1. SciScore for 10.1101/2021.07.16.21260200: (What is this?)

    Please note, not all rigor criteria are appropriate for all manuscripts.

    Table 1: Rigor

    Ethicsnot detected.
    Sex as a biological variablenot detected.
    Randomizationnot detected.
    Blindingnot detected.
    Power Analysisnot detected.

    Table 2: Resources

    Software and Algorithms
    The time series models were a) exponential smoothing state space models (ETS) [20], b) exponential smoothing state space models with screening for Box-Cox transformation, ARMA errors and trend and seasonal components (TBATS) [21] and c) additive models with non-linear trends fitted by seasonal effects (PROPHET) [22].
    suggested: (Prophet, RRID:SCR_017083)

    Results from OddPub: We did not detect open data. We also did not detect open code. Researchers are encouraged to share open data when possible (see Nature blog).

    Results from LimitationRecognizer: We detected the following sentences addressing limitations in the study:
    Strength and weaknesses: A strength of our study were the data of four years from nine hospitals representing about half of all inpatient psychiatric admissions in Hesse, Germany. This allowed both to give a representative picture of inpatient psychiatric care in Germany and to show how the forecasting approaches work at different study sites. Furthermore, it was possible to analyse the effect of sudden changes in hospital admissions to the performance of different modelling approaches due to the commencement of the Corona hospital regulation in March 2020. A limitation of our study was the lack of data to differentiate between causes of reduced hospital admissions after the corona regulation came into effect in March 2020. The reduced admissions could have been a result of different supply side and demand side effects, such as avoidance of elective admissions, reduced capacities due to isolation and quarantine requirements and unwillingness of patients to enter hospitals during the Corona crisis. Another limitation of our study was its restriction to one large German provider of inpatient mental health care, which requires a lot of care when translating to different healthcare systems or different clinical settings. C. Comparison to previous research: Previous studies often focused on emergency departments [26] and there were no previous studies that analysed forecasting of psychiatric hospital admissions comparable to our study in scale and scope. Vollmer et al 2021 predict...

    Results from TrialIdentifier: No clinical trial numbers were referenced.

    Results from Barzooka: We did not find any issues relating to the usage of bar graphs.

    Results from JetFighter: We did not find any issues relating to colormaps.

    Results from rtransparent:
    • Thank you for including a conflict of interest statement. Authors are encouraged to include this statement when submitting to a journal.
    • Thank you for including a funding statement. Authors are encouraged to include this statement when submitting to a journal.
    • No protocol registration statement was detected.

    Results from scite Reference Check: We found no unreliable references.

    About SciScore

    SciScore is an automated tool that is designed to assist expert reviewers by finding and presenting formulaic information scattered throughout a paper in a standard, easy to digest format. SciScore checks for the presence and correctness of RRIDs (research resource identifiers), and for rigor criteria such as sex and investigator blinding. For details on the theoretical underpinning of rigor criteria and the tools shown here, including references cited, please follow this link.

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