Quantitizing, commonly understood to refer to the numerical translation, transformation, or conversion of qualitative data, has become a staple of mixed methods research. Typically glossed are the foundational assumptions, judgments, and compromises involved in converting disparate data sets into each other and whether such conversions advance inquiry. Among these assumptions are that qualitative and quantitative data constitute two kinds of data, that quantitizing constitutes a unidirectional process essentially different from qualitizing, and that counting is an unambiguous process. Among the judgments are deciding what and how to count. Among the compromises are balancing numerical precision with narrative complexity. The standpoints of ``conditional complementarity,'' ``critical remediation,'' and ``analytic alternation'' clarify the added value of converting qualitative data into quantitative form.

The new imperative in the health disciplines to be more methodologically inclusive has generated a growing interest in mixed research synthesis, or the integration of qualitative and quantitative research findings. Qualitative metasummary is a quantitatively oriented aggregation of qualitative findings originally developed to accommodate the distinctive features of qualitative surveys. Yet these findings are similar in form and mode of production to the descriptive findings researchers often present in addition to the results of bivariate and multivariable analyses. Qualitative metasummary, which includes the extraction, grouping, and formatting of findings, and the calculation of frequency and intensity effect sizes, can be used to produce mixed research syntheses and to conduct a posteriori analyses of the relationship between reports and findings. © 2006 Wiley Periodicals, Inc. Res Nurs Health 30: 99–111, 2007

Mixed methods–mixed research synthesis is a form of systematic review in which the findings of qualitative and quantitative studies are integrated via qualitative and/or quantitative methods. Although methodological advances have been made, efforts to differentiate research synthesis methods have been too focused on methods and not focused enough on the defining logics of research synthesis—each of which may be operationalized in different ways—or on the research findings themselves that are targeted for synthesis. The conduct of mixed methods–mixed research synthesis studies may more usefully be understood in terms of the logics of aggregation and configuration. Neither logic is preferable to the other nor tied exclusively to any one method or to any one side of the qualitative/quantitative binary.

Research from JAMA Internal Medicine — “Are You at Peace?” — One Item to Probe Spiritual Concerns at the End of Life

Objectives:To validate the QUAL-E, a new measure of quality of life at the end of life.Methods:We conducted a cross-sectional study to assess the instrument's psychometric properties, including the QUAL-E's associations with existing measures, evaluation of robustness across diverse sample groups, and stability over time. The study was conducted at the VA and Duke University Medical Centers, Durham, North Carolina, in 248 patients with stage IV cancer, congestive heart failure with ejection fraction ≤20%, chronic obstructive pulmonary disease with FEV₁≤ 1.0 l, or dialysis-dependent end stage renal disease. The main outcome measures included QUAL-E and five comparison measures: FACIT quality of life measure, Missoula-VITAS Quality of Life Index, FACIT-SP spirituality measures, Participatory Decision Making Scale (MOS), and Duke EPESE social support scales.Results:QUAL-E analyses confirmed a four-domain structure (25 items):life completion(α = 0.80),symptoms impact(α = 0.87),relationship with health care provider(α = 0.71), andpreparation for end of life(α = 0.68). Convergent and discriminant validity were demonstrated with multiple comparison measures. Test–retest reliability assessment showed stable scores over a 1-week period.Significance of results:The QUAL-E, a brief measure of quality of life at the end of life, demonstrates acceptable validity and reliability, is easy to administer, performs consistently across diverse demographic and disease groups, and is acceptable to seriously ill patients. It is offered as a new instrument to assist in the evaluation of the quality and effectiveness of interventions targeting improved care at the end of life.