This post refracts a PLOS One qualitative study into practical methods for AI-enabled qualitative research on community pharmacist health promotion. Evidano is an AI-powered qualitative data analysis platform that helps researchers analyze interviews, open-ended surveys, and documents. According to the PLOS One study (Hasan Ibrahim et al., 2026), community pharmacists in Amman, Jordan, described evolving roles in health promotion and disease prevention but faced structural, educational, and motivational barriers. The primary keyword for this post is "community pharmacist health promotion" and the following sections show how researchers can replicate, code, and scale similar thematic and COM-B mapping studies using AI tools while retaining transparency and auditability.
Key Takeaways
According to the PLOS One study (Hasan Ibrahim et al., 2026) PLOS One, Jordanian community pharmacists perform diverse health promotion tasks but are limited by workload, owner priorities, and lack of incentives.
- 15 community pharmacists were interviewed between 1 January and 30 April 2025; data saturation was reached after 14 interviews, according to the PLOS One study (Hasan Ibrahim et al., 2026).
- In the PLOS One sample (published 5 August 2026), 10 of 15 participants were female (66.7%), and 11 of 15 (73.3%) had under five years of community pharmacy experience.
- According to the PLOS One study (Hasan Ibrahim et al., 2026), common barriers reported in April 2025 included high daily patient volumes (about 100 patients per day in one participant’s report) and often only one pharmacist per shift (10 of 15 participants, 66.7%).
- The PLOS One authors mapped themes to the COM-B framework in their August 2026 report and concluded capability, opportunity, and reflective motivation shaped pharmacists’ engagement in preventive services.
What the 2026 Jordan study did and how it was analyzed
Answer: The study used semi-structured, face-to-face interviews and inductive thematic analysis with deductive COM-B mapping to interpret pharmacists’ behavior.
According to the PLOS One study (Hasan Ibrahim et al., 2026), interviews were conducted in Amman between 1 January and 30 April 2025 and audio-recorded, transcribed verbatim in Arabic, translated to English, and analyzed in NVivo® QSR 14.
According to the PLOS One study (Hasan Ibrahim et al., 2026), the researchers used Braun and Clarke’s six-step thematic approach, two independent coders for investigator triangulation, and then mapped final themes to the Capability, Opportunity, Motivation-Behavior (COM-B) model.
According to the PLOS One study (Hasan Ibrahim et al., 2026), the final results identified four themes: diverse and evolving roles in HPDP; barriers; professional requirements and capacity building; and impacts on patients and the system.
Findings snapshot
| Date | Metric | Value | Implication |
|---|---|---|---|
| 1 Jan–30 Apr 2025 | Interviews conducted | 15 CPs, face-to-face | Sufficient for saturation, qualitative depth |
| Apr 2025 (reported) | Participant gender | 10 female (66.7%) | Sample skew toward early-career female pharmacists; consider purposive balance in future studies |
| Apr 2025 (reported) | Experience level | 11 with <5 years (73.3%) | Findings may reflect early-career perspectives on HPDP roles |
| Apr 2025 (reported) | Staffing per shift | 10 of 15 only pharmacist on duty (66.7%) | Workload and single-staff shifts are major opportunity barriers |
| 5 Aug 2026 | Publication date | PLOS One article published | Peer-reviewed dissemination and COM-B mapping available for replication |
Implications for qualitative researchers studying community pharmacist health promotion
Answer: Researchers should combine rigorous thematic coding with behavior-change frameworks and document translation and reflexivity steps explicitly.
According to the PLOS One study (Hasan Ibrahim et al., 2026), best practices included audio-recording, verbatim transcription in the source language, back-translation checks, and dual independent coding to improve credibility.
Researchers should report practical details that AI can leverage: interview dates, sampling window, participant demographics (for example, the PLOS One study reported mean age 27.5 ± 6.1 years and average interview length 40 minutes), and the point of saturation (14 interviews in this study).
Researchers should map inductive themes to a theoretical framework like COM-B to make findings actionable and reproducible: the PLOS One team mapped capability, opportunity, and reflective motivation factors for HPDP engagement.
For multi-language datasets, preserve original-language transcripts and aligned translations to allow AI-assisted checks for semantic drift and to enable reproducible coding audits.
How Evidano helps researchers analyze community pharmacist health promotion data
Problem: Manual transcription and translation slow analysis
Solution: Evidano is an AI-powered qualitative data analysis platform that helps researchers analyze interviews, open-ended surveys, and documents.
Feature mapping: Use Evidano’s Speech-to-text pipeline for Arabic audio → verbatim transcripts, then apply the platform’s translation and alignment tools to retain original-language context while producing English extracts for cross-team review.
Problem: Time-consuming inductive coding and COM-B mapping
Solution: Evidano accelerates iterative thematic coding with AI-assisted suggestions and hierarchical code trees, enabling fast deductive mapping to behavioral frameworks such as COM-B.
Feature mapping: Apply Evidano’s thematic, frequency, and co-occurrence analyses to reproduce the PLOS One approach and export reproducible codebooks and visualizations for publication and policy briefs. See Features for details.
Problem: Ensuring auditability and secure sharing
Solution: Evidano provides encrypted storage and exportable audit trails so translation decisions, coding rounds, and consensus notes are preserved for methods sections and peer review.
Feature mapping: Use Evidano’s versioned exports and AI chat-over-data to answer reviewer questions with source-linked quotes and timestamps.
FAQ: community pharmacist health promotion
What were the main barriers identified to pharmacists delivering health promotion services?
Answer: The main barriers were workload, limited staffing per shift, lack of owner support, and absence of financial incentives, according to the PLOS One study (Hasan Ibrahim et al., 2026).
Supporting detail: The PLOS One participants reported average daily patient loads of up to about 100 and that 10 of 15 pharmacists were often the only pharmacist on duty, which constrained time for counseling.
How did the authors apply the COM-B framework in their analysis?
Answer: The authors conducted inductive thematic analysis and then deductively mapped themes to COM-B to interpret capability, opportunity, and motivation drivers, according to PLOS One (Hasan Ibrahim et al., 2026).
Supporting detail: The PLOS One mapping found psychological capability (knowledge, skills), physical and social opportunity (staffing, space, owner support), and reflective motivation (professional responsibility, recognition) as central influences.
Can AI tools reliably analyze translated interviews like those in the Jordan study?
Answer: Yes, AI can reliably assist analysis if transcripts and translations are aligned and quality-checked; the PLOS One team reviewed translated transcripts against Arabic originals, which is a recommended practice.
Supporting detail: The PLOS One study (Hasan Ibrahim et al., 2026) translated Arabic transcripts into English and checked them for accuracy, a step AI pipelines should preserve via parallel-language alignment and human verification.
How should policymakers use findings like these to expand pharmacist-led prevention?
Answer: Policymakers should address staffing models, consultation spaces, training, and incentive structures, as the PLOS One authors recommend in their August 2026 conclusions.
Supporting detail: The PLOS One study (Hasan Ibrahim et al., 2026) specifically suggests integrating HPDP competencies into pharmacy curricula, creating private counseling areas, fostering physician collaboration, and considering reimbursement mechanisms.
Conclusion & Next Steps
Answer: The PLOS One qualitative study (Hasan Ibrahim et al., 2026) documents that Jordanian community pharmacists are active in health promotion but constrained by capability, opportunity, and motivation factors.
Researchers and implementers can reproduce and scale the study’s methods by combining careful transcription, bilingual translation checks, inductive thematic coding, and deductive COM-B mapping.
Evidano helps teams accelerate those steps with secure AI-assisted transcription, coding, and visualization while preserving audit trails for publication.
If you want to run a reproducible thematic analysis or map interview data to behavior change frameworks, Try Evidano for free.
Topics
- community pharmacist health promotion
- health promotion by pharmacists
- qualitative analysis of pharmacists
- COM-B mapping pharmacists
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