Statistical Analyses Paper

A CONTENT ANALYSIS OF QUANTITATIVE RESEARCH IN JOURNAL OF MARITAL AND FAMILY THERAPY:

A 10-YEAR REVIEW

Elizabeth O. Parker, Jennifer Chang, and Volker Thomas University of Iowa

We examined the trends of quantitative research over the past 10 years in the Journal of Marital and Family Therapy (JMFT). Specifically, within the JMFT, we investigated the types and trends of research design and statistical analysis within the quantitative research that was published in JMFT from 2005 to 2014. We found that while the amount of peer-re- viewed articles have increased over time, the percentage of quantitative research has remained constant. We discussed the types and trends of statistical analysis and the implica- tions for clinical work and training programs in the field of marriage and family therapy.

In the field of marriage and family therapy (MFT), the role of research has greatly evolved over the past several decades. Competing with other mental health fields, many believe that the field should continue to provide evidence that supports the effectiveness of MFT interventions in improving the clients’ well-being (Hawley, Bailey, & Pennick, 2000). Additionally, Hawley and his colleagues state that, “research can strengthen the field by legitimizing [marriage and] family ther- apy as an approach to other mental health disciplines and third-party payers and by helping improve services to our consumers, the clients” (p. 9).

The evolution of MFT has been influenced by the use of different qualitative and/or quantita- tive research methods and procedures (Køppe & Dammeyer, 2014). With the advancement of tech- nology, statistical analyses have become easier to complete and have become more sophisticated over time (Køppe & Dammeyer, 2014). In particular, in recent years, technology has advanced more quickly than ever before, expanding the possibilities of ways quantitative research data may be analyzed. When examining the field of MFT over the past 10 years, how the trends in quantita- tive research methods and statistical analyses are reflected in the top journals of the field has not been investigated. In this study, the authors conducted a content analysis to examine these trends in a leading journal of MFT, the Journal of Marital and Family Therapy (JMFT).

LITERATURE REVIEW

The Research–Practice Gap According to Sprenkle and Piercy (2005), “Over the course of its history, the field of MFT has

had an ambivalent relationship with research” (p. 3). While the founding of MFT was built on early family therapy pioneers, or “researchers,” who examined the interactional patterns of prob- lem families, the field has maintained only a relatively small empirical research tradition compared to its clinical component more than 70 years later (Sprenkle & Piercy, 2005). One reason that may explain this discrepancy is that a master’s degree was established since 1970 to be the minimal degree required to enter into the field (Sprenkle & Piercy, 2005). Additionally, many master’s pro- grams do not include a rigorous research curriculum in their training (Crane, Wampler, Sprenkle, Sandberg, & Hovestadt, 2002; Hawley & Gonzalez, 2005; Sprenkle & Piercy, 2005). With that, it is

Elizabeth O. Parker, MA, Department of Rehabilitation and Counselor Education, University of Iowa; Jennifer

Chang, BA, Department of Counseling Psychology, University of Iowa; and Volker Thomas, PhD, Department of

Rehabilitation and Counselor Education, University of Iowa.

Address correspondence to Elizabeth O. Parker, Department of Rehabilitation and Counselor Education,

University of Iowa, N338 Lindquist Center, Iowa City, Iowa 52242; E-mail: [email protected]

January 2016 JOURNAL OF MARITAL AND FAMILY THERAPY 3

Journal of Marital and Family Therapy 42(1): 3–18 doi: 10.1111/jmft.12138 © 2016 American Association for Marriage and Family Therapy

possible that many master’s level therapists may feel that research is irrelevant to their clinical work and thus may not feel the need to produce research (Ko�suti�c, Sanderson, & Anderson, 2012; Owenz & Hall, 2011).

Although the field of MFT has grown over the last several decades, a research–practice gap is still present (Hawley & Gonzalez, 2005; Owenz & Hall, 2011; Sprenkle & Piercy, 2005). Based on a quali- tative study by Owenz and Hall, a number of barriers have posed as difficulties in bridging the gap:

One common stereotype in the literature is that master’s level students are interested in only becoming practitioners (Crane et al., 2002; Gelso, 2006). When program decisions about student interests are based on this stereotype, students may not receive the inte- grated research–practice training they desire or need, which is a missed opportunity for the students, their programs, and their fields in general. Results from the present study indicate that some master’s students are interested in research, others are ambivalent about it, and some were motivated to apply to doctoral programs.(p. 29)

With varying degrees of interest in research, it is important to support these interests, especially encouraging those who express a desire in conducting research.

Major Trends in MFT Research Sprenkle and Piercy (2005) identified five major trends in the history of MFT research. The

first trend arose during the founding of the field with “soft” research conducted by prominent fam- ily therapy pioneers, such as Gregory Bateson, Murray Bowen, Don Jackson, and Jay Haley (Sprenkle & Piercy, 2005). These “researcher–clinicians,” examined the effects of therapeutic inter- ventions on clients and their families. In terms of methods, they discussed their therapy sessions with one another, reviewed audiotapes of their sessions, and studied live sessions through a one- way mirror (Sprenkle & Piercy, 2005).

To add more rigor to MFT research being conducted, the second trend emerged when family therapists began conducting quantitative and experimental research (Sprenkle & Piercy, 2005). Researchers began operationalizing concepts and developing reliable and valid measures. During this time, outcome research was gaining popularity in comparing family therapy to other treat- ments, such as inpatient or individually based psychotherapies. In addition, process research was on the rise, where researchers began studying the processes that occur within the therapy sessions that affect client outcomes (Sprenkle & Piercy, 2005).

While the second trend focused on quantitative research, the third trend consisted of the con- duct of qualitative research (Sprenkle & Piercy, 2005). Deviating from the analysis of numbers, family therapists instead were concentrating on the thick, rich data that described the “subtleties and complexities of therapy” (Sprenkle & Piercy, 2005, p. 6). The fourth trend combined the sec- ond and third trends together, emphasizing pluralism, accepting a wider array of quantitative and qualitative research. Mixed methods research—the use of both quantitative and qualitative meth- ods—were also become increasingly common (Sprenkle & Piercy, 2005).

Advancement of Technology Currently, the field of MFT is experiencing the fifth trend, “the growing sophistication and

multiplicity of family therapy [research] methods” (Sprenkle & Piercy, 2005, p. 6). Particularly with quantitative research, the evolution of quantitative methods and analyses coincides with the advancement of technology. In more recent decades, the rapid development of computer technolo- gies has “revolutionized statistics and its practice” (Hand, 2009, p. 289). As stated in Køppe and Dammeyer (2014) on the changes in research in psychology and child development:

With the development of technology it has become much easier to complete advanced statistical procedures on a large amount of data. Before the invention of the computer it was difficult–expensive and time consuming–to complete complex statistical procedures on a large amount of data. . . . Today the trend is to use more advanced statistical analyses due to more powerful analytic computer abilities available. This, in turn, may demand an increased attention to how [and which] statistical methods are used in psychology. (p. 332–333)

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While Køppe and Dammeyer (2014) discussed the evolution of research in psychology, similar changes in statistical analyses also can be applied to research in MFT. With MFT research, the growth of technology has given rise to more sophisticated statistical software, and in turn, advanced quantitative analyses, such as different approaches to prediction and regression, multi- level growth modeling, and structural equation modeling (Miller & Johnson, 2014; Sprenkle & Piercy, 2005). Quantitative research approaches have grown exponentially so that it is nearly impossible for an individual to have competence and expertise in all forms of MFT quantitative research (Sprenkle & Piercy, 2005).

JOURNAL OF MARITAL AND FAMILY THERAPY

While there is acknowledgment that the field of MFT is experiencing a rapid growth in quanti- tative research, are these advanced methods and analyses actually being applied and published? In our study, we decided to examine the JMFT because of its large influence on the field of MFT. According to the American Association for Marriage and Family Therapy (AAMFT):

JMFT is a peer-reviewed journal [by the association] that advances the professional understanding of marital and family functioning and the most effective psychotherapeutic treatment of couple and family distress. . . . JMFT publishes articles on research, theory, clinical practice, and training in marital and family therapy.(“Journal of Marital and Family Therapy,” 2015)

Because of its prominence in the field of MFT, it is no surprise that previous content analyses have been conducted on the journal, along with other leading family therapy journals. Past content analyses have focused on the number of trends, such as research topics of interest, the academic degrees and/or institutional affiliations of the authors, the amount and type of research conducted, trends in qualitative research publications, and trends in mixed methods (Faulkner, Klock, & Gale, 2002; Gambrel & Butler, 2013; Hawley & Gonzalez, 2005; Hawley et al., 2000). However, there has not been a content analysis that specifically analyzed the trends of quantitative research published in JMFT, particularly in more recent years.

PURPOSE OF STUDY

The main purpose of this study was to identify the quantitative research trends, over the past 10 years, in the JMFT. More specifically, from 2005 to 2014: (1) Was there an increase of quantita- tive methods used over time? (2) What trends were present in research design methods of quantita- tive research? and (3) What trends were present in statistical analytic methods used in quantitative research?

METHODS

Sample Our sample included published articles in the JMFT from 2005 to 2014. Of the 538 articles

published in JMFT during those years, 376 were identified as peer-reviewed articles. Of the 376 articles identified as peer reviewed, 142 were classified as employing quantitative research methods.

Procedure Our analysis process was conducted in multiple steps. The authors searched through all issues

of JMFT from the years of 2005 to 2014 and excluded obituaries, book reviews, comment/replies, and editorials from the analysis. The remaining titles included theoretical articles, qualitative, mixed methods, and quantitative research. These remaining articles were categorized as peer-re- viewed articles. These peer-reviewed articles were used as our remaining N to analyze how many quantitative articles were being published out of the total number of peer-reviewed articles.

The titles and abstracts of the remaining 376 peer-reviewed articles were read, and 142 were identified as containing quantitative statistical analytic methods. In other words, 38% peer-re- viewed articles published in JMFT during the reporting period used quantitative research methods.

January 2016 JOURNAL OF MARITAL AND FAMILY THERAPY 5

If the type of research used in the article was unidentifiable from the title and abstract, the authors read the methods section. As a cross-check, the authors used the “Quantitative Study” option under the Methodology section in PsycINFO to verify the classification of articles.

Once we identified the articles as quantitative studies, we followed the data analytic plan. We recorded the type of research design and statistical analysis used. We categorized research design into the following: experimental design, randomized clinical trial, survey research, observational design, and other. We assigned each article to one category. Experimental design included studies where the researchers gave participates measures before the treatment, conducted the treatment, and then administered the measures again. Randomized clinical trial is a design that randomly assigns participants into an experimental group or control group. Survey research included studies where the researchers gave the participants surveys to complete. Observational design researchers used observational measures in their research design. An other category was created for data ana- lytic plans that were not represented by the previous categories but were not big enough in number to warrant a new category.

The categories for the type of statistical analyses include the following: comparison of means, regression, path analysis, multilevel growth modeling, measure development, and other. These cate- gories emerged from the data as categorically distinct methods of statistical analyses. We combined similar types of analyses to identify themes (Figure 1). For example, we combined ANOVAs, ANCOVAs, t-tests, and Mann–Whitney U-tests into the comparison of means category. Similarly, we placed different types of regressions, that is, hierarchical regressions or multiple regressions, under the category of regression. Path analysis included structural equation modeling, exploratory and confirmatory factor analysis, and canonical correlation analysis, which is a similar path analy- sis to structural equation modeling but can be used on smaller sample sizes. Multilevel growth mod- eling included growth curve modeling, linear growth models, and multilevel growth models. Measure development included analyses that used reliability and validity to either create or test sta- tistical measures. The other category included cost analysis, effect size, Delphi method, and corre- lations. The other category was created because these analyses were not better represented by any of the other categories yet were so few in number as to not provide enough information to create a new category. Creating broader categories generated larger Ns for each category and allowed for trends to emerge from the data.

If a study conducted one type of analysis multiple times, the type of analysis was recorded once. For example, if the researchers had three research questions and conducted an ANOVA for each question, we marked one tally for ANOVA. If a study conducted multiple types of analyses to answer different research questions, then each type of analysis was recorded. For example, if regression was used for the first research question and structural equation modeling was used for the second research question, then both methods were recorded. However, we did not record any analyses that were used as a preliminary analysis for a more sophisticated analysis. For example, if structural equation modeling was used, we did not include the correlations that were conducted as it was a required primary step for the structural equation model test. We conducted the content analysis this way to get a more accurate picture of how many studies used a particular technique. If we had tallied each time a type of analysis was used in a particular study, those methods could have been overrepresented in the content analysis.

Research design and statistical analysis were recorded for each quantitative article identified. Research design and statistical analysis were grouped into 2005–2009 and 2010–2014. Chi-square different tests were then conducted to test for significant changed between the time periods of 2005–2009 and 2010–2014. Chi-squares were conducted for overall quantitative articles as well as for each category for research design and statistical analysis (Table 1).

RESULTS

Of a total of 376 peer-reviewed articles, 142 (38%) were classified as quantitative research. From 2005 to 2009, 170 articles published in JMFT were identified as peer reviewed. Of those, 64 (38%) were classified as quantitative research. From 2010 to 2014, 206 articles were identified as peer reviewed. Of those, 78% or 38% were classified as quantitative research. A breakdown in per- centages, by year, of articles identified as quantitative is represented in Figure 1.

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We grouped research design procedures of the articles into the following categories: experi- mental design (n = 45), randomized clinical trial (n = 16), survey research (n = 66), and observa- tional design (n = 8). We then divided the categories in years 2005–2009 and 2010–2014 and calculated percentages for each type of research design (Figure 2). From 2005 to 2009, out of the total quantitative research articles (n = 64), we categorized 30% as experimental design, 19% as randomized clinical trials, 44% as survey research, and 8% as observational design. From 2010 to 2014, out of the total quantitative research articles (n = 78), we categorized 35% as experimental design, 6% as randomized clinical trials, 49% as survey research, 4% as observational design, and 5% other. Chi-square analysis found no significant difference between the two time periods

Table 1 Examples of Statistical Analyses per Category

Category Examples

Comparison of Means Analysis of variance Analysis of covariance Multiple analysis of variance Multiple analysis of covariance Mann–Whitney U-test T-test

Regression Hierarchical regression Multiple regression Logistical regression

Path Analysis Canonical correlation Confirmatory factor analysis Exploratory factor analysis Structural equation modeling

Multilevel Growth Modeling

Growth curve modeling Linear growth model Multilevel growth model

Measure Development Analyses using reliability and validity to create or test statistical measures

Other Cost analysis Effect size Delphi method Correlation

0

10

20

30

40

50

60

70

2005 2006 2007 2008 2009 2010 2011 2012 2013 2014

Quantitative articles per year (percentages)

Quantitative articles

Figure 1. Quantitative articles per year (percentages) from 2005 to 2009.

January 2016 JOURNAL OF MARITAL AND FAMILY THERAPY 7

(2005–2009 and 2010–2014) for experimental design (v2 = 0.68, p = .41), survey design (v2 = 0.35, p = .55), or observational design (v2 = 1.04, p = .31). Significant difference was found for random- ized clinical trials (v2 = 4.1, p = .04).

We combined the type of statistical analyses into six categories: comparison of means (n = 58), regression analysis (n = 46), path analysis (n = 23), multilevel growth modeling (n = 10), measure development (n = 17), and other (n = 6). We grouped analytic methods into 2005–2009 and 2010– 2014, and we calculated percentages for each method (Figure 3). From 2005 to 2009, out of the total quantitative research articles (n = 65), 38% conducted comparison of means, 26% used regression analysis, 14% path analysis, 12% employed multilevel growth modeling, 8% did mea- sure development, and 2% other. From 2010 to 2014, out of the total quantitative research articles (n = 78), 44% conducted comparison of means, 37% used regression analysis, 18% path analysis, 3% employed multilevel growth modeling, 15% did measure development, and 5% other. Chi- square analysis found no significant difference between the two time periods (2005–2009 and 2010– 2014) for comparison of means (v2 = 0.54, p = .46), regression (v2 = 1.8, p = .18), path analysis (v2 = 0.39, p = .53), or measure development (v2 = 1.9, p = .17). Significant difference was found for multilevel growth modeling (v2 = 5.3, p = .02).

0

10

20

30

40

50

60

Experimental design Randomized clinical trial Survey research Observational design

Research design (percentages)

2005-2009 2010-2014

*

Figure 2. Types of research designs (percentages) used in articles published between 2005–2009 and 2010–2014. Note. *p < .05.

0 5

10 15 20 25 30 35 40 45 50

Comparison of means

Regression Path analysis Multilevel growth modeling

Measure development

Other

Statistical analysis (percentages)

2005-2009 2010-2014

***

*

Figure 3. Types of statistical analyses (percentages) conducted in articles published between 2005– 2009 and 2010–2014. Note. *p < .05; **p < .01; ***p < .001.

8 JOURNAL OF MARITAL AND FAMILY THERAPY January 2016

We then grouped comparison of means and regression into one group (n = 104) and path analysis and multilevel growth modeling (n = 43) into another. We did this to see whether there was significant difference between the use of more statistically sophisticated analysis (path analysis and multilevel growth modeling) verses less sophisticated analysis (comparison of means and regression). Chi-square analysis found that there was a significant difference between these two groups (v2 = 52.47, p = .00001) with the less sophisticated analysis being used more often.

DISCUSSION

In our first research question, we asked if there was an increase in quantitative methods used over time. Our results suggest a stable amount of quantitative articles being published in JMFT. Results do suggest an increase of peer-reviewed articles being published in JMFT over the 10-year period. From 2005 to 2009, 170 were peer-reviewed articles, while from 2010 to 2014, 206 articles were peer-reviewed articles. However, the percentage of quantitative research articles being pub- lished has remained stable over time. Both time periods had 38% of articles using quantitative sta- tistical analysis. In other words, while the overall amount of theoretical articles, qualitative research, mix methods research, and quantitative research increased over time, the percentage of quantitative methods remained consistent.

We believe the increase in overall peer-reviewed articles represents a positive change for our profession. The field of family therapy can and does benefit from a variety of publication types, including theoretical articles qualitative and mixed methods research. However, while there has been an increase in overall peer-reviewed articles, there has not been an increase in quantitative research. This finding could be problematic in several ways. First, as stated above, the field of fam- ily therapy has had a movement toward evidenced-based practice. It is important that our field conducts quantitative research, studying these evidenced-based practices and continuing to test their effectiveness in community settings. Many of the readers of JMFT are clinicians practicing family therapy and presumably, many of those clinicians are practicing evidence-based practices. This lack of quantitative articles seems to give further evidence to the researcher–practitioner gap, where there is a misalignment between what clinicians are practicing and what researchers are studying.

Second, it is possible that due to the clinical focus of JMFT, that clinicians may be less able to interpret or use the quantitative studies in their work. If this is the case, this may give evidence to a gap in our master’s level training programs, where clinicians may not being sufficiently taught how to read and apply quantitative research.

Third, this lack of increase in publishing quantitative research articles could indicate a gap in our doctoral programs, where quantitative methods may not be emphasized or fully integrated into research training. Likewise, they may not be fully embraced by doctoral students, who ulti- mately choose between using quantitative and qualitative methods in their own future research.

Researchers in the field of family therapy should be working toward empirically validating the foundational theories of our field. To do this, generally requires using quantitative research meth- ods to empirically test the efficacy of the field’s theories and practices. While some research exists in this area, our results seem to indicate that there is room for growth. In order to continue to strengthen the field of family therapy, it is essential that our training programs, both on the mas- ter’s and doctoral-level, make understanding, implementing, and conducting quantitative research a priority.

In our second research question, we asked what trends were present in research design meth- ods of quantitative research. As seen from the content analysis, data were more commonly col- lected through experimental design (30% from 2005 to 2009; 35% from 2010 to 2014) and survey research (44% from 2005 to 2009; 49% from 2010 to 2014) than randomized clinical trials (19% from 2005 to 2009; 6% from 2010 to 2014) and observational design (8% from 2005 to 2009; 4% from 2010 to 2014) over the past 10 years.

Based on our chi-square analyses, the only significant change over the years was a decrease in randomized clinical trials. It is possible that fewer randomized clinical trials are being conducted because of the concerns over generalizability to broader populations. As stated by Dattilio, Piercy, and Davis (2014):

January 2016 JOURNAL OF MARITAL AND FAMILY THERAPY 9

We suspect that family therapists are much like professionals in other fields in the reasons they place relatively little emphasis on randomized clinical trials. For one thing, many feel that what goes on in a laboratory setting comes nowhere close to capturing what actually occurs in a clinician’s office. Often, “therapists” in these research studies are doctoral stu- dents or neophytes who, although they work under supervision, still have very little clini- cal experience. . . .Treatments delivered during the course of randomized clinical trials may differ from treatment provided in a routine clinical setting because protocols may be artificially constrained to what a therapist does and when the therapist does it.(p. 7)

So, the lower proportion of randomized clinical trials compared to other types of research design may reflect concerns around the researcher–clinician gap (Dattilio et al., 2014). Instead, other research design methods are being used, such as experimental designs and survey research, which may encompass more diverse samples. By collecting data from more diverse samples, the results may have greater external validity and thus be more generalizable and applicable to client popula- tions’ that marriage and family therapists may actually see. Although experimental design and sur- vey research were not have significantly different between 2005–2009 and 2010–2014, it may be more important to note that the results did not show a significant decrease in these research designs. Instead, the results indicate that the use of experimental design and survey research was stable across both time periods. This may suggest that researchers, and clinicians, find utility in these research designs over randomized clinical trials and observational design. However, as obser- vational methods develop, and as more research sites pool their resources, it may be that we will see an increase in both these research methods.

Survey research was found to be used more than other research designs. When looking at the growth over time, both experimental design and survey research increased by five percent. Due to the need for a large sample size for the more sophisticated quantitative analysis, the use of survey research seems to be an understandable trend to increase the feasibility of using certain analyses.

In our third research question, we asked what trends were present in statistical analytic meth- ods used in quantitative research. Overall, the most common type of analysis used was the compar- ison of means (n = 58), regression analysis (n = 46), path analysis (n = 23), measure development (n = 17), and multilevel growth modeling (n = 10). The only statistically significant change over time was the decrease in the use of multilevel growth modeling. The use of comparison of means, regression, path analysis, and multilevel growth modeling did not significantly change over time. However, when grouped together, comparisons of means and regression were used more often over the last 10 years than more sophisticated analysis of path analysis and multilevel growth modeling. These results seem to indicate that while more sophisticated analysis are available to answer research questions, they are being underutilized in family therapy research.

Our findings show no differences in any statistical analyses, except for a decrease in one of the more sophisticated analyses. These findings are troubling for several reasons. As statistical analyses become more sophisticated, this allows for an increase in our ability as researchers to study certain phenomena in new ways. For example, path analyses, such as structural equation modeling, allow us to create and test models that could potentially add to our understanding of basic family therapy concepts, such as differentiation (Parker & Priest, under review). Similarly, growth curve modeling can help the field move forward in process research by deepening our understanding of potential trajectories of client process in therapy (Pinsof & Wynne, 2000). However, based on our results, we are not seeing these kinds of innovations being fully imple- mented in the JMFT. One possible reason could again be related to our training programs, where students are not being taught how to conduct path analysis or multilevel growth model- ing. Another reason could be that researchers are using these more sophisticated analyses but are not framing their research question in a way that is applicable to clinicians and therefore are not getting accepted into JMFT.

One possible reason multilevel growth modeling specifically is not being used more could be related to feasibility. While both structural equation modeling and multilevel growth modeling require large sample sizes, multilevel growth modeling requires an additional requirement of longi- tudinal data with at least three time points. It is possible that the lack of availability to large longi- tudinal data sets could explain the discrepancy of use between multilevel growth modeling and

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structural equation modeling. Another possible explanation could be that while the precedent for looking at trajectories of growth has been set in other fields (i.e., child development), it has not been set in MFT. For MFT researchers, it could be important to encourage the use of multilevel growth modeling, in order to better understand change patterns over time.

While our results have shown trends in research design and statistical analyses that were statis- tically significant as well as not significant, it is beneficial to examine all of the results of the content analysis. Not only do our results provide insight into how the trends of quantitative research have changed over the past 10 years, but they also appear to reflect the researcher–practitioner gap that still needs to be addressed. In addition, with advances in technology that allow researchers to con- duct statistical analyses more sophisticated than ever before, it is imperative that MFT research continue to strengthen its research methods to move forward as a field. We hope that the results of this content analysis may serve as a catalyst toward this end.

Limitations We would like to point out several limitations in this study. One limitation was the content

analysis was conducted with just one family therapy journal, JMFT, and therefore, reported trends from one journal. As numerous researchers compete to be published in JMFT, not all of the methodologically sound quantitative studies submitted can be accepted into the journal (Piercy, personal communication, 2015). Thus, it is possible that the trends presented in the content analy- sis may not accurately reflect the overall trends in research design and data analytic methods across all quantitative research being conducted in the field of MFT. It may be fruitful to examine the trends of quantitative studies across other family therapy journals to gain a more accurate picture of quantitative trends in family therapy research.

Although there were limitations to the study, the content analysis provided useful information about the directions in MFT research, particularly quantitative research. It will be interesting to see how MFT research continues to evolve over the next 10 years and how the field addresses the researcher–practitioner gap as well as how technology and statistical analyses continue to be refined.

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*These articles were analyzed in the content analysis.

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