PSPB receives manuscript submissions through a web-based system called SageTrack. Authors should register with SageTrack and will be issued a login ID and password to access the system (including future manuscript submissions). Manuscripts can then be uploaded through an easy, step-by-step process. The SageTrack system also serves as the center for editorial staff to communicate with authors, editors, and reviewers electronically throughout the review process. If you need assistance, please contact Managing Editor, Supriya Bidola for further instructions.
SPSP recommends that authors read "Improving the Dependability of Research in Personality and Social Psychology" before submitting manuscripts to PSPB.
If you or your funder wishes your article to be freely available online to nonsubscribers immediately upon publication (gold open access), you can opt for it to be included in SAGE Choice, subject to payment of a publication fee. The manuscript submission and peer review procedure is unchanged. On acceptance of your article, you will be asked to let SAGE know directly if you are choosing SAGE Choice. To check journal eligibility and the publication fee, please visit SAGE Choice. For more information on open access options and compliance at SAGE, including self author archiving deposits (green open access) visit SAGE Publishing Policies on our Journal Author Gateway.
As of January 1, 2021 PSPB has adopted TOP Level II guidelines (https://www.cos.io/top). Some important changes to existing PSPB guidelines include:
- Authors must post the following in a trusted repository (see trusted repositories) and link to them in the manuscript.
- Analysis code
- Any data that is not already publicly accessible
- A codebook for interpreting the data file(s) describing all variables and how they are coded
- Authors need to state whether study and analysis plan pre-registration exists or not.
- Exceptions should be communicated to the Editor directly in the cover letter and acknowledged in the Author Note on the title page. If you think you might need to request an exception, please check this FAQ guide first for help navigating common challenges to data and code sharing.
Compliance with these policies is verified upon submission of manuscripts. Failure to comply with the policies will prevent submission and review.
Style: All manuscripts should follow the style guidelines set forth in the Publication Manual of the American Psychological Association, Seventh Edition (APA, 2020).
Citations: Please take care to give credit where credit is due. In addition to citing papers, please cite and list in the reference section all data sets, programs, analytic tools and apps, and code/packages (with version numbers) that are not original to the current manuscript. Whenever possible, include a persistent identifier, such as a Digital Object Identifier (DOI). For example, an author using the R package lsr would run the code [citation("lsr")] to find the appropriate citation information, cite the package in the manuscript text [e.g., “We used R package lsr (Version 0.5; Navarro, 2015)”], and include it in their reference section:
Navarro, D. J. (2015). Learning statistics with R: A tutorial for psychology students and other beginners (Version 0.5). Adelaide, Australia: University of Adelaide.
Length: Manuscripts must not exceed 10,000 words in length, including the abstract, references, figures, and notes. The word count must appear on the title page. Rare exceptions to this policy can be requested as part of the submission process (justified by the nature, number, or complexity of studies or methods reported, for example). Even in such cases, authors should avoid exceeding 10,000 words.
Abstract and keywords: The page following the title page must include an abstract of no more than 150 words, and below the abstract, 4-5 keywords.
Methods reporting and sharing: All manuscripts must include a report of the following items for each study:
- Explain how sample size was determined, including whether and how looking at the results influenced the collection of additional data. If sample size was determined ahead of time using a power analysis, please report the basis for the expected effect size and all information required to reproduce the power analysis.
- Report (1) the total number of excluded observations, (2) the reasons for making these exclusions, (3) how they were distributed across conditions.
- Disclose the existence of all variables and conditions that were part of the study. These can be summarized, or put in a footnote or supplementary material in the case of large numbers of variables, but there should be enough information for a reader to judge whether the variables and/or conditions are potentially theoretically relevant or not.
- State the above two disclosures in the text of the manuscript (e.g., “We report all manipulations, measures, and exclusions in these studies”).
- Report procedures in sufficient detail to allow close replication by an independent lab.
- All manuscripts should report complete statistics relevant to the analyses, using supplementary materials if needed:
- Cell means, SD, and n for experimental designs
- Correlations between variables for multivariate designs including regression and repeated-measures
- Inferential statistics with exact p-values (to 3 decimal places), effect sizes, and confidence intervals for effect sizes regardless of significance level
- If figures use error bars, these should be explained in a caption (e.g., standard error, 95% confidence interval, etc.)
- If meeting any of these requirements proves impractical, authors should explain why
Authors are required to post to a trusted public online repository all stimulus materials that are not already publicly accessible, including the verbatim wording of all independent and dependent variable instructions, manipulations, and measures. A link to the materials should appear in the text of the manuscript. Exceptions must be identified at article submission. (If the research was conducted in a language other than English, the materials file can provide the original materials and a rough translation into English that has been created using Google Translate or a similar free online program, as long as the manuscript itself provides sufficient detail for reviewers and readers to evaluate the presented research.)
Data sharing: Data (including all columns of data described anywhere in the manuscript) must be posted to trusted repository (see trusted repositories) and a link should appear in the manuscript. Exceptions must be identified at article submission. If you are using existing datasets that are already publicly accessible, please provide a link with appropriate citation (no need to upload separately). Data should ideally be in csv or a non-proprietary format. Ensure uploaded data are anonymous (e.g., make sure to remove potentially identifying information such as IP address, birthday, email address, name, latitude and longitude). Authors should also be cautious when posting rich datasets from identifiable subgroups and ensure that individuals cannot be identified based on “triangulating” across demographic variables such as age, gender, ethnicity, occupation, school, etc.
Codebook: Authors should provide a guide to interpreting the data file (sometimes called a data dictionary or codebook). The codebook should define (a) what every variable name in the data file means (how it connects to the variables in the materials file) and (b) how each variable is coded (e.g., 0 = failed attention check, 1 = passed attention check). Even if authors cannot share all columns of data described in the manuscript, describe them all in the codebook. Here are some examples of codebooks that accomplish these criteria, as illustrations: Project Implicit, Joel (2018).
Code sharing: Analysis code must be posted to a trusted repository and a link should appear in the manuscript. Exceptions must be identified at article submission. Authors must provide (commented/annotated) program code or syntax that demonstrates how data were analyzed or otherwise provide sufficient details to exactly reproduce all results in the manuscript.
Result reporting: Data-based submissions must:
- Report effect sizes and their confidence intervals for primary findings in each study.
- Address issues of sample size and consequent issues of power in each study or, in the case of multiple-study articles, in the context of evaluating the overall case for the reliability of the primary findings. Please do not report “observed” power for a test calculated using the effect size estimate from that same test.
Statistical power: Please report at least one power analysis for each study (see calculating and reporting power for guidance on selecting an appropriate power analysis and examples of how to write them up). Describe all information necessary for an independent researcher to reproduce the results of your power analysis, including the program you used, the specific test for which you were calculating power (e.g., was it one of the main effects, an interaction, or a follow-up pairwise comparison?), and all input values (e.g., effect size estimate, alpha, one-or-two-sided test, desired power, mean or median correlation among repeated measures).
Preregistration: Please indicate within the manuscript whether each of the following elements for each study was preregistered and (if yes) provide a link to the time-stamped preregistration:
- Study design (e.g. number of conditions, how key variables will be measured)
- Planned sample size or a pre-planned stopping rule
- Inclusion/exclusion criteria
- Planned analyses
Feel free to adapt the sample statements available here. If the answers to all questions are the same for all studies in the manuscript, you can include one overall statement for all studies. Any pre-registration form/template can be used, as long as they are publicly viewable in an independent registry that provides time-stamps and persistent links (options include: Aspredicted.org, clinicaltrials.gov, and OSF.io).
For preregistered planned analyses: Please include a statement in the main body of the manuscript confirming that you have (a) reported all pre-registered analyses in the main body of the manuscript, appendices, and/or supplemental materials and (b) clearly marked any deviations from the preregistered analysis plan in the main body of the paper.
Deviations from preregistration: Note any deviations from pre-registration in the main text of the manuscript and include reasons for the deviations. There are many reasons why deviations may occur (e.g., data extremely violating assumptions of pre-registered tests, unforeseen needed exclusions criteria) and deviations are not inherently problematic; they simply need to be clearly reported so that reviewers and readers have access to the information. If any pre-registered planned analyses are not included in the main manuscript, authors should make clear where those analyses do appear (e.g. in a specific appendix or supplement) or provide a rationale for not reporting the analyses at all.
Exploratory analyses: Unplanned analyses that are done in addition to pre-registered planned analysis do not need to be labelled as deviations, since they are supplementing the pre-registered analyses rather than replacing them. However, these analyses should be clearly marked as not being part of the pre-registered analyses.
Replication: PSPB will now consider manuscripts that directly (or closely) replicate the procedures of studies previously published at PSPB. Following other journals (e.g., Psychological Science and Journal of Research in Personality), the authors of a replication study must clearly articulate their rationale for conducting the replication and the interest value of it. Authors should inform the Editor that they are planning this replication-related work and this email should articulate the potential value of the contribution. Subsequently, the research will be evaluated in a two-stage sequence, the first of which involves an evaluation of the proposal (introduction plus methods and analysis plan) and the second of which involves an evaluation of the final product.
Double-blind review: PSPB conforms to a double-blind peer review process. Please ensure that supporting files are anonymized as much as possible. If using the OSF, authors can create a view-only link that will remove their names from the project by checking the “anonymize” option (see https://help.osf.io/hc/en-us/articles/360019930333-Create-a-View-only-Link-for-a-Project). If using AsPredicted, authors can create an anonymous PDF and include this URL in the paper for review purposes. In the manuscript itself, please remove self-citations when they can be used to identify any of the authors. Authors may substitute "Citation Blinded' in place of these identifying citations.
Ethical Practices Verification: Corresponding authors of submitted papers must verify that:
- The same or substantially similar manuscript has not been simultaneously submitted for consideration by another journal
- The same or substantially similar manuscript has not already been published in whole or part
- data collection complied with current APA Ethical Principles of Psychologists and Code of Conduct
See Resources page for Additional Guidance.
PSPB is sent free of charge to all members of SPSP. PSPB is published monthly by Sage Publications. Information about electronic and print subscriptions to PSPB for both institutions and individuals can be found here.