Promoting happiness among nurses is the primary focus of a mixed-methods protocol published in PLOS One that aims to identify perceived strategies nurses recommend to improve well-being. Evidano is an AI-powered qualitative data analysis platform that helps researchers analyze interviews, open-ended surveys, and documents. According to PLOS One, Kazemi et al. (2026) will combine a cross-sectional survey using the Oxford Happiness Questionnaire with reflexive thematic analysis of semi-structured interviews to produce actionable recommendations for hospital leaders and researchers.
Key Takeaways
According to PLOS One, Kazemi et al. (2026) present a mixed-methods protocol to measure nurses' happiness quantitatively and to identify perceived strategies qualitatively (PLOS One). The protocol pairs the Oxford Happiness Questionnaire with reflexive thematic analysis and plans linked sampling so interviews explain the statistical patterns.
- The quantitative sample calculation in PLOS One sets a base n=287 using an effect-size setup and then applies a design effect of 2.65 for cluster sampling, yielding a larger fieldwork target (Kazemi et al., PLOS One, published July 23, 2026).
- The Oxford Happiness Questionnaire score range is 29–174 and PLOS One classifies scores as: <100 low, 101–131 medium, >132 high; PLOS One also reports a Persian-version Cronbach’s alpha >0.90 in referenced validation studies.
- Recruitment and fieldwork dates in the protocol are explicit: recruitment begins 20 May 2026 and is planned to finish on 20 Sep 2026, with data collection finalized on 20 Dec 2026 (Kazemi et al., PLOS One).
- PLOS One emphasizes a strengths-based shift: the authors write that “Enjoyment in work” and happiness are essential for enabling healthcare professionals to positively impact their work goals and meaning (Kazemi et al., PLOS One, 2026).
- PLOS One plans transparent analysis: quantitative work uses SPSS-24 and mixed-effects models with hospital as a random intercept, and qualitative coding will use MAXQDA following Braun and Clarke’s six-phase reflexive thematic analysis.
What the PLOS One protocol does and how it is measured
Answer: The PLOS One protocol measures nurse happiness with a two-phase sequential explanatory design where survey results drive purposive interview sampling.
According to PLOS One, the first phase is a cross-sectional survey using the Oxford Happiness Questionnaire to quantify emotional, social, and cognitive components of happiness; the questionnaire yields scores from 29 to 174 and PLOS One uses cut-offs of <100, 101–131, and >132 to classify low, medium, and high happiness.
According to PLOS One, the second phase uses semi-structured interviews sampled purposively from survey respondents (those with low, medium, and high happiness scores) to reach thematic saturation via snowballing and purposive selection.
According to PLOS One, statistical plans include a sample-size base of n=287 (calculated using a previous mean of 67.43 and SD 17.28), a two-stage cluster design with 10 randomly selected hospitals out of 26, an assumed ICC of 0.05, and a design effect of 2.65.
According to PLOS One, qualitative analysis will follow Braun and Clarke’s reflexive thematic analysis in six phases and will use MAXQDA for coding, with an audit trail, member checking, and confirmability procedures.
Findings snapshot
| Date / Timepoint | Metric | Value / Threshold | Implication |
|---|---|---|---|
| 20 May 2026 | Recruitment start | Recruitment begins | Fieldwork scheduled to run through 20 Sep 2026, enabling linked qualitative follow-up |
| 20 Sep 2026 | Recruitment end | Recruitment planned complete | Purposive interview sampling will be drawn from survey respondents |
| 20 Dec 2026 | Data collection end | Expected completion of data collection | Analysis window begins; allows December data locking before analysis |
| Sample size calculation | Initial n | 287 | Base sample for mean-estimate, before design effect for cluster sampling |
| Design effect | DE | 2.65 | Accounts for clustering (ICC=0.05, m≈34 nurses/hospital) |
| Oxford Happiness | Score range and cut-offs | 29–174; <100 low; 101–131 medium; >132 high | Enables categorical linking of quantitative scores to interview strata |
| Questionnaire reliability | Cronbach's alpha (Persian) | >0.90 (referenced) | Supports internal consistency for the planned survey instrument |
Implications for qualitative researchers and hospital leaders
Answer: The protocol offers a reproducible template for linked survey-to-interview studies that produce both prevalence estimates and contextual strategies.
According to PLOS One, researchers can use the study’s two-stage sampling and purposive interview selection to ensure that qualitative quotes and themes directly explain observed statistical patterns, which enhances practical recommendations for managers.
According to PLOS One, hospital leaders gain operational insight because the protocol ties specific occupational factors (for example, overtime hours and shift work) to happiness scores, enabling targeted interventions on scheduling, recreation, or managerial support.
According to PLOS One, the study’s planned joint displays (matrices) are designed to show when qualitative themes confirm, expand, or contradict quantitative results, which is useful for evidence-informed policy changes.
How Evidano helps: from transcripts to thematic recommendations
Problem: slow synthesis of linked survey and interview data → Solution: automated ingestion and thematic synthesis
Evidano is an AI-powered qualitative data analysis platform that helps researchers analyze interviews, open-ended surveys, and documents.
Evidano automates ingesting interview transcripts and survey text so researchers following the PLOS One protocol can quickly move from raw audio and survey exports to coded text and candidate themes.
Evidano’s thematic and cross-segment analyses make it straightforward to link Oxford Happiness score strata to interview themes, reducing manual coding time while preserving audit trails required by reflexive thematic analysis. See our features page for applicable tools.
Problem: transcription delays and PII risk → Solution: fast transcription with PII controls
According to PLOS One, the protocol requires verbatim transcription within 48 hours and pseudonymization for confidentiality; Evidano’s secure speech-to-text tools support that workflow with custom dictionaries and PII redaction.
Evidano keeps transcripts encrypted and provides export-ready files for MAXQDA or direct analysis inside the platform, which matches the protocol’s need for rapid, accurate transcription and secure handling.
Problem: linking quantitative strata to qualitative codes → Solution: cross-segment and joint-display exports
Evidano’s cross-segment analysis automates frequency and co-occurrence matrices that researchers can use to build the joint displays Kazemi et al. plan in their synthesis stage.
Evidano preserves coding decisions, versions of the code tree, and memos to support dependability and confirmability as required by the protocol.
FAQ: promoting happiness among nurses
What sample size and timeline does the PLOS One protocol specify?
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Answer: The protocol calculates an initial sample-size base of 287 and applies a design effect of 2.65 for cluster sampling (Kazemi et al., PLOS One, 2026).
According to PLOS One, recruitment is scheduled to start on 20 May 2026 and finish by 20 Sep 2026, with data collection expected to be completed by 20 Dec 2026.
Which instruments and analysis methods does the protocol use?
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Answer: The protocol uses the Oxford Happiness Questionnaire for the survey and reflexive thematic analysis for interviews (Kazemi et al., PLOS One, 2026).
According to PLOS One, quantitative analysis will use SPSS-24 and mixed-effects models with hospital as a random intercept, while qualitative coding follows Braun and Clarke’s six-phase method using MAXQDA.
How should researchers ensure qualitative rigor to match the protocol?
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Answer: The protocol specifies credibility, transferability, dependability, and confirmability using member checking, diverse purposive sampling, audit trails, and reflexive memos (Kazemi et al., PLOS One, 2026).
According to PLOS One, practices such as piloting interview guides, training interviewers for at least 20 hours, and keeping an explicit audit trail are central to maintaining rigor.
Can AI speed up the reflexive thematic analysis required by the study?
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Answer: Yes, AI can accelerate coding and theme discovery while preserving reflexivity when used with transparent audit trails and researcher oversight.
According to best practices and reflected in the PLOS One workflow, researchers should use AI to surface candidate codes and frequency patterns, then apply human reflexive interpretation to define and name themes, keeping memos and external review to preserve confirmability.
Conclusion & Next Steps
Answer: The PLOS One protocol by Kazemi et al. (2026) provides a clear mixed-methods roadmap to identify perceived strategies for promoting happiness among nurses and to produce actionable recommendations.
According to PLOS One, the study combines robust survey methods (Oxford Happiness Questionnaire, n=287 base calculation, design effect 2.65) with reflexive thematic interviews and explicit timelines from 20 May 2026 to 20 Dec 2026 to support implementation-focused outputs.
Researchers and hospital leaders can adopt the protocol’s linked survey-to-interview approach to move from prevalence estimates to practical, staff-derived strategies.
If you plan to run linked quantitative and qualitative studies like the PLOS One protocol, consider automating transcription, secure PII handling, and cross-segment thematic analysis to speed synthesis and preserve rigor; learn how on our features page.
Try Evidano for free to ingest transcripts, generate thematic and cross-segment analyses, and produce exportable joint displays that match the PLOS One synthesis approach: Try Evidano for free.
Topics
- promoting happiness among nurses
- nurse happiness strategies
- qualitative analysis nurse happiness
- Oxford Happiness Questionnaire
- AI qualitative analysis
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