Estrés relacionado con el trabajo y sintomatología mental en personas trabajadoras: Un análisis de género / Work-related stress and mental symptoms in working people: A gender analysis

El objetivo fue analizar el estrés laboral de mujeres y hombres con empleo y categorías laborales y demográficas similares, estudiando su asociación con la sintomatología mental. Estudio exploratoriodescriptivo y transversal con una muestra de conveniencia formada por 2643 personas con empleo y edades entre 18 y 64 años de las cuales el 54.3% son hombres y el 45.7% mujeres. Todas fueron evaluadas mediante cinco autoinformes y una hoja de recogida de datos sociodemográficos y de usos del tiempo. Resultados: El 67.5% de los hombres y el 66.5% de las mujeres tuvo algún tipo de estrés relacionado con el trabajo, no existiendo diferencias entre mujeres y hombres en ninguna de las medidas de estrés laboral, en insatisfacción con el rol laboral, ni en la asociación entre el estrés laboral y la sintomatología mental, asociación que era muy baja en mujeres y en hombres. Las mujeres tenían más estrés crónico no laboral y mayores contrariedades diarias que los hombres, además de mayor sintomatología mental de ansiedad, depresión grave, somática y de disfunción social. Asimismo, dedicaban más tiempo a las tareas domésticas y de cuidado y menos al ocio y a las actividades físico-deportivas que los hombres. Conclusiones: los resultados evidenciaron que el rol laboral no supone amenazas específicas para la salud mental de las mujeres con empleo, aunque sí parecen suponerlas su mayor dedicación a las tareas domésticas y de cuidado. Los resultados del presente trabajo son relevantes para el diseño de políticas y programas destinados a fomentar la salud de la ciudadanía y al logro de mayor igualdad de género(AU)

The objective was to analyze work stress in women and men with similar occupation and demographic categories, studying its association with mental symptomatology. Exploratory-descriptive and cross-sectional study with a convenience sample of 2643 employed persons aged 18 to 64 years, 54.3% of whom were men and 45.7% women. All were assessed by five self-reports and a sociodemographic and time-use data collection sheet. Results: 67.5% of the men and 66.5% of the women had some type of work-related stress. There were no differences between women and men in any of the measures of work stress, in dissatisfaction with the work role, or in the association between work stress and mental symptomatology, association that was very low in both women and men. Women had more chronic non-work stress and greater daily hassles than men, as well as greater symptomatology of anxiety, severe depression, somatic and social dysfunction. In addition, they spent more time on housework and caregiving and less time on leisure and physical-sports activities than men. Conclusions: the results show that the work role does not pose specific threats to the mental health of working women, although their greater dedication to domestic and caregiving tasks does seem to do so. The results of this study are relevant for the design of policies and programs aimed at promoting the health of citizens and achieving greater gender equality(AU)

Update from the Clificol Project: Omicron in Hong-Kongand worldwide overview of the pandemic

The Clificol® COVID-19 Support Project is an innovative international data collection project aimed at documenting the presenting symptoms, use of homeopathy through the pandemic and tackling some of the core questions in homeopathy. The Covid-19 pandemic raised many questions and mobilised many resources. In order to make good use of resources, sound knowledge of the presenting complaints and demographics are required. In particular, we aimed to characterise the recent Omicron wave in Hong-Kong and to get an overall picture of the global pandemic as experienced by the homeopathic community. This online multi-national data-collection project is supported by the ECH, ECCH, ICH, HRI, LMHI, and other professional associations. The collected data includes demographic information, severity, conventional diagnosis and treatment, presenting symptoms as well as the remedies prescribed. The outcome of treatment was tracked using the ORIDL scale. More recently a 23-items prospective questionnaire was added to the input in order to gather targeted data about the presenting complaints. The recent wave of the Omicron variant in Hong-Kong, was analysed (N=372 cases) in terms of the symptomatology of this variant. The data from the 23-items questionnaire is compared to the longer questionnaire (150 items) used by the Hong-Kong team (21 practitioners). The most frequently reported common Clinical symptoms were extreme tiredness (60%), sore throat (46%), headache during fever (45%), dryness of mouth (37%), poor appetite (37%), runny nose (34%) and unusual muscle pains (31%).Also, the cases collected from around the world over the course of the pandemic (N=1300) were analysed, providing an overall picture of the pandemic and its specificities per country and over time. Clificol has shown and continues to show the value of data collection for the homeopathy community, providing important information for the management of future pandemics and opening new avenues for research in homeopathy.

Why we should monitor disparities in old-age mortality with the modal age at death.

Indicators based a fixed "old" age threshold have been widely used for assessing socioeconomic disparities in mortality at older ages. Interpretation of long-term trends and determinants of these indicators is challenging because mortality above a fixed age that in the past would have reflected old age deaths is today mixing premature and old-age mortality. We propose the modal (i.e., most frequent) age at death, M, an indicator increasingly recognized in aging research, but which has been infrequently used for monitoring mortality disparities at older ages. We use mortality and population exposure data by occupational class over the 1971-2017 period from Finnish register data. The modal age and life expectancy indicators are estimated from mortality rates smoothed with penalized B-splines. Over the 1971-2017 period, occupational class disparities in life expectancy at 65 and 75 widened while disparities in M remained relatively stable. The proportion of the group surviving to the modal age was constant across time and occupational class. In contrast, the proportion surviving to age 65 and 75 has roughly doubled since 1971 and showed strong occupational class differences. Increasing socioeconomic disparities in mortality based on fixed old age thresholds may be a feature of changing selection dynamics in a context of overall declining mortality. Unlike life expectancy at a selected fixed old age, M compares individuals with similar survival chances over time and across occupational classes. This property makes trends and differentials in M easier to interpret in countries where old-age survival has improved significantly.

The tension between ethics and rigor when using Amazon MTurk for eating disorder research: Response to commentaries on Burnette et al. (2021).

We respond to commentaries on our 2021 paper "Concerns and recommendations for using Amazon MTurk for eating disorder research." The commentators raised many thoughtful and nuanced points regarding data validity and ethical means of online data collection. We echo concerns about the ethics of recruiting via platforms such as MTurk, and highlight tensions between recommendations for ethical data collection and ensuring data integrity. Especially, we highlight the consistent finding that MTurk workers display elevated (often remarkably so) rates of psychopathology, and argue such findings merit further scrutiny to ensure both data are valid and workers not exploited.

Use of Real-World Data and Evidence in Drug Development of Medicinal Products Centrally Authorized in Europe in 2018-2019.

Real-world data/real-world evidence (RWD/RWE) are considered to have a great potential to complement, in some cases, replace the evidence generated through randomized controlled trials. By tradition, use of RWD/RWE in the postauthorization phase is well-known, whereas published evidence of use in the pre-authorization phase of medicines development is lacking. The primary aim of this study was to identify and quantify the role of potential use of RWD/RWE (RWE signatures) during the pre-authorization phase, as presented in the initial marketing authorization applications of new medicines centrally evaluated with a positive opinion in 2018-2019 (n = 111) by the European Medicines Agency (EMA). Data for the study was retrieved from the evaluation overviews of the European Public Assessment Reports (EPARs), which reflect the scientific conclusions of the assessment process and are accessible through the EMA website. RWE signatures were extracted into an RWE Data Matrix, including 11 categories divided over 5 stages of the drug development lifecycle. Nearly all EPARs included RWE signatures for the discovery (98.2%) and life-cycle management (100.0%). Half of them included RWE signatures for the full development phase (48.6%) and for supporting regulatory decisions at the registration (46.8%), whereas over a third (35.1%) included RWE signatures for the early development. RWE signatures were more often seen for orphan and conditionally approved medicines. Oncology, hematology, and anti-infectives stood out as therapeutic areas with most RWE signatures in their full development phase. The findings bring unprecedented insights about the vast use of RWD/RWE in drug development supporting the regulatory decision making.

[CAR-T CELLS: How does the EBMT registry monitor European activities, identify hurdles and prepare for changes in regulations]. / CAR-T cells : comment le registre de l'EBMT monitore les activités en Europe, identifie les contraintes et prépare l'évolution des régulations.

CAR-T Cells are gene therapy medicinal products, a subcategory of Advanced Therapy Medicinal Products as defined in the EC Regulation 1394/2007. They may represent the first example of such medicinal products that are industry-manufactured and commercialized on a large scale. Their very nature, their manufacturing processes, pricing and conditions upon which they were approved by regulatory agencies, all lead the latter to require long-term follow-up after marketing approval with a view for a better definition of CAR-T Cells safety profile and efficacy profile in real world conditions. Collection and analysis of data over a 15-year period of time represents a technical and political challenge. So does the a priori definition of data to be collected for a wealth of forthcoming analyses that focus on the interests of a variety of stakeholders. EBMT has been collecting and analyzing data on hematopoietic cell transplants for decades. EBMT currently works with many interested parties to collect data on patients treated with CAR-T Cells.

RECONSTRUCTION, VERIFICATION AND ANALYSIS OF RESULTS OF WBC MEASUREMENTS DATED 1986 THAT WERE INPUTTED TO ELECTRONIC DATABASE IN 2019-2021. / VIDNOVLENNIa, VERYFIKATsIIa TA ANALIZ REZUL'TATIV LVL/VYMIRIuVAN' 1986 R., ShchO VNESENI DO ELEKTRONNOÏ BAZY U 2019­2021 rr.

Objective of research is to improve the electronic database of WBC measurements dated 1986 by inputting of newinformation from paper carriers, reconstruction of information gaps, verification and analysis of new entered data,revision of internal exposure doses that are based on results of WBC measurements dated 1986. MATERIALS AND METHODS: In 2013-2015 during a revision of databases (DB) of WBC measurements results dated1986-2014, it was discovered a great amount of paper carriers with information about WBC measurements, includ-ing the ones dated 1986, that were not inputted to the electronic DB. The paper carriers were systematized andordered by the following indicators: place of residence of a person and place of WBC measurement, institution andoperator that made the measurement, measurement device and date of measurement. For a comfortable inputtingof the information to the electronic DB, it was additionally created a form which exists as an option in existing program complex Silbody (Version 19.0.9). In the revised DB of WBC measurements dated 1986 internal exposure dosesfrom radio-cesium of Chornobyl origin were computed based on an ecological and dosimetric model for radio-cesiummigration in environment and a model for radio-cesium metabolism in human body. In the work, mathematical andstatistical methods of research were used. RESULTS: In 2019-2021 additionally 35,319 notes were inputted to the electronic DB of WBC measurement dated1986, and as a result its volume increased in 2.2 times. Mostly those are data on results concerning residents of Kyiv,Zhytomyr, Donetsk, Cherkasy, Odessa, Ivano-Frankivsk, and Rivne Oblasts. It was established the information onmeasurement devices and respectively on the minimal detected activity (MDA) for 27,119 notes (76.7 % of all newentered). Information is reconstructed about the body mass of all persons under investigation. Evaluation is madefor values of intake of incorporated radionuclides 137Cs and 134Cs for all new entered to DB. Quality of reconstructedinformation was analyzed. To group 1, «qualitative¼, it was classified 18,598 notes (53 % of all new entered), measurements in 1986 (including new entered). Dose not exceeding 1 mSv was obtained by 80 % of adults (older than20), as well as 73 % of persons younger than 20. CONCLUSION: To DB of WBC measurements, it was additionally inputted 35,319 notes on results of measurementsdated 1986. New entered information is verified and distributed by the quality groups. Individual exposure dosesevaluated based on those data can be used for further scientific research.

Accuracy comparison study of new smartphone-based semen analyzer versus laboratory sperm quality analyzer.

PURPOSE: This study aimed to test the clinical efficacy of a portable smartphone-based App assisted semen analysis (SA) system, O'VIEW-M PRO® to clinically accurate in comparison with results of laboratory-based conventional semen analyses including manual microscopic and computer-assisted semen analysis (CASA) for self-evaluation of seminal parameters. MATERIALS AND METHODS: From January to May 2021, a total of 39 semen samples were analyzed for the sperm concentration and motility with new smartphone-based App assisted semen analyzer, O'VIEW-M PRO®, and results compared with those from laboratory-based manual microscopic SA with Makler Counting Chamber and CASA. RESULTS: The coefficient factors among the results of the measurement with Makler chamber and laboratory-based CASA comparing to O'VIEW-M PRO® were 0.666 and 0.655 for sperm density, 0.662 and 0.658 for sperm motility, respectively. There were no particular problems with clinical use of the O'VIEW-M PRO®. Device performance in classifying samples is positive (<15×106 sperm/mL) and negative (>15×106 sperm/mL) for sperm concentration criteria, and positive (<40%) and negative (>40%) for sperm motility criteria. The smartphone-based App assisted SA O'VIEW-M PRO® showed a sensitivity of 92.6%, a specificity of 66.7%, and overall accuracy rate of 84.6%. CONCLUSIONS: This study shows a novel smartphone-based App assisted SA system. O'VIEW-M PRO® can easily obtain semen parameter information through self-diagnosis at home and induce infertile men's treatment and help patients after receiving infertile men's treatment before receiving treatment.

Detection of overdose and underdose prescriptions-An unsupervised machine learning approach.

Overdose prescription errors sometimes cause serious life-threatening adverse drug events, while underdose errors lead to diminished therapeutic effects. Therefore, it is important to detect and prevent these errors. In the present study, we used the one-class support vector machine (OCSVM), one of the most common unsupervised machine learning algorithms for anomaly detection, to identify overdose and underdose prescriptions. We extracted prescription data from electronic health records in Kyushu University Hospital between January 1, 2014 and December 31, 2019. We constructed an OCSVM model for each of the 21 candidate drugs using three features: age, weight, and dose. Clinical overdose and underdose prescriptions, which were identified and rectified by pharmacists before administration, were collected. Synthetic overdose and underdose prescriptions were created using the maximum and minimum doses, defined by drug labels or the UpToDate database. We applied these prescription data to the OCSVM model and evaluated its detection performance. We also performed comparative analysis with other unsupervised outlier detection algorithms (local outlier factor, isolation forest, and robust covariance). Twenty-seven out of 31 clinical overdose and underdose prescriptions (87.1%) were detected as abnormal by the model. The constructed OCSVM models showed high performance for detecting synthetic overdose prescriptions (precision 0.986, recall 0.964, and F-measure 0.973) and synthetic underdose prescriptions (precision 0.980, recall 0.794, and F-measure 0.839). In comparative analysis, OCSVM showed the best performance. Our models detected the majority of clinical overdose and underdose prescriptions and demonstrated high performance in synthetic data analysis. OCSVM models, constructed using features such as age, weight, and dose, are useful for detecting overdose and underdose prescriptions.

Barriers and Facilitating Factors for Conducting Systematic Evidence Assessments in Academic Clinical Trials.

Importance: A systematic assessment of existing research should justify the conduct and inform the design of new clinical research but is often lacking. There is little research on the barriers to and factors facilitating systematic evidence assessments. Objective: To examine the practices and attitudes of Swiss stakeholders and international funders regarding conducting systematic evidence assessments in academic clinical trials. Design, Setting, and Participants: In this qualitative study, individual semistructured qualitative interviews were conducted between February and August 2020 with 48 Swiss stakeholder groups (27 primary investigators, 9 funders and sponsors, 6 clinical trial support organizations, and 6 ethics committee members) and between January and March 2021 with 9 international funders of clinical trials from North America and Europe with a reputation for requiring systematic evidence synthesis in applications for academic clinical trials. Main Outcomes and Measures: The main outcomes were practices and attitudes of Swiss stakeholders and international funders regarding conducting systematic evidence assessments in academic clinical trials. Interviews were analyzed using conventional content analysis. Results: Of the 57 participants, 40 (70.2%) were male. Participants universally acknowledged that a comprehensive understanding of the previous evidence is important but reported wide variation regarding how this should be achieved. Participants reported that the conduct of formal systematic reviews was currently not expected before most clinical trials, but most international funders reported expecting a systematic search for the existing evidence. Whereas time and resources were reported by all participants as barriers to conducting systematic reviews, the Swiss research ecosystem was reported not to be as supportive of a systematic approach compared with international settings. Conclusions and Relevance: In this qualitative study, Swiss stakeholders and international funders generally agreed that new clinical trials should be justified by a systematic evidence assessment but that barriers on individual, organizational, and political levels kept them from implementing it. More explicit requirements from funders appear to be needed to clarify the required level of comprehensiveness in summarizing existing evidence for different types of clinical trials.

An evidence mapping of systematic reviews and meta-analysis on traditional Chinese medicine for ulcerative colitis.

BACKGROUND: Traditional Chinese Medicine (TCM) has been a proposed treatment option for ulcerative colitis (UC), however it has been difficult to understand the breadth and depth of evidence as various Chinese medicine therapies may produce effects differently. The aim of this evidence mapping is to visually understand the available evidence in the use of TCM in the treatment of UC, and to identify gaps in evidence to inform priorities of future research. METHODS: A systematic electronic literature search of six databases were performed to identify systematic reviews (SRs) on different Chinese medicine therapies in the treatment in UC. Methodological quality of the included SRs was assessed using AMSTAR 2. RESULTS: The mapping was based on 73 SRs, which included nine interventions that met eligibility criteria. The quality of the included SRs was very low. The diseases stages of patients with UC varied greatly, from active to remission, to non-acute outbreak, to not reported. The results mostly favored the method of intervention. Oral administration combined with enema was the most widely used route of administration in secondary research. CONCLUSION: Based on the current evidence, the treatment of UC with TCM can only be recommended cautiously. A majority of included SRs did not report the location of the disease, the disease classification, and the route of administration of the intervention. Further research is needed on the effectiveness of Chinese medicine alone in the treatment of UC. The effectiveness of combined Chinese and conventional medicine combined with different routes of administration cannot be confirmed. Attention should be paid to the methodological quality of the systematic review. Unifies the outcome indicators used in the evaluation of effectiveness.

Discovering New Trends & Connections: Current Applications of Biomedical Text Mining.

The explosive growth of digital information in recent years has amplified the information overload experienced by today's health-care professionals. In particular, the wide variety of unstructured text makes it difficult for researchers to find meaningful data without spending a considerable amount of time reading. Text mining can be used to facilitate better discoverability and analysis, and aid researchers in identifying critical trends and connections. This column will introduce key text-mining terms, recent use cases of biomedical text mining, and current applications for this technology in medical libraries.

Measuring All-Cause Mortality With the Census Numident File.

OBJECTIVES: To assess the quality of population-level US mortality data in the US Census Bureau Numerical Identification file (Numident) and describe the details of the mortality information as well as the novel person-level linkages available when using the Census Numident. METHODS: We compared all-cause mortality in the Census Numident to published vital statistics from the Centers for Disease Control and Prevention. We provide detailed information on the linkage of the Census Numident to other Census Bureau survey, administrative, and economic data. RESULTS: Death counts in the Census Numident are similar to those from published mortality vital statistics. Yearly comparisons show that the Census Numident captures more deaths since 1997, and coverage is slightly lower going back in time. Weekly estimates show similar trends from both data sets. CONCLUSIONS: The Census Numident is a high-quality and timely source of data to study all-cause mortality. The Census Bureau makes available a vast and rich set of restricted-use, individual-level data linked to the Census Numident for researchers to use. PUBLIC HEALTH IMPLICATIONS: The Census Numident linked to data available from the Census Bureau provides infrastructure for doing evidence-based public health policy research on mortality.

ADL-dependent older adults were identified in medico-administrative databases.

OBJECTIVE: We aimed to develop an algorithm for the identification of basic Activities of Daily Living (ADL)-dependency in health insurance databases. STUDY DESIGN AND SETTING: We used the AMI (Aging Multidisciplinary Investigation) population-based cohort including both individual face-to-face assessment of ADL-dependency and merged health insurance data. The health insurance factors associated with ADL-dependency were identified using a LASSO logistic regression model in 1000 bootstrap samples. An external validation on a 1/97 representative sample of the French Health Insurance general population of Affiliates has been performed. RESULTS: Among 995 participants of the AMI cohort aged ≥ 65y, 114 (11.5%) were ADL-dependent according to neuropsychologists individual assessments. The final algorithm developed included: age, sex, four drug classes (dopaminergic antiparkinson drugs, antidepressants, antidiabetic agents, lipid modifying agents), three type of medical devices (medical bed, patient lifter, incontinence equipment), four medical acts (GP's consultations at home, daily and non-daily nursing at home, transport by ambulance) and four long-term diseases (stroke, heart failure, coronary heart disease, Alzheimer and other dementia). Applying this algorithm, the estimated prevalence of ADL-dependency was 12.3% in AMI and 9.5% in the validation sample. CONCLUSION: This study proposes a useful algorithm to identify ADL-dependency in the health insurance data.

Imputing intracluster correlation coefficients from a posterior predictive distribution is a feasible method of dealing with unit of analysis errors in a meta-analysis of cluster RCTs.

BACKGROUND: Incorporating cluster randomized trials (CRTs) into meta-analyses is challenging because appropriate standard errors of study estimates accounting for clustering are not always reported. Systematic reviews of CRTs often use a single constant external estimate of the intraclass correlation coefficient (ICC) to adjust study estimate standard errors and facilitate meta-analyses; an approach that fails to account for possible variation of ICCs among studies and the imprecision with which they are estimated. Using a large systematic review of the effects of diabetes quality improvement interventions, we investigated whether we could better account for ICC variation and uncertainty in meta-analyzed effect estimates by imputing missing ICCs from a posterior predictive distribution constructed from a database of relevant ICCs. METHODS: We constructed a dataset of ICC estimates from applicable studies. For outcomes with two or more available ICC estimates, we constructed posterior predictive ICC distributions in a Bayesian framework. For a selected continuous outcome, glycosylated hemoglobin (HbA1c), we compared the impact of incorporating a single constant ICC versus imputing ICCs drawn from the posterior predictive distribution when estimating the effect of intervention components on post treatment mean in a case study of diabetes quality improvement trials. RESULTS: Using internal and external ICC estimates, we were able to construct a database of 59 ICCs for 12 of the 13 review outcomes (range 1-10 per outcome) and estimate the posterior predictive ICC distribution for 11 review outcomes. Synthesized results were not markedly changed by our approach for HbA1c. CONCLUSION: Building posterior predictive distributions to impute missing ICCs is a feasible approach to facilitate principled meta-analyses of cluster randomized trials using prior data. Further work is needed to establish whether the application of these methods leads to improved review inferences for different reviews based on different factors (e.g., proportion of CRTs and CRTs with missing ICCs, different outcomes, variation and precision of ICCs).

COVID-19 in persons aged 70+ in an early affected German district: Risk factors, mortality and post-COVID care needs-A retrospective observational study of hospitalized and non-hospitalized patients.

BACKGROUND: Cohorts of hospitalized COVID-19 patients have been studied in several countries since the beginning of the pandemic. So far, there is no complete survey of older patients in a German district that includes both outpatients and inpatients. In this retrospective observational cohort study, we aimed to investigate risk factors, mortality, and functional outcomes of all patients with COVID-19 aged 70 and older living in the district of Tübingen in the southwest of Germany. METHODS: We retrospectively analysed all 256 patients who tested positive for SARS-CoV-2 in one of the earliest affected German districts during the first wave of the disease from February to April 2020. To ensure inclusion of all infected patients, we analysed reported data from the public health department as well as the results of a comprehensive screening intervention in all nursing homes of the district (n = 1169). Furthermore, we examined clinical data of all hospitalized patients with COVID-19 (n = 109). RESULTS: The all-cause mortality was 18%. Screening in nursing homes showed a point-prevalence of 4.6%. 39% of residents showed no COVID-specific symptoms according to the official definition at that time. The most important predictors of mortality were the need for inpatient treatment (odds ratio (OR): 3.95 [95%-confidence interval (CI): 2.00-7.86], p<0.001) and care needs before infection (non-hospitalized patients: OR: 3.79 [95%-CI: 1.01-14.27], p = 0.037, hospitalized patients: OR: 2.89 [95%-CI 1.21-6.92], p = 0.015). Newly emerged care needs were a relevant complication of COVID-19: 27% of previously self-sufficient patients who survived the disease were not able to return to their home environment after discharge from the hospital. CONCLUSION: Our findings demonstrate the importance of a differentiated view of risk groups and long-term effects within the older population. These findings should be included in the political and social debate during the ongoing pandemic to evaluate the true effect of COVID-19 on healthcare systems and individual functional status.

Resource use during systematic review production varies widely: a scoping review.

OBJECTIVE: We aimed to map the resource use during systematic review (SR) production and reasons why steps of the SR production are resource intensive to discover where the largest gain in improving efficiency might be possible. STUDY DESIGN AND SETTING: We conducted a scoping review. An information specialist searched multiple databases (e.g., Ovid MEDLINE, Scopus) and implemented citation-based and grey literature searching. We employed dual and independent screenings of records at the title/abstract and full-text levels and data extraction. RESULTS: We included 34 studies. Thirty-two reported on the resource use-mostly time; four described reasons why steps of the review process are resource intensive. Study selection, data extraction, and critical appraisal seem to be very resource intensive, while protocol development, literature search, or study retrieval take less time. Project management and administration required a large proportion of SR production time. Lack of experience, domain knowledge, use of collaborative and SR-tailored software, and good communication and management can be reasons why SR steps are resource intensive. CONCLUSION: Resource use during SR production varies widely. Areas with the largest resource use are administration and project management, study selection, data extraction, and critical appraisal of studies.