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Navigating cancer care is complex and is exacerbated by pre-existing comorbidities managed by multiple providers. In this quality improvement study, we evaluated changes in perceived care coordination, navigation, and chronic illness care with community health worker (CHW) and mHealth support among Black breast cancer and prostate cancer patients with hypertension and/or diabetes. We collected patient and provider surveys on chronic illness care coordination at baseline and six months and found improvements in multiple domains. These findings support engaging CHWs to improve care coordination among cancer patients with comorbidities and demonstrate a use case of importance with emerging navigation reimbursement policies.
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INTRODUCTION: Evidence-based strategies are needed to sustain improvements in outcomes following diabetes care management (DCM) programs. We examined the impact of Boot Camp-Plus (BC-Plus), an innovative sustaining strategy, on A1C among adults with type 2 diabetes completing a 3-month Diabetes Boot Camp (DBC). This health system sponsored program consisted of diabetes self-management education and support, medical nutrition therapy and antihyperglycemic medications management. RESEARCH DESIGN AND METHODS: From March 2019 to July 2021, adult DBC completers with Medicare or a health system Medicaid or employee commercial plan were enrolled in BC-Plus for 9 months. DBC completers not meeting insurance eligibility or who declined to participate in BC-Plus acted as controls. During the first 3 months, BC-Plus participants received ongoing daily remote blood glucose (BG) monitoring; and during all 9 months, they received monthly check-in calls with BG review by a medical assistant who addressed needs for supplies/drugs, whether participants were checking BGs, and self-care encouragement. Escalation to a nurse practitioner occurred if the monthly BG trend was >200 mg/dL and/or several BG <80 mg/dL and/or new A1C >9.0% were identified. A1C was followed for an additional 9 months post-BC-Plus. A longitudinal mixed effects analysis was used to assess change in A1C from month 0 to month 21 of follow-up between BC-Plus participants versus controls. RESULTS: A total of 838 DCM completers were identified, among whom 281 joined the BC-Plus intervention and 557 acted as controls. Mean age was 55.9 years; 58.2% were women; 66.2% were black; and 30.6% insured by Medicare. BC-Plus participants experienced significantly lower A1C compared with controls and remained below 8.0% to month 18. CONCLUSIONS: Among completers of a 3-month DCM program, a low intensity 9-month sustaining strategy maintained A1C under 8.0% (HEDIS (Healthcare Effectiveness Data and Information Set) threshold for diabetes control) compared with controls for 15 months after completion of the initial DCM intervention.
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Diabetes Mellitus, Type 2 , Adult , Humans , Female , Aged , United States , Middle Aged , Male , Diabetes Mellitus, Type 2/drug therapy , Glycated Hemoglobin , Feasibility Studies , Blood Glucose/analysis , MedicareABSTRACT
OBJECTIVE: To investigate the influence of the degree of circadian adaptation to night work on sleep architecture following night shift. METHODS: Thirty four night workers (11 females; 33.8 ± 10.1years) completed a simulated night shift following 2-7 typical night shifts. Participants completed a laboratory-based simulated night shift (21:00-07:00 hours), followed by a recovery sleep opportunity (â¼09:00-17:00 hours), recorded using polysomnography. Urinary 6-sulphatoxymelatonin (aMT6s) rhythm acrophase was used as a marker of circadian phase. Sleep duration and architecture were compared between individuals with aMT6s acrophase before (unadapted group, n = 22) or after (partially adapted group, n = 12) bedtime. RESULTS: Bedtime occurred on average 2.16 hours before aMT6s acrophase in the partially adapted group and 3.91 hours after acrophase in the unadapted group. The partially adapted group had more sleep during the week before the simulated night than the unadapted group (6.47 ± 1.02 vs. 5.26 ± 1.48 hours, p = .02). After the simulated night shift, both groups had similar total sleep time (partially adapted: 6.68 ± 0.80 hours, unadapted: 6.63 ± 0.88 hours, p > .05). The partially adapted group had longer total rapid eye movement sleep duration than the unadapted group (106.79 ± 32.05 minutes vs. 77.90 ± 28.86 minutes, p = .01). After 5-hours, rapid eye movement sleep accumulation was higher in the partially adapted compared to the unadapted group (p = .02). Sleep latency and other stages were not affected by circadian adaptation. DISCUSSION: Partial circadian adaptation to night shift was associated with longer rapid eye movement sleep duration during daytime sleep, highlighting the influence of entrainment between the sleep-wake cycle and the circadian pacemaker in night workers. The findings have important implications for sleep and subsequent alertness associated with shift work.
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Objective: Given the bidirectional relationship between type 2 diabetes and periodontal disease, this study sought to compile the available data regarding the relationship between home oral hygiene, specifically toothbrushing, and glycemic control and oral health in people with type 2 diabetes. Methods: A systematic scoping review was conducted using a combination of controlled vocabulary and keyword terms for type 2 diabetes and home oral care in PubMed and CINHAL. Publications from the past 20 years were considered for inclusion. Study data were summarized. Results: A total of 11 studies met our inclusion criteria. In all survey research identified, self-report of more frequent toothbrushing in people with type 2 diabetes was always found to be associated with self-report of better glycemic control and was often associated with better clinician-conducted measures oral health. In the interventional studies identified, health coaching about oral health was associated with improvements in glycemic control, and health coaching compared with health education was found to be associated with enhanced improvement in glycemic control and self-reported toothbrushing behavior. Conclusion: The available data suggest that improved engagement in toothbrushing behavior may be associated with improved oral health and better glycemic control in people with type 2 diabetes. Whether improvement in glycemic control is a direct result of change to the oral environment, succeeding with one behavior change stimulating engagement in other health behavior changes, a combination of the two, or something else cannot be determined from this review. Additional studies are needed to further explore the potential for oral health coaching to improve the well-being of people with type 2 diabetes.
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OBJECTIVE: examine the prevalence of driver distraction in naturalistic driving when implementing European New Car Assessment Program (Euro NCAP)-defined distraction behaviours. BACKGROUND: The 2023 introduction of Occupant Status monitoring (OSM) into Euro NCAP will accelerate uptake of Driver State Monitoring (DSM). Euro NCAP outlines distraction behaviours that DSM must detect to earn maximum safety points. Distraction behaviour prevalence and driver alerting and intervention frequency have yet to be examined in naturalistic driving. METHOD: Twenty healthcare workers were provided with an instrumented vehicle for approximately two weeks. Data were continuously monitored with automotive grade DSM during daily work commutes, resulting in 168.8 hours of driver head, eye and gaze tracking. RESULTS: Single long distraction events were the most prevalent, with .89 events/hour. Implementing different thresholds for driving-related and driving-unrelated glance regions impacts alerting rates. Lizard glances (primarily gaze movement) occurred more frequently than owl glances (primarily head movement). Visual time-sharing events occurred at a rate of .21 events/hour. CONCLUSION: Euro NCAP-described driver distraction occurs naturalistically. Lizard glances, requiring gaze tracking, occurred in high frequency relative to owl glances, which only require head tracking, indicating that less sophisticated DSM will miss a substantial amount of distraction events. APPLICATION: This work informs OEMs, DSM manufacturers and regulators of the expected alerting rate of Euro NCAP defined distraction behaviours. Alerting rates will vary with protocol implementation, technology capability, and HMI strategies adopted by the OEMs, in turn impacting safety outcomes, user experience and acceptance of DSM technology.
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BACKGROUND: Glucose-guided eating (GGE) improves metabolic markers of chronic disease risk, including insulin resistance, in adults without diabetes. GGE is a timed eating paradigm that relies on experiencing feelings of hunger and having a preprandial glucose level below a personalized threshold computed from 2 consecutive morning fasting glucose levels. The dawn phenomenon (DP), which results in elevated morning preprandial glucose levels, could cause typically derived GGE thresholds to be unacceptable or ineffective among people with type 2 diabetes (T2DM). OBJECTIVE: The aim of this study is to quantify the incidence and day-to-day variability in the magnitude of DP and examine its effect on morning preprandial glucose levels as a preliminary test of the feasibility of GGE in adults with T2DM. METHODS: Study participants wore a single-blinded Dexcom G6 Pro continuous glucose monitoring (CGM) system for up to 10 days. First and last eating times and any overnight eating were reported using daily surveys over the study duration. DP was expressed as a dichotomous variable at the day level (DP day vs non-DP day) and as a continuous variable reflecting the percent of days DP was experienced on a valid day. A valid day was defined as having no reported overnight eating (between midnight and 6 AM). ∂ Glucose was computed as the difference in nocturnal glucose nadir (between midnight and 6 AM) to morning preprandial glucose levels. ∂ Glucose ≥20 mg/dL constituted a DP day. Using multilevel modeling, we examined the between- and within-person effects of DP on morning preprandial glucose and the effect of evening eating times on DP. RESULTS: In total, 21 adults (59% female; 13/21, 62%) with non-insulin-treated T2DM wore a CGM for an average of 10.5 (SD 1.1) days. Twenty out of 21 participants (95%) experienced DP for at least 1 day, with an average of 51% of days (SD 27.2; range 0%-100%). The mean ∂ glucose was 23.7 (SD 13.2) mg/dL. People who experience DP more frequently had a morning preprandial glucose level that was 54.1 (95% CI 17.0-83.9; P<.001) mg/dL higher than those who experienced DP less frequently. For within-person effect, morning preprandial glucose levels were 12.1 (95% CI 6.3-17.8; P=.008) mg/dL higher on a DP day than on a non-DP day. The association between ∂ glucose and preprandial glucose levels was 0.50 (95% CI 0.37-0.60; P<.001). There was no effect of the last eating time on DP. CONCLUSIONS: DP was experienced by most study participants regardless of last eating times. The magnitude of the within-person effect of DP on morning preprandial glucose levels was meaningful in the context of GGE. Alternative approaches for determining acceptable and effective GGE thresholds for people with T2DM should be explored and evaluated.
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BACKGROUND: Diabetes self-management education and support (DSMES) improves diabetes outcomes yet remains consistently underutilized. Chatbot technology offers the potential to increase access to and engagement in DSMES. Evidence supporting the case for chatbot uptake and efficacy in people with diabetes (PWD) is needed. METHOD: A diabetes education and support chatbot was deployed in a regional health care system. Adults with type 2 diabetes with an A1C of 8.0% to 8.9% and/or having recently completed a 12-week diabetes care management program were enrolled in a pilot program. Weekly chats included three elements: knowledge assessment, limited self-reporting of blood glucose data and medication taking behaviors, and education content (short videos and printable materials). A clinician facing dashboard identified need for escalation via flags based on participant responses. Data were collected to assess satisfaction, engagement, and preliminary glycemic outcomes. RESULTS: Over 16 months, 150 PWD (majority above 50 years of age, female, and African American) were enrolled. The unenrollment rate was 5%. Most escalation flags (N = 128) were for hypoglycemia (41%), hyperglycemia (32%), and medication issues (11%). Overall satisfaction was high for chat content, length, and frequency, and 87% reported increased self-care confidence. Enrollees completing more than one chat had a mean drop in A1C of -1.04%, whereas those completing one chat or less had a mean increase in A1C of +0.09% (P = .008). CONCLUSION: This diabetes education chatbot pilot demonstrated PWD acceptability, satisfaction, and engagement plus preliminary evidence of self-care confidence and A1C improvement. Further efforts are needed to validate these promising early findings.
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Objective: Development of personalized sleep-wake management tools is critical to improving sleep and functional outcomes for shift workers. The objective of the current study was to test the performance, engagement and usability of a mobile app (SleepSync) for personalized sleep-wake management in shift workers that aid behavioural change and provide practical advice by providing personalized sleep scheduling recommendations and education. Methods: Shift workers (n = 27; 20 healthcare and 7 from other industries) trialled the mobile app for two weeks to determine performance, engagement and usability. Primary outcomes were self-reported total sleep time, ability to fall asleep, sleep quality and perception of overall recovery on days off. Secondary performance outcomes included sleep disturbances (insomnia and sleep hygiene symptoms, and sleep-related impairments) and mood (anxiety, stress and depression) pre- and post-app use. Satisfaction with schedule management, integration into daily routine and influence on behaviour were used to determine engagement, while the usability was assessed for functionality and ease of use of features. Results: Total sleep time (P = .04), ability to fall asleep (P < .001), quality of sleep (P = .001), insomnia (P = .02), sleep hygiene (P = .01), sleep-related impairments (P = .001), anxiety (P = .001), and stress (P = .006) were all improved, with non-significant improvements in recovery on days off (P = .19) and depression (P = .07). All measures of engagement and usability were scored positively by the majority of users. Conclusions: This pilot trial provides preliminary evidence of the positive impact of the SleepSync app in improving sleep and mood outcomes in shift workers, and warrants confirmation in a larger controlled trial.
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INTRODUCTION: Food insecurity (FI) has been associated with adverse health outcomes and increased healthcare expenditures. Many families experienced reduced access to food during the coronavirus disease 2019 (COVID-19) pandemic. A 2019 study revealed that the pre-pandemic prevalence of FI at an urban, tertiary care hospital's emergency department (ED) was 35.3%. We sought to evaluate whether the prevalence of FI in the same ED patient population increased during the COVID-19 pandemic. METHODS: We performed a single-center, observational, survey-based study. Surveys assessing for FI were administered to clinically stable patients presenting to the ED over 25 consecutive weekdays from November-December 2020. RESULTS: Of 777 eligible patients, 379 (48.8%) were enrolled; 158 (41.7%) screened positive for FI. During the pandemic, there was a 18.1% relative increase (or 6.4% absolute increase) in the prevalence of FI in this population (P=0.040; OR=1.309, 95% CI 1.012-1.693). The majority (52.9%) of food-insecure subjects reported reduced access to food due to the pandemic. The most common perceived barriers to access to food were reduced food availability at grocery stores (31%), social distancing guidelines (26.5%), and reduced income (19.6%). CONCLUSION: Our findings suggest that nearly half of the clinically stable patients who presented to our urban ED during the pandemic experienced food insecurity. The prevalence of FI in our hospital's ED patient population increased by 6.4% during the pandemic. Emergency physicians should be aware of rising FI in their patient population so that they may better support patients who must choose between purchasing food and purchasing prescribed medications.
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COVID-19 , Humans , COVID-19/epidemiology , Emergency Service, Hospital , Food Insecurity , Food Supply , PandemicsABSTRACT
OBJECTIVE: To survey persons with type 2 diabetes (PWD) on their experiences with diabetes education to better understand what it means when a PWD says they have "had diabetes education." METHODS: We conducted a cross-sectional descriptive study among a convenience sample of adult PWD receiving primary care and/or diabetes self-management education and support in a mid-Atlantic regional US healthcare system. Descriptive, bivariate, and regression analyses were used to describe and explore the diabetes education experience. RESULTS: Participants (n = 498) were majority female, African American, and non-Hispanic. Half reported having "had diabetes education." Of those, 44% had only one session. Education was most often provided in clinical settings by a dietitian (68%) or doctor (51%), in one-on-one (70%) sessions. While most participants reported receiving core diabetes knowledge, fewer reported education on topics that are not related to their daily routine, such as what to do about diabetes medications when sick. CONCLUSION: The self-reported diabetes education experience varies in content, modality, setting, and education provider. Education receipt is low, and for those who receive education, the amount is low. PRACTICAL IMPLICATIONS: The diabetes education experience may fall short of the comprehensive US National Standards-recommended process. Innovative strategies are needed to address these gaps.
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Diabetes Mellitus, Type 2 , Humans , Adult , Female , Diabetes Mellitus, Type 2/therapy , Cross-Sectional Studies , Self Care , Health Education , Delivery of Health CareABSTRACT
CAG repeat-expansion spinocerebellar ataxias (CAG-SCAs) are genetically defined multisystemic degenerative diseases, resulting in motor symptoms including dysarthria with a substantial impact on daily living. Whilst speech therapy is widely recommended in ataxia, very limited evidence exists for its use. We evaluated the efficacy of a home-delivered, ataxia-tailored biofeedback-driven speech therapy in CAG-SCA in 16 individuals with SCA1, 2, 3, or 6. Treatment was delivered intensively over 20 days. Efficacy was evaluated by blinded ratings of intelligibility (primary) and acoustic measures (secondary) leveraging an intra-individual control design. Intelligibility improved post-treatment (Z = -3.18, p = 0.004) whilst remaining stable prior to treatment (Z = 0.53, p = 1.00).
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Dysarthria , Spinocerebellar Ataxias , Biofeedback, Psychology , Dysarthria/etiology , Dysarthria/therapy , Humans , Speech , Spinocerebellar Ataxias/genetics , Trinucleotide Repeat ExpansionABSTRACT
PURPOSE: The National Standards for Diabetes Self-Management Education and Support (DSMES) provide guidance and evidence-based, quality practice for all DSMES services. Due to the dynamic nature of health care and diabetes research, the National Standards are reviewed and revised approximately every 5 years by key stakeholders and experts within the diabetes care and education community. For each revision, the Task Force is charged with reviewing the current National Standards for appropriateness, relevance, and scientific basis and making updates based on current evidence and expert consensus. In 2021, the group was tasked with reducing administrative burden related to DSMES implementation across diverse care settings. CONCLUSION: The evidence supporting the 2022 National Standards clearly identifies the need to provide person-centered services that embrace cultural differences, social determinants of health, and the ever-increasing technological engagement platforms and systems. Payers are invited to review the National Standards as a tool to inform and modernize DSMES reimbursement requirements and to align with the evolving needs of people with diabetes (PWD) and physicians/other qualified health care professionals. The American Diabetes Association and the Association of Diabetes Care & Education Specialists strongly advocate for health equity to ensure all PWD have access to this critical service proven to improve outcomes both related to and beyond diabetes. The 2022 National Standards update is meant to be a universal document that is easy to understand and can be implemented by the entire health care community. DSMES teams in collaboration with primary care have been shown to be the most effective approach to overcome therapeutic inertia.
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Diabetes Mellitus , Self-Management , Delivery of Health Care , Diabetes Mellitus/therapy , Educational Status , Health Behavior , Humans , Self-Management/educationABSTRACT
BACKGROUND: Self-monitoring of blood glucose (SMBG) has been shown to reduce hemoglobin A1C (HbA1C). Accordingly, guidelines recommend SMBG up to 4-10 times daily for adults with type 2 diabetes (T2DM) on insulin. For persons not on insulin, recommendations are equivocal. Newer technology-enabled blood glucose monitoring (BGM) devices can facilitate remote monitoring of glycemic data. New evidence generated by remote BGM may help to guide best practices for frequency and timing of finger-stick blood glucose (FSBG) monitoring in uncontrolled T2DM patients managed in primary care settings. This study aims to evaluate the impact of SMBG utility and frequency on glycemic outcomes using a novel BGM system which auto-transfers near real-time FSBG data to a cloud-based dashboard using cellular networks. METHODS: Secondary analysis of the intervention arm of a comparative non-randomized trial with propensity-matched chart controls. Adults with T2DM and HbA1C > 9% receiving care in five primary care practices in a healthcare system participated in a 3-month diabetes boot camp (DBC) using telemedicine and a novel BGM to support comprehensive diabetes care management. The primary independent variable was frequency of FSBG. Secondary outcomes included frequency of FSBG by insulin status, distribution of FSBG checks by time of day, and hypoglycemia rates. RESULTS: 48,111 FSBGs were transmitted by 359 DBC completers. Participants performed 1.5 FSBG checks/day; with 1.6 checks/day for those on basal/bolus insulin. Higher FSBG frequency was associated with greater improvement in HbA1C independent of insulin treatment status (p = 0.0003). FSBG frequency was higher in patients treated with insulin (p = 0.003). FSBG checks were most common pre-breakfast and post-dinner. Hypoglycemia was rare (1.2% < 70 mg/dL). CONCLUSIONS: Adults with uncontrolled T2DM achieved significant HbA1C improvement performing just 1.5 FSBGs daily during a technology-enabled diabetes care intervention. Among the 40% taking insulin, this improvement was achieved with a lower FSBG frequency than guidelines recommend. For those not on insulin, despite a lower frequency of FSBG, they achieved a greater reduction in A1C compared to patients on insulin. Low frequency FSBG monitoring pre-breakfast and post-dinner can potentially support optimization of glycemic control regardless of insulin status in the primary care setting. TRIAL REGISTRATION: Trial registration number: NCT02925312 (10/19/2016).
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Blood Glucose Self-Monitoring/methods , Diabetes Mellitus, Type 2/therapy , Primary Health Care , Telemetry/methods , Aged , Blood Glucose , Diabetes Mellitus, Type 2/metabolism , Female , Glycated Hemoglobin/metabolism , Humans , Hypoglycemia/chemically induced , Hypoglycemia/epidemiology , Hypoglycemia/metabolism , Hypoglycemic Agents/therapeutic use , Insulin/therapeutic use , Male , Middle Aged , Non-Randomized Controlled Trials as Topic , Telemedicine , Time FactorsABSTRACT
Stereotypical depictions of speech in cannabis users often suggest slow, laboured output, yet objective evidence supporting this assumption is extremely limited. We know that depressants or hallucinogenic drugs such as cannabis can cause acute changes in communication and speech rate, but the long-lasting effects of cannabis use on speech are not well described. The aim of this study was to investigate speech in individuals with a history of recreational cannabis use compared to non-drug-using healthy controls. Speech samples were collected from a carefully described cohort of 31 adults with a history of cannabis use (but not use of illicit stimulant drugs) and 40 non-drug-using controls. Subjects completed simple and complex speech tasks including a monologue, a sustained vowel, saying the days of the week, and reading a phonetically balanced passage. Audio samples were analysed objectively using acoustic analysis for measures of timing, vocal control, and quality. Subtle differences in speech timing, vocal effort, and voice quality may exist between cannabis and control groups, however data remain equivocal. After controlling for lifetime alcohol and tobacco use and applying a false discovery rate, only spectral tilt (vocal effort and intensity) differed between groups and appeared to change in line with duration of abstinence from cannabis use. Differences between groups may reflect longer term changes to the underlying neural control of speech. Our digital analysis of speech shows there may be a signal differentiating individuals with a history of recreational cannabis use from healthy controls, in line with similar findings from gait and hand function studies.
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Cannabis , Hallucinogens , Adult , Humans , Speech , Speech Acoustics , Speech Production MeasurementABSTRACT
PURPOSE: This study examined the efficacy of a lighting intervention that increased both light intensity and short-wavelength (blue) light content to improve alertness, performance and mood in night shift workers in a chemical plant. PATIENTS AND METHODS: During rostered night shifts, 28 workers (46.0±10.8 years; 27 male) were exposed to two light conditions each for two consecutive nights (~19:00-07:00 h) in a counterbalanced repeated measures design: traditional-spectrum lighting set at pre-study levels (43 lux, 4000 K) versus higher intensity, blue-enriched lighting (106 lux, 17,000 K), equating to a 4.5-fold increase in melanopic illuminance (24 to 108 melanopic illuminance). Participants completed the Karolinska Sleepiness Scale, subjective mood ratings, and the Psychomotor Vigilance Task (PVT) every 2-4 hours during the night shift. RESULTS: A significant main effect of time indicated KSS, PVT mean reaction time, number of PVT lapses (reaction times > 500 ms) and subjective tension, misery and depression worsened over the course of the night shift (p<0.05). Percentage changes in KSS (p<0.05, partial η2=0.14) and PVT mean reaction time (p<0.05, partial η2=0.19) and lapses (p<0.05, partial η2=0.17) in the middle and end of night shift, expressed relative to start of shift, were significantly improved during the lighting intervention compared to the traditional lighting condition. Self-reported mood did not significantly differ between conditions (p>0.05). CONCLUSION: Our findings, showing improvements in alertness and performance with exposure to blue-enriched, increased intensity light, provide support for light to be used as a countermeasure for impaired alertness in night shift work settings.
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STUDY OBJECTIVES: The study aimed to, for the first time, (1) compare sleep, circadian phase, and alertness of intensive care unit (ICU) nurses working rotating shifts with those predicted by a model of arousal dynamics; and (2) investigate how different environmental constraints affect predictions and agreement with data. METHODS: The model was used to simulate individual sleep-wake cycles, urinary 6-sulphatoxymelatonin (aMT6s) profiles, subjective sleepiness on the Karolinska Sleepiness Scale (KSS), and performance on a Psychomotor Vigilance Task (PVT) of 21 ICU nurses working day, evening, and night shifts. Combinations of individual shift schedules, forced wake time before/after work and lighting, were used as inputs to the model. Predictions were compared to empirical data. Simulations with self-reported sleep as an input were performed for comparison. RESULTS: All input constraints produced similar prediction for KSS, with 56%-60% of KSS scores predicted within ±1 on a day and 48%-52% on a night shift. Accurate prediction of an individual's circadian phase required individualized light input. Combinations including light information predicted aMT6s acrophase within ±1 h of the study data for 65% and 35%-47% of nurses on diurnal and nocturnal schedules. Minute-by-minute sleep-wake state overlap between the model and the data was between 81 ± 6% and 87 ± 5% depending on choice of input constraint. CONCLUSIONS: The use of individualized environmental constraints in the model of arousal dynamics allowed for accurate prediction of alertness, circadian phase, and sleep for more than half of the nurses. Individual differences in physiological parameters will need to be accounted for in the future to further improve predictions.
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Sleep Disorders, Circadian Rhythm , Arousal , Circadian Rhythm/physiology , Humans , Sleep/physiology , Wakefulness/physiology , Work Schedule Tolerance/physiologyABSTRACT
PURPOSE: The primary aim of this pilot study was to examine the feasibility of codelivering a mental health intervention with an evidence-based type 2 diabetes (T2DM) boot camp care management program. The preliminary impact of participation on symptom scores for depression and anxiety and A1C was also examined. METHODS: This was a 12-week, non-randomized pilot intervention conducted with a convenience sample of adults with uncontrolled T2DM and moderate depression and/or anxiety at an urban teaching hospital. Co-management intervention delivery was via in-person and telehealth visits. Participants were assessed at baseline and 90 days. RESULTS: Participants (n = 18) were African American, majority female (83%), and age 50.7 ± 13.4 years. Significant improvements in mental health outcomes were demonstrated, as measured by a reduction in Patient Health Questionnaire - 9 scores of 2.4 ± 2.9 (P = .01) and in Generalized Anxiety Disorder - 7 scores of 2.3 ± 1.9 (P = .001). The pre-post intervention mean A1C improved by 3.4 ± 2.1 units from 12% ± 1.4% to 8.5% ± 1.7% (P < .001). CONCLUSION: The data generated in this pilot support the feasibility of delivering a diabetes and mental health co-management intervention using a combination of in-person and telemedicine visits to engage adults with T2DM and coexisting moderate depression and/or anxiety. Further research is warranted.