Meta Synthesis Guide

Meta-synthesis is to qualitative research what meta-analysis
is to quantitative research -- it systematically combines
findings from multiple studies to produce higher-order
interpretations.

Key differences from meta-analysis:
  - Interpretive, not statistical aggregation
  - Aims to generate new understanding, not average effect sizes
  - Synthesizes themes, concepts, and metaphors across studies
  - Product is a new interpretation, not a pooled statistic

Appropriate when:
  - Multiple qualitative studies exist on a topic
  - You want to build theory or deepen understanding
  - Individual studies have limited scope but collectively cover a phenomenon
  - Policy or practice needs an integrated evidence base from qualitative work

Not appropriate when:
  - Studies are too heterogeneous in topic to meaningfully compare
  - Fewer than 3 qualitative studies exist
  - The goal is to measure effect sizes (use meta-analysis instead)

def meta_ethnography_steps() -> dict:
    """
    The seven steps of meta-ethnography (Noblit & Hare, 1988).
    """
    return {
        "step_1_getting_started": {
            "description": "Identify the research question and intellectual interest",
            "output": "Clear synthesis question"
        },
        "step_2_deciding_what_is_relevant": {
            "description": "Systematic search and selection of qualitative studies",
            "output": "Final set of included studies",
            "note": "Use PRISMA flow diagram to document selection"
        },
        "step_3_reading_the_studies": {
            "description": (
                "Read and re-read included studies carefully. "
                "Identify key metaphors, themes, and concepts in each."
            ),
            "output": "List of first-order (participant quotes) and "
                      "second-order (author interpretations) constructs"
        },
        "step_4_determining_how_studies_are_related": {
            "description": (
                "Create a grid mapping constructs across studies. "
                "Determine if studies are reciprocal (about similar things), "
                "refutational (contradictory), or form a line of argument."
            ),
            "output": "Construct comparison table"
        },
        "step_5_translating_studies": {
            "description": (
                "Translate the concepts of one study into the terms of another. "
                "This is the core analytical step -- finding common meaning "
                "expressed in different language."
            ),
            "output": "Translated constructs across all studies"
        },
        "step_6_synthesizing_translations": {
            "description": (
                "Develop third-order constructs -- new interpretations "
                "that go beyond what any single study found."
            ),
            "output": "Third-order constructs (the synthesis)"
        },
        "step_7_expressing_the_synthesis": {
            "description": "Write up the synthesis in a form accessible to the audience",
            "output": "Published meta-synthesis paper"
        }
    }

Reciprocal translation:
  Studies are about similar things. Translate them into each other.
  "Study A calls it 'navigating uncertainty'; Study B calls it
   'managing ambiguity'; Study C calls it 'living with not knowing'.
   The overarching construct is 'Tolerating the Unknown.'"

Refutational synthesis:
  Studies contradict each other. Explore why.
  "Study A found empowerment through peer support; Study B found
   peer support increased anxiety. This refutation may be explained
   by the stage of illness at which support was received."

Line of argument synthesis:
  Studies address different aspects that together form a whole.
  "Study A covers diagnosis, B covers treatment, C covers recovery.
   Together they reveal a trajectory of 'Reconstructing Identity.'"

Stage 1: Free coding of findings
  - Treat the findings sections of included studies as data
  - Code them line by line, as in primary qualitative analysis

Stage 2: Organizing codes into descriptive themes
  - Group codes into descriptive themes
  - These are "close to" the original studies

Stage 3: Generating analytical themes
  - Go beyond the content of the original studies
  - Generate new interpretive constructs
  - Answer the synthesis research question

Tools for appraising qualitative study quality:

  CASP Qualitative Checklist (10 items):
    - Was there a clear statement of aims?
    - Is a qualitative methodology appropriate?
    - Was the research design appropriate?
    - Was the recruitment strategy appropriate?
    - Was data collected in a way that addressed the research issue?
    - Was the relationship between researcher and participants considered?
    - Were ethical issues considered?
    - Was data analysis sufficiently rigorous?
    - Was there a clear statement of findings?
    - How valuable is the research?

  JBI Checklist for Qualitative Research (10 criteria)

Decision: Include all studies or exclude low-quality studies?
  - Sensitivity analysis: Run the synthesis with and without
    lower-quality studies to see if conclusions change.