Psychological Safety in Medication Conversations

Psychological safety in medication conversations matters to clinicians, researchers, and patient-experience teams because it shapes whether patients speak up about side effects, errors, or preferences. The primary keyword for this post, psychological safety in medication conversations, describes environments where patients feel heard, respected, and able to ask questions. According to PLOS One (El-Kotob et al., 2026), 21 adults participated in interviews and focus groups between May and August 2024 to explore this topic; the study was published on August 20, 2026. This post refracts those findings through the lens of AI-enabled qualitative research and shows practical, reproducible ways teams can measure, visualize, and act on patient psychological-safety signals.

Key Takeaways

According to PLOS One (El-Kotob et al., 2026), patient psychological safety in medication conversations depends on feeling heard, receiving clear information, and being invited into decisions.

21 participants were interviewed or engaged in focus groups between May and August 2024, data later analyzed in a secondary deductive study published on August 20, 2026.
In the PLOS One sample, 19 of 21 participants were aged 40 or older, 14 identified as women, and 14 identified as White (El-Kotob et al., 2026).
Respectful listening reduced distress while dismissal or stigma increased mistrust; one participant reported, “I was disbelieved and dismissed” (participant P02, quoted in El-Kotob et al., 2026).
Clear, contextualized medication communication and invitations to participate improved patient engagement; a participant said, “I want to be a part of the decisions that are made about my care and my treatment including the medications I’m prescribed” (participant P03, quoted in El-Kotob et al., 2026).

What happened and how the study was done

Answer: El-Kotob et al. conducted a qualitative secondary analysis of interview and focus group data to explore patient psychological safety during medication conversations in Ontario, Canada.

According to PLOS One (El-Kotob et al., 2026), the research used the Patient Psychological Safety (PPS) framework with three constructs: Patient Belonging, Patient Learning, and Patient Participating.

According to El-Kotob et al. (2026), data collection occurred between 01/05/2024 and 31/08/2024 via semi-structured interviews and focus groups, sessions lasted up to 60 minutes, were audio-recorded, and transcribed for analysis.

According to El-Kotob et al. (2026), analysts coded transcripts into an Excel data-display matrix aligned with PPS constructs and used weekly consensus meetings to resolve differences.

Findings snapshot

Date	Metric	Value	Implication
May–Aug 2024	Data collection window	Interviews and focus groups (audio-recorded, up to 60 minutes)	Source data suitable for thematic and deductive PPS analysis
Aug 20, 2026	Publication date	PLOS One article (El-Kotob et al., 2026)	Findings are peer-reviewed and citable
Sample counts	Participant characteristics	n = 21 total; n = 19 aged ≥40; n = 14 women; n = 14 White	Limited demographic diversity; transferability requires caution
PPS constructs	Key themes	Belonging, Learning, Participating	Actionable domains for intervention design and evaluation

Implications for qualitative researchers and health teams

Answer: Researchers and health-system teams should center measurement on the PPS constructs (belonging, learning, and participation) when studying medication conversations.

According to PLOS One (El-Kotob et al., 2026), respectful listening and clear explanations improve psychological safety and may reduce medication-related distress; operationalizing those features makes them testable in implementation studies.

Qualitative researchers should note that El-Kotob et al. (2026) used purposive, convenience, and snowball sampling, and that the sample skewed older and White; researchers aiming to study equity impacts should oversample younger patients and underrepresented racial groups.

Health teams designing interventions should measure process outcomes such as whether clinicians invited patient input during medication decisions and whether patients report feeling heard, using mixed qualitative and brief patient-reported experience items.

How Evidano helps teams measure and act on psychological safety

Problem: Interviews and transcripts are rich but scattered → Solution: rapid thematic synthesis

Evidano is an AI-powered qualitative data analysis platform that helps researchers analyze interviews, open-ended surveys, and documents.

Evidano can ingest audio recordings and verbatim transcripts, auto-code to thematic frameworks like PPS, and produce content, frequency, and cross-segment analyses so teams can quantify how often issues like dismissal or stigma appear.

For teams that need transcription with domain vocabulary and PII redaction, Evidano supports accurate speech-to-text workflows and custom dictionaries via the speech-to-text feature.

Problem: Teams need to link themes to subgroups (age, race, medication type) → Solution: cross-segment analysis

Evidano’s cross-segment analysis helps replicate the PLOS One approach by combining demographic metadata (for example age ≥40) with coded excerpts to show which groups report lower psychological safety.

Evidano visualizations, such as hierarchical code trees and co-occurrence networks, let teams prioritize actionable themes (for example, repeated reports of being 'dismissed' in a subgroup) and prepare targeted clinician training.

Problem: Large projects need auditability and reproducibility → Solution: exportable matrices and traceable coding

Evidano preserves source excerpts and coding provenance so audit trails match qualitative standards like the Standards for Reporting Qualitative Research, enabling teams to reproduce the Excel display-matrix workflow used by El-Kotob et al. (2026).

For implementation studies, Evidano’s exportable tables and dashboards speed stakeholder reporting and integration with quantitative measures.

Try-it link

Learn more about relevant features on the Evidano features page.

FAQ: psychological safety in medication conversations

What is psychological safety in medication conversations?

Answer: Psychological safety in medication conversations means patients feel respected, able to ask questions, and safe to raise concerns without fear of judgment.

According to PLOS One (El-Kotob et al., 2026), the Patient Psychological Safety framework operationalizes this concept with three domains: belonging, learning, and participating.

How was the PLOS One study designed and what are its limits?

Answer: The PLOS One study used semi-structured interviews and focus groups collected May–Aug 2024 and analyzed deductively with the PPS framework.

According to El-Kotob et al. (2026), the study’s limitations include a small sample (n = 21) skewed toward older White women, which limits transferability to younger or more diverse populations.

Can AI help analyze qualitative data about psychological safety?

Answer: Yes, AI can accelerate coding, surface co-occurring themes, and quantify frequencies while preserving excerpt-level traceability for verification.

AI-enabled platforms can replicate the matrix-based deductive coding used in El-Kotob et al. (2026), and help teams test whether interventions change the frequency of themes like 'dismissal' or 'invitation to participate'.

How do I report counts and dates correctly when summarizing qualitative findings?

Answer: Always name the source and include absolute dates and counts in-sentence (for example, 'According to PLOS One (El-Kotob et al., 2026), n = 21 interviews were conducted between May and August 2024').

El-Kotob et al. (2026) demonstrate clear reporting by including sample counts (n = 21) and dates (May–August 2024) and by quoting participants with identifiers such as P02 or P03.

Conclusion & Next Steps

Respectful listening, clear medication information, and invitations to participate are key levers for improving psychological safety in medication conversations, according to PLOS One (El-Kotob et al., 2026).

Qualitative teams can reproduce the study’s matrix-based approach and scale it with AI to detect subgroup signals and track changes over time.

If you run qualitative studies, need accurate transcription, or want reproducible thematic and cross-segment analyses, consider a platform that supports audit trails and AI-assisted coding.

Get hands-on and see how Evidano supports these workflows: Try Evidano for free.

Topics

psychological safety in medication conversations
patient psychological safety
medication communication
qualitative analysis medications

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