Single-System Studies
Single-System Studies
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Social work practice at all system levels involves action leading to behav- ioral or cul tural change. The primary role of social work research is to provide knowledge that contributes to such professional action. vVhile descriptive research about human and cultural conditions, as discussed elsc·where in this volume, can be valuable for guiding professional action,
knowing how to most effectively support change is critical for practice. A central question for social work research, therefore, is “what works” in practice, what works to address what goals and issues, with what populations, under what contextual conditions. While descriptive research ca11 suggest hypotheses, the only way to really determ ine howweU any form of practice works is to test it, under the most rigorous conditions possible.
Experimen tal research is therefore critical for advancing social work practice. Unfon·tunately, only a small proportion of social work research is experimental (Thyer, 200 I). Experimental research is of two types, group experiments (e.g., randomized clinical trials [RCTs]) and single-system research (SSR, also commonly referred to as single case resealfch, N of 1 research, or interrupted time-series experiments). Single-system experi- mental research, however, has often been underemphasized in social work, in part because of limited understanding of the logic of natural science among social scientists and wcial workers.
SSR is experimental research; its purpose, as noted by Horner and colleagues (2005), is “to document causal, or functional, relationships between independent and dependent variables” (p. 166). The methodology has been used with all system levels-micro, mezzo, and macro-m aking it widely appliCable for studying social work concerns. For example, Moore, Delaney, and Dixon (2007) studied ways to enhance quality of life for quite impaired patients with Alzheimer’s disease using single-system methods and were able to both individualize interven tions and produce generalizable knowledge from their study in ways that perhaps no other research strategy could equal. In another example, Serna, Schumaker, Sherman, and Sheldon (1991) worked to improve family interactions in families with preteen and teenage children. The first several interventions they attempted (interventions that are common in social work practice) fa iled to produce changes that generalized to homes. Single-system procedures, however, allowed them to rigorously and sequentially test multiple approaches until an adequately powerful intervention strategy was refi ned. (Note that Lhis would be impossible using group methods without under- mining the rigor of the study.)
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242 PART II • QUANTITATIV( APPROACHES: TYPES OF STUDIES
Turning to larger systems, single-system designs can be used, for example, to examine the relative effects of different sets of organizational and community contex.’tS on the effectiveness of school violence prevention efforts (Mattaini, 2006). Furthermore, Jason, Braciszewski, Olson, and Ferrari (2005) used multiple baseline single-system methods to test the impact of policy changes on the rate of opening mutual help recovery homes for substance abusers across entire states. Embry and colleagues (2007) used a similar design to test the impact of a statewide intervention to reduce sales of tobacco to m inors.
Although single-system methods are widely used for practice monitoring in social work, research and monitoring are different endeavors with different purposes. This chapter focuses on the utility of SSR for knowledge building. Readers interested in 1 he use of single-system methods for practice monitoring are likely to find Bloom, Fischer, and Orme (2006) and Nugent, Sieppert, and Hudson (2001 ) particularly helpful.
Understanding Single-System Research
Single-system experimental research relies on natural science methodologies, while much of the rest of social work research, including a good deal of group experimental research, emphasizes social science methods. The differences are real and substantive. In 1993, Johnston and Pennypacker noted,
The natural sciences have spawned technologies that have dramatically transformed the h uman culture, and the pace of technological development only seems to increase. The social sciences have yet to offer a single well-developed technology that has had a broad impact on daily life. (p. 6)
There is lillie evidence that this s ituation has changed. The reasons involve both meth- ous and philosophies of science. Critically, however, analysis is central in most natural sci- ences and is best achieved through the direct manipulation of variables and observation of the impact of those manipulations over a period of time. As one expert noted, the heart or SSR is demonstrating influence by “mak[ing] things go up and down” under precisely specified conditions (J. Moore, personal communication, 1998). Such analysis is often best done one case at a time.
SSR has particular strengths for social work research. SSR focuses on the individual sys- tem, the individ ual person, the individual family, and the individual neighborhood, typi- cally the level of analysis of primary interest in social work. Furthermore, SSR allows detailed analysis of intervention outcomes for both responders and nonresponders, which is critical for practice because each client, not just the average client, must be of concern. Relevant variables can then be further manipulated to understand and assist those who have not responded to the initial manipulations (Horner ct al., 2005). furthermore, as noted by Horner and colleagues (2005), rigorous SSR can be implemented in natural and near natural conditions, making it a practical strategy for elaborating and refining inter- ventions with immediate applicabili ly in standard service setti ngs.
Contrasts With Group Experimental Research Most group experimental research relies on comparing the impact of one or more inter- ventions (e.g., experimental treatment vs. standard care, placebo therapy. or no treat- ment) applied to more or less equivalent samples. Ideally, these samples are randomly
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selected from a larger population of interest, but in social work research, it is more common for samples to be chosen on the basis of availability or convenience. Comparison studies include (a) classical experiments with randomization and no- intervention controls, (b) contrast studies that compare one intervention with another, and (c) a wide range of quasi-experimental designs. W”hilc comparison studies, espe- cially randomized clinical trials, are often regarded as the gold standard for ex-perimen- tal research, the often unacknowledged strategic and tactical limits of !>uch comparison studies are serious (Johnston & Pennypacker, 1993, p. 119). Conclusions rely on proba bilistic methods drawn from the social sciences, rather than on the analytic methods of SSR. As a result, Johnston and Pennypacker ( 1993) suggest that comparison studies “often lead to inappropri~te inferences with poor generali ty, based on improper evidence gathered in support of the wrong question, thus wasting the field’s limited experimental resources” (p. 120). (Similar criticisms have been made of much descrip- tive research.)
While comparison studies are useful for many purposes (as outlined elsewhere in this volume), it is important to understand their limits. As is true of most social science research, comparison studies at their core are actuarial. They attempt to determine which of two procedures produces better results on average (Johnston & Pennypacker, 1993 ). Jn pretty much all cases, however, some persons (or groups, organizations, or communities) will do bcller, some will show minimal change, and others will do worse. Comparison studies by their nature do not provide in formation about the variables that may explain why these within-group differences occur; rather, such differences, while acknowledged, are generally treated as error. Analytic natural science methods, however, including rigor- ous SSR, can do so.
In addition,
although two procedures may address the same general behavioral goal, a number of detailed differences among them may often make each an inappropriate metric for the other. These differences may include (a) the exact characteristics of the populations and settings where each works best, (b) the target behaviors and their controlling influences, or (c) a variety of more administrative considerations such as the characteristics of the personnel conducting each procedure. (Johnston & Pennypacker, 1993, p. 122)
Similar issues are present for large system work like that done in community practice and prevention science. Biglan, Ary, and Wagenaar (2000) note a number of limitation!> lo the use of comparison studies in community research, including “(a) the high cost of research d ue to the number of communities needed in such studies, (b) the difficulty in developing generalizable theoretical principles about community change proccs. e through randomized trials, (c) the obscuring of relationships that are unique to a subset of communities, and (d) the problem of diffusion of intervention activities from inter- vention to control communities” (p. 32) . SSR, particularly the use of sophisticated time- series designs with matched communities (Biglan et al., 2000; Coulton, 2005), provides powerful alternatives that do not suffer from these limitations.
Analytic investigations, in contrast to actuarial studies, allow the researcher to manip- ulate identified variables one at a time, oflen with one system at a time, to explore the impact of those variables and the differences in such impacts across systems, as well as to test hypoth eses about the differences found. This is the natural science approach to inves- tigation, this is how generalizable theory is built, and this is primarily how scientific advance occurs. Kerlinger (1986) states, “The basic aim of science is theory. Perhaps less
244 PART II 8 Q uANTITATIVE APPROACH~S: T YPES Of STUDIES
cryptically, the basic aim of science is to explain na tural phenomena” (p. 8). Social ·vork needs to be able to understand how personal and contextual factors important to client welfare and human rights can be influenced, and analytic studies are needed to move the field in that direction and thus “transform . .. human culture” (Johnston & Pennypacker, l ~93, p. 6 ). Once the relevant variables and contingent relationships have been clarified through analytic s tudies, group experimental comparisons may have unique contribu- tions to make in organizational cost-benefit comparisons and other areas as outlined else where in this volume.
The Logic of Single-System Research The basic logic underlying SSR is straightforward. Data on the behavior of interest are collected over a period of time until the baseline rate is dearly established. Intervention is then introduced as data continue to be collected. In more rigorous single-system studies, intervention is independently introduced at several points in time, while holding contex- tual conditions constant, to confirm the presence of functional (causal) relationships. (Repeated measurement of the dependent variable[s] over time, therefore, is central to SSR.) As discussed later, a great deal is now kJ1own about how to achieve high levels of experimental control and validity in the use of these procedures.
Behaviors of interest in SSR may include those of individuals (clients, family members, service providers, policy makers) as well as aggregate behaviors among a group (students in a class, residents in a state). In addition, behavior as used here includes all ronns of actions in context (Lee, 1988), including motor behaviors (e.g., going to bed), visceral behaviors {e.g., bodily changes associated with emotions), verbal behaviors (e.g., speaking or covert self-talk), and observational behaviors (e.g., hearing or dreaming).
A number of dimensions of behavior can be explored and potentially changed in SSR, including rate (frequency by uni t of time), in tensity, duration, and variability. Single- system researchers therefore can measure the impact of intervention (or prevention) on (a) how often something occurs (e.g., rate of suicide in a state), (b) how strongly it is present (e.g., level of stress), (c) how long something occurs (e.g., length of tantrums), and (d) how stable a phenomenon is (e.g., whether spikes in violence can be eliminated in a neighborhood). Nearly everything that social work research might be interested in, therefore, can be studied using SSR techniques, from a client’s emotional state to rates of violations of human rights v.rithin a population.
Nearly all SSR designs depend on first establishing a stable baseline, the rate (or inten- sity, duration, variabili ty) of behavior before intervention. Since all behavior varies to some extent over time, multiple observations are generally necessary to establish the extent of natural variability. In some cases, a baseline of as few as three data points may be adequate; in general, however, the more data points collected to establish baseline rates, the greater the rigor of the study.
Once a stable baseline has been obtained, it is possible to introduce a systematic varia- tion in conditions (i.e., an intervention, or one in a planned series of interventions) and to determine whether that intervention is followed by a change in the behavior(s) of interest. The general standard for change in SSR is a shift in level, trend, or variability that is large, clearly apparent, relatively immediate, and clinically substantive. (Technical details regarding how such changes can be assessed graphically and statistically are provided later in this chapter.) Figure 14.1 presents the most basic structure of the approach, depicting a clear change between phases.