Toward Integrating Qualitative and Quantitative Methods: An Introduction

Department of Health Behavior and Health Education, School of Public Health, University of North Carolina, Chapel Hill 27599-7400.
Health education quarterly 02/1992; 19(1):1-8. DOI: 10.1177/109019819201900101
Source: PubMed

ABSTRACT Both the qualitative and quantitative paradigms have weaknesses which, to a certain extent, are compensated for by the strengths of the other. As indicated in this article, the strengths of quantitative methods are that they produce factual, reliable outcome data that are usually generalizable to some larger population. The strengths of qualitative methods are that they generate rich, detailed, valid process data that usually leave the study participants' perspectives in tact. This article discusses how qualitative and quantitative methods can be combined and it introduces the articles included in this issue.

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Available from: Kenneth Mcleroy, Sep 28, 2015
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    • "Various evaluation methods and strategies have been developed [8]. Evaluations that mix methodologies are considered robust [9] [10] and particularly useful in the medical setting [11] [12]. There are many ways to combine methods, such as mixing qualitative and quantitative methods [13], involving users of varying perspectives for data collections [14], or using various data collection methods to achieve greater data validity. "
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    ABSTRACT: Underspecified user needs and frequent lack of a gold standard reference are typical barriers to technology evaluation. To address this problem, this paper presents a two-phase evaluation framework involving usability experts (phase 1) and end-users (phase 2). In phase 1, a cross-system functionality alignment between expert-derived user needs and system functions was performed to inform the choice of "the best available" comparison system to enable a cognitive walkthrough in phase 1 and a comparative effectiveness evaluation in phase 2. During phase 2, five quantitative and qualitative evaluation methods are mixed to assess usability: time-motion analysis, software log, questionnaires - System Usability Scale and the Unified Theory of Acceptance of Use of Technology, think-aloud protocols, and unstructured interviews. Each method contributes data for a unique measure (e.g., time motion analysis contributes task-completion-time; software log contributes action transition frequency). The measures are triangulated to yield complementary insights regarding user-perceived ease-of-use, functionality integration, anxiety during use, and workflow impact. To illustrate its use, we applied this framework in a formative evaluation of a software called Integrated Model for Patient Care and Clinical Trials (IMPACT). We conclude that this mixed-methods evaluation framework enables an integrated assessment of user needs satisfaction and user-perceived usefulness and usability of a novel design. This evaluation framework effectively bridges the gap between co-evolving user needs and technology designs during iterative prototyping and is particularly useful when it is difficult for users to articulate their needs for technology support due to the lack of a baseline.
    Journal of Biomedical Informatics 12/2013; 52. DOI:10.1016/j.jbi.2013.12.004 · 2.19 Impact Factor
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    • "When studying a sensitive subject, it is important to leave the participants' perspective intact while collecting rich, detailed and valid data. As recommended by Steckler et al. (1992), a qualitative design is most suitable for this purpose. The I-Change Model (De Vries et al., 2003, 2008; see Fig. 1) served as the theoretical framework of this research. "
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    ABSTRACT: Objective: two studies aimed to explore the advice Dutch midwives give and the information Dutch pregnant women and partners of pregnant women receive about alcohol consumption in pregnancy. Design: study 1 included individual semi-structured interviews with midwives. Study 2 involved focus groups and individual semi-structured interviews with pregnant women and partners. Interview content was based on the I-Change Model. Setting: study 1 was conducted nation-wide; Study 2 was conducted in the central and southern regions of the Netherlands. Participants: 10 midwives in Study 1; 25 pregnant women and nine partners in Study 2. Measurements and findings: study 1 showed that midwives intended to advise complete abstinence, although this advice was mostly given when women indicated to consume alcohol. Midwives reported to lack good screening skills and sufficient knowledge about the mechanisms and consequences of antenatal alcohol use and did not involve partners in their alcohol advice. In Study 2, the views of pregnant women and partners were congruent to the findings reported in Study 1. In addition, pregnant women and partners considered midwives as an important source of information on alcohol in pregnancy. Partners were interested in the subject, had a liberal view on antenatal alcohol use and felt ignored by midwives and websites. Pregnant women indicated to receive conflicting alcohol advice from their health professionals. Key conclusions: midwives' alcohol advice requires improvement with regard to screening, knowledge about mechanisms and consequences of antenatal alcohol use and the involvement of the partners in alcohol advice during pregnancy. Implications for practice: training should be given to Dutch midwives to increase their screening skills and their alcohol related knowledge to pregnant women. Research is needed to determine how the midwife's alcohol advice to the partner should be framed in order to optimise the partner's involvement concerning alcohol abstinence in pregnancy. More attention to the topic at a national level, for example via mass media campaigns, should also be considered to change views about alcohol use during pregnancy in all stakeholders.
    Midwifery 11/2013; 29(11). DOI:10.1016/j.midw.2012.11.014 · 1.57 Impact Factor
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    • "The Dholuo version was then independently translated back into English. The results of the translated English version were compared with the original English version and decentered, i.e., both the source and the target language versions were modified to make them congruent [15,16]. "
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    ABSTRACT: The two issues mostly affecting the success of tuberculosis (TB) control programmes are delay in presentation and non-adherence to treatment. It is important to understand the factors that contribute to these issues, particularly in resource limited settings, where rates of tuberculosis are high. The objective of this study is to assess health-seeking behaviour and health care experiences among persons with pulmonary tuberculosis, and identify the reasons patients might not complete their treatment. We performed qualitative one-on-one in-depth interviews with pulmonary tuberculosis patients in nine health facilities in rural western Kenya. Thirty-one patients, 18 women and 13 men, participated in the study. All reside in an area of western Kenya with a Health and Demographic Surveillance System (HDSS). They had attended treatment for up to 4 weeks on scheduled TB clinic days in September and October 2005.The nine sites all provide diagnostic and treatment services. Eight of the facilities were public (3 hospitals and 5 health centres) and one was a mission health centre. Most patients initially self-treated with herbal remedies or drugs purchased from kiosks or pharmacies before seeking professional care. The reported time from initial symptoms to TB diagnosis ranged from 3 weeks to 9 years. Misinterpretation of early symptoms and financial constraints were the most common reasons reported for the delay.We also explored potential reasons that patients might discontinue their treatment before completing it. Reasons included being unaware of the duration of TB treatment, stopping treatment once symptoms subsided, and lack of family support. This qualitative study highlighted important challenges to TB control in rural western Kenya, and provided useful information that was further validated in a quantitative study in the same area.
    BMC Public Health 06/2011; 11(1):515. DOI:10.1186/1471-2458-11-515 · 2.26 Impact Factor
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