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Exposure to noise can increase biological stress reactions, which may increase adverse health effects, including metabolic disorders; however, the certainty in the association between exposure to noise and metabolic outcomes has not been widely explored. The objective of this review is to evaluate the evidence between noise exposures and metabolic effects.A systematic review of English and comparative studies available in PubMed, Cochrane Central, EMBASE, and CINAHL databases between January 1, 1980 and December 29, 2021 was performed. Risk of Bias of Nonrandomized Studies of Exposures was used to assess risk of bias of individual studies and certainty of the body of evidence for each outcome was assessed using the Grading of Recommendations Assessment, Development and Evaluation (GRADE) approach.Fifty-six primary studies reporting on cortisol, cholesterol levels, waist circumference, glucose levels, and adrenaline and/or noradrenaline were identified. Although meta-analyses suggested that there may be an increase in waist circumference and adrenaline with increased noise exposure, the certainty in the evidence is very low. Overall, the certainty in the evidence of an effect of increased noise on all the outcomes were low to very low due to concerns with risk of bias, inconsistency across exposure sources, populations, and studies, and imprecision in the estimates of effects.The certainty of the evidence of increased noise on metabolic effects was low to very low, which likely reflects the inability to compare across the totality of the evidence for each outcome. The findings from this review may be used to inform policies involving noise reduction and mitigation strategies, and to direct further research in areas that currently have limited evidence available.

PURPOSE: This evidence-based guideline intends to support patients, clinicians, and others regarding interventions and processes to support patient adherence to oral anticancer medications (OAMs). METHODOLOGIC APPROACH: A panel of healthcare professionals and patient representatives developed a clinical practice guideline to support patients taking OAMs. GRADE (Grading of Recommendations Assessment, Development, and Evaluation) methodology and criteria for trustworthy guidelines were followed. Risk of bias was assessed using the Cochrane Risk of Bias 2 tool. A quantitative or narrative synthesis of the evidence was completed. Certainty of the evidence was assessed using GRADE. FINDINGS: The panel agreed on recommendations and suggested an adherence risk assessment, education addressing adherence, ongoing assessment, proactive follow-up, coaching, and motivational interviewing in addition to usual care. The panel suggested the implementation of a structured OAM program. IMPLICATIONS FOR NURSING: As cancer treatment shifts from clinic to home settings, interventions and programs to support patients on OAMs are needed.

PROBLEM IDENTIFICATION: An interprofessional approach is necessary to support the multifactorial process of patient adherence to oral anticancer medications (OAMs). This scoping review aims to identify structured OAM programs in published literature, identify components within studies, and propose a framework for institutions developing or maintaining OAM programs. LITERATURE SEARCH: Embase(®), PubMed(®), and CINAHL(®) databases were searched for studies published between January 2000 and April 2021. DATA EVALUATION: Two reviewers screened studies and extracted data. Characteristics and specific domains of the OAM programs were captured. Key components of the programs were identified, and a framework was created to guide program development. SYNTHESIS: Components identified among the 21 studies were education; counseling; follow-up; dedicated clinician contact; adverse event and toxicity monitoring; adherence monitoring; drug procurement, delivery, and supply; patient- and system-level cost reduction; information technology; and risk assessment. IMPLICATIONS FOR RESEARCH: Based on the findings, a framework for building and evaluating OAM adherence programs is proposed. Future studies should evaluate the reliability and validity of this framework because further testing may lead to the development of additional components.

Literature suggests that unrestricted and undisturbed sleep is vital for basic human function and performance; however, it is unclear as to what amount of sleep disturbance leads to dysregulation in biomarkers, which may underscore the development of adverse health effects. This systematic review aims to identify the amount of sleep disturbance that contributes to biomarker changes as a potential precursor to the development of adverse health effects. English-language comparative studies available in PubMed, Cochrane Central, EMBASE, and CINAHL databases from 1 January 1980 to 31 July 2021 were searched. Where possible, random-effects meta-analyses were used to examine the effect of sleep disturbances on adverse health effects. The risk of bias of individual studies was assessed using the Cochrane Risk of Bias Tool and the Risk of Bias of Nonrandomised Studies - of Exposures instruments and the certainty of the body of evidence for each outcome was assessed using the Grading of Recommendations Assessment, Development and Evaluation approach. The search identified 92 primary studies reporting on blood pressure, hypertension, heart rate, cardiac arrhythmia, cardiac output, waist circumference, cortisol, adrenaline, noradrenaline, immune system markers, glucose, insulin, cholesterol, and triglyceride levels. Although some meta-analyses suggested there may be an association between sleep disturbances and certain outcomes, the certainty in the evidence was very low due to concerns with risk of bias, inconsistency across exposures, populations, and imprecision in the estimates of effects. Further research is needed to explore the point at which types, levels and duration of sleep disturbances may begin to increase the risk of developing adverse health outcomes to inform and tailor health interventions.

This systematic review compared the efficacy of interventions to usual care on adherence to oral anticancer regimens.Embase®, PubMed®, and CINAHL® were searched for eligible comparative studies published between January 2000 and May 2021. Outcomes of interest included adherence, cancer-related morbidity, quality of life, patient satisfaction, and other patient-specific outcomes.Reviewers assessed risk of bias using the Cochrane Risk of Bias 2 tool and Risk of Bias in Nonrandomized Studies of Interventions. Certainty of evidence was assessed using the GRADE framework.Risk assessment, ongoing or periodic assessment, proactive follow-up, motivational interviewing, or structured programs may improve adherence. Education or coaching interventions may improve or have little to no effect on adherence. Technological interventions may improve adherence, but interactive compared to noninteractive technology may have little to no effect.As more cancer treatments move to oral formulations, work remains to identify the most effective interventions to support people receiving oral anticancer regimens.

320 Background: The increase in patients receiving oral oncolytics requires oncology health care professionals to have processes and interventions that support patient adherence. Because adherence to oral oncolytics is a priority for achieving optimal outcomes, the ASCO QOPI Standards emphasize the need to assess for adherence at meaningful intervals as well as implement interventions to promote adherence. Technology-based interventions have the potential to assess and support adherence. The objective of this review is to evaluate the overall effect of any technology-based intervention, as well as compare the use of interactive technology rather than non-interactive technology to improve oral oncolytic adherence. This review will serve as the evidence base for a clinical practice guideline on oral oncolytic adherence. Methods: A medical librarian searched EMBASE, PubMed, and CINAHL for comparative studies published in English from January 2000 to May 2021. Two reviewers screened titles and abstracts, and eligible full text articles independently and in duplicate using Covidence. When possible, quantitative findings were pooled in a meta-analysis. Risk of bias assessment for randomized controlled trials was done using the Cochrane Collaboration risk-of-bias 2.0 tool and for observational studies, the ROBINS-I instrument was used. The certainty of evidence was assessed using the GRADE (Grading of Recommendations Assessment, Development and Evaluation) approach. Results: Out of 663 studies, we identified 14 as eligible for analysis. Of the six RCTs (n = 737) that compared any technological intervention to no intervention, there was some heterogeneity across interventions (e.g., text messaging, mobile app, computer program) and reported outcome measures for adherence, including adherence rates, relative dose intensity (RDI), and number of weeks adherent. Patients using any technology rather than no technology may have higher adherence rates (MD: 8.81; 95% CI: 3.82, 13.81); however, there may be little effect on RDI (MD: -0.01; 95% CI: -0.04, 0.02) and number of weeks adherent (MD: -0.70; 95% CI: -1.96, 0.56), respectively. One RCT (n = 444) reported on adolescents receiving interactive and non-interactive interventions. There may be little effect on adherence rates among patients receiving interactive technology interventions rather than non-interactive education intervention (MD: 1.5; 95% CI, −0.2, 3.2). Conclusions: Better systems of oral oncolytic care are needed to support patients and their caregivers. Technology-based interventions may improve medication adherence in cancer patients on oral oncolytics; however, we are uncertain about the impact on other measure of adherence or the superiority of interactive rather than non-interactive technology interventions. Due to inconsistency in the evidence, additional research in this area is recommended.