2-phase Approach Research Articles

Finances and Future Health

First-generation college students experience disproportionate levels of stress, anxiety, and lack of preparation for undergraduate education in comparison to their multi-generational peers in relation to their levels of financial support and literacy. This impacts on their levels of resiliency, their physical and mental wellbeing, academic success, and levels of attrition. This not only has impacts on their health and wellbeing in the present, but can also negatively impact both their health and their career trajectory in the future as well. Using a 2-phase approach, researchers collected both quantitative and qualitative data related to how first-generation EOF students think about the role of financial literacy, and in particular Federal Work Study, as a component of their current and future health status and academic success. Qualitative analysis gave rise to 3 themes related to student feelings of stress, pressure/obligation, lack of preparation, and uncertainty about the role of college education in their current and future lives. Findings are shared in order to better inform and guide institutions of higher education on how to best educate and support their first-generation students, particularly in how to aid these students in improving their financial literacy and financial support to improve resiliency, wellbeing, and academic success.

Effects of exercise dosage on the treatment of fibromyalgia: A meta-analysis of randomised controlled trials.

Exercise intensity is a key component of an exercise prescription. This meta-analysis aimed to investigate the treatment effect of different exercise doses on fibromyalgia syndrome. PubMed, Embase, Web of Science, and the Cochrane Library were searched from their inception until 29 December 2023. The studies were subjected to screening using a 2-phase approach by 2 independent reviewers. Reference lists of the included studies were manually searched. Two independent reviewers extracted information regarding the origin, characteristics of study participants, eligibility criteria, characteristics of interventions, outcome measures, and main results using a pre-defined template. This meta-analysis encompassed a total of 19 randomized controlled trials comprising 857 patients. Compared with the low compliance/uncertain group according to ACSM, the high compliance group showed better effectiveness in general condition improvement (SMD: -1.15>-0.71), pain relief (SMD: -1.29>-1.04), sleep quality enhancement (SMD: -1.66>-1.08), and fatigue relief (SMD: -1.72>-1.32). However, there was no difference in the improvement of mental health between the two groups (SMD: -0.93>-0.92). Compared to the ACSM group with compliance uncertainty (<70%), the high compliance group showed improvement in general conditions, pain, sleep quality, and fatigue. However, there was no difference in terms of mental health.

Team-Based Approach to Successful Annual Wellness Visits.

The purpose of this study was to implement a 2-phase approach to rapidly increase the number of annual wellness visits (AWVs) and build a sustainable model at 3 study units (Mayo Clinic in Rochester, Minnesota, and clinics in 2 regions of Mayo Clinic Health System), which collectively serve approximately 80 000 patients who qualify for an AWV annually. In the rapid improvement phase, beginning in July 2022, goals at the facilities were reoriented to prioritize AWVs, educate staff on existing AWV resources, and create low-effort workflows so that AWVs could be incorporated into existing patient appointments. Staff at all 3 study units worked independently and iterated quickly. In the second phase, all study units collaborated to design and implement a best-practice solution while they leveraged the engagement and lessons learned from the first phase and invested in additional system elements and change management to codify long-term success. The number of AWVs completed monthly increased in each study unit. In the rapid improvement phase, the number of AWVs increased but then plateaued (or decreased at some study units). In April 2023, the final scheduled outreach automation and visit tools were implemented, and the number of AWVs was sustained or increased, while outreach and scheduling times were decreased. The number of completed AWVs increased from 1148 across all study units in the first 6 months of 2022 to 14 061 during the first 6 months of 2023. The lessons learned from this project can be applied to other health systems that want to provide more patients with AWVs while improving operational efficiency. The keys are to have a clear vision of a successful outcome, engage all stakeholders, and iterate quickly to find what works best for the organization.

Landscape review of global real-world data sources for studying medication use in pregnancy and lactation that support regulatory decision making.

Most pregnant people take at least one medication during gestation or while breastfeeding, however data are lacking on the safety of medication use in these populations. We conducted a landscape review of real-world data sources specific to medication use in pregnancy and breastfeeding populations that have met, or have potential to meet, health authorities' requirements for post-authorization safety studies. A 2-phase approach identified data sources from literature, publicly available registers of non-interventional post-authorization studies of pregnant women, existing database inventories, and emerging data sources known to the authors. Required key attributes were assessed according to current regulatory guidance, resulting in selection of 49 suitable data sources. All global regions were represented, with North America (37%) and Europe (33%) most common; 12% of the data sources included pregnancy information from low-to middle-income countries. Administrative healthcare claims (25%) and electronic healthcare records (21%) comprised the largest types of data sources. Across data sources, 53% were managed by national or regional governments, 27% by industry, and 20% by academic institutions. Maternal age, diagnoses, prenatal care, and reproductive history were available in most, whereas fewer included demographic data (e.g., race/ethnicity). Breastfeeding data were collected in 37% of the final data sources. We conducted a systematic approach to data source evaluation of pregnancy and breastfeeding to be used as a resource for investigators to consider when designing pregnancy-related research studies to satisfy regulatory requirements.

A 2-phase prediction of a non-stationary time-series by Taylor series and reinforcement learning

Prediction of a non-stationary time-series is hard as the frequency components and their amplitudes in the series vary randomly over time. This paper proposes a 2-phase approach for prediction of such non-stationary time-series. The first phase employs Taylor series to approximately predict the next time-point value in the series from its current and last two preceding sample values. The Taylor series based prediction, however, presumes that the time-series is locally stationary. The second phase employs reinforcement learning to refine the Taylor series based prediction further, particularly at the juncture of structural changes in the time-series. The reinforcement learning based prediction is realized with the help of an adaptive probabilistic learning matrix that evolves to encode the mapping between current prediction error and the error-compensation for the next sample. On convergence of the matrix, the saved probabilities are used to determine the error-compensation for the next sample from the estimated error at the current sample. The additive error-compensation is then utilized to rectify the results of prediction obtained by Taylor series. Experiments undertaken confirm that the proposed 2-phase prediction outperforms the state-of-the-art prediction techniques by a significant margin of prediction accuracy.

Identification of Key Factors for Optimized Health Care Services: Protocol for a Multiphase Study of the Dubai Vaccination Campaign.

Mass vaccination of the global population against the novel COVID-19 outbreak posed multiple challenges, including effectively administering millions of doses in a short period of time while ensuring public safety and accessibility. The government of Dubai launched a mass campaign in December 2020 to vaccinate all its citizens and residents, targeting the population aged >18 years against COVID-19. The vaccination campaign involved a transformation of multiple commercial spaces into mass vaccination centers across the city of Dubai, the largest of which was the Dubai One Central (DOC) vaccination center. It was operational between January 17, 2021, and 27 January 27, 2022. The multiphase research study aims to empirically explore the opinions of multiple health care stakeholders, elicit the key success factors that can influence the effective delivery of emergency health care services such as a COVID-19 mass vaccination center, and explore how these factors relate to one another. To understand more about the operations of the DOC vaccination center, the study follows a multiphase design divided into 2 phases. The study is being conducted by the Institute for Excellence in Health Professions Education at Mohammed Bin Rashid University of Medicine and Health Sciences between December 2021 and January 2023. To elicit the key success factors that contributed to the vaccination campaign administered at DOC, the research team conducted 30 semistructured interviews (SSIs) with a sample of staff and volunteers who worked at the DOC vaccination center. Stratified random sampling was used to select the participants, and the interview cohort included representatives from the management team, team leaders, the administration and registration team, vaccinators, and volunteers. A total of 103 people were invited to take part in the research study, and 30 agreed to participate in the SSIs. To validate the participation of various stakeholders, phase 2 will analytically investigate one's subjectivity through Q-methodology and empirically investigate the opinions obtained from the research participants during phase 1. As of July 2022, 30 SSIs were conducted with the research participants. The study will provide a comprehensive 2-phase approach to obtaining the key success factors that can influence the delivery of high-quality health care services such as emergency services launched during a global pandemic. The study's findings will be translated into key factors that could support designing future health care services utilizing evidence-based practice. In line with future plans, a study will use data, collected through the DOC vaccination center, to develop a simulation model outlining the process of the customer journey and center workflow. DERR1-10.2196/42278.

Development and validation of a hospital frailty risk measure using Canadian clinical administrative data.

Accessible measures specific to the Canadian context are needed to support health system planning for older adults living with frailty. We sought to develop and validate the Canadian Institute for Health Information (CIHI) Hospital Frailty Risk Measure (HFRM). Using CIHI administrative data, we conducted a retrospective cohort study involving patients aged 65 years and older who were discharged from Canadian hospitals from Apr. 1, 2018, to Mar. 31, 2019. We used a 2-phase approach to develop and validate the CIHI HFRM. The first phase, construction of the measure, was based on the deficit accumulation approach (identification of age-related conditions using a 2-year look-back). The second phase involved refinement into 3 formats (continuous risk score, 8 risk groups and binary risk measure), with assessment of their predictive validity for several frailty-related adverse outcomes using data to 2019/20. We assessed convergent validity with the United Kingdom Hospital Frailty Risk Score. The cohort consisted of 788 701 patients. The CIHI HFRM included 36 deficit categories and 595 diagnosis codes that cover morbidity, function, sensory loss, cognition and mood. The median continuous risk score was 0.111 (interquartile range 0.056-0.194, equivalent to 2-7 deficits); 35.1% (n = 277 000) of the cohort were found at risk of frailty (≥ 6 deficits). The CIHI HFRM showed satisfactory predictive validity and reasonable goodness-of-fit. For the continuous risk score format (unit = 0.1), the hazard ratio (HR) for 1-year risk of death was 1.39 (95% confidence interval [CI] 1.38-1.41), with a C-statistic of 0.717 (95% CI 0.715-0.720); the odds ratio for high users of hospital beds was 1.85 (95% CI 1.82-1.88), with a C-statistic of 0.709 (95% CI 0.704-0.714), and the HR of 90-day admission to long-term care was 1.91 (95% CI 1.88-1.93), with a C-statistic of 0.810 (95% CI 0.808-0.813). Compared with the continuous risk score, using a format of 8 risk groups had similar discriminatory ability and the binary risk measure had slightly weaker performance. The CIHI HFRM is a valid tool showing good discriminatory power for several adverse outcomes. The tool can be used by decision-makers and researchers by providing information on hospital-level prevalence of frailty to support system-level capacity planning for Canada's aging population.

A 2-phase approach for planning of hazardous waste collection using an unmanned aerial vehicle

A 2-phase approach for planning of hazardous waste collection using an unmanned aerial vehicle

Developing and Testing Remote Implementation for the Changing Talk Online (CHATO) Communication Intervention for Nursing Home Staff: A Pilot Pragmatic Randomized Controlled Trial.

Background and ObjectivesThe Changing Talk (CHAT) communication training effectively reduces elderspeak and subsequent behavioral challenges in residents with dementia in nursing homes (NHs). As part of the pilot pragmatic clinical trial testing Changing Talk: Online Training (CHATO), a new online version, a remote implementation design, and process evaluation were developed to capture contextual factors, ensure fidelity, and determine effective implementation strategies.Research Design and MethodsThe Expert Recommendation for Implementing Change compilation informed this 2-phase approach to develop and test remote implementation. An Advisory Board guided the developmental phase while pilot testing used a cluster-randomized design. Data were analyzed to evaluate NH characteristics; implementation strategies used; CHATO participation, completion, and passing rates; and leadership evaluation.ResultsFive out of 7 NHs were nonprofit with above average quality ratings (M = 4.3 of 5). Staff participants (N = 237) were mostly female (90%), non-Hispanic White (91%), and nursing assistants (46%). Implementation time ranged from 54 to 86 days (M = 70.3, standard deviation [SD] = 9.3), with planning phase ranging from 11 to 29 days (M = 20.1, SD = 6.7), and training phase ranging from 35 to 58 days (M = 50.0, SD = 7.6). A range from 3 to 11 implementation strategies were used by each NH. Assigning champions, including the social worker on the implementation team, utilizing multiple mediums for reminders, giving rewards or public recognition, supporting onsite discussions, and other tailoring strategies were associated with improved outcomes. Participation ranged from 20% to 76%. Over 63% of participants completed training (N = 150) and 87% passed the posttest (N = 130). Leadership evaluations noted staff used CHATO concepts in practice and improved communication culture.Discussion and ImplicationsLeadership who took an active role, engaged multiple team members, and varied strategies had better outcomes. Effectiveness of the strategies will be evaluated in a national pragmatic clinical trial testing CHATO’s effects on reducing behavioral and psychological symptoms in dementia care.

Predicting Changes in Depression Severity Using the PSYCHE-D (Prediction of Severity Change-Depression) Model Involving Person-Generated Health Data: Longitudinal Case-Control Observational Study.

BackgroundIn 2017, an estimated 17.3 million adults in the United States experienced at least one major depressive episode, with 35% of them not receiving any treatment. Underdiagnosis of depression has been attributed to many reasons, including stigma surrounding mental health, limited access to medical care, and barriers due to cost.ObjectiveThis study aimed to determine if low-burden personal health solutions, leveraging person-generated health data (PGHD), could represent a possible way to increase engagement and improve outcomes.MethodsHere, we present the development of PSYCHE-D (Prediction of Severity Change-Depression), a predictive model developed using PGHD from more than 4000 individuals, which forecasts the long-term increase in depression severity. PSYCHE-D uses a 2-phase approach. The first phase supplements self-reports with intermediate generated labels, and the second phase predicts changing status over a 3-month period, up to 2 months in advance. The 2 phases are implemented as a single pipeline in order to eliminate data leakage and ensure results are generalizable.ResultsPSYCHE-D is composed of 2 Light Gradient Boosting Machine (LightGBM) algorithm–based classifiers that use a range of PGHD input features, including objective activity and sleep, self-reported changes in lifestyle and medication, and generated intermediate observations of depression status. The approach generalizes to previously unseen participants to detect an increase in depression severity over a 3-month interval, with a sensitivity of 55.4% and a specificity of 65.3%, nearly tripling sensitivity while maintaining specificity when compared with a random model.ConclusionsThese results demonstrate that low-burden PGHD can be the basis of accurate and timely warnings that an individual’s mental health may be deteriorating. We hope this work will serve as a basis for improved engagement and treatment of individuals experiencing depression.

Development of a Machine Learning Model Using Multiple, Heterogeneous Data Sources to Estimate Weekly US Suicide Fatalities

Suicide is a leading cause of death in the US. However, official national statistics on suicide rates are delayed by 1 to 2 years, hampering evidence-based public health planning and decision-making. To estimate weekly suicide fatalities in the US in near real time. This cross-sectional national study used a machine learning pipeline to combine signals from several streams of real-time information to estimate weekly suicide fatalities in the US in near real time. This 2-phase approach first fits optimal machine learning models to each individual data stream and subsequently combines predictions made from each data stream via an artificial neural network. National-level US administrative data on suicide deaths, health services, and economic, meteorological, and online data were variously obtained from 2014 to 2017. Data were analyzed from January 1, 2014, to December 31, 2017. Longitudinal data on suicide-related exposures were obtained from multiple, heterogeneous streams: emergency department visits for suicide ideation and attempts collected via the National Syndromic Surveillance Program (2015-2017); calls to the National Suicide Prevention Lifeline (2014-2017); calls to US poison control centers for intentional self-harm (2014-2017); consumer price index and seasonality-adjusted unemployment rate, hourly earnings, home price index, and 3-month and 10-year yield curves from the Federal Reserve Economic Data (2014-2017); weekly daylight hours (2014-2017); Google and YouTube search trends related to suicide (2014-2017); and public posts on suicide on Reddit (2 314 533 posts), Twitter (9 327 472 tweets; 2015-2017), and Tumblr (1 670 378 posts; 2014-2017). Weekly estimates of suicide fatalities in the US were obtained through a machine learning pipeline that integrated the above data sources. Estimates were compared statistically with actual fatalities recorded by the National Vital Statistics System. Combining information from multiple data streams, the machine learning method yielded estimates of weekly suicide deaths with high correlation to actual counts and trends (Pearson correlation, 0.811; P < .001), while estimating annual suicide rates with low error (0.55%). The proposed ensemble machine learning framework reduces the error for annual suicide rate estimation to less than one-tenth of that of current forecasting approaches that use only historical information on suicide deaths. These findings establish a novel approach for tracking suicide fatalities in near real time and provide the potential for an effective public health response such as supporting budgetary decisions or deploying interventions.

Three-dimensional condylar changes from Herbst appliance and multibracket treatment: A comparison with matched Class II elastics

The purpose of this study was to quantify and qualify the 3-dimensional (3D) condylar changes using mandibular 3D regional superimposition techniques in adolescent patients with Class II Division 1 malocclusions treated with either a 2-phase or single-phase approach. Twenty patients with Herbst appliances who met the inclusion criteria and had cone-beam computed tomography (CBCT) images taken before, 8weeks after Herbst removal, and after the completion of multibracket appliance treatment constituted the Herbst group. They were compared with 11 subjects with Class II malocclusion who were treated with elastics and multibracket appliances and who had CBCT images taken before and after treatment. Three-dimensional models generated from the CBCT images were registered on the mandible using 3D voxel-based superimposition techniques and analyzed using semitransparent overlays and point-to-point measurements. The magnitude of lateral condylar growth during the orthodontic phase (T2-T3) was greater than that during the orthopedic phase (T1-T2) for all condylar fiducials with the exception of the superior condyle (P<0.05). Conversely, posterior condylar growth was greater during the orthopedic phase than the subsequent orthodontic phase for all condylar fiducials (P<0.05). The magnitude of vertical condylar development was similar during both the orthopedic (T1-T2) and orthodontic phases (T2-T3) across all condylar fiducials (P<0.05). Posterior condylar growth during the orthodontic phase (T2-T3) of the 2-phase approach decreased for all condylar fiducials with the exception of the posterior condylar fiducial (P<0.05) when compared with the single-phase approach. Two-phase treatment using a Herbst appliance accelerates condylar growth when compared with a single-phase regime with Class II elastics. Whereas the posterior condylar growth manifested primarily during the orthopedic phase, the vertical condylar gains occurred in equal magnitude throughout both phases of the 2-phase treatment regime.

A single allocation hub location and pricing problem

This study introduces a new problem for uncapacitated single allocation hub location in which pricing is taken into account. The objective is profit maximization by choosing the best hub and spoke topology and applying the optimal pricing, in the case of price-dependent demand. It is assumed that the source determining the number of hubs is endogenous. Two variants of the considered problem are addressed: deterministic and robust. For the initial non-linear model, we show how the deterministic variant can be reformulated as a mixed-integer linear program, excluding the price variables. In the robust counterpart case, the quantity of commodity flows between the pairs of customers is of stochastic nature. The goal of the robust variant is to design a hub and spoke network, together with the pricing structure, that would be immune to small perturbations of demand. Starting from the original model for the robust case, we have shown how to formulate an equivalent mixed-integer conic-quadratic program. In addition, we have proposed a 2-phase matheuristic approach for the robust variant. A computational study was conducted on the set of hub instances from the literature using the commercial state-of-the-art solver. The obtained computational results are thoroughly discussed, location patterns are analyzed and some managerial insights are provided. The experimental study also showed that the proposed matheuristic approach for the robust variant performs better compared to the commercial solver.

A Web-Based Intervention for Relatives of People Experiencing Psychosis or Bipolar Disorder: Design Study Using a User-Centered Approach

BackgroundRelatives of people experiencing bipolar mood episodes or psychosis face a multitude of challenges (eg, social isolation, limited coping strategies, and issues with maintaining relationships). Despite this, there is limited informational and emotional support for people who find themselves in supporting or caring roles. Digital technologies provide us with an opportunity to offer accessible tools, which can be used flexibly to provide evidence-based information and support, allowing relatives to build their understanding of mental health problems and learn from others who have similar experiences. However, to design tools that are useful to relatives, we first need to understand their needs.ObjectiveThe aim of this study was to use a user-centered design approach to develop an accessible Web-based intervention, based on the Relatives Education And Coping Toolkit (REACT) booklet, to support the informational and emotional needs of relatives of people experiencing psychosis or bipolar disorder.MethodsWe engaged relatives of people with experiences of bipolar disorder or psychosis in workshops to identify their needs and design requirements for developing a Web-based version of a paper-based toolkit. We used a 2-phase qualitative approach to explore relatives’ views on content, design, and functionalities, which are considered to be engaging and useful in a Web-based intervention. In phase 1, we consulted 24 relatives in 2 workshops to better understand their existing support infrastructure, their barriers for accessing support, unmet needs, and relatives’ views on online support. On the basis of the results of these workshops, we developed a set of design considerations to be explored in a smaller workshop. Workshop 3 then involved working with 2 digitally literate relatives to design a usable and acceptable interface for our Web-based toolkit. Finally, in phase 2, we conducted a heuristic evaluation to assess the usability of the toolkit.ResultsOur findings indicated that relatives require technologies that (1) they can place their trust in, particularly when discussing a highly sensitive topic, (2) enable learning from the lived experiences of others while retaining confidentiality, and (3) they can work through at their own pace in a personalized manner.ConclusionsOur study highlights the need for providing a trustworthy, supportive tool where relatives can engage with people who have similar experiences to their own. Our heuristic evaluation showed promise in terms of perceived usability of the REACT Web-based intervention. Through this work, we emphasize the need to involve stakeholders with various characteristics, including users with limited computer literacy or experience in online support.

Relationship between very low low-density lipoprotein cholesterol concentrations not due to statin therapy and risk of type 2 diabetes: A US-based cross-sectional observational study using electronic health records.

BackgroundObservations from statin clinical trials and from Mendelian randomization studies suggest that low low-density lipoprotein cholesterol (LDL-C) concentrations may be associated with increased risk of type 2 diabetes mellitus (T2DM). Despite the findings from statin clinical trials and genetic studies, there is little direct evidence implicating low LDL-C concentrations in increased risk of T2DM.Methods and findingsWe used de-identified electronic health records (EHRs) at Vanderbilt University Medical Center to compare the risk of T2DM in a cross-sectional study among individuals with very low (≤60 mg/dl, N = 8,943) and normal (90–130 mg/dl, N = 71,343) LDL-C levels calculated using the Friedewald formula. LDL-C levels associated with statin use, hospitalization, or a serum albumin level < 3 g/dl were excluded. We used a 2-phase approach: in 1/3 of the sample (discovery) we used T2DM phenome-wide association study codes (phecodes) to identify cases and controls, and in the remaining 2/3 (validation) we identified T2DM cases and controls using a validated algorithm. The analysis plan for the validation phase was constructed at the time of the design of that component of the study. The prevalence of T2DM in the very low and normal LDL-C groups was compared using logistic regression with adjustment for age, race, sex, body mass index (BMI), high-density lipoprotein cholesterol, triglycerides, and duration of care. Secondary analyses included prespecified stratification by sex, race, BMI, and LDL-C level. In the discovery cohort, phecodes related to T2DM were significantly more frequent in the very low LDL-C group. In the validation cohort (N = 33,039 after applying the T2DM algorithm to identify cases and controls), the risk of T2DM was increased in the very low compared to normal LDL-C group (odds ratio [OR] 2.06, 95% CI 1.80–2.37; P < 2 × 10−16). The findings remained significant in sensitivity analyses. The association between low LDL-C levels and T2DM was significant in males (OR 2.43, 95% CI 2.00–2.95; P < 2 × 10−16) and females (OR 1.74, 95% CI 1.42–2.12; P = 6.88 × 10−8); in normal weight (OR 2.18, 95% CI 1.59–2.98; P = 1.1× 10−6), overweight (OR 2.17, 95% CI 1.65–2.83; P = 1.73× 10−8), and obese (OR 2.00, 95% CI 1.65–2.41; P = 8 × 10−13) categories; and in individuals with LDL-C < 40 mg/dl (OR 2.31, 95% CI 1.71–3.10; P = 3.01× 10−8) and LDL-C 40–60 mg/dl (OR 1.99, 95% CI 1.71–2.32; P < 2.0× 10−16). The association was significant in individuals of European ancestry (OR 2.67, 95% CI 2.25–3.17; P < 2 × 10−16) but not in those of African ancestry (OR 1.09, 95% CI 0.81–1.46; P = 0.56). A limitation was that we only compared groups with very low and normal LDL-C levels; also, since this was not an inception cohort, we cannot exclude the possibility of reverse causation.ConclusionsVery low LDL-C concentrations occurring in the absence of statin treatment were significantly associated with T2DM risk in a large EHR population; this increased risk was present in both sexes and all BMI categories, and in individuals of European ancestry but not of African ancestry. Longitudinal cohort studies to assess the relationship between very low LDL-C levels not associated with lipid-lowering therapy and risk of developing T2DM will be important.

Building a Caring-Based Hyperglycemic Crisis Prevention Model for Patients With Diabetes Mellitus, Thailand

The purpose of this study was to understand patient experiences of hyperglycemic crisis (HC) and develop a caring-based, interdisciplinary model for preventing HC in Thailand. A 2-Phase approach was used. In Phase 1, qualitative interviews were conducted with 15 in-patients with diabetes mellitus who had experienced a HC. Four themes emerged: not knowing, depending on others for care, experiencing stress, and seeking help for self-care. In Phase 2, interdisciplinary, participatory team focus groups were conducted using data from Phase 1 to develop a model of hyperglycemic crisis prevention.

Effects of High Sound Exposure During Air-Conducted Vestibular Evoked Myogenic Potential Testing in Children and Young Adults

Vestibular evoked myogenic potential (VEMP) testing is increasingly utilized in pediatric vestibular evaluations due to its diagnostic capability to identify otolith dysfunction and feasibility of testing. However, there is evidence demonstrating that the high-intensity stimulation level required to elicit a reliable VEMP response causes acoustic trauma in adults. Despite utility of VEMP testing in children, similar findings are unknown. It is hypothesized that increased sound exposure may exist in children because differences in ear-canal volume (ECV) compared with adults, and the effect of stimulus parameters (e.g., signal duration and intensity) will alter exposure levels delivered to a child's ear. The objectives of this study are to (1) measure peak to peak equivalent sound pressure levels (peSPL) in children with normal hearing (CNH) and young adults with normal hearing (ANH) using high-intensity VEMP stimuli, (2) determine the effect of ECV on peSPL and calculate a safe exposure level for VEMP, and (3) assess whether cochlear changes exist after VEMP exposure. This was a 2-phase approach. Fifteen CNH and 12 ANH participated in phase I. Equivalent ECV was measured. In 1 ear, peSPL was recorded for 5 seconds at 105 to 125 dB SPL, in 5-dB increments for 500- and 750-Hz tone bursts. Recorded peSPL values (accounting for stimulus duration) were then used to calculate safe sound energy exposure values for VEMP testing using the 132-dB recommended energy allowance from the 2003 European Union Guidelines. Fifteen CNH and 10 ANH received cervical and ocular VEMP testing in 1 ear in phase II. Subjects completed tympanometry, pre- and postaudiometric threshold testing, distortion product otoacoustic emissions, and questionnaire addressing subjective otologic symptoms to study the effect of VEMP exposure on cochlear function. (1) In response to high-intensity stimulation levels (e.g., 125 dB SPL), CNH had significantly higher peSPL measurements and smaller ECVs compared with ANH. (2) A significant linear relationship between equivalent ECV (as measured by diagnostic tympanometry) and peSPL exists and has an effect on total sound energy exposure level; based on data from phase I, 120 dB SPL was determined to be an acoustically safe stimulation level for testing in children. (3) Using calculated safe stimulation level for VEMP testing, there were no significant effect of VEMP exposure on cochlear function (as measured by audiometric thresholds, distortion product otoacoustic emission amplitude levels, or subjective symptoms) in CNH and ANH. peSPL sound recordings in children's ears are significantly higher (~3 dB) than that in adults in response to high-intensity VEMP stimuli that are commonly practiced. Equivalent ECV contributes to peSPL delivered to the ear during VEMP testing and should be considered to determine safe acoustic VEMP stimulus parameters; children with smaller ECVs are at risk for unsafe sound exposure during routine VEMP testing, and stimuli should not exceed 120 dB SPL. Using 120 dB SPL stimulus level for children during VEMP testing yields no change to cochlear function and reliable VEMP responses.

Measuring the implementation of ecodesign management practices: A review and consolidation of process-oriented performance indicators

Ecodesign plays an important role in manufacturing companies’ quest for improved sustainability performance. However, many ecodesign efforts are geared towards tackling single-issue discrete improvements, in contrast to operationalizing, measuring and acting upon the consistent improvement of ecodesign implementation and management. To enable a systematic and streamlined integration of ecodesign practices into the product development processes, adequate mechanisms are needed to capture and measure performance improvements, and thereby achieve consistent improvements in a company’s efforts towards enhanced sustainability performance. In face of this challenge, this paper aims at providing organizations with a set of process-oriented indicators to supporting and enhancing ecodesign implementation and management. This research was grounded on a 2-phase approach to (i) cross-analyze performance indicators from literature against ecodesign practices at the process level and (ii) propose, evaluate and consolidate new indicators. After being subjected to the evaluation of 8 experts in ecodesign, a repository is presented with 27 indicators from literature and a set of 114 newly proposed indicators for companies to customize, adapt, mix and derive according to their needs, strategic drivers and overall context.

A therapist-focused knowledge translation intervention for improving patient adherence in musculoskeletal physiotherapy practice

BackgroundNonadherence to treatment remains high among patients with musculoskeletal conditions with negative impact on the treatment outcomes, use of personal and cost of care. An active knowledge translation (KT) strategy may be an effective strategy to support practice change. The purpose of this study was to deliver a brief, interactive, multifaceted and targeted KT program to improve physiotherapist knowledge and confidence in performing adherence enhancing activities related to risk, barriers, assessment and interventions.MethodsWe utilised a 2-phase approach in this KT project. Phase 1 involved the development of an adherence tool kit following a synthesis of the literature and an iterative process involving 47 end-users. Clinicians treating patients with musculoskeletal conditions were recruited from two Physiotherapy and Occupational therapy national conferences in Canada. The intervention, based on the acronym SIMPLE TIPS was tested on 51 physiotherapists in phase 2. A pre- and post-repeated measures design was used in Phase 2. Graham’s knowledge-to-action cycle was used as the conceptual framework. Participants completed a pre—intervention assessment, took part in a 1-h educational session and completed a post—intervention assessment. A questionnaire was used to measure knowledge of evidence—based treatment adherence barriers, interventions and measures and confidence to perform evidence—based adherence practice activities. Data was analysed using descriptive statistics (frequency and percentage), Fisher’s exact test and Wilcoxon Sign-Ranked tests.ResultsBarriers and facilitators of adherence were identified under three domains (therapist, patient, health system) in phase 1. Seventy percent of the participants completed the questionnaire. Results indicated that 46.8% of respondents explored barriers including the use of behaviour change strategies and 45.7% reported that they measured adherence but none reported the use of validated outcomes. A significant improvement in post-self-efficacy scores for the four adherence enhancing activities was observed immediately after the workshop.ConclusionThe use of a multi-modal KT intervention is feasible in an educational setting. A brief interactive educational session was successfully implemented using a toolkit and caused a significant increase in physiotherapists’ knowledge and confidence at performing adherence enhancing activities in the very short-term. Further testing of SIMPLE TIPS on long-term adherence practices could help advance best practices specific to treatment adherence in MSK practice.

Using Visual Metaphors in Health Messages: A Strategy to Increase Effectiveness for Mental Illness Communication

Depression is highly prevalent among college students. Although treatment is often available on university campuses, many stigma-based barriers prevent students from seeking help. Communication strategies, such as the use of metaphors, are needed to reduce barriers. Specially, the use of visual metaphors, as a strategic message design tactic, may be an effective communication strategy to increase message appeal and engagement. Using a 2-phase approach, this study first identified common metaphors students use to conceptualize mental illness. Messages incorporating conceptual and visual metaphors were then designed and tested to determine their potential in reducing stigma. Participants (n = 256) were randomly assigned to 1 of 4 conditions in a between-subjects experiment: messages with visual and textual metaphors, messages with straightforward visuals and textual metaphors, text-based metaphor messages, or a control group. Overall, metaphorical messages are appealing, the use of visual metaphors leads to greater message engagement, and messages based on conceptual metaphors have the potential to reduce stigma. The use of conceptual and visual metaphors in campaign design is an effective strategy to communicate about a complex health topic, such as mental illness, and should be considered for use in campaigns to reduce barriers for help-seeking behavior.