เปรียบเทียบวิธี

	การสัมภาษณ์เชิงกึ่งโครงสร้างที่ผ่านการทดลองนำร่อง	การสัมภาษณ์เชิงลึกที่ผ่านการทดลองนำร่อง
สาขาวิชา	ระเบียบวิธีสำรวจ	ระเบียบวิธีสำรวจ
ตระกูล	Process / pipeline	Process / pipeline
ปีกำเนิด	1970s–1980s (as formalised pilot testing of qualitative instruments)	1990s–2000s (pilot testing of qualitative instruments formalized)
ผู้ริเริ่ม	Standard qualitative methods practice; systematised in social research methodology literature	Rooted in interview methodology tradition; pilot testing practice systematized by Kvale and others
ประเภท	Qualitative data collection technique with pre-validation phase	Qualitative data collection technique
แหล่งต้นตำรับ	Bryman, A. (2016). Social Research Methods (5th ed.). Oxford University Press. ISBN: 9780198714965	Kvale, S., & Brinkmann, S. (2009). InterViews: Learning the Craft of Qualitative Research Interviewing (2nd ed.). Sage. ISBN: 978-0761925422
ชื่อเรียกอื่น	pilot semi-structured interview, pre-tested qualitative interview, pilot interview protocol, trial semi-structured interview	pretested in-depth interview, pilot in-depth interview, pilot-tested IDI, pilot interview protocol
ที่เกี่ยวข้อง	4	3
สรุป	A pilot-tested semi-structured interview combines the flexibility of semi-structured interviewing — a guide of open-ended questions allowing conversational depth — with a mandatory pre-study pilot phase in which the guide is trialled on a small subset of participants or informants. The pilot reveals ambiguous questions, poor sequencing, and missing topics before the main data collection begins, substantially strengthening the validity and efficiency of the final instrument.	A pilot-tested in-depth interview is a qualitative data collection approach in which the interview guide is administered to a small number of participants before the main study, specifically to identify ambiguous questions, refine probes, estimate session duration, and verify that the protocol elicits rich, relevant narratives. The revised guide is then used in the full data collection phase, improving data quality and interview consistency.