AI methods for qualitative analysis of sexual satisfaction

Solution: Evidano supports accurate automated transcription with custom dictionaries and PII redaction to securely transcribe long interviews like the 50–85 minute recordings described in PLOS One.

Why it matters: The PLOS One study depended on verbatim transcripts; automated, editable transcripts reduce time to first-pass coding and preserve participants' phrasing for quotations.

Solution: Evidano performs thematic, content, frequency, and cross-segment analyses so teams can convert the 720 inferential codes reported in PLOS One into merged code groups and frequency tables in hours instead of weeks.

Tool note: Use Evidano features for AI-assisted code clustering and the co-occurrence network visualization to spot concept overlap across couple and individual interviews.

Solution: Evidano offers controlled translation with custom dictionaries so researchers can translate Persian interviews with preserved technical terms and idioms before meta-coding.

Operational tip: For cross-site comparisons or publication, a validated translation step close to the PLOS One workflow protects nuance while enabling team-wide coding.

Solution: Evidano provides AI chat over your documents and visualizations so teams can ask extractable questions like "show all codes related to virginity norms" and export supporting quotes for audit trails.

Security note: Evidano uses encrypted storage and does not share your data with third-party LLM providers, which helps meet confidentiality requirements for sensitive sexual-health interviews; see Evidano data security.

Answer: For in-depth, context-specific psychosocial exploration, a purposive sample of 30–40 participants with both individual and dyadic interviews is often sufficient to reach saturation, as shown by Toghiyani et al. in PLOS One (36 interviews with 31 participants, saturation achieved).

Supporting detail: The PLOS One team continued sampling until no new codes appeared and validated transfers with additional couples; replicate this iterative stop rule rather than using a fixed numeric threshold.

Answer: Yes, when AI tools include customizable dictionaries, PII redaction, encrypted storage, and human-in-the-loop review; the PLOS One study relied on verbatim transcripts and human coding to ensure nuance and ethical handling.

Supporting detail: Use AI for transcription speed and initial clustering, then perform human validation and member-checking as the PLOS One authors did to preserve trustworthiness.

Answer: Inductive qualitative content analysis is appropriate for culturally specific topics, and Toghiyani et al. used Graneheim and Lundman’s method as reported in PLOS One on 13 August 2026.

Supporting detail: Inductive approaches let themes emerge from narratives rather than imposing a priori codes, which is critical for uncovering local norms such as virginity expectations reported in the PLOS One findings.

Answer: Ask for code frequency tables, co-occurrence matrices, exemplar quotations by code, and cross-segment comparisons (for example by gender or interview type), which directly map to the 234 merged codes and three categories reported in PLOS One.

Supporting detail: These outputs enable transparent audit trails and rapid synthesis for policy briefs, curricula, or intervention design informed by the PLOS One themes.