Moreover, a high frequency of systemic arterial hypertension and physical inactivity was observed. The average NRF for CVDs was above ten, at the three evaluation times. Women with higher NRF had higher levels of CRP (p = 0.003), a predictor of cardiovascular risk, however, there was no significance with PhA (p = 0.256). Thus, intervention is needed to improve lifestyle.The increased risk for cardiovascular diseases (CVDs) in breast cancer survivors has been widely discussed in the literature and occurs due to the cardiotoxicity of antineoplastic treatments, and also to the common risk factors between these diseases. Thus, the objective of our study was to evaluate, prospectively, the number of risk factors (NRF) for CVDs in women during endocrine therapy, and to associate the NRF with C reactive protein (CRP) and phase angle (PhA). The following risk factors for CVD were evaluated at three times: anthracycline chemotherapy, radiotherapy, comorbidities, inadequate diet, overweight, abdominal adiposity, alcoholism, smoking, physical inactivity and altered lipid profile. There was inadequacy in the most components of the Brazilian Healthy Eating Index—Revised and inadequate consumption of various types of fats and fibers. Most women in this study presented excessive abdominal fat and overweight, but these parameters have not changed over time ( Breast cancer (BC) is the most common type of cancer in women . ImproveEndocrine therapy is prescribed, aiming to reduce BC recurrence and mortality ,9. AmongThe adoption of a better-quality diet is associated with a reduction in the incidence of and mortality from BC  and CVDsLight or moderate alcohol consumption appears to have a positive impact on cardiovascular health in the general population , and in Due to the large number of CVD deaths among BC survivors, we hypothesize that these women present several CVD risks that predispose them to the disease. Besides that, the greater number of risk factors (NRF) may be related to markers such as higher CRP and lower PhA. Thus, this prospective study aimed to assess the presence of risk factors for CVDs and their change over time in BC survivors undergoing endocrine therapy, associating the NRF for CVDs with CRP and PhA.A prospective study carried out from January 2016 to August 2018 with BC survivors undergoing endocrine therapy with AIs at the Clinical Hospital of the Federal University of Uberlandia (HC/UFU). The follow-up time was 24 months, and the evaluations were carried out in three assessments, denoted T0, initial follow-up period; T1, intermediate follow-up period, 12 months after T0; and T2, final follow-up period (T2), 24 months after T0.The recruitment of participants and exclusion criteria are described in In order to characterize the population through the analysis of medical records (T0), data on the type of surgery, radiotherapy and previous CT, tumor subtype, clinical stage, histological grade, positivity of hormone receptors, molecular subtype and duration of AIs were obtained. Anthracycline CT and radiotherapy were counted as cardiovascular risk factors.Through interviews at T0, T1 and T2, personal, comorbidity and socioeconomic data were obtained, such as age, education, income and self-reported race and presence or absence of self-reported DM and SAH. Patients with SAH used medications such as diuretics , beta-blockers , calcium channel antagonists (nifedipine or anlodipine), angiotensin-converting enzyme inhibitors , angiotensin II receptor antagonists (losartan or diovan), direct vasodilators  and/or sympatholytic drugs (methyldopa). Diabetic patients used medications such as biguanides (metformin), sulfonylureas (gliclazide) and insulin. Data on the history of CVDs were obtained through the analysis of medical records. Lifestyle data were also obtained, such as smoking (smokers or non-smokers), alcohol consumption (excessive or not) and physical activity . Race and education were evaluated only at T0.To be considered excessive, alcohol consumption should be at least 8 drinks per week, with each dose equivalent to approximately one can of beer or one glass of wine . Other t2) and classified according to the recommended ranges for the adult population (age > 18 years and <60 years): without overweight up to 24.9 kg/m2 and overweight ≥ 25 kg/m2) [2 and overweight ≥ 27 kg/m2 [Weight, height, waist circumference (WC) and hip circumference were measured. Specific protocol was used for all measures . WC was 5 kg/m2) , and eld27 kg/m2 . The wai27 kg/m2  and acco27 kg/m2 . Additio27 kg/m2 . The CI The horizontal tetra polar bioelectrical impedance (BIA)  was used to evaluate body compartments and phase angle, according to the protocol by Cômodo and collaborators . Partici2), TGs (mmol/L) and HDL (mmol/L) data:Venous blood was collected at the time of the interview after overnight fasting (up to 12 h) and under standard conditions . Serum Con (LAP) , calculaFood consumption information was collected through 24 h dietary recalls (24HRs). At each study session , three non-consecutive 24HRs were applied, one referring to a weekend day, to better reflect the participants’ eating habits, totaling nine 24HRs during the study. The first 24HR was carried out in person and the others via telephone, following the technique used in the Vigitel  study. FTo verify food consumption over time, due to its intrinsic variability, the data were attenuated, that is, corrected by inter- and intra-individual variability, following the methodology by Nusser and collaborators , using tThe Healthy Eating Index (HEI)  was adapThe data with household measurements from the 24HRs were converted to units of measurement (grams or milliliters) by the Table to Evaluate Food Consumption in Household Measurements  to calcuThe number of daily servings was adjusted by 1000 kcal/day. Thus, the scores for each food component and the BHEI-R total score were calculated. For most components, the recommendations by the Food Guide for the Brazilian Population  regardinn = 65) and T2 (n = 38). T0 was not included in analysis 2, as there was no blood collection at this time  were used to count the risk factors per participant at each time, with all risk factors having the same load . In analhis time .n = 89; T1: n = 65; T2: n = 38).After counting risk factors for CVDs, the average number of risk factors at each time was verified. A percentage of women with a certain amount of inadequate dietary factors was also evaluated among the 11 counted at each time  was used to compare the mean values of the variables over time, adjusting the models by age, income, education and AI usage duration. The lipid profile was adjusted by cholesterol-lowering medication. In addition, the GMM was used to verify the impact of NRF  and the number of inadequate dietary factors on serum CRP levels and phase angle. For prospective analyses, the 38 women who participated in the three study sessions were considered. For the following analyses of the average number of risk factors for CVDs and percentage of inadequacy of CVD risk factors and dietary factors, all women recruited in the study were considered .p < 0.05. The figures referring to the number of inadequate dietary factors and the average number of risk factors for CVDs were created using Excel.All statistical analyses were performed using IBM SPSS Statistics version 21.0, considering confidence intervals (CIs) of 0.95 and p = 0.888, p = 0.008), identified by the post hoc comparison. There was also an increase in the consumption of the Oils component between T1 and T2 (p = 0.022). For the other components, no significant changes were detected . There was also less consumption of polyunsaturated fats at T1 when compared to T0 (p = 0.010). At T2, there was a reduction in the consumption of saturated fats and cholesterol, as well as an increase in the consumption of sodium and omega 3 . In addition, there was a reduction in the consumption of proteins, trans fats and omega 3/6 ratio  across the three times  across the three times (p = 0.212), but there was a reduction in soluble fiber at T2 when compared to T0 and T1 (p = 0.015)  .p < 0.001). In addition, there was a reduction in LAP at T2 (p = 0.007). Regarding biochemical results, a reduction in total cholesterol, non-HDL cholesterol, LDL, VLDL and TGs  was identified, as shown in T2  of women did not reach the maximum score for the majority of BHEI-R components, except for the Oils component  (data not shown). The percentage of inadequacy of each risk factor for CVDs is shown in Regarding anthropometric data, there was a high percentage of overweight  and abdominal adiposity  .As for the lipid profile, non-HDL showed a high percentage of inadequacy at T1 (43.4%). Women reported DM  and a high percentage of SAH  .For the lifestyle variables, a high percentage of physical inactivity was observed at all times . There was no excessive alcohol consumption in the women evaluated at any time . At T0, p = 0.003). There were no significant differences in the NRF categorization in the phase angle values, however, there was an increase in this variable at T1 and T2 in relation to T0 (p < 0.001) (The impact of the NRF (categorized by the median) on serum levels of CRP and PhA values was verified. Considering the 20 risk factors , it was observed that women with an NRF equal to or above the median (≥11 factors) had higher serum CRP levels than women with an NRF below the median (< 0.001) . The anaTo the best of our knowledge, this is the first study to assess the number of risk factors for CVDs in BC survivors during endocrine therapy with AIs. It is important to evaluate aspects beyond cancer, to treat women in their entirety. The results of this prospective study indicate a high percentage of several risk factors for CVDs. Inadequacy of quantitative and qualitative food consumption was verified, with most of the evaluated nutrients not reaching the intake recommendations and important food groups of the BHEI-R had low scores. There was a high percentage of previous cardiotoxic treatments, excess body weight and abdominal adiposity, physical inactivity and the presence of comorbidities. Despite not having excessive alcohol consumption and having improved phase angle, LAP and lipid profile, with reduction in total cholesterol, non-HDL cholesterol, LDL, VLDL and triglycerides, most women had a worrying number of risk factors for CVDs at all times of the study. In addition, women with a higher NRF had higher levels of CRP, a predictor of cardiovascular risk. These observations are important to guide the multidisciplinary treatment for BC survivors.In our study, we observed that most women underwent potentially cardiotoxic treatments, such as CT with anthracycline and radiotherapy. The literature shows that CT leads to inhibition of topoisomerase in both cancer cells and cardiomyocytes, causing cardiotoxicity due to the accumulation of double-stranded DNA breaks and mitochondrial dysfunction, which leads to the activation of cell death pathways and the accumulation of reactive oxygen species . RadiothDespite the importance of controlling modifiable risk factors for CVDs, in the present study, there was a high percentage of inadequacy of both qualitative and quantitative dietary factors, overweight, abdominal adiposity and physical inactivity. Milliron et al.  showed tDespite the lower consumption of energy, carbohydrates, and sugars at T1 and T2, which suggests a reduction in food consumption, an overconsumption of total, monounsaturated and saturated fats was observed. In addition, the reduction in the consumption of polyunsaturated fats diverged from the recommendations for cardiovascular protection, which propose the substitution of saturated fats with polyunsaturated fats . FurtherStudies showed a high prevalence of physical inactivity among BC survivors ,63, corrIn addition to inappropriate diet and physical inactivity, there was a high frequency of overweight in our study. In patients with hormone-positive tumors, obesity may lead to BC-specific mortality  and is aThe conicity index (CI), visceral adiposity index (VAI) and LAP are important measures for assessing cardiovascular risk ,44,45. IThere was an increase in the phase angle at T1 and T2 in relation to T0. A study showed that women with BC who had a phase angle above 5.6 have a better prognosis . Thus, tIn the present study, comorbidities such as DM and SAH were reported, with the latter being observed in more than 50% of women at all evaluated times. BC survivors are more likely to have DM and systemic arterial hypertension than individuals not diagnosed with the disease . The adoThere was an absence of excessive alcohol consumption and a low percentage of smoking. A study showed that among survivors of various types of cancer, adherence to the recommendation of not smoking is more common than physical activity and the consumption of fruit and vegetables , corroboNegative changes in the lipid profile increase cardiovascular risk, such as for atherosclerosis, stroke and heart attack . HoweverDespite the absence of excessive alcohol consumption and positive changes in the lipid profile, the present study shows worrying results, with women presenting a higher average of risk factors for CVDs at all evaluated times. In women over 45 years of age, the greater the number of risk factors, the greater the mortality from CVDs. Compared with the absence of risk factors for CVDs, the presence of one, two or three or more raises the risk ratios for CVD mortality by 2.566, 3.655 and 5.416 times, respectively . ConsideThis study has some limitations. First, the biochemical data were collected only at T1 and T2, although the other variables were collected at the three evaluated times of the study. In addition, the assessment of food consumption is subject to error due to memory bias, but to minimize this, the interviews were conducted by properly trained nutritionists and the data were adjusted and mitigated to reduce inter- and intra-individual variability. A strength of the study was the evaluation of several variables, which allowed an overview of the cardiovascular risk profile of BC survivors. Furthermore, to the best of our knowledge, this is the first study to assess cardiovascular risk in BC survivors. Further studies, with larger samples, are needed to confirm our results.Due to the high average number of risk factors for CVDs, the implementation of protocols to assess risk factors for CVDs should be suggested to women undergoing breast cancer treatment. In addition, lifestyle interventions to improve modifiable factors are of great value. A multidisciplinary approach is important, with dietary intervention, a physical training protocol, medical monitoring of pre-existing comorbidities and psychological monitoring to support behavioral changes. Psychological counseling is important for changing habits, and also for improving quality of life and reducing anxiety and depression in BC patients . AnotherThe results showed that most women had a worrying amount of risk factors for CVDs, and those with a higher NRF had higher levels of CRP, a predictor of cardiovascular risk. In the prospective analysis, an improvement in the lipid profile and phase angle was observed. Despite this, there was a high percentage of inadequacy in terms of dietary and anthropometric factors, in addition to the presence of comorbidities and physical inactivity. For this reason, emphasizing dietary and physical activity guidelines during and after treatment is necessary so that BC survivors can adopt healthier practices.


Background: Shared decision-making (SDM) in mental healthcare has received increased attention as a process to reinforce person-centered care. With the rapid development of digital health technology, researchers investigate how digital interventions may be utilized to support SDM. Despite the promise of digital interventions to support SDM, the effect of these in mental healthcare has not been evaluated before. Thus, this paper aims to assess the effect of SDM interventions complimented by digital technology in mental healthcare.Objective: The objective of this review was to systematically examine the effectiveness of digital SDM interventions on patient outcomes as investigated in randomized trials.Methods: We performed a systematic review and meta-analysis of randomized controlled trials on digital SDM interventions for people with a mental health condition. We searched for relevant studies in MEDLINE, PsycINFO, EMBASE, CINAHL, and the Cochrane Central Register of Controlled Trials. The search strategy included terms relating to SDM, digital systems, mental health conditions, and study type. The primary outcome was patient activation or indices of the same , adherence to treatment, hospital admissions, severity of symptoms, and level of functioning. Secondary outcomes were satisfaction, decisional conflict, working alliance, usage, and adherence of medicine; and adverse events were defined as harms or side effects.Results: Sixteen studies met the inclusion criteria with outcome data from 2,400 participants. Digital SDM interventions had a moderate positive effect as compared with a control condition on patient activation , a small effect on general symptoms , and working alliance  and for improving decisional conflict . No effect was found on self-efficacy, other types of mental health symptoms, adverse events, or patient satisfaction. A total of 39 outcomes were narratively synthesized with results either favoring the intervention group or showing no significant differences between groups. Studies were generally assessed to have unclear or high risk of bias, and outcomes had a Grading of Recommendations Assessment, Development and Evaluation (GRADE) rating of low- or very low-quality evidence.Conclusions: Digital interventions to support SDM may be a promising tool in mental healthcare; but with the limited quality of research, we have little confidence in the estimates of effect. More quality research is needed to further assess the effectiveness of digital means to support SDM but also to determine which digital intervention features are most effective to support SDM.Systematic Review Registration: PROSPERO, identifier CRD42020148132. Digital health technology has become an integrated part of the global healthcare system and is continuously developing and growing. Within mental healthcare, traditional means of care are being complemented by health technology such as smartphone decision aids, web-based self-management systems, or online support groups. As technology develops, new possibilities arise; and the World Health Organization advocated through the global strategy on digital health for 2020–2024 to use digital technology for more person-centered healthcare . Person-Researchers within mental healthcare have increasingly turned their attention to shared decision-making (SDM) as a process to reinforce person-centered care . SDM canPrevious systematic reviews and meta-analyses have found that SDM interventions have a small effect on empowerment for people with psychosis and that SDM may increase provider facilitation of patient involvement , 9, whilThis systematic review and meta-analysis followed the PRISMA statement and adhered to the registered online protocol at PROSPERO (CRD42020148132) .We defined SDM in this review as a process with three main components: (1) sharing information; (2) discussing treatment options; and 3) reaching a mutual decision that both parties can agree upon. Around these three components lie several surrounding mechanisms affecting this process such as learning about the patient, supporting the patient to initiate discussions with the provider, or evaluating the decision. The process of SDM and its surrounding mechanisms is illustrated in  reachingDigital interventions were defined as information and/or communication technology delivered via phones, computers, personal digital assistants, or other similar devices. Interventions did not have to be internet-based.Diagnostic and Statistical Manual of Mental Disorders (DSM) and International Classification of Diseases (ICD).Mental health conditions were defined in concordance to the We conducted a systematic literature search of the following databases up to March 2021: MEDLINE, CINAHL, EMBASE, PsycINFO, and the Cochrane Central Register of Controlled Trials. The PICO framework was used to develop the search strategy. Our search terms focused on SDM, digital health technology, mental health, and RCTs. The complete search strategy is listed in the Only RCTs presenting original data were included in the review. For a study to be included in the review, 50% of the participants needed to have a mental health condition as defined by the DSM and ICD. Besides having a mental health condition, there were no restrictions regarding clinical or demographic characteristics of the participants. Exclusion criteria were studies focusing on relatives rather than the patient or provider. For an intervention to be included, it had to cover one of the three main components of SDM and use a digital tool for people with a mental health condition (as defined above).The search strategy was developed by the author TV and approved by CH and LK , control condition, type of setting, and baseline demographics . The authors of the retrieved papers were contacted if clarification was needed or if data were not accessible from the article.All analyses were conducted by Review Manager 5.3.5, using random-effects model to account for heterogeneity. The total difference in changes on measurements for patient activation or indices of the same between digital interventions and controls were pooled to compute the overall effect size of the digital interventions with 95% confidence intervals. TV and CH assessed the risk of bias in the included studies using Cochrane Collaboration's Risk of Bias tool. This tool assesses studies six areas, ranking each area as high, low, or unknown for risk of bias. The areas are sequence generation, allocation sequence concealment, blinding of participants and personnel, blinding of outcome assessment, incomplete outcome data, and selective outcome reporting. In addition, TV and CH used the Grading of Recommendations Assessment, Development and Evaluation (GRADE) system to assess the quality of evidence of each outcome by downgrading from high by one level for each serious issue identified in the domains: risk of bias, inconsistency, indirectness, imprecision, and publication bias . In caseDecisional conflict was not originally planned as an outcome for our meta-analysis according to our protocol; however, after discovering several of the studies measuring this area and considering its relation to SDM, it was included –18.The search resulted in 1,911 references, 1,098 after duplicates were removed and 277 after title screening. After abstract screen and full-text assessment, 12 articles were assessed as eligible. Four additional articles were included after reading protocols from the initial search where authors of unpublished results were contacted. Thus, 16 RCTs investigating digital SDM interventions within mental health were included in the meta-analysis. The progress of including and excluding articles is shown in the PRISMA flow diagram Characteristics of the 16 study populations, aim, duration, comparison treatment, and outcome measures are presented in Overall, 2,400 participated in the 16 trials with a mean sample size of 150 ranging from 50 to 507 participants. Mean age for the participants was 40 years (SD = 8.5) ranging from 15 to 51 years. The proportion of females was 49% across all studies ranging from 14 to 100%. The mean duration of the interventions was approximately 3.4 months ranging from 1 day to 12 months. Because of this variation, studies were divided into either short-term intervention (3 months or less) or long-term intervention (more than 3 months): 11 trials were categorized as short-term interventions , 27, 29 All included studies were assessed for risk of bias using the Cochrane Collaboration's Risk of Bias tool on the following domains: random sequence generation, allocation concealment, selective reporting, blinding of participants and personnel, blinding of outcome assessments (objective and subjective), attrition bias, and other bias. The risk of bias for each study is presented in N = 77, standardized mean difference (SMD) = 0.56, CI: 0.10, 1.01, p = 0.02) . There was no significant effect on self-efficacy  . Meta-analysis on empowerment and patient involvement was not applicable due to only one study respectively reported data on these areas. Still, the results of these single studies are included in p = 0.06) (p = 0.95)  , 31. Var = 0.74) , 29, 30. = 0.06)  or patieN = 769, −0.17, CI: −0.31, −0.03, p = 0.02) (p = 0.07)     , 23, 30  = 0.62) , 31, dep = 0.32) , 29, or  = 0.09) , 18. Due2 = 0.23, p = 0.63, I2 = 0%), negative symptoms , overall psychiatric symptoms , or anxiety  but was present for general symptoms  and depressive symptoms . Egger's test was not performed due to the small sample of studies.Variation across trials due to heterogeneity was not present for positive symptoms  . Subgroup analysis for the primary outcomes showed no significant differences, which are included in the Results of the pooled effect size from digital SDM interventions on adverse events defined as harms or side effects together with the individual effect of each intervention are presented in  = 0.67) , 31. VarN = 423, SMD = 0.21, CI: 0.02, 0.41, p = 0.03)    but not for satisfaction  and working alliance . Assessment of publication bias was only performed for patient satisfaction due to the limited amount of studies for each pooled outcome. Via visual inspection of funnel plots, we did not assess any publication bias for patient satisfaction. Subgroup analysis on satisfaction by duration, type of intervention, and diagnosis showed no statistical significant differences between groups  , 30, 31, = 0.02) –18, and  = 0.21) , 30, 31.n groups –8. Subgrn groups –11. SubgThe outcomes had a GRADE rating of very low quality for patient activation and low quality for self-efficacy, adverse events, symptoms, working alliance, decisional conflict, and patient satisfaction. This implies that we have little confidence in the estimates of effect for these outcomes.Our review on the effectiveness of digital SDM interventions in mental healthcare included 2,400 participants across 16 RCTs examining digital interventions to support SDM with the majority conducted on psychosis, schizophrenia, or similar disorders.The main analysis found that digital SDM interventions led to a moderate significant effect on improving patient activation in mental healthcare but not on self-efficacy, empowerment, or subjective level of patient involvement. Such result could be that digital SDM tools are more effective at addressing the concepts of patient activation. However, only two small sampled studies investigated the effectiveness on patient activation, three studies on self-efficacy, and one study each on empowerment and patient-involvement. Therefore, more quality research on the effectiveness of SDM interventions on patient activation or indices of the same are greatly needed to investigate this further.As for symptoms, the use of a digital SDM intervention had a significant effect on general symptoms but not on positive, negative, anxiety, depressive, or overall psychiatric symptoms. Still, subgroup analysis showed no differences between types of symptoms, and with the GRADE level of the symptom outcomes, more research is needed to assess the effects of digital SDM tools on severity of symptoms.We identified two trials that included an outcome of adverse events showing no significant differences between groups. In addition, none of the studies investigated potential negative effects of using the digital intervention. The current evidence on the effectiveness of digital interventions on adverse events is scarce, which also has been highlighted by other systematic reviews . While tFor the secondary outcomes, a small significant effect was found for working alliance and decisional conflict. The most frequent outcome measured by the 16 trials, patient satisfaction, revealed no significant effect; but authors of the included trials indicates that “instruments focusing on satisfaction might suffer from ceiling effects” . As prevThe significant effect on patient activation, working alliance, and decisional conflict may indicate that SDM benefits the collaboration between patient and provider. Future research may wish to investigate whether SDM is directly associated with an effect on health outcomes or if the collaboration serves as a mediator for health outcomes .The fact that the most frequent outcome measures in this review were assessed by half of the trials and that only two trials measured our planned primary outcome, patient activation, highlights the vast differences in how trials evaluate their SDM interventions. Furthermore, although all included interventions support SDM, only three studies directly measured the level of SDM , 27, 31.Although all included studies investigated an intervention to support SDM, none of the included studies addressed all aspects of SDM, and only three studies included a measurement to assess the overall level of SDM. This may highlight a challenge in how to measure and evaluate the effect on SDM. The included trials in this review could be divided into two groups of systems: (1) a system developed to be used independently of the involvement of a provider or (2) a system developed to be incorporated into the collaboration with the provider. A system to support the patient could be a tool aimed at improving the patient's knowledge on needs, values, options, and the feeling of being prepared for the consultation. A system to support the consultation could be a tool aimed to ensure that a range of life domains and treatment aspects were consistently and structurally addressed and that patients' perspectives were always elicited at the consultation. For interventions not actively including the provider, patients were still encouraged to use the tool in collaboration with their provider . However, a challenge occurs when either the patient or provider is not actively included: the responsibility of incorporating and using the tool in the consultation is no longer shared and is instead solely placed on either the patient or provider—a responsibility that may be overwhelming for some. Also, as reported by one of the studies “A one-off intervention […] may be insufficient to improve patient involvement in decision-making” , indicatWith the vast differences in how researchers are developing tools to support SDM, quality guidance to develop and to assess these tools are needed. Such assessment is possible for, e.g., patient decision aids where International Patient Decision Aid Standards (IPDAS) may be used to assess the quality of the tool . In thisA majority of the included trials investigated either a web-based intervention or a computer software, while only three studies investigated a smartphone or tablet application. This limited the possibilities to assess the effectiveness of a digital intervention depending on its features or system category . To determine what digital features are the most effective at supporting SDM, more research investigating different types of features is needed.Our review has several strengths. Firstly, it provides evidence regarding the effectiveness of digital SDM interventions, which has not been conducted before. Secondly, this meta-analysis strictly follows the registered protocol describing our search strategy, types of studies to be included, data extraction, and targeted outcome measures . The onlDigital interventions to support SDM may be a promising tool in mental healthcare. The complexness of SDM and possibilities with digital tools create many possibilities for researchers as showcased in this review. It is still unclear which features of digital tools are most effective at supporting the SDM process. More quality research is needed to further assess the effectiveness of digital means to support SDM but also to determine which intervention features are most effective in supporting SDM.tobias.vitger@regionh.dk (I am happy to put you in contact with those authors who delivered raw data).The data analyzed in this study is subject to the following licenses/restrictions: Most data from the included trials can be found online. For some trials, we had to contact the corresponding author to receive the data for analysis. Requests to access these datasets should be directed to TV, CH, and LK designed the search strategy and the study protocol. TV and CH screened the identified studies against inclusion/exclusion criteria to determine eligibility for selection. TV performed the data analysis under supervision of CH and wrote the first draft of the manuscript. CH, LK, MN, SA, and LP all critically revised the manuscript. All authors approved the final version 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.All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.


M = 21.56; SD = 3.07) during the beginning of the first semester, March 2020 (T1), and their experiences at the end of the same academic period, September 2020 (T2). We used convenience non-probability sampling. Participants responded to the questionnaire on Expectations toward virtual education in higher education for students and the questionnaire on virtual education experiences in higher education. The results showed that students’ responses reflected low expectations regarding peer relationships and comparison with face-to-face education (T1). This perception was maintained during the evaluation of experiences (T2). Students reported positive experiences regarding online teaching and learning, online assessment, and their self-efficacy beliefs at T2. Statistically significant differences between measurements were found, with the expertise presenting higher averages than expectations. Furthermore, differences by gender were identified, reporting a positive change in the scores of women. In addition, results reflected differences according to the disciplinary area, showing Social Sciences and Medical and Health Sciences students a more significant size effect. Findings regarding the empirical evidence and the implications for future teaching scenarios in Higher Education are discussed.Due to COVID-19, university students continued their academic training remotely. To assess the effects of emergency remote teaching (ERT), we evaluated the expectations and, subsequently, the experiences of university students about online education. This study employed a simple prospective design as its method. We assessed the expectations of 1,904 students from different discipline areas (1,106 women and 798 men; age  Higher education institutions had to face the challenge of providing continuity to the educational process remotely due to the COVID-19 pandemic. This scenario implied a drastic transformation without the possibility of preparation, having both teachers and students quickly develop online education competencies . EmergenCurrently, online courses are created using an instructional design, such as ADDIE, and implemented through Learning Management Systems (LMS), like Canvas. In these courses, designers and teachers apply technological and pedagogical innovations to obtain high-quality standards. In this teaching modality, educational experiences occur synchronously and asynchronously using multiple devices to access the internet. Therefore, students can interact with teachers, content, and peers from wherever they are . It requQuality online teaching considers evaluating course characteristics, including the design of learning materials, the virtual environment, and the alignment of curricular components with learning outcomes. It also considers aspects related to the interaction experience of students with their peers and teachers .Due to the COVID-19 pandemic, students’ expectations about how their academic year would unfold were rapidly modified and adjusted. This is relevant due to empirical evidence that supports that student expectations are predictors of academic success . StudentSeveral studies have reported a variety of results regarding the expectations and subsequent experience of university students. For example, descriptive research conducted with 1612 undergraduates from 59 on-site Spanish universities says that students consider that the institutions did not adapt adequately to the ERT scenario (84%), especially regarding teaching methods and the implementation of assessments (64.5%). Furthermore, they state that the adopted institutional measures were not sufficient, affecting their academic performance (88.5%) during this period. In terms of experience, in the same research, students were not satisfied with virtual education, especially regarding courses’ assessment . These rConsistent with the above, another study indicates that students perceived an overload in their academic responsibilities due to excessive activities and assignments, which made the process more exhausting . MoreoveN = 30,383) claimed to be satisfied with the support provided by their instructors and institutions. In this case, specific sociodemographic characteristics such as gender, academic area, and other elements of the students favorably impacted these beliefs  and then the experience  of the students with online education during the ERT, to subsequently study the relationships found between the variables (A simple ariables .M = 21.56 (SD = 3.07). On the other hand, 635 (33.35%) of the participants were in their first academic year. According to their undergraduate program, students’ classification according to the areas of the Organization for Economic Co-operation and Development (OECD) is presented in A total of 1,904 students belonging to a traditional Chilean university participated, of which 1106 (58.1%) were women, and 798 (41.9%) were men, with mean age The Expectations toward Virtual Education in Higher Education for Students (CEEVESE) questionnaire aims to know higher education students’ expectations about virtual education during ERT. It consists of 28 items distributed in six dimensions about virtual education. The items were elaborated based on available scientific literature and evaluated employing expert judgment . Table 22(335) = 5354.88, p < 0.001, CFI:0.961; TLI:0.956; SRMR:0.041; RMSEA:0.06]. The reliability analysis of the responses was: peer relationship α = 0.894, online learning α = 0.922; online teaching α = 0.907; self-efficacy for online learning α = 0.882, online assessment α = 0.787; comparison with face-to-face education α = 0.779; full scale: α = 0.954  was employed. The average of each dimension and the full scale was analyzed, in which scores higher than 3 indicate positive expectations. Previous studies have examined the factorial structure of the scale, finding an adequate adjustment of the 6 factors . Reliability analysis of the responses by dimensions was as follows: peer relationship α = 0.869, online learning α = 0.883; online teaching α = 0.876; self-efficacy for online learning α = 0.872, online assessment α = 0.753; comparison with face-to-face education α = 0.671; full scale: α = 0.931 .The factorial structure of this version confirmed an adequate adjustment of the 6 factors  were found. Hence, students’ experience with ERT at the end of the academic period exceeded their expectations. In this sense, results respond positively to the proposed hypothesis, identifying differences in the scores between T1 and T2.When performing the comparative analysis between the general expectations of the students (T1) and the experience after the end of the semester (T2), statistically significant differences ; comparison with face-to-face education ; online teaching ; peer relationship ; and self-efficacy for online learning . In the case of the online assessment dimension, no statistically significant results were observed.We examined each dimension independently to answer the hypothesis regarding the existence of differences between expectations and experiences related to undergraduate students’ gender during ERT  = 10.64, p < 0.01, GES.006]. Online teaching: experience . Peer relationship: experience  and Self-efficacy for online learning: experience .Regarding the main effect of gender, a significant effect for experience, but not for expectations in the following four dimensions was observed online learning: experience , but not for experience (p = 0.06).On the other hand, in the case of comparison with face-to-face education, the results were significant for expectation  and men . In the Comparison with face-to-face education, women  and men . In the Online teaching, women  and the men . In the peer relationship, women  and men .The simple main effect of the differences between expectations and experience were also analyzed, observing statistically significant results for women and men in four of the dimensions: online learning, women . Even though men and women presented higher scores at T2, women showed the most significant change reflecting a positive experience with online education , the results by dimension are presented below.Regarding differences between the scores from expectations and experience of university students during ERT during the COVID-19 pandemic according to disciplinary areas  = 3.54, p < 0.01, GES = 0.003], online teaching , online assessment , online learning , peer relationship , and self-efficacy for online learning .For all six dimensions a statistically significant bidirectional interactions among the OECD area and the differences between T1 and T2 scores was found. The results by dimensions are the following: Comparison to face-to-face education  and the expectations : online assessment: experience  and expectations ; online learning: experience  and expectations ; self-efficacy for online learning: experience  and expectations .Regarding the main effect of OECD area, a significant effect for experience and for expectations was observed in the following four dimensions: Comparison to face-to-face education: experience , but not in experience (p = 1). On the other hand, for peer relationship, a significant effect was shown for experience  but not for expectations (p = 1).Regarding online teaching, a significant effect was observed in expectation , Medical and Health Sciences , Natural Sciences , Social Sciences , Humanities , and Engineering and Technology . Online teaching: Agricultural Sciences , Medical and Health Sciences , Natural Sciences , Social Sciences , Humanities , and Engineering and Technology .Finally, the simple main effect of the differences between expectations and experience for each dimension was analyzed, observing in some cases statistically significant effects for all six OECD areas, while in others only for one see . The resF = 70.57, p < 0.001, GES = 0.05] and Social Sciences . Online learning: Medical and Health Sciences , Natural Sciences , Social Sciences , Humanities , and Engineering and Technology . Peer relationship: Medical and Health Sciences , Social Sciences , and Engineering and Technology . Self-efficacy for online learning: Social Sciences .The following differences in the dimension of online assessment between discipline areas were found: Medical and Health Sciences [Due to the COVID-19 pandemic, the transition to ERT impacted students’ expectations and experiences during their professional training. This research aimed to analyze students’ expectations and experiences considering the gender and disciplinary area of the participants. Findings are analyzed and discussed in terms of the hypotheses raised in section “The Present Study.”Changes between students’ expectations and experiences during ERT were found. Students’ expectations at T1 about online education were negative. However, at the end of the academic period, students indicated having a positive experience in most studied dimensions. They only showed a negative experience regarding the relationship with their peers and the comparison with face-to-face.Several studies during the pandemic point out the lack of confidence toward the different educational actors and online education opportunities. This mistrust is associated with a lack of knowledge of the modality and its advantages  and littStudents’ perception of the limited opportunities virtual classrooms and other technological tools provided them to interact and work collaboratively with peers is particularly noteworthy. Several reports emphasize the benefits of cooperative work versus a competitive or individualistic methodology in higher education. The former generates better learning and significant commitment and involvement in academic tasks . Also, cThe observation that students face online education with a high sense of self-efficacy, believing that they have the skills to respond to the learning challenges that this modality presents, could be explained by the lack of knowledge and experience, as well as underestimating the necessary skills. Consequently, students perceive a lower complexity than the real one, as described by the “Durning Kruger effect” . It is pThe perception of a better experience concerning the initial expectation suggests that the implementation of ERT, although not devoid of difficulties, responded to students’ needs. Hence, higher education institutions’ response and the teachers’ and students’ adaptation adequately provided a well-perceived learning environment. Furthermore, the above is consistent with other research during the pandemic that reported positive experiences by teachers and students in terms of having been able to face the educational process despite the adversities of the confinement and its urgency .We can conclude that the educational community and higher education authorities have learned greatly during ERT. Therefore, it will be interesting to study how to translate these lessons into explicit guidelines and practices when returning to normality post-pandemic.When evaluating changes in expectation and experience scores considering the sex of the participants, at the beginning of ERT, men and women presented similar levels of expectations about online education. However, experiences showed differences according to gender. Although both perceived the educational experience as positive, women gave higher values than men, in the dimension with lower punctuation in the experience compared with a face-to-face modality and peer relationship.These results are consistent with the study reported by In another study on online university education in the context of COVID-19 , the autResearch on the effects of the COVID-19 pandemic in the context of higher education has identified significant challenges for implementing online education, such as inequality, funding, and ways to develop learning in general . In thisDifferences in the expectations and experiences of university students in the six disciplinary areas classified according to their undergraduate programs were found. Unfortunately, there is little literature on the influence of the disciplinary area to which students’ undergraduate programs belong regarding experience with online education in ERT. Knowing about students’ experience in each disciplinary area will allow teachers and educational authorities to identify weaknesses and good practices that will otherwise not be detected to design and develop monitoring plans and improve the quality of online education in the future.We found differences within expectations in the online teaching dimension for all disciplinary areas. On the other hand, Students from Engineering and Technology and Medical and Health Sciences areas reported higher experience scores in this dimension, which implies that these students felt more confident about the actions performed by their instructors. This result could be related to the use of technology by Engineering and Technology teachers and the teacher training in the medical education area, often advanced.Despite the improvement between student expectations and experiences of the online assessment dimension, changes presented null  or small  size effect. The assessment processes continue to be an area of concern. Other reports support this statement. For example, Jordanian university students perceived that assessment during the pandemic allowed them to obtain higher grades than face-to-face assessments. Nonetheless, most students perceived that the evaluative processes were unfair and learned more minor than the quality reflected . ConsistAn interesting finding is a large-size effect obtained in the differences between the scores of expectations and experience of students of Agricultural Sciences and Medical and Health Sciences, for the comparison with face-to-face education dimension. Further research is required to identify good practices teachers and students implement in undergraduate programs classified in these two OCDE discipline areas.We believe that the differences in the results of the students’ expectations and experience according to the disciplinary area are due to the different challenges encountered in the adaptation of the courses (efficient ones). Accordingly, strategies used, for example, in Health Sciences, can be used in realistic training scenarios that relate to people . One of these strategies can be using remote standardized patients who have meetings with students through the Internet. These activities allow teachers and standardized students to have spaces for evaluation and feedback . This teConcerning the dimension of self-efficacy for online learning, no significant changes in four of the six knowledge evaluated areas were observed. Agricultural Sciences and Social Sciences displayed differences with small-size effect. Thus, ERT did not increase students’ confidence beliefs toward taking classes in the online teaching modality.Despite valuable information that has been obtained for this study, some limitations are identified. First, the results presented correspond to university students’ responses from a single educational institution, so the interventions of university authorities could bias expectations and subsequent experiences in the context of ERT. Second, it was not part of this study to evaluate access gaps and other student variables that could affect the results. Finally, variables associated with the teacher or course characteristics that may influence the outcomes could not be controlled. Therefore, the results aim to study changes between students’ expectations and experience in an exploratory way. Other studies must consider the assessment of student , professor , or course  variables that may affect undergraduate expectations and experiences.In this research, we found that students’ experiences with online education during the ERT were more optimistic than their expectations at the beginning of the semester. For this reason, the results found, together with other sources of institutional information such as learning analytics and institutional indicators, will allow authorities and teachers to develop guidelines to promote quality online education. It is also possible that university authorities could consider these preferences to design and create online courses for their students .The relationship with peers and professors is still considered a weak point of online education. This is a crucial aspect to be addressed by university professors. In the context of virtuality, professors need to maintain communication channels that allow them to provide students with timely feedback from online video tutorials or email guides after class . We idenWe found differences in the students’ experiences according to the scientific areas. These results translate into a challenge to identify the strategies and actions that facilitated a positive experience to replicate them in similar formative contexts. Further, studies can be performed to identify good practices applied in general contexts and those appropriate for each discipline. Higher education institutions are expected to accompany teachers and students in the different scientific areas during the post-pandemic academic continuity. Exceptional support is scheduled in aspects such as planning and prioritization of practical classes, promoting a combined approach of virtual and face-to-face education .Future research could assess how students’ variables , courses’ factors , teachers’ aspects  or the institution’s elements  impact the expectations and subsequent experience of students during the development of online courses., especially regarding strength and weaknesses according to discipline areas.The findings of this work contribute to identifying dimensions and areas that require special attention to establish preventive and corrective actions by university authorities for the near future and propose the opportunity of further studying good practices of better-perceived experiences of discipline areas.The students’ experiences during ERT due to the COVID-19 pandemic exceeded expectations. Students reported high expectations about their self-efficacy to cope with this new scenario, even though low expectations regarding peer relationships, online teaching, and comparison with face-to-face education were observed concerning the experience after the semester. Students indicated positive experiences with online learning and teaching. They felt that the professor provided adequate support in terms of education, instruction, and assessment. Negative experiences persisted regarding peer relationships and the overall experience compared to face-to-face teaching. Additionally, men and women presented similar expectations at the beginning of the semester regardless of their discipline, while women were more optimistic about educational experiences during ERT. Finally, concerning the disciplinary area, differences in most of the assessed dimensions were observed, representing an opportunity to study further and identify good practices in those dimensions and disciplines that presented positive perception and effect.The original contributions presented in the study are included in the article/supplementary material, further inquiries can be directed to the corresponding author.The studies involving human participants were reviewed and approved by Institutional Ethics Committee of University of Concepción. The patients/participants provided their written informed consent to participate in this study.KL and RC-R: conceptualization. KL, RC-R, and CB: methodology. JM-N: formal analysis and visualization. KL, RC-R, and AM-T: research and writing—preparing the original draft. AM-T, CB, and CF: resources, project management, and fundraising. JM-N and RC-R: data curation. CB and CF: writing—revising and editing. KL, CB, and CF: monitoring.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.All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.


This meta-analysis aimed to compare the efficacy of artificial urinary sphincter (AUS) and slings for the treatment of moderate male stress urinary incontinence (SUI) based on existing data.The study was in accordance with the Preferred Reporting Items for Systematic Reviews and Meta-Analysis. We searched the widely acknowledged database including PubMed, Embase (Ovid version), Medline (Ovid version), and Cochrane Central Register of Controlled Trials (till February 2021). Male patients with moderate SUI who underwent AUS or slings procedure over 18 years old and had been monitored with a mean follow-up time of at least 12 months were included. The primary outcome was success rate defined as daily pad use with 0–1 pad/d postoperatively. Articles with congruent outcomes were suitable for inclusion. The secondary outcome included complication rate of infection, erosion, acute urinary retention, and surgical revision.P = 0.86).Five studies with a total of 509 patients (295 for slings and 214 for AUS) were recruited. The success rate was higher in AUS with an odds ratio (OR) = 0.57 (95% CI: 0.36–0.90). As for the overall complication rate, no significant difference was discovered between slings and AUS groups (OR = 1.06, 95% CI: 0.58–1.92, To conclude, AUS was better than slings for moderate male SUI treatment according to daily pad use with an acceptable complication rate. The slings also had clinical value and were options when aging male patients were AUS naive and refused inserted mechanical devices. High-quality pieces of evidence are needed to confirm the efficacy of AUS and slings in moderate male SUI.Systematic Review Registration:https://www.crd.york.ac.uk/prospero/display_record.php?RecordID=271203, identifier: CRD42021271203. Male stress urinary incontinence (SUI) is not a rare disease and is recognized to have a negative impact on the patients' quality of life. It has been reported that the prevalence of SUI in male patients increased with age, with a proportion of around 2 and 4% for 48–64 years old and over 65, respectively . As for Two main solutions are recommended for the treatment of male SUI after the failure of conservative therapy: artificial urinary sphincter (AUS) and slings. Up till now, AUS is still recognized as the gold standard for the treatment of moderate-to-severe postprostatectomy SUI,  for its Some studies have explored the clinical outcome of postprostatectomy SUI between AUS and slings, but the results are confusing , 13–15. The study was in accordance with the Preferred Reporting Items for Systematic Reviews and Meta-Analysis (PRISMA). The work was registered in PROSPERO with registration number CRD42021271203.We searched the widely acknowledged database including PubMed, Embase (Ovid version), Medline (Ovid version), and Cochrane Central Register of Controlled Trials (till February 2021). The keywords were described as artificial urinary sphincter and sling and urinary incontinence.The articles were eligible if they contained the comparison of AUS and slings for the treatment of moderate male SUI in patients above 18 years old. As not all studies reported 24 h pad test results, we discussed and decided that the degree of moderate male SUI was defined as overall pad use ≤ 5 pad/d. The mean overall follow-up for both AUS and slings groups was required to be at least 12 months. Cohort study, case-controlled study, and randomized controlled study were all included. Reviews, guidelines, systematic reviews, and meta-analyses were excluded. Conference articles, editorial comments, protocols, and cases involved with pediatric patients were also excluded. The article language was restricted to English, and the articles with inadequate follow-up of <12 months in either the AUS group or slings group were excluded.The primary outcome was surgical success defined as daily pad use of 0–1 pad/d postoperatively. The articles with congruent outcomes reporting were suitable for inclusion, for example, some articles described success as ≤ 1 pad/d postoperatively for patients requiring ≥2 pad/d preoperatively, and 0 pad/d for those requiring 1 pad/d preoperatively . The secWe screened the title and abstract to identify eligible references, and then assessed the full text to determine the ultimate selection for qualitative and quantitative analysis. A discrepancy was carefully discussed and resolved when met.Based on the literature available online, our team determined to collect data as follows: first author, years of publication, country, study design, patients' selection, outcome definition, number of cases for each group, mean age for each group, mean preoperative and postoperative pad used daily for each group, mean follow-up time for each group, success rate for each group, and complication rate for each group. For the articles reporting median data, we tried to convert them to mean data as possible as we could to retain the accuracy of raw data, in accordance with feasible methods , 19.We assessed the risk of bias for articles eligible in the final meta-analysis, which was modified from the Newcastle-Ottawa Quality Assessment Scale (NOS), including representativeness of the cohort, ascertainment of intervention, documentation that outcome of interest was not present at the start of the study, comparability of cohorts on the basis of the design or analysis, assessment of outcomes, follow-up long enough for outcomes to occur, and adequacy of follow-up of cohorts. After reviewing the full-text carefully, low risk of bias, high risk of bias, and unclear risk of bias were applied to each eligible article according to stated information. All the procedure was completed on RevMan 5.3 .2 and I2-tests. Chi2 test with P > 0.10 and I2 <50% were thought to have acceptable heterogeneity. If so, it was reliable to utilize a fixed-effect model for meta-analysis and there was no need to exert a subgroup or sensitivity analysis. Otherwise, we would use a random effect model. As for the overall effect, the Z-test was used to certify the statistical significance, which was defined as P < 0.05. The results were presented as a forest plot.The meta-analysis was operated on RevMan 5.3 , with an odds ratio (OR) using Mantel-Haenszel statistical method for dichotomous data. The pooled results were reported as OR with 95% CI. The heterogeneity test was completed by ChiThe publication bias was evaluated through a funnel plot using RevMan 5.3 . Ideal results were presented as symmetrical spots distribution along the central axis.Initially, 909 articles were included after we searched the designated databases. Considering the inclusion and exclusion criteria for the study, 520 articles were screened and 303 full-texts were assessed carefully for eligibility. Finally, 5 eligible articles were selected in meta-analysis , 15. TheFive studies with a total of 509 patients (295 for slings and 214 for AUS) were recruited. Two were in Korea, 1 in the USA, and the other countries were Canada and Italy. The included patients' criteria varied slightly among studies. Four presented with moderate SUI and the other one included postprostatectomy incontinence with a mean pad use of 4.8 per day. Surgical success definition and other detailed information were illustrated in The risk of bias explanation was detailed in P-value for the overall effect was far lower than 0.05, indicating that the model was authenticated. As for the heterogeneity I2 =32%, we considered a fixed model was appropriate and there was no need to conduct subgroup analysis or sensitivity analysis. The Forest plot was shown in The success rate yielded a statistically significant outcome in a fixed-model analysis, with pooled OR of 0.57 (95% CI: 0.36–0.90). Heterogeneity was permissible and P = 0.86) with acceptable heterogeneity. The subgroup analysis for specific complication types were detailed in Among the 5 included articles, one had not made clear what kind of complication happened in both the slings and AUS groups. As we only included the above-mentioned complication of infection, erosion, and acute urinary retention, finally 4 articles were included in further analysis, which was depicted in The publication bias was shown in the funnel plot . RoughlyIn this study, we discovered that the success rate of AUS was significantly higher than that of slings, while the overall complication rate was comparable between the two groups. Considering the gold standard of AUS, we repeatedly certified its role in the treatment of moderate male SUI with appreciable success rate and acceptable complication.Artificial urinary sphincter, after over 30 years of introduction, has shown pronounced results based on the long period of experience and a great deal of evidence . HoweverSeveral articles have also explored the effect of slings and AUS on the treatment of male SUI. Chen YC evaluated the efficacy of male slings and AUS for postprostatectomy SUI, focusing on daily pad use, cure rate, and so on . It is fRecently, an article came out and published its outcomes in a randomized control design (MASTER) . It enroTo our acknowledgment, this is the first meta-analysis to directly compare the efficacy of slings vs. AUS based on daily pad use and complication including infection, erosion, acute urinary retention, and surgical revision. We drew a conclusion that, after integrating all available evidence, AUS turned out to show a considerable success rate without increasing complication rate significantly. The funnel plot did not show obvious publication bias, although the number of eligible studies was small. Still, from the available pieces of evidence, we believed the results illustrated a trend that AUS had a priority over slings in the clinical practice of treating moderate male SUI.Among the 5 included studies, we discovered that one article had the risk of baseline comparability, which was because of mean overall daily pad use close to 5 pads/d, which is a generally accepted boundary between moderate and severe SUI. We considered a mean follow-up time of 12 months would be appropriate to observe the mid-term outcomes of AUS and slings procedures. In addition, as there were varieties of sling types, we described the specific name of sling types, including two articles utilizing adjustable slings. We did not think readjustment was a complication for adjustable slings because it was easy to handle and patients usually had good compliance. Hence, we only included complications mentioned above, which were common for both AUS and slings.P = 0.046)  . Angelis= 0.046) . The sliIt is of great regret that our meta-analysis only included cohort studies and lacked evidence of randomized controlled studies. We tried to assess all the eligible studies with the tool of NOS, which was standardized and widely used for non-randomized controlled studies. The assessment outcomes showed that most articles were well-designed and had little risk of bias. The included patients in each study differed slightly, some based on moderate daily pad use , 14, 15,To conclude, AUS was better than slings in moderate male SUI with an acceptable complication rate in our study. The slings also had clinical value and were options when aging male patients were AUS naive and refused inserted mechanical devices. More evidence with higher quality is needed to confirm the efficacy of AUS and slings in moderate male SUI.The original contributions presented in the study are included in the article/LL, WS, and XG: conception and design of the study and acquisition of data. LL: data analysis and/or interpretation. LL and LZ: drafting of the manuscript and/or critical revision. LZ: approval of a final version of manuscript. All authors contributed to the article and approved the submitted version.The work was supported by the 1.3.5 project for disciplines of excellence, West China Hospital, Sichuan University (ZY2016104).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.All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.


Interestingly, the spring phenology is the main VF in the humid region for runoffs reduction, while both spring and autumn growth phenology are the main VFs in the semi-humid region, because large autumn phenology delay and less water supply capacity in spring amplify the effect of advanced spring phenology. This article reveals diverse linkages between climatic and VFs, and runoff in different hydroclimatic regions, and provides insights that vegetation phenology influences the ecohydrology process largely depending on the local hydroclimatic conditions, which improve our understanding of terrestrial hydrological responses to climate change.Climate warming has changed vegetation phenology, and the phenology-associated impacts on terrestrial water fluxes remain largely unquantified. The impacts are linked to plant adjustments and responses to climate change and can be different in different hydroclimatic regions. Based on remote sensing data and observed river runoff of hydrological station from six river basins across a hydroclimatic gradient from northeast to southwest in China, the relative contributions of the vegetation , and gross primary productivity) and climatic factors affecting the river runoffs over 1982–2015 were investigated by applying gray relational analysis (GRA). We found that the average GSLs in humid regions (190–241 days) were longer than that in semi-humid regions (186–192 days), and the average GSLs were consistently extended by 4.8–13.9 days in 1982–2015 period in six river basins. The extensions were mainly linked to the delayed autumn phenology in the humid regions and to advanced spring phenology in the semi-humid regions. Across all river basins, the GRA results showed that precipitation ( Climate warming has substantially extended the length of vegetation growing period in temperate and boreal zones  and sequ2 concentration  determine the river runoffs and the vegetation factors (VFs), especially the vegetation phenology, is also affected the river runoffs, but its relative importance is climatic region-dependent. The relative contributions of the VFs  and CFs affecting river runoff across a hydroclimatic gradient were quantified by applying the gray relational analysis (GRA). The aim of this study was to (1) analyze the temporal–spatial changes in both phenology and river runoffs across hydroclimatic gradient river basins; (2) quantify potential influences of climatic and VFs on river runoff; and (3) explore the differences between humid and semi-humid regions in primary factors impacting river runoff.Six river basins were selected across a hydroclimatic gradient, i.e., Wu and Hailaer river basins, changing from subtropical in the south to the cool temperature zones in the north of China . Accordi1 (2 (3 The phenology data including start of growing season (SOS) and end of growing season (EOS) with the 0.05° × 0.05° spatial resolution were provided by the Vegetation Index and Phenology Lab, The University of Arizona, in 20114   using MATLAB 2020a (MathWorks).The meteorological data, including daily precipitation, temperature, relative humidity, wind speed, and radiation with 0.1° × 0.1° spatial resolution from 1982 to 2015, were provided by the China Meteorological Forcing Dataset and were produced by the Institute of Tibetan Plateau Research, Chinese Academy of Sciences1 . The mea1 (2 . Gross pin 20114 . Start o (GLEAM) . The mon (GLEAM) . The lanLinear regression analysis was used to analyze the temporal changes of phenological dates, i.e., the spring growth onset (SOS), the end of vegetation growth (EOS), and the GSL over the study period 1982–2015. The vegetation productivity during growing season (GPP_GS) was defined at the mean values of GPP between SOS and EOS. The temporal changes in climatic variables, i.e., temperature, precipitation, and runoff, were also estimated using linear regression. Due to the large differences in the basin size and also in the discharge magnitudes of the six basins, normalization, which we defined the runoff in the first year  as the standard and calculated the proportion of change of other years in each river basin, was applied to the data before analyzing and comparing the temporal trends in runoff among the six river basins. And we applied min–max normalization to factors with different units when comparing the variation of runoff, GSL_GS, and GSL.To explore the difference in temporal dynamics of the runoff between humid and semi-humid regions, we applied the analysis of covariance (ANCOVA) to the runoff depth (ratio of runoff to watershed area) of humid and semi-humid river basins, following the previous study . All staTo compare the relative importance of phenology, vegetation growth, and climate variables on the runoff, we applied the GRA, which was widely used in complex inter-relationships among the multiple performance characteristics by quantifying the gray relational grades . The GRAThe reference sequence, i.e., runoffs in this study, is expressed as:x0 stands for reference sequence, and n indicates the number of records.where m sequences to be compared as:We denote the xi represents the ith sequence to be compared and m is the total number of sequences to be compared.where We normalized the sequences to ensure that all of them are in the same order, and the normalized sequences can be denoted by:ith normalized sequence to be compared, and m is the total number of sequences to be compared.where xi, and the reference sequence, x0, for the jth record, , is defined as:The gray relational coefficient between the compared sequence, where Then, the gray relational grade is derived as:i is the gray relational grade for the ith factor and n is the number of records (years).where εA larger gray correlation coefficient means a stronger correlation between the reference sequence and explanatory factor. We applied the GRA at each river basin and estimated the mean GRA coefficients across six basins for each impact factor. The reference sequence is river runoff, and the impact factors include CFs, i.e., precipitation, air temperature, soil moisture (SMroot), ET and radiation, and VFs, i.e., SOS, EOS, GSL, and GPP_GS.During 1982–2015, the MAT of all the river basins increased significantly except the Hailaer river basin. The increment in Wei river basin , Fen river basin , and Han river basin  is larger than the rest of the basins . The MAPP < 0.10, which is a confidence level close to significance) from 1982 to 2015, except for the Fen river basin (P = 0.65) (P < 0.05), and the relatively reduced magnitudes were significantly larger in semi-humid river basins  than in humid basins (0.01 per year)    . Across Among the six basins, the largest annual ET is in the Han river basin (859 mm), and the smallest is in the Hailaer river basin (399 mm). The spatial patterns of ET in the six basins are similar to that of GPP , and ET is relatively larger in the region  with a h2 day) and 4.34 gC/(m2 day), respectively] than that in semi-humid regions   across all six river basins. The increase rates in GPP were reduced from humid to semi-humid river basins, and the largest increase rates of GPP were found in the Wei river basin with an average rate at 3.11 × 10 –2 gC/(m2 day year), and the increasing GPP accounts for 93.5% of the total basin area.The annual GPP showed less spatial variability in the humid regions [Wu and Han river basins with mean GPP = 3.86 gC/(mThe longest vegetation GSL (234 days) with the earliest SOS [day of the year (DOY) = 102] and the latest EOS (DOY = 336) was found in the Wu river basin, followed by the Han river basin. The vegetation growing season in humid river basins is longer than in semi-humid river basins. The shortest GSL was found in the Luan river basin with the latest SOS (DOY = 119) and almost earliest EOS (DOY = 305) . Spatialr = 0.59), SOS (r = 0.65), EOS (r = 0.59), and GSL (r = 0.61), on runoffs is larger than temperature (r = 0.56) and radiation (r = 0.59) , while GPP_GS (except the Hailaer river basin) and GSL showed an increase and delay trend during 1982–2015, respectively , 6. The  = 0.59) .r = 0.82, and the SMroot is the dominant factor in semi-humid river basins (r = 0.72). The third important factor is the SOS for both humid and semi-humid river basins with average r = 0.68 and 0.63, respectively. For the VFs, we found that the spring phenology SOS (r = 0.65) largely impacted the runoff in humid river basins, but the autumn phenology EOS (r = 0.61) mainly impacted the runoff in semi-humid river basins. Overall, we found that the phenological factors impacted the runoffs as the secondary dominators, and the spring phenology mainly impacted the humid regions, but both the spring and autumn phenology mainly impacted the semi-humid regions.We further estimated the mean GRA coefficients of each climate and VF for humid and semi-humid river basins , 8. ConsClimate warming promotes vegetation growth, as long as water and nutrients are not limited . The larWe found decreasing trend of runoff across all six river basins in China, which is in line with previous studies . The reaAlthough precipitation was the most important factor affecting river runoff in both humid and semi-humid regions, we found that the impacts of vegetation phenology on runoff can also be seen, and the impacts were different between humid and semi-humid regions. In detail, spring phenology mainly affected the runoff in humid river basins, but both spring and autumn phenology affected the runoff in semi-humid river basins. The larger values of GPP_GS are associated with larger water loss (ET) . In the The observed runoff data were obtained from the hydrological stations; although we selected river basins to try to avoid human activities effects (land-use change), differences between observed runoff and natural runoff (the effect of land-use change) are difficult to rule out; however, during 1980–2015, the change of land use in the study basins was small, and the proportion of various land uses remained basically unchanged . We assuIn this study, six river basins in the humid and semi-humid regions in China were selected to analyze the temporal changes in runoff and vegetation dynamics during 1982–2015. We found that the observed runoff decreased in all basins, and the decrease in semi-humid area was larger than that in the humid area. The vegetation in all basins showed a greening trend, with a larger increase in the humid area than that in the semi-humid area, and the length of the growing season has also increased (1.4–4.1 days per decade). In the humid region, the extension of the growing season was mainly due to the delayed autumn phenology, while in the semi-humid region, the extension of the growing season was mainly due to the advanced spring phenology. The GRA results suggested that precipitation and soil moisture content are the dominant factors affecting runoff in both humid and semi-humid river basins, but VFs (GPP in growing season and phenology) are the secondly important factors, similar to or larger than ET, which are highly associated with plant factors, larger than temperature. Meanwhile, the impacts of phenology factors on runoff were different across different hydroclimatic zones. The spring phenology is the main VF in the humid region, while spring and autumn phenology are the main VFs in the semi-humid region. Overall, this study revealed the potential influences of climatic and VFs on river runoff in different hydroclimatic regions, which provide insights into hydrological processes between humid and semi-humid regions.The original contributions presented in the study are included in the article/YF: conceptualization, writing—reviewing and editing, project administration, and funding acquisition. FH: conceptualization. SC: methodology, software, formal analysis, resources, and writing—original draft preparation. XZ, ZX, and ZH: validation. XG: investigation. JT: data curation, visualization, and supervision. All authors have read and agreed to the published version of this 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.All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.