Twenty-two community-dwelling patients with chronic hemiplegia participated in this study. Eight participants performed only discrete-skill step training during the loading response phase, focusing on paretic hip extension movement (LR group). Another eight performed only discrete-skill step training during the preswing phase, focusing on paretic swing movement (PSw group). The remaining six were trained using both training methods, with at least 6 months in each group to washout the influence of previous training. Therefore, the final number of participants in each group was 14. The braking and propulsive forces of GRFs were measured during gait before and after 30 repetitions of the discrete-skill step training.  Although both groups showed a significant increase in stride length, walking speed was increased only in the LR group. The PSw group showed an increase in braking forces of both sides without any change in propulsion. In the LR group, paretic braking impulse did not change, while nonparetic propulsion increased.  The discrete-skill step training during loading response phase induced an increase in nonparetic propulsion, resulting in increased walking speed. This study provides a clear understanding of immediate effects of the discrete-skill step training in patients with chronic stroke and helps improve interventions in long-term rehabilitation. Stroke is a leading cause of long-term dysfunctionality in daily living due to motor paralysis, muscle weakness, abnormal muscle tone, and sensory impairments. Although the majority of patients post stroke are able to walk independently, many cannot walk with sufficient speed and endurance for resuming daily activities . PreviouThe important walking phase concerned with paretic lower limb deficit is the double-stance phase. The major role of this phase, step-to-step transition, is to control the center of mass (COM) trajectory using ground reaction forces (GRFs) generated from both the paretic and nonparetic limbs . Since tEssentially, motor skills are classified into discrete, serial, and continuous . WalkingThis pilot study presents a preliminary exploration of long-term interventions in individuals with chronic stroke. We hypothesized that the discrete-skill step training based on loading response and preswing phases of the paretic limb movement results in a faster gait speed immediately by regulating the paretic braking force and propulsion, respectively. This study investigates whether a single session of step training using discrete skills on step-to-step transition can improve walking in individuals with chronic stroke.Twenty-two community-dwelling patients with hemiplegia due to chronic stroke participated in this study. All participants could walk independently. The inclusion criteria were as follows: (i) history of a single stroke at least 6 months prior to this study and (ii) the ability to walk independently for at least 5 m without using a cane, with or without ankle-foot orthosis (AFO). The exclusion criteria were as follows: (i) orthopedic diseases affecting measurements and (ii) other neurological diseases such as Parkinsonism and ataxia.The participants were randomly assigned to each group and trained on the paretic lower limb movement using a discrete skill in one session. Eight participants performed only discrete-skill step training during the loading response phase, focusing on paretic hip extension movement (LR group). The other eight performed only discrete-skill step training during the preswing phase, focusing on paretic swing movement (PSw group). The remaining six were trained using both training methods. In this case, a period of more than 6 months was set up to washout the influence of previous training. Finally, the number of participants added up to 14 in both groups.This study was approved by the Institutional Ethics Committee. All participants provided written informed consents prior to participation in this study.In this study, we focused on developing discrete skills of the paretic lower limb during two double-stance phases of gait including loading response and preswing.The loading response phase requires weight acceptance and redirection of the COM with the leading limb . In indiThe preswing phase is also important since the COM is propelled forward and upward by the propulsion generated on the trailing limb in this phase . In indiAll participants performed step training by grasping the parallel bar using the nonparetic hand. Those who used an AFO during gait evaluation prior to the step training also used it during step exercise. Prior to the training, one of the two skilled physical therapists instructed verbally and displayed how to perform the step training. In the training, instructions and feedback of the step movement were provided by the therapist. Firstly, the participants in the LR group were given instructions: “Strengthen the hip extension of the paretic limb.” If the therapist observed that the paretic movement was difficult or inadequate, he gave the second instruction: “More forward stepping of the nonparetic limb.” On the other hand, the participants in the PSw group were given the first instruction: “Try to relax the knee of the paretic limb.” Similarly, if the therapist noticed that the paretic movement was performed inadequately or inappropriately, he gave the second instruction: “Immediately transfer the weight toward the nonparetic side.” These second instructions were to facilitate a smooth weight transfer.Gait parameters were measured before and after each step training session. Two pieces of force plates  were used to measure GRFs during gait rehabilitation. The force plates were 60 cm long and 40 cm wide. They were arranged side by side along their length in the middle of the walkway (4 m 40 cm). The participants were instructed to walk at a comfortable walking speed without a cane. If some participants were unable to walk without AFO, they were allowed to wear it . The GRF data were recorded at a sampling rate of 1,000 Hz during the stance phase on the paretic and nonparetic limbs. Due to the setting of force plates, the GRF data were measured on one side for each trial. The GRF data were collected from more than three successful stance phases of both sides. In addition, the number of steps and the time taken during the 3 m walk were also measured. A time interval of a few minutes was set between the preassessment and training period and between the training period and the postassessment to prevent fatigue. If the participants needed, a further few minutes was given as appropriate.For the clinical evaluation, the following tests were performed to assess the physical function in both groups: a score on the Fugl-Meyer Assessment (FMA) scale was evaluated for motor function, and the Functional Ambulation Categories (FAC) score was evaluated for walking ability.GRF data were filtered with a low-pass fourth-order Butterworth filter at 6 Hz forward and backward in time. Peak forces, impulses, and duration time in both braking and propulsive phases were calculated. Each parameter was averaged by the number of measured trials. Peak forces and impulses were normalized according to the participant's body weight. Walking speed and cadence were calculated using the number of steps and the time taken for a 3 m walk. Stride length was also calculated by doubling the average step length.t-tests for parametric or Wilcoxon signed-rank tests for nonparametric. Similarly, the differences in temporospatial parameters, such as walking speed, stride length, and cadence, were compared using the same tests, as appropriate. Statistical significance was set at P < 0.05.First, we investigated the normality of all variables using Shapiro-Wilk tests. The differences in GRF parameters, such as peak forces, impulses, and duration of braking and propulsive forces of both sides, were measured before and after the step training and comparatively analyzed using paired Two participants in the LR group and one participant in the PSw group were excluded from the analysis because it was difficult for them to walk by placing the affected limb properly on the force plates. Therefore, the enrolled participants in this study finally were 12 in the LR group and 13 in the PSw group. Six participants in the LR group and ten participants in the PSw group were not able to walk without AFO, so they were allowed to use the AFO during step training and gait evaluation.P = 0.038), whereas impulse and duration time did not change significantly . Nonparetic propulsive forces increased significantly . Simultaneously, the duration time of the nonparetic propulsive phase decreased significantly. While nonparetic braking forces increased significantly , paretic propulsive forces did not change significantly but tended to increase .As immediate effects on the LR group, stride length and walking speed increased significantly after the training . Among tRegarding immediate effects on the PSw group, stride length increased, and cadence decreased significantly . HoweverThis study revealed that the single discrete-skill step training session could immediately change paretic and nonparetic GRFs while performing a continuous skill such as walking. The findings of this study can be beneficial for gait rehabilitation in patients with gait dysfunction due to chronic stroke.The stride length and walking speed immediately increased in patients of the LR group after the repetitive step training that emphasized on the paretic hip extension during loading response. In general, the impulses of anteroposterior GRFs are expected to increase as the stride length and walking speed increase , 22. In Nonparetic propulsion increased significantly with peak force and impulse in this study. However, paretic braking force increased only in peak force, not in impulse. It is noteworthy that there was a difference between changes in peak force and impulse in paretic braking forces. The increase in peak braking force of the paretic leading limb suggests that the paretic limb could receive a greater propulsive force from the nonparetic limb as walking speed increases. On the other hand, no change in paretic braking impulse would indicate another reason. Turns et al. reported that paretic braking impulse increased as compared to the nonparetic limb in individuals with severe hemiparesis . This exNeptune et al. showed that the hamstring muscles accelerated the trunk forward at the beginning of stance . Since tThe stride length of PSw group patients increased, although their cadence was decreased without changes in walking speed. A decreased cadence indicated a prolonged gait cycle. Therefore, although the stride length was increased, walking speed remained unchanged due to the prolonged gait cycle. Only braking forces (peak and impulse) of both limbs increased along with the increase in stride length. Conversely, the propulsive forces of both limbs did not change.Previous studies on walking simulations reported that the triceps surae muscles contribute to the propulsion and swing of the lower limb . The proThe training in the PSw group emphasized on knee flexion during paretic swing phase. However, the difficulty of paretic swing control may slow down the swing motion and lead to a prolonged gait cycle after training. In addition, we ascribed that the step length increased due to the increase in paretic swing movement, resulting in an increase in paretic braking force. Previous studies reported that the iliopsoas is also a contributor muscle to the knee flexion during preswing , 27. RegIf clinicians want to increase the patient's walking speed immediately, the step training with consciousness of the paretic hip extension during loading response may be beneficial. On the other hand, although propulsive force is generated during the preswing phase, it may be difficult to improve walking speed immediately by step training with consciousness of paretic swing movement.There are some limitations to this study. First, the effects of step training using a discrete skill were not compared with another training using a continuous skill. In the future, it is necessary to clarify the effects of step training using discrete skill by comparison with a step training session based on using continuous skill. Second, more detailed kinetic and kinematic parameters, such as step length of both limbs and joint motion, could not be measured because of environmental hindrances. Further investigation is needed to reveal the effects of discrete-skill step training using more detailed gait parameters.The current study revealed that a single session of repetitive step training using the discrete skill could change gait performance immediately in individuals after chronic stroke. Notably, discrete-skill step training, which focuses on paretic hip extension movement during loading response, immediately increases walking speed because of the increased nonparetic propulsion by regulating paretic braking force. On the other hand, the step training that focused on paretic swing movement during preswing immediately increased stride length and decreased cadence. The participants in this group immediately increased only braking forces of both limbs with no change in walking speed. These findings suggest that step training may be useful as an explicit learning to change GRFs during gait.


Knowledge about GDM significantly improved after education, with few differences between the two education settings. Both patients in group and individual education were equally satisfied with the content and duration of the initial and follow-up education. Of all group participants, 91.8% (n = 90) were satisfied with group size (on average three participants) and 76.5% (n = 75) found that group education fulfilled their expectations. In conclusion, women diagnosed with GDM were overall satisfied with the education session’s content leading to a better understanding of their condition, independent of the education setting. Group education is a valuable alternative to better manage the increasing workload and is perceived as an added value by GDM patients.The value of diabetes education, focusing on lifestyle measures, in women with gestational diabetes mellitus (GDM) is acknowledged, but requires intensive education and input of resources if done on an individual basis. Group education could be a valuable alternative to individual education. This study aims to investigate the impact of multidisciplinary group education on women’s knowledge about GDM, education, treatment satisfaction, and emotional status. Two hundred women with GDM were enrolled in a prospective observational study. Dutch speaking women were offered group education at their first visit after GDM diagnosis. Non-Dutch speaking women or women for whom group education was not possible received individual education. Individual follow-up with a dietitian was planned within two weeks for all women. Women receiving individual education ( Gestational diabetes mellitus (GDM) is one of the most frequent medical conditions during pregnancy and is defined as diabetes diagnosed in the second or third trimester of pregnancy, provided that overt diabetes early in pregnancy has been excluded . GDM is Treatment of women with GDM results in a lesser degree of perinatal complications and can potentially improve the health-related quality of life ,3,12,13.Group education is a well-documented alternative to individual education in the organization of diabetes care in general, serving as a method to meet the educational needs of diabetes patients while at the same time providing peer support and motivation ,16. HoweClinicaltrials.gov (NCT02528162). Participants provided written informed consent before inclusion in the study.This study was performed in compliance with the principles of the Declaration of Helsinki (2008) and received approval from the local Ethics Committee of UZ Leuven (B322201525589). Prior to the first inclusion, the study was registered in This monocentric prospective observational cohort study was conducted at the University Hospital UZ Leuven in Belgium from October 2015 to September 2018. Since October 2015, the endocrinology department of UZ Leuven replaced the initial individual education session for the management of GDM as much as possible by structured group education sessions. Screening for GDM was based on a universal two-step screening strategy with a 50 g glucose challenge test (GCT) and a 75 g oral glucose tolerance test (OGTT) using the IADPSG/2013 WHO criteria. After diagnosis of GDM, Dutch speaking women were invited to attend a multidisciplinary group education session of maximum 1.5 h with a maximum of six participants. The session was organized on a weekly basis and was provided by a certified diabetes educator and a specialized diabetes dietitian. For non-Dutch speaking women or if group education was not possible, the first education session was delivered individually. A structured PowerPoint presentation was used both in the group and individual education sessions to educate about the pathophysiology, consequences and treatment of GDM—including dietary intake, physical activity and SMBG. The structure and content of this presentation was evaluated on a regular basis and adapted if necessary to the most recent guidelines and recommendations. For non-Dutch speaking patients, the presentation was translated to French and English. At the end of the education session, women received the handouts of the presentation, a brochure with information on physical activity, a glucose monitoring diary, a seven-day diet journal, a brochure on specific dietary guidelines with adapted recipes and material for SMBG.Regardless of the initial education setting, all women were offered an individual follow-up session of 30 min with a dietitian within two weeks after the initial education session. During this session, women received further advice regarding their gestational weight gain and dietary habits based on their seven-day diet journal together with the SMBG results. The glycemic targets of the American Diabetes Association (ADA) were followed (fasting plasma glucose < 95 mg/dL (5.3 mmol/L) and two hours after meals < 120 mg/dL (6.6 mmol/L)) [Women diagnosed with GDM could participate if at least 18 years old. Women were excluded if they had a history of bariatric surgery, were diagnosed with pregestational diabetes or if they could not speak fluently Dutch, French or English. All other women attending a group or individual education session were invited to participate in the study. Data were collected from the electronic medical records and through questionnaires. Outcome data from women who received the initial education session in group were compared to those from women who received the initial education session individually.All participants—both in group and individual education—were asked to complete several questionnaires at three different time points during the multidisciplinary education program: prior to the initial education session, immediately after the initial education session and after the individual follow-up session with the dietitian. The questionnaires aimed to evaluate the education of GDM, the knowledge on GDM and the emotional status. For this purpose, the questionnaires measured sociodemographic characteristics of the subjects, knowledge of GDM, feelings of depression and anxiety associated with the diagnosis of GDM, and the satisfaction with the education and the treatment. It took about 10 to 15 min at each point in time to fill in the questionnaires. All questionnaires were translated into French and English for non-Dutch speaking participants. An overview of the questionnaires administered at each time point is given in Questionnaire I on sociodemographic characteristics: A self-designed sociodemographic questionnaire—including data on education level, ethnicity, financial and marital status—was administered at the start of the initial education session. This questionnaire was based on a questionnaire that has previously been used in the Belgian Diabetes in Pregnancy Study .Questionnaire II on knowledge of GDM: Knowledge of GDM was assessed before and after the initial session and after the follow-up session to measure knowledge gains, using a self-designed questionnaire containing 14 multiple-choice questions on risk factors for and consequences of GDM, diagnosis of GDM, treatment of GDM and follow-up after delivery. Proportions of correct responses on the knowledge questionnaire of the total cohort prior to the initial education session were compared to those after the follow-up session in order to evaluate knowledge improvement after education. In order to compare the knowledge about GDM between participants in group education and those in individual education, response rates on the knowledge questionnaire after the initial education session were compared between both groups. Questionnaire IIIa and IIIb on satisfaction with the education sessions: Two self-designed questionnaires were created to evaluate satisfaction with the education program and whether treatment goals could be achieved. The first education satisfaction questionnaire (IIIa) was administered after the initial education session and evaluated the participant’s degree of agreement with the clarity and relevance of the explanation on twelve items that were discussed during the presentation, using a five-point Likert scale. This questionnaire also contained an extra section with multiple choice questions for women attending the group education to evaluate perceptions on the duration of the group session, the advantages and disadvantages of group education and the size of the group. At the end of the questionnaire, an open question was included to share comments about the education session. The second education satisfaction questionnaire (IIIb) was completed after the follow-up session with the dietitian and again assessed participant’s satisfaction with the twelve discussed items during the session. An additional set of questions on a five-point Likert scale was included regarding patient satisfaction on accomplishing lifestyle modifications in the week following the initial education session. At the end of this questionnaire, women were given the opportunity to share their opinions about the education session in an open question. Questionnaire IV on depression: To measure possible feelings of depression, the ‘Center for Epidemiologic Studies Depression’ (CES-D) questionnaire was completed at all three time points. The CES-D questionnaire is a validated tool to use in pregnancy and consists of 20 items with each item being scored between 0 and 3 on a four-point Likert scale, from respectively ‘rarely or none’ to ‘almost all the time’. Total score on the CES-D questionnaire can range from 0 to 60, with a score of ≥ 16 being suggestive for clinical depression . Questionnaire V on anxiety: The validated six-item short-form of the Spielberger State-Trait Anxiety Inventory (STAI-6) questionnaire was administered at each point in time to measure state anxiety level. The six items are scored from ‘very much’ to ‘not at all’ with a four-point Likert scale and a total score ranging from 6 to 24, with a higher score referring to a greater level of anxiety ,23. Questionnaire VI on treatment satisfaction: The Diabetes Treatment Satisfaction Questionnaire—status version (DTSQs) is a validated tool for measuring satisfaction with diabetes treatment regimens and was administered after the follow-up session. This is an eight-item questionnaire in which each item is scored on a seven-point Likert scale from 0 to 6 . The DTS2), obesity (BMI ≥ 30 kg/m2), gestational weight gain , parity, family history of diabetes, smoking, alcohol intake during pregnancy and history of GDM. Excessive gestational weight gain was defined according to the most recent Institute of Medicine (IOM) guidelines [Data from the participant’s electronic medical record (EMR) were collected during pregnancy, at delivery and at three months postpartum. Maternal characteristics recorded were age, ethnicity, height, body weight, body mass index (BMI) at first prenatal visit and at delivery, overweight , preeclampsia -syndrome), preterm delivery (<37 weeks of gestation) and cesarean section (planned and emergency sections combined). Neonatal pregnancy outcomes recorded were: gender, birth weight, macrosomia (birth weight > 4 kg), large-for-gestational age infants , small-for-gestational age infants , shoulder dystocia, Apgar score at five minutes and admission at the neonatal intensive care unit (NICU) .p-value of <0.05 (two-tailed) was considered significant.Statistical analyses were performed using SPSS software for Windows . Continuous data were expressed as mean and standard deviation (SD) if normally distributed, otherwise, variables were displayed as median and interquartile range (IQR). Categorical data were presented as frequencies and percentages. To compare variables between two groups, independent sample t-tests were used for normally distributed continuous variables, Mann-Whitney U-tests for non-normal variables and Chi-square tests for categorical variables. To evaluate the effect of the education, the Wilcoxon Signed Rank test was used for non-normal variables and McNemar test for categorical variables. Multivariable models were used to correct for significant differences in general patient characteristics between both groups. Linear regression was used for continuous outcomes and logistic regression for binary outcomes. A n = 392). Women with GDM who did not participate in the study despite meeting the inclusion criteria (n = 145), were mostly women who received the initial education during hospitalization, were unable to participate due to practical reasons such as arriving too late for the education session, or women who declined to participate. Of all participants, 100 attended the initial education session in group and 100 received the initial education session individually. As this was an observational study, the equal division of participants over the two groups occurred by chance. The average number of women seen in each group education session was three. Results did not differ when excluding non-Dutch speaking women. The A total of 200 pregnant women with a recent diagnosis of GDM were enrolled. The prevalence of GDM over this period was 6.6% (n = 13 of 116 women with more than one pregnancy) had a previous history of GDM, 23.7% (n = 47) had an ethnic minority (EM) background. The most frequent EM background was Asian in 10.6% (n = 21), Black-African in 4.0% (n = 8), Northern-African in 4.0% (n = 8), Middle-Eastern in 2.0% (n = 4) and Turkish in 1.5% (n = 3). Women receiving individual education were more often from an EM background than women in group education (32.0% (n = 32) versus 15.3% (n = 15), p = 0.01). There were no other significant differences in characteristics between women in each setting (n = 170) attended the postpartum OGTT of which 40.4% (n = 67) had glucose intolerance  had excessive gestational weight gain, 8.2% (n = 16) had preeclampsia and 30.3% (n = 59) had a cesarean section. Of all babies, 9.3% (n = 18) was LGA, 9.9% (n = 19) SGA and 5.2% (n = 10) had macrosomia. There were no significant differences in pregnancy outcomes between the different education groups  completed the knowledge questionnaire prior to the initial session and after the follow-up session. Women generally had good knowledge about GDM before the initial education session, which improved significantly for almost all items after the follow-up session .Women showed an overall good knowledge of most topics after the initial education session, with almost no significant differences between the group and individual education groups .Patients were overall satisfied with the content and duration of both the initial and follow-up education sessions . The majn = 98), 91.8% (n = 90) were pleased with the size of the group. A large majority of 76.5% (n = 75) indicated that group education fulfilled their expectations, although 22% (n = 22) indicated that they would prefer supplementary individual education after group education. Only four women (4.1%) preferred individual education alone. The most frequently reported advantages of group education were ‘learning from the questions of others’  and ‘learning from the experience of others’ , followed by ‘feeling supported by the group’  and ‘helping you to stick to the advice’ . However, 10 women (10.2%) reported no advantages of group education and four women (4.1%) indicated that they felt inhibited by the group.Of all women who completed the additional questions about group education (n = 152), a large majority agreed that is was possible to follow the advice about diet, physical activity, weight gain, and glycemic measurements. Almost all participants agreed or strongly agreed with the statement that they were confident in the given advice . However, 23.0% (n = 35) perceived the advice to be too strict and indicated that they felt starved. There were no significant differences in agreement with the feasibility of the advice between women who received group education and those who received individual education . Mean total score for the two items on perceived hyper- or hypoglycemia was 3.1 (± 2.1) and this was not significantly different between both education groups .Mean total score of the DTSQs was 27.3 (± 0.5) and this was not significantly different for women in group or individual education , 25.0% (n = 37) had a total score ≥ 16 at the CES-D questionnaire prior to the initial education session and were therefore considered at risk for clinical depression. This percentage declined to 18.9% (n = 28) after the follow-up session (p = 0.137). The median total score on the STAI-6 questionnaire decreased significantly from 12 (10–14) at the start of the initial education session to 11 (8–13) at the end of the follow-up session (p < 0.0001).Of all responders (p = 0.967) or median anxiety scores  were observed between both education groups after the initial education session.No significant differences in clinical depression rates (25.6% versus 24.2%, In general, most women indicated that the explanation was sufficient and felt that all of their questions had been addressed during the education sessions. However, topics such as postpartum follow-up and future risks should have been addressed in more detail according to a few women. Another recurring comment was the demand for specific recipes and nutritional instructions. Women often indicated that they were well aware of what they should not eat, but struggled with deciding what they were allowed to eat instead.Due to the worldwide obesity epidemic and the adoption of the 2013 WHO diagnostic criteria, the prevalence of GDM will continue to increase. This contributes to a number of practical challenges in the management of GDM, such as an increased workload for health care providers and a growing demand for additional resources ,28. In oImproved knowledge about GDM in newly diagnosed women might result in better adoption of a healthy lifestyle, better treatment adherence and better self-management. A Malaysian study among 175 women with GDM demonstrated that better knowledge about GDM is related to better glycemic control . Our stuPatient satisfaction is an important consideration in the organization of medical care, since improved satisfaction rates appear to be associated with a more effective engagement in health care programs . In thisThe results of the DTSQs revealed that the participants were generally very satisfied with their treatment, whether they received group or individual education. A Malaysian study in women with GDM showed that higher treatment satisfaction is associated with better glycemic control . Other sMore than 90% of all group participants were satisfied with the group size and almost 80% indicated that group education met their expectations. Only a small minority reported that they felt inhibited by the group and preferred individual education. This is in contrast to the findings of a study from New Zealand, establishing that only a minority of the people surveyed would consider participating in a group session, fearing that less attention would be paid to the individual needs of each patient . In our Depression is a common condition in women with GDM, with studies reporting depression rates between 15% and 20% in this population ,37. In oWe present the first prospective study on the impact of group education on patient’s knowledge about GDM, their satisfaction with the education and treatment, and emotional status. Our study demonstrates that group education is at least as good an alternative to individual education with regard to these outcomes. Moreover, our results did not differ when non-Dutch speaking women were excluded from the analyzes.Our study has several strengths. We provide prospective data of a large cohort of women with GDM, allowing the evaluation of the impact of group education compared to individual education. In addition, we used several validated questionnaires to evaluate treatment satisfaction and emotional status of women with GDM. When validated questionnaires were not available, we used self-designed questionnaires based on our experience and previous research in women with GDM. We included French and English speaking women in our cohort, ensuring that our results are representative of a multi-ethnic population. However, we could not evaluate group education for non-Dutch-speaking, since group education was only offered to Dutch-speaking women in line with routine care in our hospital. A limitation of our study is the observational design. Women following individual education were more often from an EM background than women in group education, but we corrected for this difference through multiple regression analysis. In addition, some participation bias is likely since not all eligible patients participated in the study and we have no data available on their characteristics. The results of this study show that women with newly diagnosed GDM are overall satisfied with their education and treatment, and have a better understanding of their condition after education, independent of the education setting. We show that group education is a valuable alternative to better organize education in view of the increasing GDM prevalence and is perceived as an added value by GDM patients.


N = 94) were asked to evaluate five environments in terms of spatio-cognitive and emotional dimensions while listening to music. Two types of music were selected: music with a fast tempo and music with a slow tempo. In contrast with a previous study by Pleasant and Mystery. The environmental features of the evaluated locations had a stronger effect than music on the evaluation of the environments. Environments with natural elements were perceived as more pleasant, interesting, coherent, and mysterious than urban built environments regardless of the music. It is suggested that the intensity of music may be an important factor in addition to the research methodology, individual variables, and cultural differences.Music may modify the impression of a visual environment. Most studies have explored the effect of music on the perception of various service settings, but the effect of music on the perception of outdoor environments has not yet been adequately explored. Music may make an environment more pleasant and enhance the relaxation effect of outdoor recreational activities. This study investigated the effect of music on the evaluation of urban built and urban natural environments. The participants ( There is a large body of studies on auditory and visual interactions. Most studies have explored the effect of music on the perception of service settings  Legibility is the extent to which elements allow an observer to understand the environment and its content. The greater the legibility, the greater the preference. (3) Complexity involves the number or diversity of elements that the environment contains. The greater the complexity, the greater the preference. (4) Mystery is the degree to which the environment contains hidden information. The greater the mystery, the higher the preference. Previous research on the effects of music on the evaluation of visual environments was mostly directed by The objective of the current study was to replicate the investigation by Another important variable that may influence the perception of the environment is the tempo of music. Because music at a fast tempo also increases ratings of subjective arousal e.g., , in the Finally, the environmental features of a visual scene are important factors that influence subjective evaluation in terms of the emotional and spatio-cognitive dimensions. As previously discussed, the natural environment is preferred over the urban environment, and the urban environment with natural elements is preferred over the urban built environment without natural elements e.g., .In summary, the objective of the current study was to explore the effect of fast  and slow  music on the evaluation of diverse types of outdoor urban environments. Participants evaluated both urban built and urban natural environments while listening to music. The effects of music in terms of the emotional and spatio-cognitive dimensions of the perceived environment were investigated. Based on the results of Ninety-four undergraduates participated in the experiment. The sample comprised young adults between the ages of 19 and 23 . Participants were enrolled in the first, second or third year of various psychology courses. They were students in informatics, financial management and tourism at the University of Hradec Králové.The musical stimuli used in our previous study  were adoVirtualDJ software, a long seamless loop was used in both songs to create soundtracks with a duration of approximately 30 min.For the purposes of the present study, we chose two songs from this selection, specifically the song “One Fine Day”  with a tempo of 187 beats per minute (bpm), which was used as the motivational music (the score of the Brunel Music Rating Inventory-2 was 28.8), and the song “Madworld”  with a tempo of 91 bpm, which was used as the non-motivational music (the score of the Brunel Music Rating Inventory-2 was 7.6). By using The sound levels of the musical tracks were adjusted to be audible as a musical background only. The sound levels of specific musical tracks were adjusted according to the assessment of the team of experimental assistants to have a low level of intensity and were constant during the experiment. The sounds were listened to through lightweight headphones (Genius HS-M200C) connected to a Nokia Lumia 520 phone, on which the musical tracks were recorded.Coherence, item 2 was related to the spatio-cognitive dimension Legibility, item 3 was related to the spatio-cognitive dimension Complexity, item 4 was related to the spatio-cognitive dimension Mystery, and item 5 was related to the spatio-cognitive dimension Openness. These items were selected from the study by Energy, item 7 was related to the emotional dimension Abandoned, item 8 was related to the emotional dimension Pleasant, and item 9 was related to the emotional dimension Interesting. Items 6–9 were selected from the more extensive questionnaire used in the study by A questionnaire that contained eleven items was used in the experiment . Item 1 The experiment was conducted in the city of Hradec Králové in the Czech Republic. The city is located in the northeastern part of the Czech Republic and has approximately 100,000 residents. Six outdoor locations were selected . We chosThe initial location was situated in front of the university building. The site was used only for training participants in the evaluation of the environment and using the electronic questionnaire. The obtained data were not further processed. The first environment, where the data were processed, was chosen as an example of an ugly and unorganized urban environment. The second environment was represented by an urban environment with traffic. The third environment was a coherent natural environment with water. The fourth environment represented a coherent natural environment with a high level of spatial openness. The fifth environment was a coherent natural environment with a lower level of spatial openness. All environments were familiar to the participants because they were located close to the university buildings.Before the experiment, the participants signed informed consent and then were instructed. They were informed that their task was to take a route near the university along the Orlice River within a smaller group of people and to evaluate 6 selected sites by means of a questionnaire. They were also informed that they would either listen to music through headphones during the experiment or would take part in the experiment without listening to any music.A between-subjects design was used. Thirty-three participants were randomly assigned to the motivational music condition, twenty-eight participants were assigned to the non-motivational music condition, and thirty-three participants were assigned to the control condition. Because not all preliminarily registered participants came to the experiment , the sample sizes of both music conditions differed.The participants were asked to find the questionnaire on their smartphones (by using a QR code). The participants in the music conditions also received Nokia phones with recorded music and headphones. The research assistant turned on the music at the initial location. The participants listened to music without any interruption during the entire walk along the route and at the locations where they were asked to evaluate the environment. The participants moved along the route in groups of 2–6 people and were accompanied by a research assistant. The research assistant stopped the participants at the specific location, showed them the area to observe and asked them to make their records in the questionnaire on their smartphones. The walking distance between specific locations was approximately 2–3 min. To eliminate a possible order effect, the participants moved along the route from environment 1 to environment 5 or from environment 5 to environment 1. The study was conducted in 2019 on three weekdays: November 12, November 13, and November 14. It was cloudy, and the temperature was approximately 8 °C.Ethical approval for the experiments was obtained from the Committee for ResearchEthics at the University of Hradec Králové (No. 8/2019). All participants signed a consent declaration in which they declared that they voluntarily participated in the experiment and that they were informed about the experimental procedure. They could decide to stop participating in the research study at any time without explanation. There were no known risks to the participants in this study.Statistica 12  was used to perform statistical analyses. First, the mean scores and standard deviations for all spatio-cognitive and emotional dimensions were calculated separately for the five evaluated environments .Given that the ANOVAs did not identify any significant effect of music on the evaluation of the environment, we examined whether the evaluation of an environment was mediated by the listener’s level of liking of the music. The levels of liking of motivational music  and non-motivational music  were almost equal , and the difference was not significant  and music liking , while the effect of the musical condition was not significant . For the dependent variable Pleasant, the ANOVA revealed a significant effect of the environment  and music liking , while the effect of the musical condition was not significant .For both music conditions , we conducted a two-way mixed ANOVA in which the music condition and liking of music were predictors, the evaluated environment was the within-subjects repeated factor, and the mean scores of particular evaluated dimensions were the dependent variables. We found a significant effect of music liking for the dimension Interesting revealed a tendency for music liking to influence the evaluation of the environment, although p lies slightly above the conventionally considered threshold for statistical significance (p = 0.087). For the dependent variable, an ANOVA revealed a significant effect of the environment  and a nonsignificant effect of music liking , while the effect of the condition was not significant .The ANOVAs conducted for the further spatio-cognitive emotional dimensions did not show a significant effect of music liking.It is also worth noting that an ANOVA conducted for the dimension Mystery and Pleasantness. If people liked the music more, they evaluated the environments as more mysterious and more pleasant. There were no differences between the effects of both types of musicIt is worth remembering that musical stimuli used in this study were chosen to be liked by participants from our previous study . Clearlyt = 1.188, p = 0.26). For both music conditions , we conducted a two-way mixed ANOVA where music condition and disturbance by music were predictors, the evaluated environment was the within-subjects repeated factor, and the mean scores of particular evaluated dimensions were the dependent variables. We found a significant effect of disturbance by music on Coherence. The ANOVA revealed a significant effect of the environment  and a significant effect of disturbance by music , while the effect of the condition was not significant . Furthermore, we found an almost significant effect (p = 0.059) of disturbance by music for Mystery. The ANOVA revealed a significant effect of the environment  and a nonsignificant effect of disturbance by music , while the effect of the condition was not significant . The ANOVAs conducted for the further spatio-cognitive and emotional dimensions did not show significant effects of disturbance by music.Finally, we analyzed responses to the item “The music disturbed me when evaluating the environment”. The scores  for motivational music  and non-motivational music  differed, but not significantly  or in various types of natural environments . Finally, in the discussion of our findings, we stressed the intensity of music as an important factor, but in this experiment, we did not manipulate this variable.The present study investigated the effects of audio-visual interactions on the perception of outdoor urban environments. In contrast with previous investigations , we did 10.7717/peerj.9770/supp-1Supplemental Information 1Click here for additional data file.


The mood and atmosphere of a service setting are essential factors in the way customers evaluate their shopping experience in a retail store environment. Scholars have shown that background music has a strong effect on consumer behavior. Retailers design novel environments in which appropriate music can elevate the shopping experience. While previous findings highlight the effects of background music on consumer behavior, the extent to which recognition of store atmosphere varies with genre of background music in sales spaces is unknown. We conducted an eye tracking experiment to evaluate the effect of background music on the perceived atmosphere of a service setting. We used a 2 (music genre: jazz song with slow tempo vs. dance song with fast tempo) × 1  within-subject design to test the effect of music genre on visual perception of a physical environment. Results show that the fixation values during the slow tempo music were at least two times higher than the fixation values during the fast tempo music and that the blink values during the fast tempo music were at least two times higher than the blink values during the slow tempo music. Notably, initial and maximum concentration differed by music type. Our findings also indicate that differences in scan paths and locations between the slow tempo music and the fast tempo music changed over time. However, average fixation values were not significantly different between the two music types. Music can have diverse effects on consumer behaviors, including emotion , purchasIn some cases, atmosphere can have a greater effect on a purchase decision than the product itself. Experimental studies about emotional response to store spaces emerged several decades ago. Using eye tracking to study visual attention, Scholars have shown that background music has a strong effect on consumer behavior . While pAn important goal for retail managers and marketers is to provide memorable and unique experiences for customers. Multisensory cues can help stores stand out from competitors and attract customers by delivering a pleasant shopping experience . Thus, rWhile vision is generally assumed to be the dominant sensory mode in retrieving external information , recent Numerous findings support the notion that auditory input during product interaction can strongly influence the perception and evaluation of products . CompareScholars have recognized the effects of using background music to influence consumer behavior in various settings and situations . FindingScholars have considered the influence of background music on consumers, including the presence or absence of music , liked oHowever, research on the effects of background music type  on consumer behavior is relatively sparse. Addressing other aspects of background music, scholars have found that quiet (vs. loud) airline cabin noise increased the intensity of sweet solutions and decreased the intensity of umami-flavored solutions . With revia eye fixations on a perceptual field. Outside that perceptual field, however, detailed information is likely to be missed. Moreover, people are normally unaware of the specific eye movements they make when performing a task. Eye movement is closely associated with covert attention. Covert attention plays a key role in information processing and decision making, not only by acting as a selection device but also by executing and maintaining central processing activity to ensure that decisions occur fast and accurately. Consequently, eye movements not only reflect selective attention but also the intensity and nature of the central cognitive processes in information perception, evaluation, and memory, providing real-time information about these ongoing processes that cannot be obtained otherwise. Thus, measuring where the eye is focused or how the eye is moving can help us understand how individuals view objects.People frequently do not choose between alternative courses of behavior; rather, they depend on cognitive abilities that are fairly well developed . Eye movement is one of the quickest and most frequent human actions, allowing people to gather numerous bits of information Data collection using eye tracking experiments does not depend on participant reports or memory. When questioned about their actions, participants might not remember their behavior. They might be unaware of what they did due to forgetting or lack of awareness. By examining data, visualizations, and replays, we can determine causes of behavior without relying on fallible human memory. Eye tracking analysis can lead to discoveries that would be considerably more difficult to uncover using other methods. Eye tracking shows how quickly and for how long customers notice features, key content, and brands and can reveal, through the accumulation of minute changes, where participants spent the most time looking.Scholars have shown that the human visual system is essential to information searching and decision making . BecauseTo test the hypotheses, we conducted a two-condition, randomized, within-subject experiment. The independent variable was music genre , and we measured visual attention using eye tracking technology.N = 109: jazz = 37; dance = 29; ballade = 23; old pop = 14; no music = 3; electronic = 2; new age = 1; and rock, world music, classic, and hip hop = 0). We used each genre with beat per minute (BPM) to create background music for the experiment (Music 1: jazz song with 88 BMP vs. Music 2: dance song with 137 BMP).We conducted a field survey to select the music genres for auditory stimuli. We visited eighty cafés in Seoul, South Korea, and classified the kinds of music they played using 10 genres . We chose jazz (Music 1) and dance (Music 2) for our auditory stimuli because these two genres had the highest frequency scores , we collected quantitative data about eye movement and fixation using eye tracking equipment. First, for visual stimuli, we selected a cafe space that participants would recognize as a setting where they might make a purchase. We used a camera  to photograph this space and create images for the experiment. We configured the indoor space  so that the person placing an order at the counter and the person seated at a table to the side were at adult eye level. As a result, the image was a close approximation of a human field of view (FOV). We also used Adobe Photoshop CS6 to enhance image quality.We recruited 40 undergraduate students  enrolled at a private university in Seoul, Korea, in exchange for extra credit. We invited participants to the lab after confirming that they did not have any vision impairment that might limit their ability to see a computer screen . We prohibited mascara and color lenses during the experiment to maximize the quality of our eye tracking data. Upon arrival to the lab, participants signed informed consent forms approved by the Institutional Review Board (IRB) and then sat down at computer stations.The distance between the monitor and each participant was roughly 650–700 mm to ensure accurate and consistent eye tracking calibration. Before the experiment, we ran a quick calibration program to prepare the eye tracking camera. On their computer screens, participants watched a white dot move to four different areas. We performed the calibration test up to two times and excluded participants who did not pass. Participants who did pass then read the following instructions on the screen: “Imagine you are visiting a coffee shop. Please look around the café and think how the atmosphere of the space and the music feels.” Because we used a within-subject study design, each participant looked at the image while listening to Music 1 and Music 2; however, the order in which they heard the two auditory stimuli was random. The first multi-sensory stimulation lasted 1 min. After a 1-min rest time, the second multi-sensory stimulation began. The experimental session lasted a total of 3 min and took place in a dark room so that the participants could focus on their task with maximum concentration.We measured the real-time eye movement of the participants. We used eye tracking equipment  to determine the impact of auditory stimuli on visual perception of the physical environment pictured in the image. We extracted raw fixation data using BeGaze 3.7 (SMI). We set the rate of recording and storage to 30 Hz .N = 40), we excluded six participants  who failed to exceed the criterion of 80% eye tracker accuracy and one participant (1) due to technical problems with raw data. Therefore, we analyzed the data from 33 participants. The mean effective rate was 90.9% (SD = ±4.13)  see . In the x-y coordinates.Using the eye tracking data, we extracted values for fixations, saccades, and blinks, the primary components of human eye movement. Fixations occur when the eyes stop scanning and hold in one place for a time while saccades are the rapid eye movements that occur between fixations, allowing the fovea to shift from one point of interest to another. When plotted in chronological order, fixations and saccades constitute a scan path. Fixation count refers to the number of fixations that occurred in an area of interest every 0.03 ms, indicating how long an individual spent looking at a particular part of the image on the screen . Frequency refers to how many times per second the eye tracker registered the position of the eyes . Blinking refers to the involuntary act of shutting and opening the eyelids. During each blink, the eyelid blocks the pupil and cornea from the illuminator, resulting in missing raw data points at particular Fixation and saccade frequencies did not differ significantly between Music 1 and Music 2. Fixation frequency for Music 1 (12.29) and Music 2 (12.22) was close. However, blink frequency for Music 2 (12.29) was twice the frequency for Music 1 (6.28). The fixation and saccade frequency and mean values were not significantly different between Music 1 and Music 2, but the blink frequency and mean values for Music 2 were two times those of Music 1 see . In addit-tests for fixation  and frequency  indicated no significant difference between Music 1 and Music 2. However, analysis of variance (s2) for fixation revealed that the standard deviation for Music 1  was more than two times Music 2 (s2 = 6294.78). Therefore, although the mean values were similar, fixation values differed across participants by music type (see Paired sample type see . Moreoven = 18) who showed more fixation during Music 1 was higher than the number of participants (n = 15) who showed more fixation during Music 2. In terms of fixation count, the number of participants (n = 17) with a higher index during Music 2 was higher than the number of participants (n = 14) with a higher index during Music 1. Two participants had the same fixation count during Music 1 and Music 2. The number of participants (n = 14) with higher average frequency for Music 1 was the same as the number of participants (n = 14) with higher average frequency for Music 2  and average maximum concentration  revealed no significant difference between Music 1 and Music 2.We defined the time at which the top 5% index value for high fixation started as initial concentration and the time at which the index value for high fixation peaked as maximum concentration. Results of paired σ2) and sample variance (s2) values among the participants, initial concentration during Music 1 was 1.5 times faster than during Music 2. Maximum concentration began at 36 s during Music 1 and 37 s during Music 2, and differences among the participants were not significant between Music 1 and Music 2. Although differences in average initial concentration were not large, differences in variance indicate different initial concentrations among the participants.On average, initial concentration began at 12 s during Music 1 and 15 s during Music 2. Based on population variance (n = 22) with earlier initial concentration during Music 2 was twice the number of participants (n = 11) during Music 1. The average initial concentration was between 10 and 15 s depending on music type, and the difference in average initial concentration between Music 1 and Music 2 was at least 5 s. Maximum concentration also differed between Music 1 and Music 2. The number of participants (n = 19) with an earlier maximum concentration during Music 1 was higher than the number of participants (n = 14) during Music 2. Maximum concentration differed among the participants (see The number of participants (ants see .n = 8) with initial concentration during Music 2 was higher than the number of participants (n = 7) during Music 1. In the second interval, the number of participants during Music 1 (n = 13) was more than three times the number of participants (n = 4) during Music 2. After 20 s, the number of participants who began concentrating during Music 2 was higher. We then analyzed maximum concentration frequency at 5-s intervals. We found no difference in the number of participants in the first two intervals. However, at 20 s, the number of participants (n = 4) during Music 1 was higher than the number of participants (n = 2) during Music 2. The difference between Music 1 (n = 7) and Music 2 (n = 1) was larger at 45 s , middle period (T2: 20 ~ 40 s), and late period (T3: 40 ~ 60 s) – and compared degrees of interest between Music 1 and Music 2. Analysis of grids during Music 1 revealed that exploration of the entire image was not intensive in T1 and that the primary area of interest was e-g’ . The distribution of eye movement was primarily in the left half of the image. In T2, areas of exploration were more spread out to the left and right of the primary area of interest in T1. In T3, the area of interest shifted from e-g’ to g-e’ . Between 10  and 45 s , the area of interest shifted from human objects to purchasable objects.Analysis of grids during Music 2 revealed that initial concentration began in T1 and that frequency decreased thereafter see . As we fTraditionally, store managers have focused on interior store aesthetics for visual stimuli. To a lesser extent, they have started to pay attention to auditory stimuli. Previous findings have shown how cross-modal sensory stimuli can affect consumer behavior . RecentlIn the current study, we analyzed differences in visual exploration and fixation by music type. First, the average fixation values did not differ significantly between Music 1 and Music 2. One possible explanation is that because visual cues trigger our dominant sense, auditory cues might not exert a strong influence on eye movement. However, according to analysis of variance, the fixation values for participants during Music 1 were at least two times higher than during Music 2, and the blink values during Music 2 were at least two times higher than during Music 1. Comparing frequencies of eye movement between the raw data and the count values, we found that the areas across which eyes moved were larger during Music 2 , but that fixation frequency was higher during Music 1 . This analysis is meaningful because objects in scenes are generally coded for visual attention because they provide external information . ThroughSecond, initial and maximum concentration differed by music type. Regardless of music type, maximum concentration began after at least 40 s on average. Initial concentration was earlier during Music 1, and variance among participants was larger during Music 2. These findings suggest differences in the way the participants responded to music. The average maximum concentration was 36 s during Music 1 and 37 s during Music 2, and the earliest maximum concentration was 35 s. When we divided the time into 5-s intervals and examined frequency of initial concentration across the participants, we found that initial concentration began in the early period for both types of music. However, during Music 1, frequency of initial concentration was high at 10 s (39%) in T1. During Music 1, the highest frequency of maximum concentration was 45 s (21%), but a high frequency also emerged at 20 s (12%) in T1.Third, our findings indicate that differences in scan paths and locations between Music 1 and Music 2 changed over time. When we divided the viewing time into T1, T2, and T3, we found that eyes moved to the menu or products on the wall in T1. In T2, scan paths differed between music types. During Music 1, scan paths dispersed across the entire image so that eyes landed on both humans and products. During Music 2, scan paths dispersed across the entire image in T3, later than during Music 1. Synchronized stimuli, resulting in cross-modal effects , present different routes for perceiving objects in the scene. Auditory cues, enabling cross-modal sensation, further explain how individuals view objects. The results show how auditory cues might interact with visual cues. As sensory marketing research shifts attention from single sensory systems to cross-modal sensory systems, scholars need better insight into the way various sensory systems might interact with each other.In the current study, we analyzed differences in eye movement and fixation during multi-sensory stimulation . Although differences in average eye-movement values between music types were not large, the results are meaningful because we were able to extract the characteristics of visual perception and degree of interest in spaces using eye tracking. Our findings should guide practitioners of neuro-marketing to consider multi-sensory stimulation when designing spaces where consumers are likely to purchase products.The limitations of the current study open pathways to future research. First, we exclusively recruited college students. Scholars should consider using wider, more random sampling in order to increase generalizability. Second, we focused on two different genres of music: jazz music with slow tempo and dance music with fast tempo. Given the variety of existing genres, scholars should consider examining the potential impact of other types of background music. Third, we conducted this study conducted in a laboratory setting rather than investigating consumers in their normal shopping environments. For visual stimuli, we selected a cafe space that participants would recognize as a setting where they might make a purchase. Then we created images for the experiment. Participants in a real-setting experiment might have responded to the questionnaire differently. Follow-up field research could more fully reveal the effect of background music on the perceived atmosphere of a service setting. Finally, scholars should qualitatively examine how consumers move their eyes across a visual field and where they place their attention in the field of view.Sensory information  is typically stored in and retrievable from a sensory memory location. Sensory memory intensifies with the repetition of sensory information, serving as a buffer for external sensory stimuli. The perception of sensory attributes occurs when the process satisfies the condition. Attention then increases with the activation of a particular sensory modality . Nearly 70% of the sensory receptors in humans are allocated to vision, making it the most important element in the human sensory system. Thus, understanding how humans process visual sensory information and how it interacts with other sensory information is important. To investigate the effect of background music on visual perception of a physical environment, we conducted an eye tracking experiment in a service setting.Although we did not find any significant differences between the slow tempo and fast tempo conditions with regard to visual perception and interaction, the individual differences between groups by music type are meaningful. Results show that the blink values during the fast tempo music were at least two times higher than the blink values during the slow tempo music. Moreover, eye movement was more active when the background music tempo was relatively fast, indicating that external auditory information might have activated the visual cortex. We also investigated how differences in scan paths and locations between the slow tempo music and the fast tempo music changed over time. Our findings provide an empirical basis for examining changes in the way consumers respond to multi-sensory stimuli.Applying The datasets generated for this study are available on request to the corresponding author.The studies involving human participants were reviewed and approved by IRB Office, Soongsil University. The patients/participants provided their written informed consent to participate in this study.JK and JYK contributed to the conception and design of the study. JK organized the database and analyzed and interpreted the data under the supervision of JYK. All authors contributed to the writing and editing of the manuscript.The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.


Cholera epidemics continue to challenge disease control, particularly in fragile and conflict-affected states. Rapid detection and response to small cholera clusters is key for efficient control before an epidemic propagates. To understand the capacity for early response in fragile states, we investigated delays in outbreak detection, investigation, response, and laboratory confirmation, and we estimated epidemic sizes. We assessed predictors of delays, and annual changes in response time.We compiled a list of cholera outbreaks in fragile and conflict-affected states from 2008 to 2019. We searched for peer-reviewed articles and epidemiological reports. We evaluated delays from the dates of symptom onset of the primary case, and the earliest dates of outbreak detection, investigation, response, and confirmation. Information on how the outbreak was alerted was summarized. A branching process model was used to estimate epidemic size at each delay. Regression models were used to investigate the association between predictors and delays to response.p = 0.03). Outbreaks signaled by immediate alerts were associated with a reduction in delay to response of 39.3% .Seventy-six outbreaks from 34 countries were included. Median delays spanned 1–2 weeks: from symptom onset of the primary case to presentation at the health facility , detection , investigation , response , and confirmation . In the model simulation, the median delay to response (10 days) with 3 seed cases led to a median epidemic size of 12 cases  and 8% of outbreaks ≥ 20 cases (increasing to 32% with a 30-day delay to response). Increased outbreak size at detection (10 seed cases) and a 10-day median delay to response resulted in an epidemic size of 34 cases (upper range 67 cases) and < 1% of outbreaks < 20 cases. We estimated an annual global decrease in delay to response of 5.2% , in 8 to 99% of scenarios, a 10-day delay to response would result in large clusters that would be difficult to contain. Improving the delay to response involves rethinking the integration at local levels of event-based detection, rapid diagnostic testing for cluster validation, and integrated alert, investigation, and response. Cholera transmission was reported in 34 countries in 2018 and 55 countries in 2019 [In 2017, the Global Task Force on Cholera Control (GTFCC) recommended that countries increase their capacity to contain small outbreaks, using rapid response teams, to aid efforts to substantially reduce global transmission by 2030 . HoweverTo understand the potential for early detection and rapid response for cholera outbreaks in fragile and conflict-affected states, we examined temporal trends in cholera epidemics to evaluate with what delays the first case or cluster presented, was detected, investigated, responded to, and was confirmed by laboratory culture. We modeled epidemic sizes corresponding to these delays. To explain these delays, we investigated the mechanisms for early warning of these outbreaks, predictors of delays, and global improvements in reducing delays.The period of 2008 to 2019 was chosen to reflect recent experience with cholera response. A list of countries that appeared ≥ 2 times during this period on the World Bank’s Harmonized List of Fragile Situations, and had a documented cholera burden as per the GTFCC’s 2017 list of cholera-affected countries, was compiled  using a date-specific keyword search  and (2) regional outbreak bulletins and journals including the WHO EMRO Weekly Epidemiological Monitor (2008 to 2019), WHO AFRO Outbreaks and Emergencies Bulletin (2017–9), WHO SEARO Journal of Public Health, WHO WPRO Western Pacific Surveillance and Response Journal, and UNICEF Cholera Outbreaks in Central and West Africa Bulletin (2015 to 2019) [We searched the peer-reviewed literature for further identification and reporting on cholera outbreaks. Peer-reviewed articles were sourced from PubMed/MEDLINE using a date-specific keyword search (“country AND cholera”). Given that only a small number of outbreaks are reported in the scientific literature, we searched the gray literature, including epidemiological summaries, national cholera preparedness and response plans, and non-peer-reviewed studies. The sources included the following: (1) Reliefweb to 2019) , 20–23. 19 , 20–2to 2019) . When lito 2019) .formal alert detected by health workers reported immediately within the surveillance system, (2) informal alert from community members or a non-governmental organization (NGO) reported immediately, or (3) weekly data analysis of surveillance trends.Outbreaks were included if at least two of the following dates were available: 1) dates of symptom onset of the primary case, and/or case presentation, and/or outbreak detection, and (2) dates of investigation and/or response. If the date of symptom onset for the primary case was missing, it was estimated as 5 days before the date of case presentation , or date of outbreak detection if date of case presentation was unavailable. If the date of case presentation was unavailable, it was replaced by the date of outbreak detection. The earliest dates of (1) symptom onset for the first identified primary case, (2) case presentation to a health facility, (3) detection of outbreak/alert raised, (4) investigation by local health authorities, (5) response, and (6) laboratory confirmation by culture were extracted  were calculated by subtracting the date of symptom onset of the primary case from the dates of (1) case presentation, (2) outbreak detection, (3) investigation, (4) earliest response, and (5) laboratory confirmation. For each outbreak, the dates were graphed on a timeline.To investigate the association between the observed delay from symptom onset of the primary case to response and potential predictor variables, a multivariate ordinary least-squares regression model was used. Delay to response was log-transformed to produce a normalized distribution. Extreme values in delay to response were judged to represent meaningful delays rather than data errors and were retained in the dataset. Predictor variables included signal type, context, crisis, WHO region, and year of outbreak onset (to detect any secular trend). Akaike information criterion (AIC) and a step-wise selection process was used to assess model fit and complexity. In separate regressions, year of outbreak onset was used as a predictor variable to investigate secular trends for delays to case presentation, outbreak detection, investigation, and confirmation. Loess curves were used to visualize the temporal trends using a smoothed trend line that down-weighted extreme values . PercentZ ~ NegB with a mean equivalent to the reproduction number  [S ~ gamma with a median of 5 days [A preliminary review of retrieved reports demonstrated that the early epidemic sizes at the dates that the outbreak was detected and responded to were rarely documented. Instead, to estimate the potential early epidemic sizes at each delay, a branching process model was used to estimate the median and range of epidemic sizes at the time points indicated by the median delays to case presentation, investigation, response, and confirmation –29. We s . Each nef 5 days , 32. We All analyses were carried out in R statistical software version 4.0.3 .Seventy-six outbreaks from 34 countries met the inclusion criteria. Overall, 1970 documents were reviewed, and 138 documents were retained . Table p = 0.03), was found  , and a bivariate model for signal type only . Using AIC for the multivariable model, including only year of outbreak onset returned the lowest AIC score  were through alerts by a health worker or community health worker and 9/46 (19.6%) through informal alerts by community members. For example, in 2015, in Aleppo, Syria, an alert was issued through the EWARN via phone after RDT testing of a suspect, and an investigation initiated based on the positive result . In 2017, in a displacement camp in Northern Nigeria, an alert of a suspect case was issued by MSF by phone through the EWARS on the same day of case presentation , demonstrating the rapid recognition of a suspect case by health workers . CompariIn several instances, early warning systems further benefited from rapid investigation and response. For example, in Afghanistan, in 2010, the DEWS provided a response mechanism to link the detection of a large cluster of 60 suspect cases in a remote and insecure village by a local NGO with rapid action which reportedly led to containment within a month . In 2011, the DEWS in Afghanistan detected an already-large outbreak of 255 suspect cases in multiple clusters but with a rapidly administered response . Reduced transmission within 3 months followed. In Liberia in 2017, a suspect case that died en route to the health facility was detected based on symptoms, triggering a rapid response to isolate additional cases in the index case’s village . In Chad in 2017, two suspect cases among children which resulted in rapid progression to death were reported to the local health facility, who investigated the source village and found a larger cluster of 50 cases and 13 deaths . Though already a large outbreak, this led to a response on the following day.Information in reports suggested improvements in surveillance, investigation, and response over time. In Cameroon in 2016, two false alerts for cholera later attributed to food poisoning and rotavirus were made by health workers and community members respectively and led to rapid investigation upon detection, testing by RDT and culture, and ongoing control activities during the investigation period . In Somalia, faster response in insecure urban areas using EWARS in 2016 and 2018 can be compared to a lack of a comprehensive early response during ongoing transmission over 2 months in 2008 . Nepal’s EWARS facilitated rapid detection and response to clusters from 2011 onwards  , 162. InLong delays from symptom onset of the primary case to response (~ 2 weeks) were observed in 29/67 (43.2%) outbreaks for which a response date was available. These appeared to be related to poor sensitivity of the formal surveillance system due to the remote locations of outbreaks  , Ethiopia (2015 onwards), and Zambia (2017–8) have suffered from late detection and/or response, which has led to surges of cases that have overwhelmed health systems , 174–176Our findings indicate that from 2008 to 2019, median delays from symptom onset of the primary case to case presentation at the health facility and to response were approximately 5 days and 10 days, respectively. Longer delays to response were documented across the whole time period. Evaluations from Nigeria, Yemen, and other settings have shown that reasons for delays to detection include poor population access to health services due to disrupted health systems and/or insecurity, difficulty in discerning diarrhea and dehydration due to cholera from other causes without rapid diagnostics, reliance on laboratory confirmation before initiating response, and less effective local response , 178. EpEnding Cholera roadmap. There are two reasons to believe that policy and practice have somewhat narrowed the gap between detection and response. First, we found a global improvement in time to response that corroborates a previous analysis of improvements for detection of all-pathogen outbreaks in low- and middle-income countries from 1996 to 2014 [Early detection and response are major aims of the  to 2014 . This ma to 2014 . Some co to 2014 –181.Detailed case studies of cholera outbreaks provide practical observations on the mechanisms of surveillance, diagnosis, and response which can reduce delays. Early detection with high-quality epidemiological data has been augmented with the use of sentinel site surveillance at hospitals equipped with RDTs and trained and vigilant health workers in Kathmandu, Nepal ; communiVibrio cholerae that causes a range of disease severity, transmission chains may be missed. Fifty-one (67%) of the 76 outbreaks were missing the date of onset of symptoms for the primary case, which then had to be estimated, limiting accuracy. The dates of response were based on the judgment of the timing of the first transmission-reducing intervention and thus may represent variable intensity of response across outbreaks. Of note, the longest delays to response noted during outbreaks in Chad, Ethiopia, Somalia, and Uganda were related to the first viable response after an inadequate local response. To address these inconsistences, we sourced multiple reports per outbreak to triangulate the information and obtain a clear timeline, and excluded a large number of outbreaks where reports lacked detailed dates. Second, we note that while outbreaks are likely to occur during conflict, they are difficult to detect amidst violence where surveillance coverage is poor [Rt value.It is important to consider the limitations inherent to a retrospective review of data from secondary sources. First, as no global registry of cholera outbreaks exists, we relied on the manual compilation of available situation reports and articles. The most comprehensive source, the WHO’s current compilation of annual cholera data, does not provide detailed information on outbreaks and misses non-reporting countries. The small annual numbers of outbreaks pre-2015 documented here may reflect the few global data sources available. As well, larger outbreaks are more likely to be detected, responded to, and therefore documented and included here. Second, the delays are estimates of reality; dates from situation reports are likely inaccurate to an unquantifiable degree as the exact dates of local investigation and response may be subjective and are documented infrequently. The identification of the primary case(s) depends on the depth of the field investigation, and with a multi-pathway pathogen like  is poor . These o is poor , 131. ThThe documentation of the occurrence and features of cholera outbreaks is currently very heterogeneous. A real-time global database using standard outbreak event reports maintained by WHO regional offices to prospectively log data and metrics from outbreaks of cholera, as well as other epidemic-prone diseases, would yield superior accuracy for the annual evaluation of timeliness. WHO AFRO’s Weekly Bulletin on Outbreaks and Emergencies provides an existing template which can feed into such a global database . WHO AFRCholera epidemics will continue to appear unpredictably and cause serious morbidity and mortality in countries affected by armed conflict and fragility. Cholera surveillance and response is dependent on rethinking the timely detection, investigation, and response to primary cases at the local level. This includes reinforcing outbreak detection through event-based surveillance, consistent weekly reporting using standard case definitions, systematic use of enriched RDTs, and integrating early investigation with preliminary local response. These measures should increasingly underpin the detection and containment of emerging epidemics.Additional file 1. Countries investigated.Additional file 2. Compilation of outbreaks by country, date of onset, delays , signal, source, and description of investigation and response.Additional file 3. Histograms of delays from symptom onset to (A) case presentation, (B) outbreak detection, (C) investigation, (D) response, and (E) confirmation.Additional file 4. Overview of alternative models for the main analyses.Additional file 5. Model parameters for additional delay analyses.


The viscoelastic behavior and reinforcement mechanism of polyethylene glycol (PEG) as an interfacial modifier in green tire tread composites were investigated in this study. The results show a clear positive effect on overall performance, and it significantly improved all the parameters of the “magic triangle” properties, the abrasion resistance, wet grip and ice traction, as well as the tire rolling resistance, simultaneously. For the preparation of the compounds, two mixing steps were used, as PEG 4000 was added on the second stage in order to avoid the competing reaction between silica/PEG and silanization. Fourier transform infrared spectroscopy (FTIR) confirmed that PEG could cover the silanol groups on the silica surface, resulting in the shortening of cure times and facilitating an increase of productivity. At low content of PEG, the strength was enhanced by the improvement of silica dispersion and the slippage of PEG chains, which are chemically and physically adsorbed on silica surface, but the use of excess PEG uncombined with silica in the compound, i.e., 5 phr, increases the possibility to shield the disulfide bonds of bis(3-(triethoxysilyl)-propyl) tetrasulfide (TESPT), and, thus, the properties were deteriorated. A constrained polymer model was proposed to explain the constrained chains of PEG in the silica-loaded composites on the basis of these results. An optimum PEG content is necessary for moderately strong matrix–filler interaction and, hence, for the enhancement in the mechanical properties. Today, silica-based green tire treads have a great importance, as they are superior to carbon black-loaded tire treads regarding the “magic triangle” properties: rolling resistance, wet skid performance and abrasion resistance ,2,3. TheThe surface of precipitated silica is covered with a polar and hydrophilic layer of acidic silanol groups. The dispersion of silica in nonpolar rubbers such as styrene–butadiene copolymers (SBR), polybutadiene (BR), etc., is significantly more difficult to achieve than for carbon black . As a coIn our previous research, the immersion of silica-loaded vulcanizates in deionized water results in the permeation of water into the vulcanizates. The absorbed water has a huge effect on the dynamic mechanical properties of silica-loaded green tire tread vulcanizates. A new tan δ peak around −5–0 °C was formed after swelling in water, and the height of this peak increased with the amount of absorbed water. The interaction between silanol groups and water molecules occurs by hydrogen bonds , resultiTherefore, the present study emphasizes the use of a kind of interfacial modifier instead of water molecules, which can physically adsorb or/and chemisorb on the silica surface and will not show the reversibility in the vulcanizates. The selected interfacial modifier should have a phase transition temperature, which is a main factor to influence the dynamic mechanical performance and other physical properties in polymer science, closed to the phase transition temperature of water (or to the best in the range of −30 °C to 0 °C), because the higher tan δ at −20 °C and 0 °C are indicators for the better performances of ice traction and wet grip. The interfacial modifiers, such as polyethylene glycol, cetyltrimethylammonium bromide, polyoxyethylene sorbitan, ionic liquids and different amines are commonly used in silica modification ,24,25,26® VN3) with a specific surface area (CTAB) of 160 m2/g from Evonik Degussa (China) Co., Ltd. . The silane coupling agent, bis(3-(triethoxysilyl)-propyl)disulfide (TESPD), was obtained from Evonik Degussa (China) Co., Ltd. . The antioxidant Vulkanox® 4020NA and the ozone wax Antilux® 500 were supplied by Lanxess (China) Co., Ltd.  and Rhein Chemie (Qingdao) Co., Ltd. . Two kinds of PEG (molecular weight: 400 and 4000 g/mol) were obtained from Xiya Reagent (Shandong) Co. Ltd. . All of the ingredients were industrial grades and used as received.A solution-polymerized styrene butadiene rubber (S-SBR) grade RC2557-S and a solution high-cis polybutadiene polymer (BR) grade BR9000, both from Sinopec Beijing Yanshan Petrochemical Co., Ltd. , were used for the preparation of the compounds. The S-SBR has a vinyl content of 53 wt.% and a styrene content of 23 wt.% and is extended with aromatic oil (24.3 wt.%). The filler used was precipitated silica (UltrasilThe reaction model was established in the solution state. We added 1 g silica and 125 mL deionized water to each flask. The TESPD solution with a known concentration (80 ppm) was obtained by diluting appropriate standard stock solutions with methanol. We pipetted 1 mL of the standard solution containing 0.08 mg TESPD into each flask. All silica slurries were heated to a temperature of 80 °C under high-speed stirring for 1 h. Then, different content of PEG 400, with a concentration of 62.5 ppm, was added into the flasks, respectively, according to the formulation as shown in −1. All of the curves have been normalized.Attenuated total reflectance-Fourier transform infrared (ATR–FTIR) spectra were measured by a VERTEX-70 FTIR spectrometer  equipped with a horizontal 45° germanium (Ge) crystal ATR device at room temperature. The spectra were the results of 30 scans in the spectral range of 4000~550 cmTGA were done by TG209F1  at a heating rate of 10 °C/min from 30 to 800 °C in nitrogen atmosphere.Mooney viscosity, ML (1 + 4) 100 °C, was performed with an Alpha Technologies MV 2000E , according to Deutsche Industrie Norm (DIN) 53523.3.Payne effect of the composites was characterized on a dynamic mechanical analyzer  in the stain mode. The strain sweeps were measured from 0.45 to 13.0% at a constant frequency of 1 Hz and temperature of 25 °C. The sample dimension was 6 × 6 × 2 mmStress/strain tests were performed at ambient temperature with a Zwick tensile tester  at a crosshead speed of 500 mm/min using optical strain control (DIN 53504). For tear strength, the vulcanizates were tested at room temperature using angle-shaped rubber specimens with the same machine and speed as applied for tensile tests, according to DIN 53507. The measurements were done 5 times, and mean values were used.For the measurements of rebound, the specimens with cylindrical shapes were used  at 23 °C, according to DIN 53512, with the Zwick rebound tester 5109.01.The compression set was done at 23 °C and 70 °C for 48 h, according to DIN 53517. Five specimens were tested for each formulation, and midvalues were used.DIN abrasion was measured with Abrasion tester of Frank 11565, according to DIN 53516. The specimen was cylindrical shapes with a diameter of 16 ± 2 mm and a minimum thickness of 6 mm. The abrading distance on the surface of the specimens and the speed were 40 m and 40 rpm, respectively.3.Dynamic mechanical analysis was characterized on a dynamic mechanical analyzer  in the tension mode. The temperature sweeps were measured from −80 to 100 °C at a constant frequency of 10 Hz, strain amplitude of 0.5% and a heating rate of 3 °C/min. The sample dimension was 6 × 4 × 2 mmv is the crosslink density, By means of equilibrium swelling the crosslink density of the vulcanizates and the polymer–filler interaction was determined. The samples were immersed in toluene in closed bottles at ambient temperature on a shaker. Three aliquots of each sample were taken out periodically and removed of the excess liquid on the specimen surface by a filter paper and then weighed immediately with an electronic balance. The weight of the swollen samples was continued until reached the equilibrium. The crosslink density was determined by means of Flory–Rehner equation :v=−ln1−VThe values of the Flory–Huggins interaction parameter χ for cured rubber with different solvents can be found in the chemistry handbooks. For toluene χ = 0.37 was used in the calculations.A JEM-2100F scanning electron microscope  was used to characterize the fracture surface of the vulcanizates after tensile testing. The specimens were examined after sputter coating with a thin film of gold. An accelerating voltage of 1.0 KV and a magnification range from 500× to 1000× were used.−1 is due to –OH bond stretching vibrations, and the whole band structure changes in a non-monotonous way. In the spectra, the absorption at around 3650 cm−1 indicated the uncombined –OH in the system; for example, the residual of free water in the mix remains almost constant intensity. However, the intensity at 3350 cm−1 is result from the number of the associated hydroxyls, including the silanol hydroxyls and the chemically combined water absorbed on the silica surface. Although the residual water is one of the factors influencing the intensity of these peaks, a slight increase of the water content can be found from the weight loss from 30 to 110 °C of TGA results . The values of the scorch time (t10) and the optimum curing time (t90) can be used to evaluate the vulcanization rate. As illustrated in The addition of PEG into the silane-modified silica composites also affected the Mooney viscosity , which iBased on the results of the cure characteristics, the possible reaction mechanisms of TESPD and PEG on silica surface after vulcanization are shown in In order to characterize filler aggregation in the composites, DMA strain sweeps were performed at 25 °C, and the dependency of storage moduli (G’) on the strain amplitude was determined by the difference between G’ at low and high strains (Payne effect). A larger difference, i.e., higher Payne effect, means a higher degree of filler–filler interactions, as well as a poorer filler dispersion. The results in The effect of PEG on the dispersion of silica was studied by SEM on the fracture surfaces of tensile testing, which were taken from PEG0 and PEG4. The respective micrographs are given in two magnifications . Figure To determine the effect of the filler–rubber interaction due to silica, silane and PEG on the crosslink density in the vulcanizate structure, the rubber contents were each divided into the silica contents to calculate the values per 1 phr of filler contributing to the crosslink density. As can be seen in The static mechanical behavior of the composites was analyzed with a tensile tester. When compared to the PEG 0, there were only small changes in the tensile strength with the increase of the PEG content, as displayed in The use of PEG further shows a slight improvement in tear strength and DIN abrasion properties, compared to the PEG-free system, as shown in The rebound resilience is used to characterize the energy recovery capability of rubber composite after elastic deformation, mostly caused by compressive stress. Generally, the rubber resilience is related to the flexibility of polymer chain, intermolecular force, crosslink density, filler dispersion and softener effect. As shown in The compression set of vulcanizates is one of the important properties to evaluate the static permanent deformation of rubber products. It is mainly dependent on the recovery ability of the polymer chains. g).The response of viscoelastic performances to cyclic or sinusoidal deformations can be investigated by DMA–temperature sweeps. The storage modulus (E’) corresponds to the elastic deformation of rubber, and the loss modulus (E’’) corresponds to the viscous deformation. The mechanical loss factor is expressed as In The dependencies of tan δ on temperature are given in To evaluate the possibility of practical application of PEG in green tire tread, the effects of PEG on the magic triangle properties were compared with the typical tread formulation. When 3 phr of PEG was introduced into the silica/silane composite (PEG 3), all the three magic triangle properties, including rolling resistance and abrasion resistance, improved 39% and 24%, respectively, compared with the composite without PEG (PEG 0). The addition of 4 phr PEG in the compound did reduce the rolling resistance by 29% and increase the wet grip by 13%, respectively, suggesting that the excellent fuel consumption and driving safety are affected. As observed also for other properties earlier, the use of PEG, for example 3–4 phr, as an interfacial modifier in the silane-modified silica composites showed optimum properties, which indicates the best balance of both physical and chemical interactions and provides a solution for solving “magic triangle” in the green tires for passenger cars.The addition of a small amount of PEG 4000 as an interfacial modifier on the second mixing stage in silane-modified silica composites improved the properties of Mooney viscosity; cure rate index; tensile strength; tensile modulus at 300% elongation; tear strength; DIN abrasion resistance; compression set at both 23 and 70 °C, due to an increase in the crosslink density; and silica dispersion. The dynamic mechanical properties, including rolling resistance, wet skid performance, ice traction and heat buildup were also improved, simultaneously. Summarizing from the perspective of tire performance, at optimum PEG content of 3–4 phr, the “magic triangle” properties were improved simultaneously, compared to the silica/silane composites. PEG can shield the silanol groups on the silica surface, leading to shortened vulcanization time, which enables an increase in productivity and energy saving. However, the excess PEG acted as lubricant and increased the possibility to shield the disulfide bonds of TESPD and resulted in the reduction of crosslink density and physical mechanical properties. An optimum PEG content is necessary for the overall performance and polymer–filler interaction. The results also demonstrated that the interfacial modifier, applied in green tire technology, physiosorbed/chemisorbed on the silica surface would improve of the performance, especially for the dynamic mechanical properties of tire tread. This finding will improve our understanding of the “magic triangle” performance of silica-loaded tire tread vulcanizates in the future.