Other research transparency standards and disclosures for journal articles

⁠APA follows a contributorship rather than an authorship model, meaning that authors are not only those who do the writing but also those who have made substantial scientific contributions to a study.

See APA Ethics Code Standard 8.12a and the seventh edition of the Publication Manual:

Authorship is reserved for persons who make a substantial contribution to and who accept responsibility for a published work. Individuals should take authorship credit only for work they have performed or to which they have substantially contributed (APA Ethics Code Standard 8.12a, Publication Credit). Authorship encompasses, therefore, not only those who do the writing but also those who have made substantial scientific contributions to a study. Substantial professional contributions may include formulating the problem or hypothesis, structuring the experimental design, organizing and conducting the statistical analysis, or interpreting the results and findings. Those who so contribute are listed in the byline. Lesser contributions, which do not constitute authorship, may be acknowledged in the author note (see Section 2.7; see also a taxonomy of authorship in the natural sciences called at CRediT). Lesser contributions may include such supportive functions as designing or building the apparatus, suggesting or advising about the analysis, collecting or entering the data, modifying or structuring a computer program, recruiting participants, and obtaining animals. Conducting routine observations or diagnoses for use in studies does not constitute authorship. Combinations of these (and other) tasks, however, may justify authorship.

Some APA journals have adopted the Contributor Roles Taxonomy (CRediT)opens in new window to automate author contributions statements in their published articles. CRediT is a high-level taxonomy comprised of 14 roles that describe each author’s specific contribution(s) to the scholarly output. Authors can select more than one contributor role, and the same role can be attributed to more than one person.

The taxonomy also allows for a broader and more representative acknowledgment of the work of researchers who may otherwise not be represented or credited.

The seventh edition of APA’s Publication Manual instructs authors to provide funder and conflict-of-interest information in the author note. Authors should disclose even interests that could potentially be perceived as conflicts.

To add a further layer of transparency, many editors ask authors to provide a statement attesting that there is no potential perceived conflict of interest.

APA Style JARS recommend describing sample populations in detail, and many editors instruct authors to include this information, along with a discussion of the generalizability of findings, in the Method and/or Discussion sections of their articles, as well as in the abstract, where it is more easily found.

Constraints on Generality (COG) statements are meant to identify and justify target populations for reported findings—clarifying which aspects of a study should be preserved in a direct replication, noting characteristics contributing to the effect as well as characteristics they think were irrelevant. Authors use this section of the article to specify the target populations and constraints for not only participants but materials, procedures, and historical and temporal context and verify the completeness of the description by saying “we have no reason to believe that the results depend on other characteristics of the participants, materials, or context.”

In 2019, the National Academies of Science, Engineering, and Medicine formed the Committee on Reproducibility and Replicability in Science and drafted 10 recommendationsopens in new window, among which was a recommendation that a discussion of the expected constraints on generality, such as which methodological features the authors think could be varied without affecting the result and which must remain constant, be included.

The seventh edition of APA’s Publication Manual asks authors to disclose whether the manuscript is based on data also used in a previously published report or a doctoral dissertation and to acknowledge the publication of related reports in the author note. Some editors ask for this information to be provided with submitted manuscripts; others ask for formal data transparency statements describing how the research question and variables reported in the manuscript differ or do not differ from previous reports.

Positionality statements intend to address potential author bias by transparently reporting how the identities of the authors relate to the research/article topic and to the identity of the participants, as well as the extent to which those identities are represented in the scientific record. In their recent study on racial inequalities in psychological research, Roberts, et al. (2020)opens in new window advocated for the use of positionality statements as a means of transparently addressing potential bias, clarifying the authors’ social identities in relation to the target populations, and to encourage authors to collaborate with diverse teams and co-authors.

Some editors are asking authors for specific statistical reporting—and some ask authors to verify that they have included the information in a disclosure section.

Some examples of required reporting include:

• Sample size, power, and precision (including determination of sample size, including power analysis, or methods used to determine precision of parameter estimates, and explanation of any interim analyses and stopping rules employed).
• Full methods for empirical studies, including all manipulations, measures, and eventual data exclusions.
• All levels of all independent variables for all predictors or manipulations relevant to the target research question, whether successful or failed.
• All dependent variables or measures collected for the target research question.
• The total number of excluded observations and the reasons for making those exclusions.
• Exact p values, effect sizes, and 95% confidence intervals, or an explanation of why this was not possible.
• Indicators of clinically significant change for results of interventions.
• All decisions that were data-dependent (e.g., deciding when to stop data collection, what observations to exclude, what covariates to include, and what analyses to conduct after rather than before seeing the data).

Where these exist, these and other requirements are outlined in each journal’s instructions to authors.