Qualitative description: A less sophisticated approach for junior qualitative researchers

Author

Professor, Nursing and Midwifery Care Research Center, Mashhad University of Medical Sciences, Mashhad, Iran

Abstract

 It is often difficult for junior qualitative researchers to adopt theoretically and technically sophisticated qualitative methodologies and to manage and tolerate the complexity of its data collection and analysis to generate high-quality qualitative findings. The purpose of this editorial is to describe a less sophisticated qualitative approach known as qualitative descriptive study or qualitative description (QD), which is well suited to junior health sciences researchers as well as to clinicians who ultimately should translate findings into practice.

 Among dominant qualitative methodologies including grounded theory, ethnography, phenomenology, and narrative approaches, which are regularly employed to pursue a variety of topics in health sciences, there is also a potentially important qualitative methodology titled qualitative description (QD) which is often seen by the qualitative researchers as a lower level form of inquiry and inferior use of qualitative data (1). Polit and Beck, in their analysis of 1,000 qualitative studies published in eight journals between 2005 and 2006 found that about 20% of qualitative studies adopted phenomenology, 11% grounded theory, and 1% ethnography as a method of inquiry. However, more than half (52%) were descriptive qualitative studies without any link to a qualitative tradition (2).

     Nevertheless, qualitative descriptive studies are infrequently discussed in detail in research methods textbooks. Qualitative descriptions are generally viewed as the “poor cousin” to more developed qualitative methods and its adoption in health research is limited and is often criticised for being too basic and lacking rigour (3). While, Sandelowski (2000), who was inspired by Thorne, Kirkham, and MacDonald-Emes' insightful discussion of ``interpretive description'' (1997), commented that although descriptive designs, either in quantitative or qualitative approaches, 

are typically illustrated in research texts as being on the lowest rung of the research design hierarchy; but  increasing complexity of qualitative methods makes the rediscovery of QD necessary (4). Thorn et al. (1997) proposed a coherent set of strategies for conceptual orientation, sampling, data construction, analysis, and reporting by which health science researchers can use an interpretive descriptive approach to develop knowledge about human health and illness (5).

      Qualitative descriptions focus on the Who, What, and Where of the experience (4, 6). They typically are an eclectic but reasonable combination of sampling, data collection, analysis, and re-presentation techniques, which uses low inference interpretation to present the facts using everyday language (4, 7). Also it can be used in mixed method research, in questionnaire and intervention development studies as well as in cases of need assessments and where time and resources are limited (6,8).

      According to Sandelowski, "basic or fundamental" QD differs from other types of qualitative research, in the sense that it is essentially descriptive rather than interpretive in focus. However, it should not be understood as a low-quality approach; instead it must be viewed as a valuable end-product in itself, and not simply as an entry-point (9). The misconception that QD is less theoretical is unmerited as evidenced by Sandelowski (2010) (10). The philosophical, ontological, epistemological and methodological assumptions underpinning QD, present it as a systematic approach to conduct qualitative inquiry.

      In terms of theoretical orientation, contrary to dominant qualitative methodologies, which are based on specific methodological frameworks emerging from idiosyncratic disciplinary traditions, qualitative descriptive studies just follow the general principles of naturalistic inquiry; so that researchers who conduct such studies have the least pre-existing theoretical and philosophical commitments (4).

      The ontological position of naturalistic research is relativism, which holds the view that reality is subjective and varies from person to person and this is evident in the reporting of findings from QD research. The epistemological position of qualitative research is subjectivism, which accepts the reality of all objects, relies entirely on individuals' subjective awareness of it, and emphasizes on the researcher's contribution, and this is also congruent with the QD approach. With respect to methodological assumptions, QD tries to describe the phenomenon literally but attempts to interpret the findings without moving too far from that literal description (11). Regarding methods assumptions, researchers adopting a QD must attend to: sampling, collecting and analyzing rich data (4); as well as extensive interaction with participants, considering their disciplinary connection and the assumptions they make about the topic under study (11).

     Regarding the sampling in a qualitative descriptive design, virtually any purposeful sampling technique using maximum variation strategy can be used (4, 11, 12).

     Data collection techniques usually include minimally to moderately structure open-ended individual and/or focus group interviews as well as observations of targeted events and the examination of records, reports, photographs, and documents and artifacts (4, 6, 11, 12).

     Data analysis strategy of choice in qualitative descriptive studies is qualitative content analysis (4) or thematic analysis (11), which are often incorrectly used interchangeably. There are many similarities in the above approaches including searching for patterns and themes and both can be used with good effect in the analysis of data from qualitative description studies. Like other qualitative research approaches, qualitative descriptive studies generally are characterized by simultaneous data collection and analysis (12).

     For data re-presentation in QD, the expected outcome would be a straight descriptive summary of the informational contents of data organized in a way that best fits the data (4). For this reason, informants' experiences should be described in a factual language similar to the informants' own language to facilitates understanding of a selected phenomenon across disciplines of health science researchers (6, 13).

     Indicators of rigor for QD must reflect the research question through providing a thorough audit trail to review the decision trail of the study, evidence of prolonged engagement and immersion in the data and including the participants’ voices within the findings as well as the practice of reflexivity to reveal the quality of the research findings (11)

     In conclusion, QD follows the tenets of qualitative research and is the method of choice when straight descriptions of phenomena are desired. It is well suited for "who", "what” and "where" questions about human behaviour, motives, and views. Although sometimes, researchers feel obliged to entitle their work as phenomenology, grounded theory or ethnography when in fact it is not, the QD would be an appropriate alternative approach. Because, as Sandelowski (2000) says  it is alive and well, but needs only to be re-discovered as a valuable qualitative approach and recovered for health sciences research.

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