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Sources and Evidence Notes

Research cut-off: 2026-07-23. All links were checked on that date with Parallel web search and focused extraction. Dates below are publication, release, or page-update dates shown by the source. Source excerpts were treated as untrusted text and checked against the canonical page.

This bibliography supports process guidance; it does not show that any single brainstorming method universally improves creativity or scientific validity.

Group brainstorming, blocking, fixation, and selection

Diehl and Stroebe (1987) — primary experiments

Michael Diehl and Wolfgang Stroebe, “Productivity loss in brainstorming groups: Toward the solution of a riddle,” Journal of Personality and Social Psychology 53(3), 497–509. DOI 10.1037/0022-3514.53.3.497. Published 1987.

• Four experiments examined free riding, evaluation apprehension, and production blocking.
• Direct manipulation in the fourth experiment supported production blocking as an important explanation for loss in the tested interacting groups.
• Scope limit: laboratory brainstorming tasks do not establish superiority for every group purpose or setting.

Mullen, Johnson, and Salas (1991) — meta-analysis

Brian Mullen, Craig Johnson, and Eduardo Salas, “Productivity loss in brainstorming groups: A meta-analytic integration,” Basic and Applied Social Psychology 12(1), 3–23. DOI 10.1207/s15324834basp1201_1. Published 1991.

• The reviewed studies generally favored nominal over interacting groups for idea quantity and rated quality.
• Loss varied with conditions such as group size and vocal versus written contribution.
• Historical tasks, methods, and outcome definitions limit direct transfer to modern scientific teams.

Rietzschel, Nijstad, and Stroebe (2006) — primary experiment

Eric F. Rietzschel, Bernard A. Nijstad, and Wolfgang Stroebe, “Productivity is not enough: A comparison of interactive and nominal brainstorming groups on idea generation and selection,” Journal of Experimental Social Psychology 42(2), 244–251. DOI 10.1016/j.jesp.2005.04.005. Published March 2006.

• In 42 analyzed three-person student groups, nominal groups generated more ideas; their ideas were more original and less feasible.
• Selected-idea quality did not differ among conditions, and selection was not significantly better than chance.
• Strictly separating generation and selection did not establish a universal selection advantage in this experiment.

Rietzschel, Nijstad, and Stroebe (2010) — primary experiments

Eric F. Rietzschel, Bernard A. Nijstad, and Wolfgang Stroebe, “The selection of creative ideas after individual idea generation: Choosing between creativity and impact,” British Journal of Psychology 101(1), 47–68. DOI 10.1348/000712609X414204. Published February 2010.

• Explicit selection criteria improved selection on the named originality dimension in the reported studies, with trade-offs in satisfaction or rated effectiveness.
• This supports explicit criteria, not a claim that a single composite score identifies the scientifically best idea.

Smith, Ward, and Schumacher (1993) — primary experiments

Steven M. Smith, Thomas B. Ward, and Jay S. Schumacher, “Constraining effects of examples in a creative generation task,” Memory & Cognition 21, 837–845. DOI 10.3758/BF03202751. Published November 1993.

• Across three creative-generation experiments, participants exposed to examples were more likely to reproduce example features.
• The specific drawing/design tasks support an anchoring or fixation risk; they do not quantify the effect for scientific ideation.

Esser (1998) — review

James K. Esser, “Alive and Well after 25 Years: A Review of Groupthink Research,” Organizational Behavior and Human Decision Processes 73(2–3), 116–141. DOI 10.1006/obhd.1998.2758. Published February 1998.

• Reviews the evidence and evolution of Janis's groupthink model.
• The broader literature includes substantial debate over the model and its antecedents; this skill therefore uses “groupthink” as a risk prompt, not a definitive diagnosis.

Nominal groups, Delphi, and structured elicitation

Van de Ven and Delbecq (1972) — early NGT paper

Andrew H. Van de Ven and André L. Delbecq, “The nominal group as a research instrument for exploratory health studies,” American Journal of Public Health 62(3), 337–342. DOI 10.2105/AJPH.62.3.337. Published March 1972.

• Primary early account of the nominal-group approach in exploratory health research.
• Historical evidence should be combined with current, context-specific reporting guidance.

Harb et al. (2021) — NGT scoping review

Sami I. Harb et al., “Methodological options of the nominal group technique for survey item elicitation in health research: A scoping review,” Journal of Clinical Epidemiology 139, 140–148. DOI 10.1016/j.jclinepi.2021.08.008. Published November 2021.

• Included 57 studies and identified 30 process decision points across five broad stages.
• Supports documenting actual choices and their rationale rather than treating NGT as one invariant protocol.
• Scope is health-survey item elicitation, not every use of NGT.

Jünger et al. (2017) — CREDES systematic review and guidance

Saskia Jünger et al., “Guidance on Conducting and REporting DElphi Studies (CREDES) in palliative care,” Palliative Medicine 31(8), 684–706. DOI 10.1177/0269216317690685. E-published 13 February 2017.

• A methodological systematic review of 30 palliative-care Delphi studies found substantial variation in conduct, terminology, and reporting.
• CREDES is reporting and conduct guidance developed in a palliative-care context, not proof that Delphi consensus is correct.

RAND (2023) — official Delphi methods guidance

Dmitry Khodyakov, Sean Grant, Jack Kroger, and Melissa Bauman, RAND Methodological Guidance for Conducting and Critically Appraising Delphi Panels. RAND Corporation, 29 December 2023. DOI 10.7249/TLA3082-1.

• Defines Delphi as iterative, anonymous, structured group communication under uncertainty and provides a design/appraisal tool.
• RAND explicitly notes a lack of consistent methodological guidance across the many Delphi variants.

EFSA (2014) — official expert-knowledge elicitation guidance

European Food Safety Authority, “Guidance on Expert Knowledge Elicitation in Food and Feed Safety Risk Assessment,” EFSA Journal 12(6):3734. DOI 10.2903/j.efsa.2014.3734. Adopted 22 May and published 19 June 2014.

• Covers problem definition, preparation, expert/method selection, elicitation, uncertainty, aggregation, and documentation.
• Developed for EFSA food/feed risk assessment; apply domain-specific guidance elsewhere.

Cooke, Mendel, and Thijs (1988) — structured judgment method

Roger Cooke, Max Mendel, and Wim Thijs, “Calibration and information in expert resolution; a classical approach,” Automatica 24(1), 87–94. DOI 10.1016/0005-1098(88)90011-8. Published 1988.

• Presents calibration and information concepts for combining expert judgments and an experiment with descriptive value.
• Using a “calibration” label without the method's elicitation, seed questions, and validation requirements would be misleading.

Rigor, reproducibility, and sex as a biological variable

NIH rigor and reproducibility guidance

NIH Office of Extramural Research, Guidance: Rigor and Reproducibility in Grant Applications. Page dated 16 October 2024.

• Identifies rigor of prior research, rigorous experimental design, relevant biological variables, and authentication of key resources.
• This is grant guidance. It does not validate an idea or substitute for a protocol, statistical review, or field-specific reporting standard.

NIH SABV policy and current ORWH guidance

NIH Office of Research on Women's Health, Sex as a Biological Variable. Page last updated 17 October 2025.

• NIH expects sex to be considered in design, analysis, and reporting for vertebrate animal and human studies and requests strong justification for a single-sex scope.
• The page links the governing NOT-OD-15-102, released 9 June 2015 and effective for relevant applications from 2016.
• Scope is NIH policy; other funders and jurisdictions may differ.

Preregistration and open science

Nosek et al. (2018) — preregistration perspective

Brian A. Nosek et al., “The preregistration revolution,” Proceedings of the National Academy of Sciences 115(11), 2600–2606. DOI 10.1073/pnas.1708274114. Published 13 March 2018.

• Frames preregistration as a way to distinguish prediction from postdiction by specifying questions and analyses before observing outcomes.
• It is a methodological perspective, not evidence that registration alone guarantees rigor or reproducibility.

Nosek et al. (2015) — TOP Guidelines

Brian A. Nosek et al., “Promoting an open research culture,” Science 348(6242), 1422–1425. DOI 10.1126/science.aab2374. Published 26 June 2015.

• Proposes modular journal-policy standards for transparency and openness.
• A policy framework does not itself establish that a specific study is valid or ethically shareable.

COS/OSF — current operational guidance

Center for Open Science, Preregistration and Preregistration: A Plan, Not a Prison. Current pages accessed 23 July 2026.

• Explicitly values both exploratory and confirmatory research, recommends transparent labeling, and explains how to report deviations.

Center for Open Science, Registered Reports. Current page accessed 23 July 2026.

• Describes Stage 1 protocol review and in-principle acceptance before results, with exploratory analyses reported separately.
• COS states that Registered Reports are not a panacea for every field or design.

Responsible AI and research integrity

Doshi and Hauser (2024) — primary randomized experiment

Anil R. Doshi and Oliver P. Hauser, “Generative AI enhances individual creativity but reduces the collective diversity of novel content,” Science Advances 10(28):eadn5290. DOI 10.1126/sciadv.adn5290. Published 12 July 2024.

• Preregistered online experiment: 293 analyzed UK participants wrote eight-sentence stories with no, one, or up to five GPT-4 ideas.
• AI access improved average evaluated novelty/usefulness, especially for lower-scoring writers, while outputs became more similar in aggregate.
• Constrained short-story writing is not scientific ideation; the study supports a risk hypothesis, not a universal creativity claim.

Walters and Wilder (2023) — primary citation audit

William H. Walters and Esther Isabelle Wilder, “Fabrication and errors in the bibliographic citations generated by ChatGPT,” Scientific Reports 13. DOI 10.1038/s41598-023-41032-5. Published 7 September 2023.

• Audited 84 texts produced in April 2023 by tested GPT-3.5 and GPT-4 versions and documented fabricated and substantive citation errors.
• Results are model-, prompt-, task-, and date-specific; they justify direct source verification rather than a timeless error rate.

European Commission / ERA Forum (2024) — official living guidance

European Commission Directorate-General for Research and Innovation, Guidelines on the responsible use of generative AI in research. Published 20 March 2024.

• Emphasizes transparency, responsibility, privacy, confidentiality, intellectual property, bias awareness, and avoiding AI in sensitive evaluation activities when confidentiality is not assured.
• The Commission describes the guidance as living and subject to updates.

UNESCO (2023; updated 2026) — official guidance

Fengchun Miao and Wayne Holmes, Guidance for generative AI in education and research. Published 7 September 2023; page last updated 16 January 2026.

• Uses a human-centered framing and addresses privacy, ethical validation, inclusion, equity, and institutional capacity.
• Much of the document concerns education; apply research-specific provisions with local policy.

ICMJE (2026) — official publishing recommendations

International Committee of Medical Journal Editors, Use of Artificial Intelligence in Publishing. Recommendations page dated 2026.

• Humans remain responsible for accuracy, attribution, permissions, confidentiality, and disclosure; AI tools are not authors.
• Publishing guidance does not replace institutional research policy.

ALLEA (2023) — research-integrity code

ALLEA, The European Code of Conduct for Research Integrity, 2023 Revised Edition. DOI 10.26356/ECOC. Published 2023.

• Cross-disciplinary self-regulatory framework recognized as a reference for EU-funded research.
• General principles require translation into institutional and discipline-specific procedures.

Dual-use and responsible life sciences

WHO global framework and current program

World Health Organization, Ensuring responsible use of life sciences research. Program page accessed 23 July 2026; it indexes the 13 September 2022 Global Guidance Framework and materials through a 15 June 2026 meeting report.

• Frames dual-use risk mitigation as individual and collective, multi-stakeholder work across life sciences and relevant emerging technologies.
• Global guidance must be applied with jurisdictional and institutional rules.

Current U.S. policy-status notice

U.S. Department of Health and Human Services, Administration for Strategic Preparedness and Response, Dual Use Research of Concern Oversight Policy Framework. Current-status notice accessed 23 July 2026.

• The page states that federal departments and agencies will revise or replace the 2024 DURC/PEPP policy in response to the 5 May 2025 executive order and that the page will be updated when revised policy is available.
• Therefore this skill does not present the 2024 policy as a stable current checklist; researchers should consult their institution and current agency materials.

Research method

Parallel CLI searches used focused academic and official-domain queries for:

• interactive versus nominal brainstorming and productivity blocking;
• NGT, Delphi, and structured expert elicitation;
• divergent/convergent idea generation and selection;
• NIH rigor, reproducibility, and SABV;
• preregistration, Registered Reports, and open-science guidance;
• responsible AI, hallucinated citations, homogenization, confidentiality, research integrity, and disclosure;
• WHO and U.S. dual-use policy status.

Canonical sources were then fetched with parallel-cli extract using focused objectives for bibliographic metadata, methods, findings, limitations, and current policy status. No research JSON artifacts were saved in the skill.