysis, one-way and probabilistic sensitivity analyses were performed. Results: The results of analysis for the base-care demonstrated that the intervention dominated standard care with an incremental cost-effectiveness ratio of -€36,537.24/quality-adjusted life year, indicating that the intervention is less costly and more effective. The one-way and probabilistic sensitivity analyses both demonstrated that the intervention dominated standard care. The model was relatively robust to variation in input parameters through one-way sensitivity analysis. The cost of discharge medication error and effect parameters relating to standard care were most sensitive to change. Discussion: The analysis demonstrated the cost-effectiveness of a complex pharmaceutical intervention which will support decision-making regarding implementation. This is the first cost-utility analysis of a complex, collaborative pharmaceutical care intervention, adding to the scant evidence-base in the field.

Potential costs and consequences associated with medication error at hospital discharge: an expert judgement study.

OBJECTIVES: Assessing the cost-effectiveness of complex pharmaceutical care interventions and medication error outcomes is hindered by lack of available data on actual outcomes consequent to errors that were intercepted for patient safety reasons. Expert judgement is an approach to acquire data regarding unknown parameters in an economic model which are otherwise insufficient or not possible to obtain. The aim of this paper is to describe a method to approach this problem using findings from a single intervention study and to calculate the potential costs and consequences associated with discharge medication error. METHODS: Using data from a previous intervention study, the hypothetical consequences of medication error(s) at hospital discharge, in terms of diagnosis, healthcare resource utilisation and impact on health-related quality of life, were identified by expert judgement of anonymised cases. Primary healthcare utilisation costs were derived from published tariffs, inpatient costs were derived by simulation in the hospital discharge activity database test environment and the difference between adjudicated baseline and posterror health state was expressed as quality-adjusted life year (QALY) decrement. RESULTS: Four experts provided judgement on 81 cases. Of these, 75 were judged to have potential clinical consequences. Between 56 and 69 of the 81 cases were variably judged to require remedial healthcare utilisation. The mean calculated cost per case (representing an individual patient), based on all 81 cases, was €1009.58, 95% CI 726.64 to 1585.67. The mean QALY loss was 0.03 (95% CI 0.01 to 0.05). CONCLUSION: An expert judgement process proved feasible and useful to estimate financial cost and QALY loss associated with hospital discharge medication error. These estimates will be employed in model-based economic evaluation. This method could be transferred to other prospective observational patient safety research which seeks to assess value for money of complex interventions.

Digital Phenotypes of Instability and Fatigue Derived From Daily Standing Transitions in Persons With Multiple Sclerosis.

Impairment in persons with multiple sclerosis (PwMS) can often be attributed to symptoms of motor instability and fatigue. Symptom monitoring and queued interventions often target these symptoms. Clinical metrics are currently limited to objective physician assessments or subjective patient reported measures. Recent research has turned to wearables for improving the objectivity and temporal resolution of assessment. Our group has previously observed wearable assessment of supervised and unsupervised standing transitions to be predictive of fall-risk in PwMS. Here we extend the application of standing transition quantification to longitudinal home monitoring of symptoms. Subjects (N=23) with varying degrees of MS impairment were recruited and monitored with accelerometry for a total of  âˆ¼  6 weeks each. These data were processed using a preexisting framework, applying a deep learning activity classifier to isolate periods of standing transition from which descriptive features were extracted for analysis. Participants completed daily and biweekly assessments describing their symptoms. From these data, Canonical Correlation Analysis was used to derive digital phenotypes of MS instability and fatigue. We find these phenotypes capable of distinguishing fallers from non-fallers, and further that they demonstrate a capacity to characterize symptoms at both daily and sub-daily resolutions. These results represent promising support for future applications of wearables, which may soon augment or replace current metrics in longitudinal monitoring of PwMS.

Chest-Based Wearables and Individualized Distributions for Assessing Postural Sway in Persons With Multiple Sclerosis.

Typical assessments of balance impairment are subjective or require data from cumbersome and expensive force platforms. Researchers have utilized lower back (sacrum) accelerometers to enable more accessible, objective measurement of postural sway for use in balance assessment. However, new sensor patches are broadly being deployed on the chest for cardiac monitoring, opening a need to determine if measurements from these devices can similarly inform balance assessment. Our aim in this work is to validate postural sway measurements from a chest accelerometer. To establish concurrent validity, we considered data from 16 persons with multiple sclerosis (PwMS) asked to stand on a force platform while also wearing sensor patches on the sacrum and chest. We found five of 15 postural sway features derived from the chest and sacrum were significantly correlated with force platform-derived features, which is in line with prior sacrum-derived findings. Clinical significance was established using a sample of 39 PwMS who performed eyes-open, eyes-closed, and tandem standing tasks. This cohort was stratified by fall status and completed several patient-reported measures (PRM) of balance and mobility impairment. We also compared sway features derived from a single 30-second period to those derived from a one-minute period with a sliding window to create individualized distributions of each postural sway feature (ID method). We find traditional computation of sway features from the chest is sensitive to changes in PRMs and task differences. Distribution characteristics from the ID method establish additional relationships with PRMs, detect differences in more tasks, and distinguish between fall status groups. Overall, the chest was found to be a valid location to monitor postural sway and we recommend utilizing the ID method over single-observation analyses.

The ChAMP App: A Scalable mHealth Technology for Detecting Digital Phenotypes of Early Childhood Mental Health.

Childhood mental health problems are common, impairing, and can become chronic if left untreated. Children are not reliable reporters of their emotional and behavioral health, and caregivers often unintentionally under- or over-report child symptoms, making assessment challenging. Objective physiological and behavioral measures of emotional and behavioral health are emerging. However, these methods typically require specialized equipment and expertise in data and sensor engineering to administer and analyze. To address this challenge, we have developed the ChAMP (Childhood Assessment and Management of digital Phenotypes) System, which includes a mobile application for collecting movement and audio data during a battery of mood induction tasks and an open-source platform for extracting digital biomarkers. As proof of principle, we present ChAMP System data from 101 children 4-8 years old, with and without diagnosed mental health disorders. Machine learning models trained on these data detect the presence of specific disorders with 70-73% balanced accuracy, with similar results to clinical thresholds on established parent-report measures (63-82% balanced accuracy). Features favored in model architectures are described using Shapley Additive Explanations (SHAP). Canonical Correlation Analysis reveals moderate to strong associations between predictors of each disorder and associated symptom severity (r = .51-.83). The open-source ChAMP System provides clinically-relevant digital biomarkers that may later complement parent-report measures of emotional and behavioral health for detecting kids with underlying mental health conditions and lowers the barrier to entry for researchers interested in exploring digital phenotyping of childhood mental health.

Toward Digital Phenotypes of Early Childhood Mental Health via Unsupervised and Supervised Machine Learning.

Childhood mental health disorders such as anxiety, depression, and ADHD are commonly-occurring and often go undetected into adolescence or adulthood. This can lead to detrimental impacts on long-term wellbeing and quality of life. Current parent-report assessments for pre-school aged children are often biased, and thus increase the need for objective mental health screening tools. Leveraging digital tools to identify the behavioral signature of childhood mental disorders may enable increased intervention at the time with the highest chance of long-term impact. We present data from 84 participants (4-8 years old, 50% diagnosed with anxiety, depression, and/or ADHD) collected during a battery of mood induction tasks using the ChAMP System. Unsupervised Kohonen Self-Organizing Maps (SOM) constructed from movement and audio features indicate that age did not tend to explain clusters as consistently as gender within task-specific and cross-task SOMs. Symptom prevalence and diagnostic status also showed some evidence of clustering. Case studies suggest that high impairment (>80th percentile symptom counts) and diagnostic subtypes (ADHD-Combined) may account for most behaviorally distinct children. Based on this same dataset, we also present results from supervised modeling for the binary classification of diagnoses. Our top performing models yield moderate but promising results (ROC AUC .6-.82, TPR .36-.71, Accuracy .62-.86) on par with our previous efforts for isolated behavioral tasks. Enhancing features, tuning model parameters, and incorporating additional wearable sensor data will continue to enable the rapid progression towards the discovery of digital phenotypes of childhood mental health.Clinical Relevance- This work advances the use of wearables for detecting childhood mental health disorders.

Bridging the gap between healthcare professions' regulation and practice: the "lived experience" of community pharmacists in Ireland following regulatory change.

BACKGROUND: Reforms to models of health and care regulation internationally have adapted to address the challenges associated with regulating healthcare professionals. Pharmacists in Ireland entered a new era of regulation with the enactment of the Pharmacy Act in 2007 which significantly updated the law regulating pharmacy in Ireland and expanded the regulatory scope considerably. An earlier study in 2017 examined the experiences of 20 community pharmacists of the Act. This follow-up study aimed to expand the scope of the original study to all community pharmacists in Ireland, to report their "lived experience" of the regulatory model introduced by the Act, assessing its impact on their professional practice using the principles of "better regulation". METHODS: Survey methodology was used to assess the perception of all community pharmacists registered with the Pharmaceutical Society of Ireland of the Act, as implemented, on their practice using an experimental design based on the seven principles of "Better Regulation". Descriptive statistics analyzed quantitative responses while answers from open-ended questions were analyzed using a combination of a modified framework analysis and a qualitative content analysis. RESULTS: Respondents agreed that the Act was necessary, although its implementation by the regulator was largely not viewed as fulfilling the remaining "Better Regulation" principles of being effective, proportional, consistent, agile, accountable and transparent. In particular, its proportionality was questioned. This resulted in pharmacists perceiving that their professional competency to act in the best interests of their patients was not appropriately acknowledged by the regulator, which in turn compromised their ability to provide optimal care for their patients. CONCLUSION: While healthcare professional regulation must primarily be concerned with public protection, it must also have regard to its impact on those delivering healthcare services. The findings highlight the challenge internationally of balancing rigidity and flexibility in professional health and care regulation, and the importance of a regulatory conversation occurring between those regulating and those regulated. This would serve to promote mutual learning and understanding to create a responsive approach to regulation, underpinned by mutual trust, effective risk assessment and adherence to the principles of "Better Regulation".

A Digital Therapeutic Intervention Delivering Biofeedback for Panic Attacks (PanicMechanic): Feasibility and Usability Study.

BACKGROUND: Panic attacks (PAs) are an impairing mental health problem that affects >11% of adults every year. PAs are episodic, and it is difficult to predict when or where they may occur; thus, they are challenging to study and treat. OBJECTIVE: The aim of this study is to present PanicMechanic, a novel mobile health app that captures heart rate-based data and delivers biofeedback during PAs. METHODS: In our first analysis, we leveraged this tool to capture profiles of real-world PAs in the largest sample to date (148 attacks from 50 users). In our second analysis, we present the results from a pilot study to assess the usefulness of PanicMechanic as a PA intervention (N=18). RESULTS: The results demonstrate that heart rate fluctuates by about 15 beats per minute during a PA and takes approximately 30 seconds to return to baseline from peak, cycling approximately 4 times during each attack despite the consistently decreasing anxiety ratings. Thoughts about health were the most common trigger and potential lifestyle contributors include slightly worse stress, sleep, and eating habits and slightly less exercise and drug or alcohol consumption than typical. CONCLUSIONS: The pilot study revealed that PanicMechanic is largely feasible to use but would be made more so with modifications to the app and the integration of consumer wearables. Similarly, participants found PanicMechanic useful, with 94% (15/16) indicating that they would recommend PanicMechanic to others who have PAs. These results highlight the need for future development and a controlled trial to establish the effectiveness of this digital therapeutic for preventing PAs.

UVM KID Study: Identifying Multimodal Features and Optimizing Wearable Instrumentation to Detect Child Anxiety.

Anxiety and depression, collectively known as internalizing disorders, begin as early as the preschool years and impact nearly 1 out of every 5 children. Left undiagnosed and untreated, childhood internalizing disorders predict later health problems including substance abuse, development of comorbid psychopathology, increased risk for suicide, and substantial functional impairment. Current diagnostic procedures require access to clinical experts, take considerable time to complete, and inherently assume that child symptoms are observable by caregivers. Multi-modal wearable sensors may enable development of rapid point-of-care diagnostics that address these challenges. Building on our prior work, here we present an assessment battery for the development of a digital phenotype for internalizing disorders in young children and an early feasibility case study of multi-modal wearable sensor data from two participants, one of whom has been clinically diagnosed with an internalizing disorder. Results lend support that sacral movement responses and R-R interval during a short stress-induction task may facilitate child diagnosis. Multi-modal sensors measuring movement and surface biopotentials of the chest and trapezius are also shown to have significant redundancy, introducing the potential for sensor optimization moving forward. Future work aims to further optimize sensor placement, signals, features, and assessments to enable deployment in clinical practice. Clinical Relevance- This work considers the development and optimization of technologies for improving the identification of children with internalizing disorders.

Beyond consumption: a qualitative investigation of hospital clinician attitudes to receiving feedback on antimicrobial prescribing quality.

Background: Feedback on optimal antimicrobial prescribing to clinicians is an important strategy to ensure antimicrobial stewardship (AMS) in the hospital setting. Objective: To explore the perceptions of antimicrobial prescribing feedback among clinicians in acute care. Study design: Prospective qualitative design. Setting: A large inner-city tertiary referral center in Dublin, Ireland. Participants: Clinicians were recruited from the hospital clinician population. Methods: A qualitative study was conducted with a purposive sample of multidisciplinary clinicians. Focus groups and semistructured interviews were used to collect data that were analyzed inductively to identify themes. Results: In total, 30 clinicians from medical, surgical, nursing and pharmacy professions participated in the study. We identified 5 themes: (1) antimicrobial consumption perceived as a proxy measure for prescribing quality; (2) lack of connection between antimicrobial prescribing and patient outcomes; (3) relevance and impact of antimicrobial prescribing feedback associated with professional role; (4) attitudes regarding feedback as an AMS strategy; and (5) knowledge regarding AMS, including antimicrobial prescribing quality measures. Conclusions: Focused feedback on antimicrobial prescribing, with clear goals for improvement, could serve as a useful AMS strategy among clinicians in the acute-care setting. The need for further education and training in AMS was also identified.