title stringlengths 1 1.19k | keywords stringlengths 0 668 | concept stringlengths 0 909 | paragraph stringlengths 0 61.8k | PMID stringlengths 10 11 |
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Participant | We used the Harvard calculator ( | PMC10586320 | ||
Experimental design | fatigue | BLOOD | Qualified 14 male and 14 female subjects were included and randomly assigned to two groups with gender parity (seven male and seven female per group): (1) no EMS group, (2) daily EMS group (quadriceps, abdominal muscles, biceps, twice a day, 30 min each time). The mean age (no EMS group: 21.6 ± 1.7; daily EMS group: 21.8 ± 2.0), height (no EMS group: 168.8 ± 11.8 cm; daily EMS group: 167.8 ± 9.9 cm) and weight (no EMS group: 64.2 ± 14.4 kg; daily EMS group: 68.5 ± 15.5 kg) of the two groups of subjects were very similar with no significant difference. All subjects underwent intervention for 8 consecutive weeks and performed resistance exercise training three times a week. Blood biochemical routine analysis was performed every 4 weeks from pre-intervention to post-intervention, and body composition, muscle strength, and explosive power were evaluated 8 weeks before and after the intervention. In addition, exercise challenges were performed after 8 weeks of intervention, and blood was collected before exercise, 30 min after exercise, and rest for 60 min after exercise to analyze fatigue biochemical indicators. | PMC10586320 |
Electric muscle stimulator (EMS) | The electric muscle stimulator (EMS) used in this study was from Funcare (Funcare Co., Ltd., Taichung, Taiwan). EMS electrodes were attached to the biceps of both hands, the abdomen, and the quadriceps of both legs sequentially. We refer to previously studies and modify the protocol ( | PMC10586320 | ||
The EMS training protocol. | PMC10586320 | |||
Resistance training (RT) | Torsion | TORSION | All subjects performed resistance training three times a week to strengthen their upper limbs, back, abdomen, and legs, respectively, using a pneumatic resistance training machine including Abs/Abduction 3520-HI5, Push-up/Pulldown 3120, Ab/Back 5310, Torsion Rehab 5340, Leg Extension/Curl 3530, and Leg Press 5540 (AB Hur Oy, Kokkola, Finland). Before beginning training, all subjects evaluated their own 3RM and calculated their 1RM according to the coefficient formula in previous literature, which was used as the standard for setting subsequent resistance training intensity ( | PMC10586320 |
Body composition | The InBody 570 device (In-body, Seoul, South Korea) is a bioelectrical impedance analyzer (BIA) that measures impedance at 1, 5, 50, 260, 500, and 1,000 kHz by the multi-frequency principle and was used in this study to measure body composition. After fasting for at least 8 h, the subject held the induction handle with both hands, with his arms outstretched, his torso at a 30° angle, stood on the bottom electrode, and kept still and did not speak during the measurement (as previously described in | PMC10586320 | ||
Maximal oxygen consumption | As previoulsy described ( | PMC10586320 | ||
Fatigue-associated and clinical biochemical variables | To assess fatigue-related indicators, subjects fasted for at least 8 h and underwent a fixed-intensity exercise challenge (60% VO | PMC10586320 | ||
Maximum handgrip strength test | fatigue | Each participant’s maximum grip strength for both hands was measured using a Takei digital grip strength meter (T.K.K.5401; Takei Scientific Instruments Co., Ltd., Niigata, Japan). Before the actual test, participants were instructed to apply minimal force to the grip to ensure a comfortable and standardized gripping distance. To initiate the formal experiment, researchers randomly assigned either the dominant or non-dominant hand to start. Participants were then instructed to exert maximum force while squeezing the gripper with one hand and to alternate hands every 60 s to prevent fatigue. This alternating method was repeated three times, and the highest grip strength values for both hands were recorded as the data ( | PMC10586320 | |
Countermovement jump assessment | The countermovement jump (CMJ) test is widely used to assess lower body speed, strength, and explosiveness ( | PMC10586320 | ||
Statistical analysis | All the data are expressed as mean ± SD. Statistical analyses were performed using SAS 9.0 (SAS Inst., Cary, NC, USA). Multi-group comparisons were analyzed using one-way analysis of variance (ANOVA). Differences between before and after intervention were analyzed using two-way repeated-measures ANOVA with Bonferroni | PMC10586320 | ||
Results | PMC10586320 | |||
Effect of 8 weeks EMS combined with RT on body composition. |
Data are presented as mean ± SD. Different superscript letters (a, b) indicate significant difference between groups at The intervention efficacy between pre- and post-intervention within the same group was statistically significant at a significance level of Additionally, the changes in body composition were assessed by calculating the delta (difference) before and after the intervention. The daily EMS group exhibited a significant reduction in fat mass compared to the no EMS group ( | PMC10586320 | ||
Biochemical characteristics of subjects before, 4-week and after 8-week EMS intervention. |
Data are presented as mean ± SD. AST, aspartate aminotransferase; ALT, alanine transaminase; BUN, blood urea nitrogen; CREA, creatinine; UA, uric acid; FFA, free fatty acid. | PMC10586320 | ||
Effect of 8 weeks EMS combined with RT on physiological adaptation and biochemical indices | As shown in | PMC10586320 | ||
Effect of 8 weeks EMS combined with RT on physiological adaptation and biochemical indices. |
Data are presented as mean ± SD. | PMC10586320 | ||
Effect of 8 weeks EMS combined with RT on maximum handgrip strength | After 8 weeks of intervention, both the no-EMS group and the daily EMS group showed a significant increase in left-hand (no-EMS group, 1.03-fold ( | PMC10586320 | ||
Effect of 8 weeks EMS combined with RT on maximum handgrip strength. |
Data are presented as mean ± SD. Different superscript letters (a, b) indicate significant difference between groups at The intervention efficacy between pre- and post-intervention within the same group was statistically significant at a significance level of | PMC10586320 | ||
Effect of 8 weeks EMS combined with RT on muscle strength and jumping force | The improvements in lower body strength and power were assessed using the CMJ test. As shown in | PMC10586320 | ||
Effect of 8 weeks EMS combined with RT on muscle strength and jumping force. |
Data are presented as mean ± SD.The intervention efficacy between pre- and post-intervention within the same group was statistically significant at a significance level of | PMC10586320 | ||
Discussion | muscle mass, EMS improves, fatigue, NHAlthough, Muscle mass, muscle mass gain | In recent years, numerous studies have demonstrated the advantages of EMS as a passive exercise for muscles. However, the gains in muscle strength or mass may still be influenced by the specific protocols and frequency of use (EMS is believed to have a significant impact on reducing body fat by increasing the resting metabolic rate (While there are differing opinions on the effects of EMS on fat loss, its benefits for increasing muscle mass are widely recognized. The mechanisms underlying the muscle mass gain observed with EMS involve several factors. EMS has been shown to enhance the regenerative capacity of satellite cells fused with mature skeletal fibers (Muscle mass and strength have been found to be closely correlated (Excessive accumulation of fatigue by-products, such as lactic acid and NHAlthough this study demonstrated that 8 weeks of resistance exercise training combined with EMS improves muscle mass and strength in young, healthy adults, there are several limitations that should be acknowledged. Firstly, the study only included a specific population of young, healthy subjects, limiting the generalizability of the findings to other populations. Additionally, the study focused on the short-term effects of EMS during the 8-week intervention period and did not assess the long-term effects of EMS on muscle and physical performance when used independently. Secondly, the sample size of the study was relatively small, which, although consistent with the calculated effective sample size, may have had a slight impact on the results. Therefore, future studies with larger sample sizes should be conducted to confirm these findings. Thirdly, although the study aimed to explore differences in body composition and muscle strength changes between different EMS, the inclusion of both male and female subjects in the same group for comparison may have been a limitation, as strength and physiological differences between genders can significantly influence the results. Fourthly, while bioelectrical impedance analysis (BIA) is a practical method for assessing body composition, it provides a global assessment and may benefit from the addition of local body composition analysis using dual-energy X-ray absorptiometry. Moreover, the study did not implement standardized interventions targeting nutrient intake. Although participants were instructed to maintain their usual eating habits during the trial, there was limited monitoring of dietary adherence. These limitations highlight areas for improvement and suggest the need for future research with more diverse populations, longer follow-up periods, larger sample sizes, and the inclusion of standardized interventions and more precise body composition assessment methods. Furthermore, in-depth mechanism research is warranted to explore the factors contributing to the effects of different EMS training programs on muscle mass and strength performance. | PMC10586320 | |
Conclusions | muscle mass | Our study demonstrates that 8 weeks of continuous resistance exercise training combined with daily EMS training targeting the upper body, lower body, and abdominal muscles can significantly improve muscle mass and upper body muscle strength, as well as significantly reduce body fat percentage. However, it did not show a significant effect on lower body explosive force. These findings suggest that the combination of resistance exercise training and EMS can be an effective strategy for enhancing muscle mass and upper body strength while reducing body fat percentage. In this study, we used a multi-frequency cyclic transformation method to perform EMS, giving different levels of muscle stimulation under 30 min of training. Our design philosophy is that this may have a larger effect than a fixed frequency. However, we need to further compare the advantages of different EMS solutions. In addition, further research is needed to explore the potential mechanisms underlying these effects and to optimize the protocols for EMS training in order to maximize its benefits on muscle performance. | PMC10586320 | |
Supplemental Information | PMC10586320 | |||
EMS data. | Click here for additional data file. | PMC10586320 | ||
Additional Information and Declarations | PMC10586320 | |||
Competing Interests | The authors declare that they have no competing interests. | PMC10586320 | ||
Human Ethics | The following information was supplied relating to ethical approvals (Institutional Review Board of Landseed International Hospital (Taoyuan, Taiwan; LSHIRB No. 21-034-A2). | PMC10586320 | ||
Data Availability | The following information was supplied regarding data availability:All the data are available in the | PMC10586320 | ||
References | PMC10586320 | |||
Introduction | PMT | Using Protection Motivation Theory (PMT), we examined the effect of threat appraisal information (perceived vulnerability-PV and perceived severity-PS) to reduce vaping intentions, and in turn reduce vaping use. Canadian university students (Canada has one of the highest rates of vaping usage in the world, with more than one-third of Canadian students having tried vaping products at some point in their lives, the highest rates of vaping being among young adults (18–24 years) (The existence of health risks associated with the use of e-cigarettes is robust, however, there is limited evidence to support the presence of health benefits and extent of health outcomes related to vaping cessation (An important practical intervention question is will information about the protective health risks of vaping behaviour have any impact on vaping intentions and behaviour for self-identified, regular vapers? | PMC10387725 | |
Current study | PMT | The purpose of the proposed study is to examine the effectiveness of an intervention grounded in the threat appraisal components of a PMT framework (i.e., PV and PS) that seeks to mitigate vaping intention and behaviour among Canadian university students that identify as regular vapers, vaping at least three times over 30 days prior to enrolling in the study (Hence, our research question was as follows: “Is health threatening information effective in motivating Canadian university students who regularly vape to reduce their intentions to vape and overall vaping behaviour?” Within this general research question, the following specific hypotheses were generated: (a) those exposed to the threat appraisal information grounded in the PMT components of severity and vulnerability will score higher on purpose-built questions reflecting these components than their attentional information control (nutrition and lifestyle information) counterparts; (b) those exposed to the threat appraisal information grounded in the PMT components of severity and vulnerability will show lower intentions to vape and lower vaping use compared to their attentional information control counterpart; and (c) increases both severity and vulnerability of vaping usage will be associated with a reduction in intentions to vape. Furthermore, reduction in intentions to vaping will be associated with lower vaping use. | PMC10387725 | |
Method | PMC10387725 | |||
Participants and sample size calculation | PMT | A convenience sample of Canadian university undergraduate students ((Completed data) demographic characteristic for the two treatment conditions.Standard deviation presented in parentheses.PMT: protection motivation theory group; | PMC10387725 | |
Design and procedure | PMT, RECRUITMENT | Study procedures were pre-registered with Clinical Trials and adheres to the requirements of the institutional registry. Data were collected in January 2021. Recruitment began in January 2021 and continued until data collection concluded in April 2021, at which point treatment effects on study outcomes were analyzed. Participants were recruited through digital posters in university student Facebook groups and the Mass Email Recruitment system at the institution. Participants were targeted to participate if they self-identified as a regular vaper (vaping at least 3× in the past 30 days) and were 18 years of age or older while being enrolled within an accredited Canadian university. Participants were allocated a participant ID (XX-YYY) upon enrollment in the study. Questionnaires used to collect data were labeled using participants’ ID and no identifiers were associated with participant ID to protect their anonymity. All communication and procedures (consent forms, distributed incentives, intervention videos, and questionnaire links) were conducted through registered emails of each respective participant. Thus, all participants read the Letter of Information and provided informed written consent prior to participation in the study. Participants were blinded and randomly allocated to one of two treatment groups using block randomization and a random number generator to allocate participants using a 1:1 ratio with block sizes of two. Participants in the PMT present group watched an 8-minute informational video that explained the current research and health risks associated with vaping, within the context of a threat appraisal focus. By design, this video focused on the severity of vaping behaviour on health and the susceptibility of young adult populations to adverse health effects with commentary by healthcare professionals and students who previously identified as regular vapers. Participants in the PMT absent group featured an 8-minute nutritional information video as an attention control (See | PMC10387725 | |
Measures | PMC10387725 | |||
Threat appraisal | PMT | Perceived vulnerability (PV) perceived severity (PS) were each assessed by four 10-point items (0 = strongly disagree to 10 = strongly agree), derived from past PMT literature ( | PMC10387725 | |
Goal intention | Goal intention was assessed by three 10-point purpose-built items (0 = | PMC10387725 | ||
Behaviour | Vaping behaviour was assessed by one 5-point purpose-built item (0 = | PMC10387725 | ||
Statistical analyses | REGRESSION | All analyses were conducted using IBM SPSS Statistics 25 for MacOS. Presentation of statistical results and analyses methods for both completed data and imputed data (sensitivity) are illustrated separately below. Both data sets used one-way ANOVAs and chi-square procedures to ensure that there were no systematic differences between groups on demographic characteristics. Separate 2 (group) by 4 (time) repeated measures ANOVAs were conducted for each of the variable measures: PV, PS, intention, and behaviour. Pearson correlation analyses were used to measure the statistical strength and direction of relationship between threat appraisal variables, vaping intention, and behaviour. Finally, a linear regression model was conducted to predict the parameters of threat appraisal on intention and intention on behaviour. | PMC10387725 | |
Results (completed data) | PMC10387725 | |||
Group differences | PMT | Separate one-way factorial repeated measure ANOVAs showed that the two treatment groups differed significantly across time on PS and PV. Specifically, the PMT intervention group scored higher on both threat components than their attention control counterparts. Non-significant treatment by time group differences for intention to reduce vaping behaviour were found. The effect size for this interaction was moderate in size and favoured the PMT intervention group. Non-significant effects were revealed between treatment groups for vaping behaviour for the follow-up assessments. The effect size for this interaction was large, and favoured the PMT intervention group, particularly towards the end of treatment ( | PMC10387725 | |
Missing and excluded data | Multiple imputation (MI) analyses were used for all missing data points across all variables within both treatment groups. The MI process included combining five plausible imputed data sets (estimated values on other available information) and appropriately combining results obtained from each of them ( | PMC10387725 | ||
Imputed group differences | PMT | Separate one-way ANOVAs showed that both treatment groups differed significantly on PS and PV across time. Significant treatment group differences across time for intention to reduce vaping behaviour and vaping use also were found. In all ANOVAS, the PMT intervention group showed higher PS, PV, and intentions as well as lower vaping use compared to the attention control group (see | PMC10387725 | |
Discussion | PMT | The results of the present study support the view that both threat appraisals (PV and PS) grounded in PMT are effective mechanisms to reduce vaping intentions among a sample of Canadian university students who regularly vape. With respect to vaping use, we found inconsistent and thus less convincing evidence for the effectiveness of the PMT intervention. Beyond these general findings, a number of specific issues warrant further commentary.Analysis with both completed and imputed data found significant differences between PV and PS favouring the experimental group. The effect sizes were large for both threat appraisal constructs when completed data were used (see Turning to intention, analysis within completed data revealed non-significant treatment by time interaction effect. An inspection of the data shows a positive change in intention to reduce vaping use for the PMT intervention group when compared to the attention control group (With respect to vaping use, we found inconsistent and thus less convincing evidence for the effectiveness of the PMT intervention (see (Complete data) mean and standard error scores between treatment groups across time for PV, PS, intention, and behaviour.T0: Baseline; T1: Day 7; T2: Day 30; T3: Day 45.Overall, we found consistent treatment effects for both completed and imputed data sets. Nevertheless, there was a noticeable discrepancy in effect size among the variables of interest between the completed and imputed data sets. We would conclude with completed data that the effects were large (with the exception of intention which was medium) among the variables of interest. In contrast, we would conclude with imputed data that the effects were medium.With respect to theoretically driven relationships among the variables of interest, we found evidence that increases in the threat components of PV and PS were associated with reductions in intentions to vape. Amongst both data sets, bivariate correlation analysis revealed that PV corroborated strongest with vaping intention overall (There are several strengths to the present study. These include a factually based threat appraisal vaping intervention grounded in PMT that is both cost effective and scalable (i.e., online intervention that can be easily implemented in public and private health settings with limited financial or structural obstacles). This study is not without limitations. For instance, although missing data were at random and appropriate imputation procedures (i.e., multiple imputation) were followed, there were large amounts of missing data, particularly from baseline to time 1 (T1). Future studies should consider implementing more user-friendly survey design features (i.e., restricting participants from submitting their questionnaires before answering each question) to mitigate missing data. Considering the medium to large effect sizes found in the present study, future studies should also aim to recruit over 50 participants per group for a between treatment design with an α level of 0.05 and a power of 0.80 ( | PMC10387725 | |
Conclusion | In conclusion, this is the first study to support the view that presenting isolated factual threat appraisal vaping information grounded in a Protection Motivation Theory framework concerning the possible negative health effects of vaping, may be effective at reducing vaping intentions and to a lesser extent vaping behaviour, among Canadian university students who regularly vape. We recommend replication work to confirm whether such message framing interventions can lead to short and long-lasting vaping behaviour change. | PMC10387725 | ||
Supplemental Material | PMC10387725 | |||
sj-docx-10-hpq-10.1177_13591053221144977 – Supplemental material for Using a protection motivation theory framework to reduce vaping intention and behaviour in Canadian university students who regularely vape: A randomized controlled trial | Click here for additional data file.Supplemental material, sj-docx-10-hpq-10.1177_13591053221144977 for Using a protection motivation theory framework to reduce vaping intention and behaviour in Canadian university students who regularely vape: A randomized controlled trial by Babac Salmani and Harry Prapavessis in Journal of Health Psychology | PMC10387725 | ||
sj-docx-8-hpq-10.1177_13591053221144977 – for Using a protection motivation theory framework to reduce vaping intention and behaviour in Canadian university students who regularely vape: A randomized controlled trial | Click here for additional data file.sj-docx-8-hpq-10.1177_13591053221144977 for Using a protection motivation theory framework to reduce vaping intention and behaviour in Canadian university students who regularely vape: A randomized controlled trial by Babac Salmani and Harry Prapavessis in Journal of Health Psychology | PMC10387725 | ||
sj-pdf-9-hpq-10.1177_13591053221144977 – Supplemental material for Using a protection motivation theory framework to reduce vaping intention and behaviour in Canadian university students who regularely vape: A randomized controlled trial | Click here for additional data file.Supplemental material, sj-pdf-9-hpq-10.1177_13591053221144977 for Using a protection motivation theory framework to reduce vaping intention and behaviour in Canadian university students who regularely vape: A randomized controlled trial by Babac Salmani and Harry Prapavessis in Journal of Health Psychology | PMC10387725 | ||
sj-spv-1-hpq-10.1177_13591053221144977 – for Using a protection motivation theory framework to reduce vaping intention and behaviour in Canadian university students who regularely vape: A randomized controlled trial | Click here for additional data file.sj-spv-1-hpq-10.1177_13591053221144977 for Using a protection motivation theory framework to reduce vaping intention and behaviour in Canadian university students who regularely vape: A randomized controlled trial by Babac Salmani and Harry Prapavessis in Journal of Health Psychology | PMC10387725 | ||
sj-spv-2-hpq-10.1177_13591053221144977 – for Using a protection motivation theory framework to reduce vaping intention and behaviour in Canadian university students who regularely vape: A randomized controlled trial | Click here for additional data file.sj-spv-2-hpq-10.1177_13591053221144977 for Using a protection motivation theory framework to reduce vaping intention and behaviour in Canadian university students who regularely vape: A randomized controlled trial by Babac Salmani and Harry Prapavessis in Journal of Health Psychology | PMC10387725 | ||
sj-spv-3-hpq-10.1177_13591053221144977 – for Using a protection motivation theory framework to reduce vaping intention and behaviour in Canadian university students who regularely vape: A randomized controlled trial | Click here for additional data file.j-spv-3-hpq-10.1177_13591053221144977 for Using a protection motivation theory framework to reduce vaping intention and behaviour in Canadian university students who regularely vape: A randomized controlled trial by Babac Salmani and Harry Prapavessis in Journal of Health Psychology | PMC10387725 | ||
sj-spv-4-hpq-10.1177_13591053221144977 – for Using a protection motivation theory framework to reduce vaping intention and behaviour in Canadian university students who regularely vape: A randomized controlled trial | Click here for additional data file.sj-spv-4-hpq-10.1177_13591053221144977 for Using a protection motivation theory framework to reduce vaping intention and behaviour in Canadian university students who regularely vape: A randomized controlled trial by Babac Salmani and Harry Prapavessis in Journal of Health Psychology | PMC10387725 | ||
sj-spv-5-hpq-10.1177_13591053221144977 – for Using a protection motivation theory framework to reduce vaping intention and behaviour in Canadian university students who regularely vape: A randomized controlled trial | Click here for additional data file.sj-spv-5-hpq-10.1177_13591053221144977 for Using a protection motivation theory framework to reduce vaping intention and behaviour in Canadian university students who regularely vape: A randomized controlled trial by Babac Salmani and Harry Prapavessis in Journal of Health Psychology | PMC10387725 | ||
sj-spv-6-hpq-10.1177_13591053221144977 – for Using a protection motivation theory framework to reduce vaping intention and behaviour in Canadian university students who regularely vape: A randomized controlled trial | Click here for additional data file.-spv-6-hpq-10.1177_13591053221144977 for Using a protection motivation theory framework to reduce vaping intention and behaviour in Canadian university students who regularely vape: A randomized controlled trial by Babac Salmani and Harry Prapavessis in Journal of Health Psychology | PMC10387725 | ||
Appendix | RECRUITMENT | CONSORT 2010 flow diagram.Number of potential participants reached through Facebook advertisements and the Mass Email Recruitment System remains uncertain. | PMC10387725 | |
Development of PMT and other material | PMC10387725 | |||
PMT video | PMT | The PMT present group watched an 8-minute informational video (video link: | PMC10387725 | |
Attention control video | PMT | The PMT absent group featured an 8-minute nutritional information video (video link: | PMC10387725 | |
Measures | PMC10387725 | |||
Demographic and modified youth vaping | Two seven-item vaping Canadian student vaping demographic and tobacco use questionnaires derived from an existing Canadian Student Tobacco, Alcohol, and Drugs Survey (CSTADS) conducted by a consortium of researchers across Canada, centralized at the University of Waterloo (2014). Excluding drugs assessment questions, the Demographic and Youth Vaping Questionnaires collected descriptive information, social influence, current behaviour, and use of past tobacco-based products. Example items include “What is your ethnicity?” (Demographic) and “Have you ever used chewing tobacco, cigarettes, cigars, cigarillos, or little cigars?” (YVQ-A). | PMC10387725 | ||
References | PMC10387725 | |||
Abstract | PMC10114117 | |||
Objective | To improve problem list documentation and care quality. | PMC10114117 | ||
Materials and methods | BLOOD DISEASES | We developed algorithms to infer clinical problems a patient has that are not recorded on the coded problem list using structured data in the electronic health record (EHR) for 12 clinically significant heart, lung, and blood diseases. We also developed a clinical decision support (CDS) intervention which suggests adding missing problems to the problem list. We evaluated the intervention at 4 diverse healthcare systems using 3 different EHRs in a randomized trial using 3 predetermined outcome measures: alert acceptance, problem addition, and National Committee for Quality Assurance Healthcare Effectiveness Data and Information Set (NCQA HEDIS) clinical quality measures. | PMC10114117 | |
Results | There were 288 832 opportunities to add a problem in the intervention arm and the problem was added 63 777 times (acceptance rate 22.1%). The intervention arm had 4.6 times as many problems added as the control arm. There were no significant differences in any of the clinical quality measures. | PMC10114117 | ||
Discussion | The CDS intervention was highly effective at improving problem list completeness. However, the improvement in problem list utilization was not associated with improvement in the quality measures. The lack of effect on quality measures suggests that problem list documentation is not directly associated with improvements in quality measured by National Committee for Quality Assurance Healthcare Effectiveness Data and Information Set (NCQA HEDIS) quality measures. However, improved problem list accuracy has other benefits, including clinical care, patient comprehension of health conditions, accurate CDS and population health, and for research. | PMC10114117 | ||
Conclusion | An EHR-embedded CDS intervention was effective at improving problem list completeness but was not associated with improvement in quality measures. | PMC10114117 | ||
BACKGROUND AND SIGNIFICANCE | diabetes, renal insufficiency | DECAY, RENAL INSUFFICIENCY, HYPERTENSION, DISEASES, DIABETES | WeedA complete patient problem list is the cornerstone of Dr Weed’s vision of the problem-oriented medical record. It serves as a valuable tool for providers assessing a patient’s clinical status and succinctly communicates this information between providers. An accurate problem list supports problem-oriented charting and can also help guide the flow of a clinical encounter, by reminding providers about important health issues to discuss or evaluate during the visit.Complete problem lists are also important for high-quality clinical decision support (CDS). Considerable evidence exists that, when effectively designed, CDS tools can improve quality of care and patient outcomes.Problem lists are also often used for clinical research and quality measurement. Many clinical improvement and research investigations, including large genomic studies, are becoming increasingly dependent on EHR data collected during clinical care.Further, the problem list is often used for quality measurements in EHRs, including those in the CMS meaningful use/promoting interoperability incentive program.An accurate problem list has been associated with higher quality care in observational studies. For example, in 2005, Hartung et alDespite this importance, coded problem lists are often inaccurate, incomplete, cluttered, and out of date. In previous work, we showed that problem list completeness in 1 network ranged from 4.7% for renal insufficiency or failure to 50.7% for hypertension, 61.9% for diabetes,Problem list completeness and use also varies dramatically by institution. For a single problem (diabetes), we found that the proportion of patients who had diabetes based on laboratory criteria had diabetes on their problem list 60.2% of the time at the lowest performing of 10 institutions, and 99.4% of the time at the highest performing institution.The causes of problem list incompleteness are myriad. In prior ethnographic work, we observed and interviewed 63 clinicians, and noted a “tragedy of the commons” occurring in many practice settings—providers reported that, frustrated with their incompleteness, they had stopped updating patient problem lists—this disuse then contributed to further decay of the problem list, causing other providers to also discontinue use.To improve problem list completeness, in prior work, we developed a series of algorithms which can identify missing problems from patient problem lists by analyzing other data in a patient’s EHR, including medications, laboratory results, and billing diagnoses. For example, if we detected a patient with a HbA1c of 9.2% who was on metformin, we inferred that they have diabetes and, if diabetes is missing from their problem list, we alerted their healthcare provider through the EHR. In a single-site randomized trial, we showed a 300% increase in problem list additions for the 17 conditions for which we had developed algorithms.Based on this prior work, we formulated 2 hypotheses: first, that the results from our single-site study could transfer to additional diseases and institutions—with CDS alerts leading to increased completeness of the problem list. Second, we further hypothesized that the CDS alerts would yield improvements in clinical quality, measured using EHR-based quality measures. | PMC10114117 |
METHODS | BLOOD, HEART, LUNG | With funding from the National Heart, Lung and Blood Institute, we developed a 4-site randomized trial of an intervention for improving problem list completeness. SitesPreviously called Partners HealthCare.Holy Spirit Hospital transitioned from the Allscripts Sunrise EHR to Epic during the intervention period and discontinued the intervention early. | PMC10114117 | |
System development | obstructive pulmonary disease (COPD)Congestive, CHF, heart failure, artery disease, infarction | BLOOD DISEASES, FIRES, CHF, HEART FAILURE, ARTERY DISEASE, INFARCTION | We developed and validated problem identification algorithms for 12 clinically significant heart, lung, and blood diseases:AsthmaAtrial fibrillationChronic obstructive pulmonary disease (COPD)Congestive heart failure (CHF)Coronary artery disease (CAD)HyperlipidemiaHypertensionMyocardial infarction (MI)Sickle cell anemiaSleep apneaStrokeTuberculosisThese algorithms used a combination of laboratory results, medications, encounter diagnosis codes, and procedures to identify patients who are likely to have one of these conditions, but who do not have a relevant problem list code on their problem list. The details of the algorithms are given in We then developed a CDS alert, which fires during a clinical encounter and suggests adding the potentially missing problem to the problem list. Screenshot of the IQ-MAPLE intervention, for CHF, at MGB.Each site used the same alerting logic and developed in-workflow CDS alerts to prompt users to add problems to the problem list. However, owing to differences in the clinical environments and EHRs at each site, they were free to tailor the presentation and workflow of the alert, following a standard framework for flexible EHR-based interventions. | PMC10114117 |
Study design | CAD | REGRESSION, CAD | Each site randomized providers (physicians, physician assistants, and nurse practitioners) to the intervention or control arm, using a random number generator. Each provider had an equal probability of being assigned to either arm. Providers in the intervention arm received the alert during clinical encounters. The alert was generated and logged for providers in the control arm; however, the alert was not actually shown to the user.Immediately after study completion, we extracted data on alert firing, alert acceptance, and problem list utilization at each site. We compared the rate of alert acceptance using a chi-squared test and the rate of problem list addition using Poisson regression.At one site (MGB), we also evaluated the effect of the alert on clinical quality measures. This analysis was done by condition and compared patients for whom an alert was generated and displayed in the intervention arm to patients for whom an alert would have generated, but not displayed, in the control arm. This analysis was done on an intention to treat basis. For example, for the “LDL Testing” measure in the CAD condition, we calculated the proportion of patients with a low-density lipoprotein (LDL) test during the measurement period, compared across the control and intervention arms. Proportions for each quality measure were compared using a chi-squared test, with a Bonferroni correction for multiple comparisons.The study was registered with clinicaltrials.gov prior to patient accrual, trial identifier NCT02596087, and was approved by the institutional review boards of MGB, Holy Spirit Hospital, Oregon Health and Science University, and Vanderbilt University. | PMC10114117 |
RESULTS | PMC10114117 | |||
Alert acceptance |
Proportion of missing problems added, by condition and arm | PMC10114117 | ||
Problem addition | We calculated the total number of study problems added across all conditions and all sites, by arm (Number of problems added, by arm and period. | PMC10114117 | ||
Quality measures | Finally, we evaluated the effect of the intervention on a predetermined set of HEDIS quality measures at one site (MGB). There were no differences in quality measures between the 2 groups (Clinical outcomes | PMC10114117 | ||
DISCUSSION | Our results demonstrate that the IQ-MAPLE intervention for problem list improvement had limited effectiveness at increasing problem list documentation, across conditions and at multiple sites. The overall acceptance rate (22.1%) is higher than those reported in many other published studies of CDSThe overall impact of the alert on problem documentation was strong—leading to a 4.6-fold increase in the number of problems added in the intervention arm. This increase is statistically significant; however, it is likely that there are still many patients who have the problems of interest missing from their problem list, again suggesting a need for alternative strategies for problem list addition.Our findings confirmed our hypothesis that the IQ-MAPLE intervention would lead to an increase in problem list additions. However, we further hypothesized that the intervention would also lead to an increase in measurable clinical quality. Unfortunately, our analysis of the HEDIS data suggests that, at least as measured by HEDIS, our intervention did not yield an increase in quality. There are several possible explanations for this. First, even after the intervention, many patients still had problem list gaps. Second, HEDIS measures may not be an accurate reflection of the true quality of care provided. | PMC10114117 | ||
Strengths and limitations | Our study has several strengths. It is the first multi-site, randomized study of problem list alerts done using a variety of EHRs and had a relatively effective intervention. It also had some important limitations. First, we did not assess whether the problems added from the alerts were accurate—we believe that they largely were, but there may have been some false positives. Second, although we had 4 sites, there were many differences in implementation strategy at each site, which meant we could not assess whether specific intervention characteristics (eg, inpatient vs outpatient, interruptive vs noninterruptive, and actionable vs nonactionable) made a difference. More sites or a longer time period of data collection, and a random allocation of alert features would be needed to draw these conclusions. Third, our data sharing plan did not include the sharing of additional baseline data about the rate of problem list utilization or number of encounters at each site, so we could not make direct comparisons beyond alert volume, acceptance, and the number of problems added at each site. However, since this study was a randomized controlled trial, we expect these to be well-balanced across arms at each site. Fourth, we focused, in this study, only on adding missing problems and not on removing inaccurate, unimportant, or redundant problems—problem lists frequently contain inaccurate or out-of-date problem entries, so this would be a useful topic for future research. Fifth, our study looked only at structured data already in the medical record to infer problems—by using, for example, natural language processing on notes, optical character recognition of scanned documents, and integration of external data (eg, through a health information exchange) additional problems could potentially be identified, possibly with higher specificity. Finally, more fully automated strategies, such as automatic creation and maintenance of the problem list could also be explored with a goal of reducing the overhead of maintaining the problem list for clinicians—such a strategy would need to be weighed against possible issues with accuracy, as well as the possibility that clinician curation of the problem list may have benefits as the clinician thinks through a patient’s problems. | PMC10114117 | ||
CONCLUSIONS | Conducting, randomized, multi-site, CDS interventions using different EHRs with different clinical workflows, upgrade cycles, patient populations, CDS governance committees, and different abilities to configure local CDS features is challenging. An EHR-embedded CDS intervention was effective at improving problem list completeness but was not associated with improvements in quality measures. The problem inference algorithms developed may have additional uses, such as improving the accuracy of clinical quality measures or EHR-based phenotyping locally or in networks such as eMERGE. | PMC10114117 | ||
Supplementary Material | Click here for additional data file. | PMC10114117 | ||
ACKNOWLEDGEMENTS | The authors express their gratitude to both Calvin Beidleman and Kevin Peters for their instrumental assistance with many technical details, including alert programming and randomization of participants. | PMC10114117 | ||
FUNDING | Research reported in this publication was supported by the National Library of Medicine of the National Institutes of Health under Award Number 1R01HL122225. The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health. | PMC10114117 | ||
AUTHOR CONTRIBUTIONS | Dr A.W. and Dr D.F.S. made substantial contributions to the conception and design of the work. All authors assisted in the acquisition, analysis, and interpretation of data. Dr A.W. wrote the initial draft, and all authors revised it critically for important intellectual content. All authors had final approval of the version to be published, and all agree to be accountable for all aspects of the work in ensuring that questions related to the accuracy or integrity of any part of the work are appropriately investigated and resolved. | PMC10114117 | ||
SUPPLEMENTARY MATERIAL | PMC10114117 | |||
CONFLICT OF INTEREST STATEMENT | None declared. | PMC10114117 | ||
DATA AVAILABILITY | The data underlying this article will be shared on reasonable request to the corresponding author. | PMC10114117 | ||
REFERENCES | PMC10114117 | |||
Subject terms | This experimental crossover study was performed to investigate whether fenestrated surgical drapes (covering the nose and mouth but with an opening over the periorbital area) with or without patients’ surgical face masks increase periorbital bacterial dispersion during simulated intravitreal injection conditions. Each of the 16 healthy volunteers performed 14 scenarios involving different mask and drape conditions in both silent and speaking situations. In each scenario, the subject lay down flat on the back with a blood agar plate being held at the inferior orbital rim perpendicular to the face to capture airflow from breathing/speaking. Another blood agar plate placed 50 cm away from the subject served as an experimental control. A total of 224 experiments were performed. Speaking situations significantly showed more colony forming units (CFUs) compared with their controls (P = 0.014). There were no significant differences in CFUs between wearing vs not wearing the masks (P = 0.887 for speaking and P = 0.219 for silent) and using vs not using the drapes (P = 0.941 for speaking and P = 0.687 for silent). Reusable and disposable drapes were also not significantly different (P = 1.00 for speaking and P = 0.625 for silent). | PMC10279653 | ||
Introduction | endophthalmitis, diabetic macular | CORONAVIRUS INFECTION, ENDOPHTHALMITIS, NEOVASCULAR AGE-RELATED MACULAR DEGENERATION, STERILE, DISEASES | Intravitreal injections of medications, particularly anti-vascular endothelial growth factors (anti-VEGF), are currently considered as one of the most common procedures in medicine to treat diseases such as neovascular age-related macular degeneration and diabetic macular edemaDuring the COVID-19 pandemic, face mask wearing has become a general routine to decrease the risk of coronavirus infection. However, there was a concern that face masks used by patients may increase oropharyngeal bacterial dispersion toward the eyes due to upward air flow from breathing or speakingIn many ophthalmology centers including our center at Siriraj hospital, sterile fenestrated surgical drapes (with an opening over the periorbital area) have been employed to cover patients’ faces before giving intravitreal injections to keep the area sterile and to increase awareness of serious procedures for both physicians and patients, although there was no significant evidence that the routine use of the drapes could reduce endophthalmitis rateThus, this study aims to investigate the amount of bacterial dispersion toward the periorbital area associated with the use of fenestrated surgical drapes with or without patients’ face masks during simulated intravitreal injection situations. | PMC10279653 |
Methods | PMC10279653 | |||
Subjects | allergy, fever | CHRONIC AIRWAY DISEASE, ALLERGY, OCULAR INFECTION | This experimental multiple crossover study was approved by the Siriraj Institutional Review Board, COA No. Si508/2021, and was performed in accordance with the Declaration of Helsinki. The study was registered in the Thai Clinical Trials Registry, No. TCTR20221222002 (22/12/2022). Healthy volunteers aged 18–80 years old were included. Subjects with the following criteria were excluded: fever or respiratory symptoms or systemic antibiotics administration within the past 2 weeks, chronic airway diseases, facial skin or ocular infection, inability to lie down flat on the back and allergy to adhesive paper tape (3M™ Micropore Tape 1530-1). Informed consent was obtained from all participants. | PMC10279653 |
Study procedures | STERILE | The study was conducted in a closed air-conditioned room, used for everyday intravitreal injections at the Intravitreal Injection Clinic, Siriraj Hospital. The room was disinfected with UVC light (Philips UVC disinfection desk lamp 24W S TC) for 30 min before each subject. There were no specialized air filtration equipment or positive/negative pressure ventilation systems.In each experiment scenario, a subject was instructed to lie down flat on an injection bed. An investigator stood behind the head position of the bed while holding a blood agar plate for 2 min at the inferior orbital rim perpendicular to the face of the subject. The second investigator held a second blood agar plate, serving as an experiment control, 50 cm away from the subject, at the same height and in a similar orientation to the first plate. Both investigators wore N95 mask (3M™ Aura™ 1870+) and remained silent throughout the experiment. Prior to the experiment phase in each subject, a blood agar plate was placed at the head position of the bed for 2 min without people in the room to serve as a room condition control. All blood agar plates were sent for bacterial culture tests.Each subject was instructed to perform 7 experiment scenarios of using fenestrated sterile drapes and/or surgical face masks. The scenarios were the following: (1) no fenestrated sterile drape and face mask; (2) face mask only; (3) face mask with taping of the superior rim of the mask with adhesive paper tape (3M™ Micropore Tape 1530-1); (4) reusable fenestrated sterile cloth drape without face mask; (5) reusable fenestrated sterile cloth drape with face mask; (6) disposable fenestrated sterile drape without face mask; and (7) disposable fenestrated sterile drape with face mask. For all subjects, the face masks were worn tight fit to the nose (with the malleable nose bridge metal strip firmly pressed around the nose) and the openings of the fenestrated sterile drapes were centered over the right eye. Each scenario was performed in both silent and speaking conditions (14 scenarios in total). For speaking conditions, the subject was instructed to count consecutive numbers (in the Thai language) out loud for 2 min. The surgical face masks used in this study were disposable 3-ply face masks with ear loops and commercially available under the tradename Medimask (ASTM, F2100, level 1). The reusable fenestrated sterile cloth drapes (45 × 45 cm) and the disposable fenestrated sterile drapes (35 × 45 cm, polyethylene nonwoven sheet, Thai Gauze Co., Ltd.) contained the oval apertures of 35 × 50 mm. For each participant, the same mask and drapes were used for all of the 14 scenarios.To minimize carryover effects of each scenario to one another on the bacterial culture outcomes, the sequences of the scenarios were randomized for each subject prior to the experiments. The randomization first involved sequences of wearing/not wearing face masks and then sequences of covering/uncovering the faces with different types of sterile drapes. For each subject, the same randomized sequence was used for both silent and speaking conditions. Speaking scenarios were always performed after silent scenarios in every subject as speaking might cause more bacterial dispersion. There was a 2-min washout period in which the investigators all wearing N95 and remaining silent in the injection room between each scenario.All blood agar plates were sealed, labeled by anonymous code number and transferred to the Microbiology Laboratory at Siriraj hospital where they were incubated for 72 h at 37 °C in a 5% carbon dioxide–rich environment. The number of bacterial colonies per plate were counted using standard laboratory techniques by microbiologists. The bacterial species were identified using the conventional biochemical techniques of the Department of Microbiology, Faculty of Medicine Siriraj Hospital (test code 201201 bacteria: culture [aerobic]). The microbiologists were blinded to the experiment scenarios. | PMC10279653 | |
Statistical analysis | STERILE | The amount of bacteria in colony forming units (CFUs) were compared between different scenarios using Wilcoxon signed-rank test. When the CFUs were either 0 or 1 in each subject, the comparisons were made using McNemar’s test.The effect of each of the factors including: (1) the presence/absence of face masks; (2) the presence/absence of fenestrated sterile drapes; and (3) the types of drapes (reusable and disposable) was analysed. Different scenarios were grouped according to the above factors. In particular, the presence of face masks included scenarios 2, 5 and 7. The absence of face masks comprised scenarios 1, 4 and 6. The presence of fenestrated sterile drapes consisted of scenarios 4, 5, 6 and 7. The absence of fenestrated sterile drapes included scenarios 1 and 2. Reusable drape consisted of scenarios 4 and 5 and disposable drape was composed of scenarios 6 and 7. The bacterial CFUs were summed within group and compared between different groups. | PMC10279653 | |
Conference presentation | The work has been presented at the 128th annual meeting of the Korean Ophthalmological Society, Seoul, Korea on 29th October, 2022. | PMC10279653 | ||
Results | STERILE | Sixteen volunteers fulfilled the inclusion and exclusion criteria and were recruited into the study. The mean ± standard deviation of age was 30 ± 5.8 years old and 63% were female. The total number of blood agar was 464 plates from 224 experiments. All 16 room control agar plates did not grow any bacteria. The distributions of subjects according to the amount of bacteria in CFUs in all speaking scenarios and all silent scenarios were shown in Fig. Comparisons of the amount of bacteria in colony forming unit (CFU) between experimental and control blood agar plates in speaking and silent scenarios.The effects of wearing face masks, using fenestrated sterile drapes, or types of drapes were separately analysed (Fig. The distributions of subjects according to the amount of bacterial colony forming units comparing between wearing vs not wearing face masks, using vs not using fenestrated sterile drapes and using reusable vs disposable drapes in speaking and silent scenarios.A total of 87 bacterial CFUs grew on the blood agar plates (53 in experiment plates and 34 in control plates). Microbial strains identified in this study. | PMC10279653 | |
Acknowledgements | The authors thank Chulaluk Komoltri, PhD, Research Group and Research Network Division, Siriraj Hospital, Mahidol University, for her assistance in statistical analyses. The study was supported by Siriraj Development Research Fund (managed by Routine to Research: R2R), Siriraj Hospital, Mahidol University # R016435062. | PMC10279653 | ||
Author contributions | N.P., S.Pr., R.J. and P.N. were involved in study conception and design. R.J., P.P., and S.Ph. collected the data. N.P., R.J. and P.P. analysed the data. N.P. and R.J. wrote the manuscript. N.P., S. Pr. and P.N. supervised the study process. All authors reviewed and approved the final version of the manuscript. | PMC10279653 | ||
Data availability | The datasets generated during and/or analysed during the current study are available from the corresponding author on reasonable request. | PMC10279653 | ||
Competing interests | The authors declare no competing interests. | PMC10279653 | ||
References | PMC10279653 |
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