Psychological safety in medication conversations is the patient experience of feeling heard, respected, and comfortable asking questions about medicines. Evidano is an AI-powered qualitative data analysis platform that helps researchers analyze interviews, open-ended surveys, and documents. This post summarizes a qualitative study that explored psychological safety during medication conversations and explains how AI-enabled qualitative research can turn interview quotes and themes into actionable recommendations. The primary keyword "psychological safety in medication conversations" appears throughout to help researchers and clinicians find practical analysis steps and examples from the PLoS One study.
Key Takeaways
According to the PLoS One study by El-Kotob et al. (published August 20, 2026), psychological safety during medication conversations depends on feeling heard, having clear medication information, and being invited to participate in decisions (PLoS One).
The PLoS One study identified barriers and facilitators to patient psychological safety that are directly observable in interview transcripts and can be coded for frequency, context, and co-occurrence using AI-assisted tools.
- Sample size and timing: the study included 21 participants who were interviewed between 01 May 2024 and 31 August 2024, as reported by El-Kotob et al. in PLoS One (2026).
- Demographics: in August 2026 the authors reported that most participants were aged 40 or older (n = 19), women (n = 14), and White (n = 14), which limits transferability to younger and racially diverse groups.
- Core finding: in PLoS One (published 20 August 2026) respectful communication, clear medication explanations, and invitation to participate were tied to increases in patient-reported psychological safety.
- Direct quote: El-Kotob et al. (PLoS One, 2026) included a participant voice: "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).
What happened: study design and measures
This section answers what the PLoS One study did and how psychological safety was measured: the authors conducted semi-structured interviews and focus groups with adults taking at least one medication for three months or more, as described by El-Kotob et al. in PLoS One (published August 20, 2026).
El-Kotob et al. used the Patient Psychological Safety (PPS) framework, which includes the constructs Patient Belonging, Patient Learning, and Patient Participating, to perform a secondary deductive content analysis of data collected between May and August 2024, according to PLoS One (2026).
The study sample included 21 participants, the majority aged 40 years or older (n = 19), with interviews conducted primarily one-on-one because of topic sensitivity, as reported in PLoS One (El-Kotob et al., 2026).
Data were audio-recorded, transcribed, and analyzed using a matrix aligned to PPS constructs; the authors reported that analysts met weekly to reach consensus on coding decisions, according to El-Kotob et al. in PLoS One (2026).
Findings snapshot
| Date | Metric | Value | Implication |
|---|---|---|---|
| 20 Aug 2026 | Publication | PLoS One | Open-access qualitative study applying the PPS framework to medication conversations |
| 01 May–31 Aug 2024 | Data collection period | Interviews and focus groups | Transcripts available for thematic coding and secondary analysis |
| 2026 (reporting) | Sample size | 21 participants | Sufficient for in-depth qualitative insights but limited demographic spread |
| 2026 (reporting) | Age distribution | n = 19 aged 40+ | Findings skew toward older adult experiences |
| 2026 (reporting) | Gender and race | n = 14 women, n = 14 White | Signals need for targeted sampling in future research |
Implications for qualitative researchers and clinicians
This section answers what researchers and clinicians should do differently after reading the PLoS One study: prioritize coding for power, dismissal, clarity, and invitation to participate when analyzing medication encounter transcripts, because El-Kotob et al. (PLoS One, 2026) linked these features to psychological safety.
Researchers should report participant counts and collection dates explicitly, as El-Kotob et al. did (data collected May–August 2024, published August 20, 2026), so readers can judge transferability.
Clinicians and implementation teams should test brief interventions that increase invitation language and clear medication explanations, because the PLoS One study found that patients who were explicitly invited to participate reported greater engagement and trust.
Ethics note: this blog summarizes peer-reviewed qualitative findings for research and quality improvement purposes and is not clinical guidance or diagnostic advice.
How Evidano Helps: from quotes to actionable recommendations
Problem: manually synthesizing 21 interviews is slow and inconsistent
Solution: Evidano is an AI-powered qualitative data analysis platform that helps researchers analyze interviews, open-ended surveys, and documents.
Evidano feature: automated transcription with PII redaction and custom dictionaries speeds transcript preparation, which matters because El-Kotob et al. collected recorded interviews between May and August 2024 and relied on transcripts for analysis.
Practical use: upload interview audio from medication conversations and get time-stamped transcripts ready for the PPS-aligned coding matrix.
Problem: tracking PPS constructs across demographics is labor intensive
Solution: Evidano provides thematic and cross-segment analyses that quantify how themes like "being dismissed" co-occur with participant attributes.
Evidano feature: cross-segment and frequency analysis lets you compare counts such as how often "dismissal" appears for participants aged 40+ (n = 19 in the PLoS One sample) versus younger groups in future studies.
Relevant link: see the platform capabilities at Evidano features.
Problem: turning qualitative findings into implementation steps
Solution: Evidano’s AI chat over your documents helps map participant quotes to concrete recommendations, for example converting the PLoS One quote "I want to be a part of the decisions..." (participant P03) into a checklist item: "Ask patient 'What are your priorities for this medication? '"
Practical use: generate deliverables such as site-specific training scripts or PREM items that operationalize the PPS domains observed in El-Kotob et al.'s data.
FAQ: psychological safety in medication conversations
What is psychological safety in medication conversations?
Psychological safety in medication conversations is the extent to which patients feel accepted, able to ask questions, and safe to express concerns during medication-related clinical encounters.
El-Kotob et al. used the Patient Psychological Safety framework (Patient Belonging, Patient Learning, Patient Participating) to define these elements in their PLoS One study (published August 20, 2026).
How did the PLoS One study measure psychological safety?
The study used deductive content analysis of interview and focus group transcripts mapped to the PPS framework.
El-Kotob et al. collected interviews between 01 May 2024 and 31 August 2024 and coded data into a display matrix aligned with PPS constructs, as described in PLoS One (2026).
Which concrete quotes from the study illustrate low psychological safety?
One participant in the PLoS One study said, "I was disbelieved and dismissed, " illustrating how dismissal erodes trust (participant P02, El-Kotob et al., PLoS One, 2026).
Another participant said, "I try to treat providers respectfully and behave in an intelligent way with them too. And they treat me as an equal" (participant P10), showing how respectful interaction fosters belonging.
Can AI tools help analyze psychological safety from interviews?
Yes. AI-enabled qualitative research tools can speed transcription, code large sets of quotes to frameworks like PPS, and quantify co-occurrence and segment differences.
Evidano’s platform supports transcription, thematic coding, and AI chat over documents so teams can move from quotes to prioritized recommendations efficiently.
Conclusion & Next Steps
The PLoS One study (El-Kotob et al., published August 20, 2026) shows that respectful communication, clear medication information, and invitation to participate are central to psychological safety in medication conversations.
Qualitative researchers can reproduce and extend these findings by collecting dated transcripts, coding to the PPS framework, and comparing theme frequency across participant segments, as the PLoS One authors did with 21 participants interviewed May–August 2024.
If your team needs to scale transcript processing, thematic coding, and cross-segment analysis for medication-related interviews, try AI-assisted workflows to produce audit-ready recommendations.
Get started by exploring how we analyze qualitative data at Evidano features or Try Evidano for free.
Topics
- psychological safety in medication conversations
- patient psychological safety
- qualitative analysis medications
- AI qualitative research
- patient-provider communication
Keep reading
- Commentary on NewsPsychological safety in medication conversationsSummarizes a PLOS One qualitative study on psychological safety in medication conversations and shows how AI-enabled qualitative research speeds synthesis and insight.
- Commentary on NewsPsychological Safety in Medication Conversations21 interviews (May-Aug 2024) show practical steps to improve psychological safety in medication conversations. AI-enabled qualitative methods for research teams. Try Evidano.
- Commentary on NewsImprove Patient Psychological Safety in Medication TalksPractical guidance for qualitative researchers on patient psychological safety in medication conversations, with PLOS One statistics, quotes, and AI analysis tips.