Accurate assessments of symptoms and diagnoses are essential for health research and clinical practice but face many challenges. The absence of a single error-free measure is currently addressed by assessment methods involving experts reviewing several sources of information to achieve a more accurate or best-estimate assessment. Three bodies of work spanning medicine, psychiatry, and psychology propose similar assessment methods: The Expert Panel, the Best-Estimate Diagnosis, and the Longitudinal Expert All Data (LEAD). However, the quality of such best-estimate assessments is typically very difficult to evaluate due to poor reporting of the assessment methods and when it is reported, the reporting quality varies substantially. Here we tackle this gap by developing reporting guidelines for such studies, using a four-stage approach: 1) drafting reporting standards accompanied by rationales and empirical evidence, which were further developed with a patient organization for depression, 2) incorporating expert feedback through a two-round Delphi procedure, 3) refining the guideline based on an expert consensus meeting, and 4) testing the guideline by i) having two researchers test it and ii) using it to examine the extent previously published articles report the standards. The last step also demonstrates the need for the guideline: 18 to 58% (Mean = 33%) of the standards were not reported across fifteen randomly selected studies. The LEADING guideline comprises 20 reporting standards related to four groups: The Longitudinal design; the Appropriate data; the Evaluation – experts, materials, and procedures; and the Validity group. We hope that the LEADING guideline will be useful in assisting researchers in planning, reporting, and evaluating research aiming to achieve best-estimate assessments.

All authors have completed the ICMJE uniform disclosure form and declare: V C Eijsbroek, K Kjell, and O Kjell received funding from FORTE (2022-01022); and H A Schwartz from the National Institutes of Health (Grant R01 AA028032-01); O Kjell and K Kjell have co-founded and hold shares in a start-up using computational language assessments to diagnose mental health problems based on best-estimate assessments; J R Boehnke is as editor part of the International Society for Quality of Life Research and the Springer Nature Group; no other relationships or activities that could appear to have influenced the submitted work.

V C Eijsbroek, K Kjell, and O Kjell received funding from FORTE (2022-01022); and H A Schwartz from the National Institutes of Health (Grant R01 AA028032-01).

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The details of the IRB/oversight body that provided approval or exemption for the research described are given below:

Swedish law (2003:460) and the Swedish Ethical Review Authority state that only research that includes i) collecting personal information, and/or ii) that involves 'obvious' (uppenbar) risk for physical or psychological harm, or iii) involves manipulating or deceiving individuals, should undergo an external ethical review. Considering that the current research involves asking participants to rate and comment on the reporting recommendations, this research does not fall within these criteria. The individual open-ended comments and closed-ended ratings in the open material are anonymized. The closed-ended ratings per reporting standard in the Supplementary Material are presented on group level. The study is deemed exempt from requiring ethical approval according to Swedish Law (see 3-4 of the Act [2003:460] on ethical review of research involving humans in Sweden). Hence the research should not be reviewed by the Swedish Ethical Review Authority. More information can be found at the Swedish Ethical Review Authority (https://etikprovningsmyndigheten.se/).

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