This post explains how to perform a qualitative analysis of interprofessional learning (IPL) between nurses and physiotherapists in hospital clinical practice and how AI can speed evidence synthesis for researchers and education leads. The primary keyword, qualitative analysis of interprofessional learning, is used throughout. The PLoS One scoping review by Åhlund, Johnsson, and Rönnerhag (published August 7, 2026) mapped facilitators and barriers to IPL and provides concrete findings that can be directly reanalyzed or annotated using AI-enabled qualitative research tools. This post gives extractable steps, concrete statistics from the PLoS One review, and a matched AI workflow you can try on your own data.
Key Takeaways
According to PLoS One, the scoping review published on August 7, 2026 found that sustainable interprofessional learning between nurses and physiotherapists depends on organizational structures, inclusive team cultures, and leadership that values collaboration.
- The PLoS One scoping review (Åhlund et al., published August 7, 2026) screened 1, 973 titles and abstracts and included 11 empirical studies after full-text screening in July 2026.
- The PLoS One review reports that 10 of the 11 included studies (91%) used qualitative interviews, and sample sizes in those studies ranged from 18 to 333 participants, with publications dated between 2009 and 2022.
- The PLoS One review identified facilitators counted across studies as: socialization/familiarization (n = 6), positive team climate (n = 5), and conducive organizational structures (n = 10); it also identified barriers counted as: limiting structural prerequisites (n = 5), constraining interprofessional interactions (n = 4), and non-conducive workplace culture (n = 5), findings summarized in July 2026.
- Åhlund et al. (2026) conclude, and we quote, "Sustainable IPL requires organizational structures that enable regular interaction among professionals, inclusive team cultures, and collaborative leadership."
What happened and how the review measured IPL
Answer: The PLoS One scoping review systematically searched three databases and synthesized empirical studies to identify facilitators and barriers to IPL between nurses and physiotherapists.
The PLoS One review by Åhlund et al. (published August 7, 2026) searched PubMed, CINAHL, and Scopus from inception and carried out the last update in July 2026, yielding 2, 206 hits before deduplication and 1, 973 titles and abstracts screened.
The PLoS One review (Åhlund et al., 2026) applied Arksey and O’Malley scoping review methods and included peer-reviewed empirical studies in English that reported on facilitators and barriers in adult hospital settings; after screening 33 full texts the authors included 11 studies in the final analysis.
The PLoS One review (Åhlund et al., 2026) extracted numeric indicators such as methods used (10/11 qualitative interviews, 5/11 field observations, 3/11 surveys) and coded facilitators and barriers into thematic groupings for cross-study comparison.
Findings snapshot
| Date / Source | Metric | Value | Implication |
|---|---|---|---|
| July 2026, PLoS One (Åhlund et al., 2026) | Records screened | 1, 973 after deduplication | Large initial yield, small final sample (need for focused inclusion criteria in workplace IPL reviews) |
| July 2026, PLoS One (Åhlund et al., 2026) | Studies included | 11 empirical studies | Evidence base is small and heterogeneous; qualitative synthesis is appropriate |
| Publications 2009–2022, PLoS One (Åhlund et al., 2026) | Study methods | 10/11 qualitative interviews (91%); 5/11 observations (46%); 3/11 surveys (27%) | Qualitative data dominate; thematic coding and contextual analysis are primary needs |
| PLoS One synthesis, July 2026 | Common facilitators/barriers (counts) | Facilitators: socialization (6), team climate (5), structures (10); Barriers: structures (5), interactions (4), culture (5) | Design interventions that target the dominant organizational and cultural factors |
Implications for qualitative analysis of interprofessional learning
Answer: For researchers and education leads doing qualitative analysis of interprofessional learning, the PLoS One review indicates you should prioritize organizational and interactional context when coding and sampling.
The PLoS One review (Åhlund et al., 2026) shows that organizational structures and physical co-location were frequently reported (conducive organizational structures, n = 10), so qualitative coding schemes should include nodes for leadership actions, staffing patterns, meeting formats, and shared spaces.
The PLoS One review (Åhlund et al., 2026) found many studies used interviews and observations, so researchers should plan for triangulation: combine interview transcripts (sample sizes 18 to 333 in primary studies) with field notes and meeting artefacts to capture both expressed and enacted IPL.
The PLoS One review (Åhlund et al., 2026) highlights that culture and hierarchy are key barriers; therefore qualitative analyses should include discourse codes for status, exclusion language, and descriptions of decision authority to reveal how culture constrains IPL.
How Evidano helps: mapping IPL analysis problems to AI-enabled solutions
Evidano definition
Evidano is an AI-powered qualitative data analysis platform that helps researchers analyze interviews, open-ended surveys, and documents.
Problem: Large, messy qualitative corpus from multiple studies, as in the PLoS One review where 1, 973 initial records produced 11 eligible studies (Åhlund et al., 2026).
Solution: Evidano ingests transcripts and field notes and runs automated thematic extraction to surface recurring facilitators and barriers across sources, accelerating the initial coding pass.
Problem: inconsistent coding across teams → Solution: thematic harmonization
According to the PLoS One review (Åhlund et al., 2026), facilitators and barriers appear in different language across studies; Evidano standardizes terms by generating hierarchical codebooks and mapping synonyms to common nodes.
Feature link: Learn more on the Evidano features page.
Problem: lost contextual metadata → Solution: cross-segment and frequency analysis
The PLoS One studies varied by country and method (Australia 4/11 studies, Sweden and Norway represented, publications 2009–2022) so segment-level analysis is needed, and Evidano produces cross-segment counts and co-occurrence networks to show where themes cluster by setting or profession.
This helps answer questions like which facilitators appear in wards with co-location versus in units using videoconferencing (Åhlund et al., 2026).
Problem: manual quote retrieval is slow → Solution: AI search and quote extraction
The PLoS One review relied on quotes from interviews across many studies (Åhlund et al., 2026); Evidano’s AI can extract verbatim quotes that match code filters, producing exportable evidence matrices for reports and presentations.
This makes it straightforward to surface quotes such as the PLoS One conclusion quote and attribute them correctly in your synthesis.
Problem: transcription and multilingual sources → Solution: integrated speech-to-text and translation
If your IPL research involves audio from ward rounds or interviews, Evidano’s transcription and translation features reduce manual prep time and preserve speaker labels and timestamps for contextual analysis.
See the speech-to-text and translation pages for technical details.
FAQ: qualitative analysis of interprofessional learning
How do I extract facilitators and barriers from multiple qualitative studies quickly?
Answer: Use AI-assisted thematic extraction to run an initial code pass and surface recurring phrases and co-occurrences.
Supporting detail: The PLoS One review (Åhlund et al., 2026) shows recurring facilitators and barriers across 11 studies, so an automated first-pass that highlights frequent themes (for example socialization, team climate, organizational structures) reduces manual coding time and focuses human review on interpretation and context.
What sample sizes are typical in workplace IPL qualitative studies?
Answer: Typical primary studies in the PLoS One review had sample sizes ranging from 18 to 333 participants.
Supporting detail: Åhlund et al. (PLoS One, 2026) reported this range across the 11 included studies published between 2009 and 2022, indicating both small focused interviews and larger mixed-methods samples exist in workplace IPL research.
Which themes should I include in a codebook for nurses-physiotherapists IPL?
Answer: Include codes for socialization/familiarization, team climate and relational trust, organizational structures and co-location, time and staffing constraints, and hierarchical culture.
Supporting detail: The PLoS One synthesis (Åhlund et al., 2026) aggregated counts for those themes (socialization n = 6; team climate n = 5; structures n = 10; barriers counts likewise), which indicates these are high-yield nodes to include in your codebook.
Can AI preserve quote provenance for systematic reporting?
Answer: Yes, AI tools that retain document-level metadata and timestamps can preserve provenance and produce evidence matrices for reporting.
Supporting detail: The PLoS One review (Åhlund et al., 2026) emphasizes extracting and quoting representative passages across studies; AI platforms that keep source labels and links enable precise attribution when you reuse quotes in syntheses.
Conclusion & Next Steps
The PLoS One scoping review (Åhlund et al., published August 7, 2026) shows that organizational structures, team climate, and socialization processes most strongly shape interprofessional learning between nurses and physiotherapists.
For researchers conducting qualitative analysis of interprofessional learning, the review’s concrete counts and dates (1, 973 screened; 11 included; last search July 2026) point to a compact but rich evidence base that benefits from AI-assisted coding, cross-segment analysis, and quote extraction.
If you want to pilot an AI workflow that ingests interview transcripts and outputs thematic codes, co-occurrence networks, and exportable evidence matrices, Try Evidano for free.
If you want to learn more about features and integrations, visit the Evidano features page or start a free trial at the registration link above.
Topics
- qualitative analysis of interprofessional learning
- interprofessional learning nurses physiotherapists
- AI-enabled qualitative research
- workplace IPL analysis
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