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Research Methods: Managing Primary Study Quality in Meta-Analyses Research in Nursing & Health, 2003, 26, 322–333 Focus on Research Methods Research Methods: Managing Primary Study Quality in Meta-Analyses Vicki S. Conn,* Marilyn J. Rantz* School of Nursing, University of Missouri–Columbia, Columbia, MO 65211 Received 3 March 2003; accepted 8 May 2003 Abstract: Meta-analyses synthesize multiple primary studies and identify patterns of relationships. Differences in primary study methodological quality must be addressed for meta-analysis to produce meaningful results. No single standard exists for addressing these quality variations. Quality measurement scales are fraught with development and application problems. Several strategies have been proposed to address quality. Researchers can set minimum levels for inclusion or require that certain quality attributes be present. An inclusive method is to weight effect sizes by quality scores. This allows the inclusion of diverse studies but relies on questionable quality measures. By considering quality an empirical question, meta-analysts can examine associations between quality and effect sizes and thus preserve the purpose of meta-analysis to systematically examine data. Researchers in- creasingly are combining strategies to overcome the limitations of using a single approach. Future work to develop valid measures of primary study quality dimensions will improve the ability of meta-analysis to inform research and nursing practice. ß 2003 Wiley Periodicals, Inc. Res Nurs Health 26:322–333, 2003 Keywords: meta-analysis; research methods An information explosion has occurred over the increasingly common (Cooper, 1998). Well-con- last 50 years as the volume of scientific literature ducted meta-analyses can guide future research has grown exponentially. Researchers strive to and inform practice (Conn & Armer, 1996). The design new studies based on existing knowledge results of meta-analyses are determined both by but face the daunting task of summarizing what the studies included and their management in the is known from extant research. Problems with meta-analysis process. The scientific rigor of po- narrative reviews have stimulated interest in quan- tential primary studies varies dramatically, and titative integration of existing research, both as a several strategies have been proposed to address foundation for future research and as a basis for quality (Moher et al., 1999; Saunders, Soomro, nursing practice. As the need to systematically Buckingham, Jamtvedt, & Raina, 2003). One solu- synthesize research grows more critical, use of the tion is to exclude all but the most rigorous studies. powerful tool known as meta-analysis is becoming Another approach is to include studies of varied Contract grant sponsor: NIH NINR (to Vicki Conn, principal investigator); Contract grant number: RO1NR07870. Correspondence to Vicki S. Conn, S317 School of Nursing–MU, Columbia, MO 65211. *Professor. Published online in Wiley InterScience (www.interscience.wiley.com) DOI: 10.1002/nur.10092 322 ß 2003 Wiley Periodicals, Inc. MANAGING PRIMARY STUDY QUALITY IN META-ANALYSIS / CONN AND RANTZ 323 quality and then address quality through weight- article we discuss (a) ways that researchers con- ing or moderator analysis procedures (Cooper, ceive of quality and assess it, (b) associations 1998). No single standard exists for managing this between study quality and outcomes, and finally, complex issue. In this article we examine stra- (c) strategies to manage study quality in quanti- tegies for managing the varied quality of primary tative syntheses. Although meta-analysis is use- studies in meta-analysis. ful in both intervention and descriptive research, we address the intervention category because studies in this category are often used to direct BRIEF OVERVIEW OF nursing practice or to suggest further intervention META-ANALYSIS research. Readers interested in further information about meta-analysis may refer to Cooper (1998) or In meta-analysis research, the pooled results of to frequently updated Web sites (e.g., that of the several primary studies are analyzed to provide a University of Maryland, http://ericae.net/meta/). quantitative review of existing empirical evidence. Meta-analysis follows a systematic process: (a) formulate the research problem, (b) search for METHODOLOGICAL QUALITY eligible studies, (c) evaluate available data, (d) pool results, (e) quantitatively analyze, and (f) Both consumers of research and the researchers interpret findings taking into account the strengths themselves consistently express concerns about and limitations of the existing studies (Cooper, methodological quality. The emphasis on quality 1998). Meta-analysts calculate an overall estimate is consistent with the goals of science to produce of the magnitude of association between the valid knowledge (Petersen & White, 1989). This variables they study. discussion focuses on internal validity aspects of Although the overall effect estimate is very quality because external validity cannot be present important, it is sometimes of equal interest to without internal validity and because external investigate differences in effect size associated validity is not an inherent attribute of individual with variations between studies by conducting a studies (Juni, Altman, & Egger, 2001). moderator analysis. Moderator analysis estimates Explicit definitions of quality generally focus effect sizes separately for different values of the on the extent to which studies generate reprodu- moderator variable under study. Intervention cible information (Moher et al., 1995). ‘‘Quality attributes and characteristics of samples are gives us an estimate of the likelihood that the typical variables for moderator analyses. For results are a valid estimate of the truth,’’ according example, in a recent meta-analysis Conn, Valen- to Moher et al. (1995, p. 62). Quality is determined tine, & Cooper (2002) reported the overall effect by the extent to which study design, conduct, and size of interventions to increase physical activity analysis systematically avoid or minimize poten- among aging adults. However, the researchers tial sources of bias (Moher et al., 1995). Sys- calculated significantly larger effect sizes for tematic bias can contribute to error, which could particular intervention components (e.g., self- favor either the experimental or the control/ monitoring) and for studies with particular subject comparison treatment. A loss of precision may characteristics (e.g., patients with specific chronic contribute to error, in which potentially effica- illnesses). This moderator analysis is especially cious treatments are abandoned as ineffective. useful for nursing intervention research, in which Studies with methodological problems can con- a basic intervention often varies somewhat tribute added variability that reduces precision between studies. and hampers scientific progress (Detsky, Naylor, The discipline of nursing will realize the im- O’Rourke, McGeer, & L’Abbe, 1992; Lohr & mense potential benefits of quantitative synthesis Carey, 1999; West et al., 2002). only when meta-analytic methods are applied Unfortunately, no gold standard exists for appropriately to primary studies. Meta-analysts determining the ‘‘true’’ scientific rigor of primary must address the critically important issue of studies (Detsky et al., 1992). Most quality dimen- primary study quality during study selection or sions have to do with preventing bias in selection, data management or both. Generally, some of the performance, detection, or attrition (Juni et al., research reports that are retrieved and assessed for 2001). Table 1 summarizes commonly noted com- inclusion in meta-analyses will be strong, and ponents of intervention research quality (Balk others will possess weaknesses. The challenge is et al., 2002; Chalmers, Celano, Sacks, & Smith, to generate the most useful information possible 1983; Juni et al., 2001; Kunz & Oxman, 1998; from the existing empirical evidence. In this Moher et al., 1998; Schulz, Chalmers, & Altman, 324 RESEARCH IN NURSING & HEALTH Table 1. Components of Primary Intervention Research Methodological Quality for Meta-Analysis Concept Issues Sample selection Sample attributes appropriate for study purpose Intervention tested with important subgroups Recruitment Recruitment strategy prevents bias Description of potential subjects who declined participation Sample size adequacy Size adequate to provide a sufficiently precise estimate of effect size Random assignment Central system generates an unpredictable assignment sequence Allocation concealment/randomization blinding Comparison group Nature of the comparison group appropriate for the area of science Management of preintervention differences between comparison groups Blinding/masking Participants Care providers Assessors measuring outcomes Data analysts Interventions Intervention reproducible by others Intervention consistent with theory Treatment integrity Prevention of treatment contamination Attrition management Attrition prevented and reported Intention to treat analysis Outcome measures Objective measures when possible Construct validity of instruments ascertainable Adequate reliability to provide sufficiently precise estimate of effect size Appropriate follow-up period to measure outcomes Avoid mono-operation bias, if appropriate Statistical analysis Assumptions of analysis consistent with data Significance level appropriate given number of tests conducted on data Potential confounders not controlled in design addressed in analysis Exact test statistic
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