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Đại cương về thiết kế nghiên cứu định tính. Gs,ts,bs lê hoàng ninh. Nghiên cứu định tính là gì ?. Tập trung trên chất chứ không phải lượng Phát triển / hình thành giả thuyết chứ không kiểm định giả thuyết Điều tra : TẠI SAO và THẾ NÀO ?
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Đạicươngvềthiếtkếnghiêncứuđịnhtính Gs,ts,bslêhoàngninh
Nghiêncứuđịnhtínhlàgì? • Tậptrungtrênchấtchứkhôngphảilượng • Pháttriển / hìnhthànhgiảthuyếtchứkhôngkiểmđịnhgiảthuyết • Điềutra : TẠI SAO và THẾ NÀO ? • Thu thậpdữliệugồm : phỏngvấn,nhómchủđích, tưliệu, quansát... • Dữliệu: bàivăn, hìnhnghệthuật, ảnh...
Tạisaodùngcáchtiếpcậnđịnhtính? • Câuhỏinghiêncứuliên can tớisựtìmhiểu, môtảmộthiệntượng / biếncốđặcbiệtnàođómàsự am hiểucònrấthạnchế • Đểcóđượcnhữngđặcđiểmkhíacạnhkhôngthểđịnhlượngđượcvếcuộcsốngcủa con người. • Hiệntượngquantâmcóliên can tớidựhiểubiếtvềsựtrảinghiệm, ý nghĩasâuxa, tìnhcảnh, sựcảmkíchvànhữngkhíacạnhxảyrahằngngàycủacácthànhviên hay củanhóm
Đềcươngnghiêncứuđịnhtính • Câuhỏivàmụctiêunghiêncứu • Hồicứu y vănvàcácghinhậncótínhlýthuyết • Ngườithamgia- Bạnquyếtđịnhbạnmuốnthếnào? • - Bạncầnbaonhiêu?- Bạnnhậnhọvàothếnào? • Thu thậpdữliệu- bạnsẽthuthậpdữliệunào?- thuthậpthếnào? • Data analysis- bạnlàmgìvớidữliệuđó ? • Chuyểndịchkiếnthức- làmcáchnàođểmọingườibiết, hiểuđượccáimàbạntìmđược qua nghiêncứu
Câuhỏivàmụctiêunghiêncứu • Câuhỏinghiêncứuphảilàmộtcâuhỏi: thườnglàTại Sao hay ThếNào ? • Mụctiêunênnêurõ, chuyênbiệtvềcáimàbạnđangmuốnlàm • Khôngcótrướcgiảthuyếtnghiêncứutrongnghiêncứuđịnhtính
Thí dụ câu hỏi nghiên cứu định tính Vănhoánghềnghiệpthểhiệnnhưthấnào ở cáchọcviênchuyênkhoa 2 của 3 tỉnhtayninh, bìnhdương, b.rvũngtàu? Bệnhnhânthểhiệnsựcảmxúcthếnàokhichờđợi 3 gio82 đểđượcbácsĩthămkhámbệnhtrong 3 phút. Họcviệnchuyênkhoacấp 2 cósuynghỉgìkhiđềcươngbịbácvàlàmlạiđềcươngkhác.?
Hồicứu y văn (Literature Review) • What has already been done? • What do we already know? • Where are the gaps in the literature? • Why is your study necessary? • Why is a qualitative approach the best option? • “sensitizing concepts”
Phươngphápđịnhtính Examples include: • Ethnography • Phenomenology • Grounded Theory • Case Study
Dântộchọc (Ethnography) • Approach rooted in Cultural Anthropology & Sociology • Focuses on the description and interpretation of cultural patterns of groups • Understanding cultural meanings people use to organize and interpret their experiences • Researcher studies the meaning, behaviour , language, and interactions of a culture-sharing group • Data collection usually involves multiple sources and often includes observation; can take many months or years
Phenomenology • Based in philosophy, psychology and sociology • Focus is to uncover the meaning of how humans experience phenomena through description of those experiences as they are lived by individuals • E.g., what is the meaning of “healing” to women with cancer? • Focuses on experiences from the perspective of the individual (not a group) • Data collection usually by individual interviews – sometimes multiple interviews of same person
Phenomenology Example • Ribau C and JP Marc-Vergnes. “Towards a phenomenology of persistant pain”Pesse Medicale 2004; 33(7): 449-52
Grounded Theory • Primarily used to develop a theory or conceptual model – based in sociology • Generally begins with a broad query and collects all relevant information • Each piece of info is reviewed, compared and contrasted with earlier collected info (constant comparison) • Range of data collection techniques can be used; usually includes interviews
Grounded Theory Examples • Chaar B and Kwong K. “Direct-to-consumer advertising: Australian pharmacists’ experiences with non-prescription medicines.”International Journal of Pharmacy Practice. 2010;18(1):43-50. • Pottie K, et al. “Pharmacist’s identity development within multidisciplinary primary health care teams in Ontario: qualitative results from the IMPACT project”Research in Social Administrative Pharmacy 2009; 5(4):319-26. • Benson A et al. “Understanding pharmacists’ values: a qualitative study of ideals and dilemmas in UK pharmacy practice”Social Science & Medicine 2009; 68(12):2223-30.
Case Study • In-depth analysis of single cases or comparison across multiple cases • Comes from Political Science, Sociology • Data collection normally includes a variety of sources including documents, interviews and observation • Data from different sources are triangulated • When multiple cases are available, case-by-case analysis is completed first, followed by cross-case comparisons
Case Study Example • Knapp DA et al. “Growth of a pharmacy school through planning, cooperation, and establishment of a satellite campus”American Journal of Pharmaceutical Education 2009; 73(6):102 • Nanji KC et al. “Overcoming barriers to the implementation of a pharmacy bar code scanning system for medication dispensing: a case study”Journal of the American Medical Informatics Association 2009; 16(5):645-50
Objectives/Questions strongly influence methodology choice • If one is interested in focusing on social groups, then one may reject phenomenology OR • if one is interested in individuals’ experiences, then ethnographic or case study approaches might be rejected
Data Collection • Match to your methodological approach • What kind of data do you need: • Individual vs group • Interviews vs focus groups • Documents • Observation • Are multiple methods appropriate (triangulation)?
Forms of Data • Generally anything that can be reduced to text:- interview and focus group transcripts- documents- field notes- observational notes- reflective journaling
Interviewing • Common to almost every form of qualitative research methodology • What varies is:- types of questions- length- amount of structure vs. flexibility- interviewers’ role- analysis • Essentially the ONLY data collection technique for phenomenology
Interviews in…. • Ethnography: hold equal weight with observation; multiple interviews over extended period of time • Phenomenology: very in-depth, unstructured, small number (<10) • Grounded Theory: continue until reaching saturation of key emerging themes in the developing theory • Case Studies: only one of multiple sources; often use key informants
Individual Interviews General Rules of Thumb • “A good interview is like a good conversation” • Good interviewer may not say much, but works hard at listening • Unstructured or semi-structured • Vary in length: average in literature 60-90 minutes
Wording Questions • Interview GUIDE with general topics and themes to be discussed • Exact wording and order should be altered to fit each individual – follow the participant’s lead • “Not knowing” questioning strategy born out of genuine curiosity • Questions should be open-ended • Avoid questions that may be perceived as “tests” of knowledge: “Tell me about that” instead of “what do you know about that?”
Sample Interview Guide
Audio Recording • Allows you to interact with the participant instead of writing notes constantly • Provides higher quality data (better record of what was actually said) • Place recording device closer to the participant • Check recording immediately after interview • Supplement with field notes • Can be costly (and time consuming) to transcribe
Transcribing • Takes 2-4 times the length of the interview • Conventions vary depending on the type of analysis planned • ID Code; date; interviewer • Number lines and pages • Leave space in right margin • Codes for emotion (e.g., laughter), pauses • Checking transcripts
Example transcript Sample Transcript
How many people do you need to interview? • depends on the focus/complexity of your research question and the diversity of your participants • Saturation: the point at which no significant new data in the key themes is being collected • 12 interviews may be enough: Guest et al. “How many interviews are enough: An experiment with data saturation and variability”Field Methods 2006; 18:59-82
Focus Groups • Group discussion with a facilitator • Groups of 4-10 • Lasts for 1-2 hours • Purpose: to facilitate description and understanding of perceptions, interpretations, and beliefs of a selected population
Stand-alone method Reveal participants’ experiences and perspectives that may not be accessible without group interaction Supplementary data Preliminary data for a quantitative study Together with individual interviews and participant observation in ethnographic research triangulation When to Use Focus Groups
Focus Group Participants Homogeneous groups • Allows for more “free-flowing” conversations • Can group by age, gender, religion, occupation, ethnicity etc. Heterogeneous groups • Sometimes helps to stimulate discussion (greater likelihood of range of opinions • Watch power dynamics
Observation • Systematically watching and recording people’s behaviours, clothing, expressions, interactions in a particular setting • Simple unobtrusive observation • Participant observation
Fieldnotes • Definition: accounts describing experiences and observations the researcher has made • Way to document experience in the “field” • Vital component of observation • Encouraged as additional contextual information for interviews and focus groups • Putting into words the “experience” of the researcher • Also includes the researcher’s perception and interpretation of the events
Advantages May more accurately reflect behaviour than self-report Relatively inexpensive Access in public places is relatively easy Disadvantages Information may be distorted by some unknown bias or intervening factor Information is interpreted from a researcher perspective (rather than a participant perspective as with interviews) Observation: Pros and Cons
Documents • Sources can include: literature; print media, diaries, graffiti, letters, government policies etc • Can be used as a supplement to other data collection or as a stand-alone method
Advantages Cheaper and less time consuming than collecting data from people Ethical consent not necessary for public documents Disadvantages Limited to what is written (i.e., can’t probe for additional information) May be shaped for an intended audience (need to factor in to analysis) Documents: Pros and Cons
Sampling • Usually purposive (not random) sampling • Variations: • Criteria-based • Maximum variation • Convenience sampling • Snowball sampling
Key Informants • Key informants: those with unique/special knowledge about the research topic who are willing/able to discuss it • Can help give you “entry into the field”
Recruitment • Start with personal contacts • May need permission/endorsement from “official” bodies • Formal letter of introduction • Multiple follow-ups often necessary
General Analysis Strategies • No consensus on how to analyze qualitative data • General strategies in common: basic content/thematic analysis = a process of coding, sorting and organizing • Start analysis during data collection
General Strategy 1 • General review of all information • Jotting down notes in the margin of the text • Writing memos and reflective notes (and/or reviewing those that are part of the field notes) • Purpose: to get an overall “sense” of the data
General Strategy 2 • Begin to reduce the data • Look closely at words, phrases and metaphors used by participants • Develop key codes or categories • Create visual displays of the information (e.g., coding trees), graphs, diagrams
General Strategy 3 • Start with 5-6 key categories and expand/contract these as needed while reviewing and re-reviewing the data • Normally don’t have more than 25-30 categories at any time • Use sub-categories to refine coding • Work to identify the 5-6 key ones that will form the basis for a paper • Note: NOT ALL the data will be used/coded
Categories • Categories consist of: • Label or name • Definition of what is contained in this category • Description of how to know when the category occurs • Any exclusions • Examples
Category Definitions
Category Names • The best category names are: • Conceptually meaningful • Clear and concise (as few words as possible) • Grounded in the data (often use participants’ language) • Minimize researcher interpretation
Unit of coding • The most basic segment or element of the raw data that can be assessed in a meaningful way regarding the phenomenon being studied • Examples: • Phrase • Uninterrupted speech section in the transcript • Essay or article
Coding Exercise • Read the transcript excerpt • Underline the “key content”: • Things you think might be important • Things that seem odd or intriguing • Create a “category”name for each thing you have underlined • Use the same category name if it is the same content in several different places (constant comparison method)
Computer Analysis Programs • Examples: NVIVO, Ethnograph • Most helpful for larger data sets (e.g., over 500 pages of text) • Not useful for small data sets – too time consuming to enter all the data