THE EFFECT OF DEMOGRAPHIC VARIABLES ON THERAPY ALLIANCE IN COUPLE THERAPY CONTROLLING FOR RELATIONSHIP ADJUSTMENT AND SYMPTOM DISTRESS Except where reference is made to the work of others, the work described in this thesis is my own or was done in collaboration with my advisory committee. This thesis does not include proprietary or classified information. _____________________________ Catherine E. Walker Certificate of Approval: ___________________________ Alexander T. Vazsonyi Professor Human Development and Family Studies ___________________________ Scott A. Ketring, Chair Associate Professor Human Development and Family Studies ___________________________ Thomas A. Smith Associate Professor Human Development and Family Studies ___________________________ George T. Flowers Interim Dean Graduate School THE EFFECT OF DEMOGRAPHIC VARIABLES ON THERAPY ALLIANCE IN COUPLE THERAPY CONTROLLING FOR RELATIONSHIP ADJUSTMENT AND SYMPTOM DISTRESS Catherine E. Walker A Thesis Submitted to the Graduate Faculty of Auburn University in Partial Fulfillment of the Requirements for the Degree of Master of Science Auburn, Alabama August 9, 2008 iii THE EFFECT OF DEMOGRAPHIC VARIABLES ON THERAPY ALLIANCE IN COUPLE THERAPY CONTROLLING FOR RELATIONSHIP ADJUSTMENT AND SYMPTOM DISTRESS Catherine E. Walker Permission is granted to Auburn University to make copies of this thesis at its discretion, upon request of individuals or institutions and at their expense. The author reserves all publication rights. ________________________________ Signature of Author ________________________________ Date of Graduation iv VITA Catherine E. Walker, daughter of Kent and Theresa Walker, was born on August 22, 1985, in Athens, Georgia. Catherine is a 2003 Honor Graduate of Nathanael Greene Academy. In 2006, she graduated Magna Cum Laude from the University of Georgia with a Bachelor of Science degree in Psychology. She specialized in Marriage and Family Therapy at Auburn University and completed a Master of Science degree in Human Development and Family Studies in August 2008. v THESIS ABSTRACT THE EFFECT OF DEMOGRAPHIC VARIABLES ON THERAPY ALLIANCE IN COUPLE THERAPY CONTROLLING FOR RELATIONSHIP ADJUSTMENT AND SYMPTOM DISTRESS Catherine E. Walker Master of Science, August 9, 2008 (B.S., University of Georgia, 2006) 85 Typed Pages Directed by Scott A. Ketring Therapy alliance is a central concern in couple therapy as alliance has been consistently shown to predict therapy outcome. However, little is known about the factors that affect alliance formation. The purpose of this thesis was to examine how the demographic variables of the client and the degree of demographic similarity between the therapist and client affect therapy alliance formation in couple therapy while controlling for relationship adjustment and symptom distress. Specifically, client ethnicity, sex, age, income, and education were analyzed. In addition, age difference, sex difference, and ethnicity difference between the therapist and client were also examined. The sample for this study was composed of couples attending therapy at the Auburn University Marriage and Family Therapy training clinic in Auburn, Alabama. While multiple demographic variables were correlated with female and male alliance scores, in a multiple regression iii model, only one demographic variable, female age, was significantly related to therapy alliance formation. On average, younger female clients reported higher alliance levels. Analysis of study results revealed some findings contrary to previous research results. Relationship adjustment was correlated with alliance formation for males and females, but the relationship was not significant in the multiple regression models. Also, symptom distress, which was the only significant predictor of male alliance in the current study, was was not a predictor of female alliance. iii ACKNOWLEDGMENTS I would like to thank my parents for their continued support and for believing in me even when I did not. I thank my grandmothers for being strong female figures within my life and instilling me with high academic expectations for myself. I would also like to thank T.J. for keeping me grounded and inspiring me to enjoy life outside of school while always supporting my dreams and aspirations. I would like to thank Dr. Thomas Smith for always being available when I needed an answer to a question or advice. Thank you to Dr. Alexander Vazsonyi for participating on my committee and providing helpful statistical knowledge. Finally, I would like to give a special thanks to Dr. Scott Ketring, who has served multiple roles: teacher, supervisor, committee chair, statistician, and overall mentor. Your enthusiasm for training students and sincere clinical advice has helped me build confidence in my own clinical skills. Thank you for all of your time and hard work, but also for the guidance and wisdom that taught me life lessons along the way. iv Style manual used: Publication Manual of the American Psychological Association, Fifth Edition. Computer software used: Microsoft Office Word, SPSS v TABLE OF CONTENTS LIST OF TABLES ...............................................................................................................x LIST OF FIGURES ........................................................................................................... ix INTRODUCTION ...............................................................................................................1 REVIEW OF LITERATURE ..............................................................................................7 METHODS ........................................................................................................................27 RESULTS ..........................................................................................................................32 DISCUSSION ....................................................................................................................46 REFERENCES ..................................................................................................................60 APPENDIX A ....................................................................................................................67 APPENDIX B ....................................................................................................................70 APPENDIX C ....................................................................................................................71 APPENDIX D ....................................................................................................................73 vi LIST OF TABLES TABLE 1. Independent samples T-Test for differences in age, relationship adjustment, and symptom distress .............................................................................................34 TABLE 2. Chi-Square Test for similarities in ethnicity, education, and income for male and female dropouts and completers......................................................................34 TABLE 3. Statistic analysis of distributions for males on measures of relationship adjustment, symptom distress, therapy alliance, and age ......................................37 TABLE 4. Statistical analysis of distributions for females on measures of relationship adjustment, symptom distress, therapy alliance, and female age ..........................37 TABLE 5. Pearson correlation coefficients for female variables ............................................38 TABLE 6. Pearson correlation coefficients for male variables ...............................................39 TABLE 7. Statistically significant Pearson correlation coefficients and p-values, as directed from the research questions ......................................................................40 TABLE 8. Regression Coefficients for model 1 prior to the sensitivity analyses ...................43 TABLE 9. Regression Coefficients for model 1 after the sensitivity analyses .......................44 TABLE 10. Regression Coefficients for model 2 ......................................................................45 vii LIST OF FIGURES Figure 1: Hypothesized model 1 ........................................................................................42 Figure 2: Hypothesized model 2 ........................................................................................42 1 INTRODUCTION The relationship between the therapy alliance and client outcomes has received increasing attention in couple therapy (Garfield, 2004; Johnson & Ketring, 2006; Knobloch-Fedders, Pinsof, & Mann, 2007). The moderate to strong relationship between the alliance and outcome has motivated some researchers to declare the alliance to be the ?gold standard? and the ?sine qua non? of marriage and family therapy outcome research (Bachelor & Horvath, 1999). The value of the therapeutic alliance requires that more attention be appropriated to this topic within couple therapy literature (Knobloch-Fedders, Pinsof, & Mann, 2004). Some topics have already been examined in relation to alliance. For example, researchers have examined the link between alliance and the type of theoretical approach (Johnson, Ketring, Rohacs, & Brewer, 2006; Werner-Wilson, Zimmerman, Daniels, & Bowling, 1999). Other variables that have received attention within the alliance research include early family-of-origin experiences and client stage of change. Researchers have consistently found that early relational experiences affect the client?s ability to form an alliance with others, including their therapist and spouse (Knobloch-Fedders, et al., 2004; Eames & Roth, 2000; Ogrodniczuk, Piper, Joyce, & McCallum, 2000). Client stage of change has been shown to effect alliance formation with clients who enter therapy with increased readiness for change reporting higher alliance ratings (Connors, DiClemente, Dermen, Kadden, Carroll, & Frone, 2000; Principe, Marci, & Glick, 2006). Likewise, 2 pre-treatment marital adjustment and individual symptoms are related to alliance formation within couple therapy. Several studies have asserted that marital adjustment is the strongest predictor of alliance in couple therapy indicating that, on average, low levels of marital adjustment negatively affect the formation of therapeutic alliance and vice versa (Garfield, 2004; Knobloch-Fedders, et al., 2004; Mamodhoussen, Wright, Tremblay, & Poitras-Wright, 2005). This finding of a strong relationship between marital adjustment and alliance in couple therapy highlights the importance of taking marital adjustment into account when studying alliance. Likewise, individual therapy studies have found high symptom distress, including depression and anxiety, to be associated with low alliance levels (Eaton, Abeles, & Gutfreund, 1988; Raue, Castonguay, Goldried, 1993). So far, this association has received mixed support in the couple therapy literature (Knobloch- Fedders, et al., 2004; Mamodhoussen, et al., 2005; Stephens, M., 2006). While, multiple individual therapy studies support the importance of symptom distress, couple therapy studies have yet to yield conclusive evidence. Therefore, this variable should be taken into account when studying alliance in couple therapy. While the importance of relationship adjustment and individual symptom distress has been debated, there has been much less attention dedicated to the relationship between client demography and the therapeutic alliance especially in conjoint treatment (Knobloch-Fedders, et al., 2004). This is ironic, because many therapy models and manuals espouse the importance of matching demographic variables in an attempt to improve the alliance (Liddle, 2002; Henggeler & Sheidow, 2003; Silverstein, 2003). 3 Certainly more attention is needed in evaluating the relationship between the therapeutic alliance and various demographic variables of the therapist and client, while controlling for relationship quality and individual symptoms at the onset of couple therapy. There is reason to believe that client and therapist demographic variables could impede or facilitate the development of a relationship (Wintersteen, Mensinger, & Diamong, 2005). Preference and perception studies suggest that clients prefer therapists who are more similar (Atkinson, Furlong, & Poston, 1986; Atkinson, Poston, Furlong, & Mercado, 1989; Atkinson, Wampold, Matthews, & Ahn, 1998; Robiner & Strondt, 1986). Preference studies ask participants to answer hypothetical questions about which characteristics they would prefer in a therapist. Perception studies ask individuals to rate their opinion of the therapist?s ability based on their interaction or an observed interaction with the therapist. These types of studies lay the theoretical framework for studying the relationship between client and therapist demography and the alliance in couple therapy. From the preference studies, results suggest that participants generally desire a therapist who is similar in age, sex, and ethnicity (Atkinson, et al., 1986, 1989, 1998). Similarly, one perception study supports a connection between client-therapist demographics and alliance (Robiner & Strorandt, 1986). The similarity in age between client and therapist was associated with participants rating the therapists? ability and disposition more favorably. These preference and perception studies suggest a link between the therapeutic relationship and demographic variables. Yet, the direct effect of demography on therapy alliance is less clear. Studies focusing on demographics and alliance in individual therapy are limited, but they do support the assumption that 4 similarity in age and same sex improves the alliance (Luborksy, Crits-Cristoph, Alexander, Margolis, & Cohen, 1983; Wintersteen, et al., 2005). There are even fewer studies focused on the effect of demographic variables in couple therapy. The therapist?s sex and the clients? education level are the only two variables that have been researched (Mamodhoussen, et al., 2005; Symonds & Horvath, 2004). These researchers found client education and alliance to be negatively related, with high income clients reporting lower alliance, and vice versa (Mamodhoussen, et al., 2005). Symonds and Horvath (2004) found that the therapist?s sex did not affect the level of alliance. Therefore, questions remain about the relevance of demography. Decidedly, couple therapy is more complex because it involves two members of a dyad in a relationship with the therapist. This larger therapeutic system adds additional complexity which requires accounting for the individual?s alliance as it is related to the partners alliance within the dyad. While couple therapy research has yet to show that alliance is affected by demographic variables of the therapist and client, the findings from preference studies, perception studies, and individual therapy research emphasize the relevance of ethnicity and sex more than other demographic variables. This increased attention to certain variables is also found throughout the theoretical literature. For example, theorists have warned that non-minority, Caucasian therapists need to be aware of the possible mistrust African-Americans might have for the dominant culture (Nichols, 2006). Handbooks and theoretical approaches also discuss how the client?s sex may affect the therapeutic context (Sexton, Weeks, & Robbins, 2003; Nichols, 2006). During the advance of 5 postmodernism, the feminist critique began to point out how sex issues may affect the treatment outcome and the relationship (Werner-Wilson, et al., 1999). Many therapy approaches emphasize the importance of client and therapist demography (Liddle, 2002; Henggeler & Sheidow, 2003; Silverstein, 2003). Multidimensional Family Therapy (MDFT) and Functional Family Therapy (FFT) both support matching the clients to a therapist with similar demographic variables, such as ethnicity (Henggeler & Sheidow, 2003). FFT and MDFT are both well-known approaches which have been empirically validated by multiple studies. An examination of feminist theory provides several broad hypotheses about how demographic variables may affect the therapeutic relationship and, therefore, the therapy outcome. Overall, feminist theory proposes that women are more open to therapy and have higher alliance levels because they are generally the family member that contacts a mental health service provider. This theory also hypothesizes that minorities are less trustful of the therapist because of the oppression and judgments they have experienced in dealing with health service professionals in the past. Finally, the theory proposes that individuals in couple therapy are more trusting of a therapist who is the same ethnicity or sex as him/herself because they are more likely to have similar values (Silverstein, 2003). While the hypotheses proposed by feminist theory are limited to sex and ethnicity, one could argue that the basic assertion of the final hypothesis listed above is that the alliance will increase when the therapist and clients have similar demographic values as these are signs to the client that the therapist has a similar value system. However, there is a 6 discrepancy in that approaches continue to suggest the importance of demographic variables even though research has yet to show that demography to affects the alliance. As a whole, the preference, perception, individual therapy, and couple therapy research seem to provide enough evidence to suggest that demographic variables in couple therapy deserve more attention, but the existence, extent, and direction of the relationship has not yet been clearly established. The main objective of this study is to explore the possible relationship between therapeutic alliance and various demographic variables in couple therapy. The exploration of this connection will extend previous literature and assemble information that may be used to provide more effective services to couples seeking therapy. Therefore, the purpose of this study is to examine how client age, sex, income, education, and ethnicity affect the therapeutic alliance as reported by both couple members. Likewise, are the client and therapist differences in demographic variables impactful? All of these factors should be taken in the context of marital adjustment and individual symptoms which have not been controlled for in previous studies. 7 REVIEW OF LITERATURE This literature review will summarize the methodology and results of previous studies related to the effect of demographic variables on therapeutic alliance. Within the alliance literature, the lack of research focusing on a relationship between couple alliance scores and demographic variables makes it necessary to review the literature from a broader perspective. After a brief introduction, the review will begin with preference studies, followed by perception studies, individual therapy research, and couple therapy research. Finally, symptom distress and relationship adjustment literature will be discussed as they relate to the therapeutic alliance. Preference Studies Preference studies are a common research method for determining which characteristics clients? desire in a therapist. In order to answer this research question, participants are usually asked to choose between two scenarios or answer questions such as, ?Would you prefer a counselor who is similar or dissimilar from you in age, race, education, etc.?? (Coleman, Wampold, & Casali, 1995). One of the first published preference studies was completed by Atkinson, et al. (1986). A two-part questionnaire was distributed in southern California during a class at a predominantly African- American community college. The first part of the survey requested basic demographic information such as race, income, and sex. The second part of the survey consisted of 120 scenarios where participants were asked to select between having a counselor who 8 was similar in one dimension or dissimilar in another dimension. This measure was created for the study and incorporated a total of sixteen counselor characteristics including similar and dissimilar religion, ethnicity, sex, attitudes, education, socioeconomic status (SES), age, and personality (Atkinson, et al., 1986). However, there is no citation within the article for this measure?s reliability or validity. Based on the answers of 42 African-American men and 86 African-American women, the preference of each characteristic was ranked for male and female respondents, and the authors concluded the majority of both sexes preferred counselors who were more educated, older, and of the same ethnic background (Atkinson, et al., 1986). The most preferred characteristic was a more educated counselor. The authors argue that it seems logical that participants also preferred an older individual since increased education is often associated with being older. Other results were not statistically significant. In a replication of this study, Atkinson, et al. (1989) used a sample of 339 Asian- Americans, Mexican-Americans, and Caucasian-Americans who were enrolled in psychology or business classes at two colleges in a large city on the West coast. This replication study offered a larger sample and a shorter questionnaire which eliminated religion as a preference variable because it was the least valued characteristic. The reduced preference questionnaire included 91 items instead of the original 120 items. Using the same procedure of ranking the characteristics for each ethnicity based on the percentage of times it was preferred, similar results were found. Asian-Americans, Mexican-Americans, and Caucasian-Americans all preferred a more educated, older, 9 same sex counselor with similar attitudes as their own. As with the previous study, there was a significant preference for a therapist of the same ethnicity (Atkinson, et al., 1989). The authors argue that the preferences for similarity may be based on the assumption that a demographically similar counselor would have similar attitudes and values leading to a better relationship with the counselor. This is an important point since it provides support for the link between preferences and possible alliance levels based on the information conveyed by demographic variables (Beutler & Bergan, 1991). Atkinson, et al. (1998) used records from a large West coast university to sample 400 students who identified themselves as Asian-American when registering for classes. These 400 students were randomly chosen and mailed a questionnaire packet that included questions regarding demographic data of the participant and a 66-item paired- comparison questionnaire that forced the participants to choose which attribute they would prefer over the other. This measure was the same questionnaire used in the previous studies, but again, the measure was shortened by discarding education as a counselor characteristic (Atkinson, et al., 1998). Since both of the previous studies found education to be, by far, the most preferred characteristic, the authors felt that it was unnecessary to continue including this variable. Using the Bradley-Terry-Luce model, which is a statistical procedure designed for paired-comparison data, the authors found that the Asian-American minority students preferred similar values or attitude the most (Atkinson, et al., 1998). However, a strong preference was also expressed for a female counselor who was similar in age. The authors suggested that the participants viewed counselors of a similar age as easier to talk 10 to and more likely to understand their problem in a personal relationship. While the authors expected participants to prefer a similar sex counselor, they believed the preference for female counselors might have reflected the notion that women are generally more caring and accepting. The study found no significant preference for a similar socioeconomic status (SES). In the past twenty years, Atkinson has added valuable information to the demographic literature by publishing some of the first articles based on individual preferences for a counselor. However, definite limitations still remain. All of the studies were based on samples made up entirely of college students in non-clinical populations. Also, the preferences were based on hypothetical scenarios and not realistic situations that the participants were experiencing. The use of a created measure is questionable since no reliability or validity information was given for any version of the paired- comparison preference questionnaire. The literature on preference studies is based on the answers that individuals reported for who they would rather see if they were to attend counseling. This information is related to therapeutic alliance because it is assumed that participants would prefer a therapist with these characteristics because they expected these characteristics to lead to higher alliance levels. Atkinson, et al. (1986, 1989) found that participants prefer a more educated, older, and same ethnicity counselor. Additionally, Atkinson, et al. (1989) found a significant preference for a same sex counselor with similar attitudes. The results from Atkinson, et al. (1998) are somewhat different since participants preferred a similar age, female counselor with similar attitudes. 11 Perception Studies While the preference studies provide useful information, perception studies allow researchers to test the effect of different therapist demographics more directly. Preference studies are cognitive in nature and ask participants direct questions about which demographic variables they would prefer in a therapist. While, preference studies assume that these inclinations would have an effect on the therapeutic alliance, perception studies ask participants to report their opinions of the therapist based on a specific interaction where the demographics are observable but not stated. One of the first studies to use this procedure examined the effect of client and therapist age (Robiner & Storandt, 1983). Thirty-two women between the ages of 25-35 and thirty-two women between the ages of 60-70 volunteered to participate in a 50 minute, face-to-face interaction with a counselor. The therapists were actually four crisis hotline workers, ages 26, 34, 58, and 66, who were picked because of their similar training and skills. By controlling for the education and ability of the counselors, researchers argued they were able to rule out the common pattern of increased education with increased age. Each counselor interviewed eight women from each age group in a counterbalanced order and discussed a personal relationship problem from the participant?s life. After the interview, each client completed the Barret-Lennard (1978) Relationship Inventory (BLRI) to measure her perception of the therapeutic progress within the interview and the Client Satisfaction Scale (CSS; Ashby, Ford, Guerney, & Guerney, 1957) to measure her overall satisfaction with the interview and the counselor. The CSS includes 25 items, which are negatively and positively worded. The CSS has a 12 Spearman-Brown reliability coefficient of .92 (Robiner & Storandt, 1983). The BLRI includes four subscales, which are empathic understanding, congruence, level of regard, and unconditional regard. No information regarding the validity or reliability of this measure is provided in the article. The reported findings from these questionnaires showed no main effect for counselor age or client age. However, the authors reported an interaction between client age and counselor age with clients generally viewing the counselor more favorably if they were similar in age. Schneider and Hayslip (1986) discovered the opposite finding several years later. Ninety-six women from an introductory psychology class at a large southwestern university volunteered to participate in the study in return for research credit. Participants were in their twenties and viewed a 10-12 minute videotape of a therapy vignette that showed only the therapist in order to minimize confounds. Two younger and two older female ?therapists? were recruited to create the vignettes. The younger women, ages 26 and 34, were both doctoral level graduate students. Due to the lack of older students, one of the older women had recently graduated with an advanced degree, and the other was an actress. Their ages were 61 and 74. In order to avoid results due to topic differences, each therapist recorded the same mild, moderate, and intense presenting problem vignettes. The procedure included each participant filling out a demographic questionnaire, viewing all three of the vignettes of one therapist, and completing the Counselor Rating Form-Short (CRF-S; Corrigan & Schmidt, 1983) and the Client Satisfaction Scale (CSS; Ashby, et al., 1957). The CRF-S was used to measure the 13 counselor?s attractiveness, expertness, and trustworthiness. Reported subscale reliabilities ranged from .82 to .93 (Schneider & Hayslip, 1986). The researchers found an interaction between the severity of the presenting problem and the therapist age. The participants thought they would have higher satisfaction levels with the younger therapists for the least severe problems, but with moderate or intense problems age was not a significant factor. This suggests a need to control for relationship problems and individual symptoms when evaluating client demography. While these studies focused on possible perception differences based on age, Campbell and Johnson (1991) were interested in how sex may affect the perception of male and female therapists. The experience similarity hypothesis proposed by Simons, Berkowitz, and Moyer (1970) suggests that clients prefer a therapist who shares similar experiences and problems. These clients may perceive that therapists with the same demographic variables are more likely to have the same experiences. Therefore, the researchers proposed 40 individual couple members, who were seeking couple therapy might rate therapists who were similar to themselves higher on the CRF-S measure and as more capable on the Marital Therapy Expectations Inventory. While the CRF-S is a common measure used throughout the literature, the Marital Therapy Expectations Inventory was created for the current study and includes 15 of the most common couple problems on a 6 point Likert-type scale. The scale measures how capable each individual thinks the therapist would be for the specific problem types. The authors reported that the measure had a coefficient alpha of .87 (Campbell & Johnson, 1991). Ratings were based 14 on a picture of the therapist and a segment from a session transcript provided after the couple members completed the demographic questionnaire. The transcripts were identical, but two pictures, one male and one female, were used. The authors concluded that therapist sex or therapist-client sex match did not affect the participant ratings. However, there was a significant effect of client sex since women were more likely to view the therapist positively and believe that the therapist would have helpful qualities (Campbell & Johnson, 1991). This study used a sample that differed from those previously discussed, in that, these participants were beginning couple therapy. The use of a clinical couple sample provides a better match to the individuals that a therapist is likely to encounter. However, while the research design included measuring the perception of the both couple members, the data was not analyzed dyadically, which would have allowed the authors to control for a possible correlation between the husband and wife?s alliance scores. While the use of perception studies is preferable to preference studies, this method is limited by its typical use of non-clinical samples. Most individuals were not actively involved in therapy. Instead, they were volunteering to participate in a research study. Nevertheless, the results of these studies provide useful information. While Robiner and Storandt (1983) found a positive effect of similar age, Schneider and Hayslip (1986) found symptom distress to affect the relationship between similar age and perceived alliance. Similar age was found to be a significant predictor for the mild presenting problem vignette. This is the only perception study to include symptom distress as a controlling variable, and the findings provide evidence for including 15 symptom distress in future studies. Campbell and Johnson (1991) found a significant effect of client sex, with women reporting better overall perceptions, but they found no effect of matched therapist/client sex. Both of these methods, preference and perception studies, build a theoretical foundation but fail to examine therapeutic alliance directly. More direct evidence comes from individual therapy research where alliance itself is the studied outcome variable. Demographic Variables in Individual Therapy Several studies within the literature have focused on the effect of demographic variables over time in individual therapy. The limitation of these studies in relation to couple therapy is the individual focus. However, because dyads consist of individuals, these studies offer an important framework for understanding the functioning of individuals within a relationship. For example, Luborsky, et al., (1983) found that demographic similarity between the therapist and client was positively correlated with the therapeutic alliance. The main purpose of this study was to test two different observation measures, Helping Alliance Rating (HA R ) and Helping Alliance Counting Signs (HA CS ), for the level of alliance within a therapeutic setting while providing support for the HA CS rating method. The reliabilities of both measures are approximately .80, but no information is included on the validity of either coding system (Luborsky, et al., 1983). Four different therapy sessions were coded for the ten most and ten least improved clients. Transcripts were completed for the 3 rd session, the 5 th session, the session marking 90% of completion, and the session previous to the 90% completion marker. 16 The included demographic variables were age, marital status, children, religion, religious activity, foreign-born parents, institutional affiliation, and cognitive style (Luborsky, et al., 1983). Using these categories, an overall similarity score was calculated by summing the total number of characteristics the therapist and client had in common. Participants also completed the Health-Sickness Rating Scale (HSRS; Luborsky, 1962) as a control predictor for the current study, which measures the individual?s psychological health and sickness. In this study, the results showed that an age and religious affiliation match were the most important to the alliance. While the possible importance of age was supported by previous studies, this was the first study to support the importance of religious affiliation. However, the authors used a unique coding method, which may have affected the findings. One concern is that that the method gives each demographic characteristic equal weight. The authors suggested that matched therapist and client characteristics could be important because of basic ?human attraction? that causes people to be drawn to others who are similar (Luborsky, et al., 1983). In more recent research within the same area, sex and ethnicity of both the therapist and client were analyzed in relation to therapeutic alliance (Wintersteen, et al., 2005). A large sample of approximately 600 adolescents was drawn from another ongoing study, and each individual was randomly assigned to a therapist. While each therapist was required to use a manual based treatment plan, they were allowed to use the model of their choice. Participants and therapists completed the 12-item version of the Working Alliance Inventory (WAI; Tracey & Kokotovic, 1989) to measure the alliance 17 following the second or third session. The WAI is an empirically validated measure with an alpha of .95 in the current study (Wintersteen, et al., 2005). However, this study did not ask participants to complete a measure of symptom distress prior to beginning therapy. The results were analyzed by creating four sex and four racial groups to represent all of the possible sex and ethnic combinations. For example, the sex groups included male therapist-male client, male therapist-female client, female therapist-female client, and female therapist-male client. Ethnicity was based on minority and non- minority categories instead of analyzing individual ethnicities separately. While the researchers found no significant effect for the sex of the therapist, same sex pairs did report a higher alliance level especially at the beginning of therapy (Wintersteen, et al., 2005). There was also a significant effect for client sex with females reporting higher alliance levels than males. For the therapist-reported alliance levels, similar ethnicity was significantly related to the alliance, but for the client-reported alliance levels, similar ethnicity was not a significant predictor of alliance (Wintersteen, et al., 2005). Therefore, these results show that ethnicity may be a factor that therapists view as related to alliance, while clients do not. The authors suggest that ethnicity is not a significant predictor, and the finding that therapists view ethnicity as a factor could be due to therapists being taught that ethnic differences can be a source of difficulty in establishing alliance with clients. To summarize, Luborsky, et al., (1983) found a significant effect of age and religion with higher alliance levels reported by individuals of a similar age and religion as the therapist. Wintersteen, et al., (2005) found higher alliance scores when the therapist 18 and client were of the same sex, but ethnicity was not a significant factor in predicting alliance. This study also found a significant effect of client sex, with women reporting higher alliance levels than men. Demographic Variables and Couple Therapy There is less evidence for the effect of demographic variables on therapeutic alliance within the couple therapy literature. Only two articles could be located which included demographic variables in the examination of couple alliance formation. Couple therapy studies have limited their analyses to examining the demographic variables of client education and therapist sex which fails to consider the effect of other demographic variables or the interactions between the demographics of the client and therapist. Symonds and Horvath (2004) studied 44 couples who volunteered to attend six couple therapy sessions in two urban cities. All couples were required to meet certain criteria such as having no psychotic episodes within the past ten years, no previous therapy attendance within the last six months, and a low risk of suicide or abuse. The couples were also required to complete the Marital Satisfaction Scale (MSS; Roach Frazier, and Bowden, 1981), which was used by the researchers to control for marital satisfaction. Participants were then randomly assigned to one of six therapists. Of the six, two therapists were female, four were male, and all were included because of their expertise in couple therapy and their ability to take on a case load of up to 10 couples. This study used the couple version of the Working Alliance Inventory (WAI-Co; Symonds, 1999) to measure the alliance of each member after the first and third sessions. The couple version of this measure is based on three well-noted subscales of alliance, including: 19 goals, tasks, and bonds (Bordin, 1979). The measure includes 63 items on a Likert-type scale and has a reported alpha of .95 to .98. Therapist?s sex was unrelated to the client ratings of the alliance (Symonds & Horvath, 2004). The authors did not analyze the results for a possible effect of client sex or an interaction between the therapist?s sex and the alliance scores of each couple member. The authors suggested that it may have been helpful to examine alliance later in the course of treatment since both measurements occurred relatively early within a normal treatment length. However, this is confusing because it is assumed that any differences due to demographics would be most noticeable in the earlier stages of therapy rather than the later stages. While Symonds and Horvath (2004) studied the effect of therapist sex on alliance levels, Mamodhoussen, et al. (2005) were interested in the psychometric properties of the overall variance in alliance scores based on demographic variables. In order to create a French version of the Couple Therapeutic Alliance Scale (CTAS; Pinsof & Catherall, 1986) and determine its reliability, new clients of a specific couple therapist group were asked to participate in the study. The therapists were associated with a French university located in Quebec, Canada and used cognitive-behavioral therapy (CBT). In total, 74 couples were recruited to participate in the study. Participation involved completing the Dyadic Adjustment Scale (DAS; Spanier, 1976), the Psychiatric Symptom Index (PSI; Ilfeld, 1976), and a demographic questionnaire prior to the first session. Participants completed the revised version of the CTAS after the third session. The DAS measures 20 the couple?s relationship adjustment, and the PSI measures the amount of individual psychological distress. While the authors found the French version of the CTAS to have similar psychometric properties of the original version, other interesting findings emerged in regard to the client demographics. The alliance scores were found to be stable across multiple client factors such as sex, age, and income when controlling for symptom distress and relationship adjustment. However, the study found a significant effect of education for female clients with more educated women reporting lower levels of alliance than women who were not as educated (Mamodhoussen, et al., 2005). By limiting the analysis to client variables, the study failed to examine factors such as client and therapist sex, age, or ethnic differences and alliance formation. To summarize, Symonds and Horvath (2004) found no significant effect of therapist sex on the therapeutic alliance. However, the study was limited by the fact that the alliance of both partners was combined to form a single score. Mamodhoussen, et al. (2005) reported a significant effect based on the level of education reported by the female client. Two couple studies are insufficient in providing much knowledge about the impact of client demography on alliance formation, and there is clearly a need for more research in this area. Symptom Distress and the Formation of Alliance Two previous studies examined the relationship between symptom distress and therapeutic alliance, and both of these focused on individual therapy (Eaton, et al., 1988; Raue, et al., 1993). Eaton, et al. (1988) focused on the effect of pretreatment symptoms 21 on therapeutic alliance in individual therapy. The study found pretreatment symptom distress to have a negative effect on the alliance and high symptoms to be associated with both decreased positive alliance and increased negative alliance. The authors argued that the findings suggest individuals with high levels of symptom distress at the onset of therapy are less likely to form a therapeutic alliance with the therapist than individuals with lower levels of symptom distress. Raue, et al. (1993) found a negative correlation between participants? symptoms and the alliance score, meaning clients with higher symptom distress reported lower alliance scores even after a session that the therapist viewed as making ?significant? progress. Both studies found evidence to support a negative relationship between symptom distress, as reported at the beginning of therapy, and the therapeutic alliance with high symptom distress predicting low reported alliance levels, on average. While this finding has yet to be replicated in couple therapy, future research on alliance should take symptom distress into consideration. Marital Adjustment and the Formation of Alliance The effect of marital adjustment on the formation of alliance has received a fair amount of attention in the couple therapy literature. Mamodhoussen, et al. (2005), previously discussed in regard to demographic variables in couple therapy, also examined the importance of marital adjustment. In this study, marital adjustment predicted alliance scores with high marital adjustment predicting high alliance scores, on average. Bourgeois, Sabourin, and Wright (1990) found marital adjustment to be unrelated to alliance formation when studying the relationship between marital adjustment, therapy alliance, and the treatment outcome using small groups for couple therapy. No 22 relationship was found between marital adjustment and alliance formation suggesting that marital adjustment had no effect on the alliance. However, the study?s design is questionable since clients received group therapy. It could be argued that alliance formation in couple group therapy involves a different process since there is alliance to other group members, as well as other dyads, and the therapist. While these studies report different findings, there is enough evidence suggesting that relationship adjustment is related to therapeutic alliance to make controlling for this variable necessary in empirical research studies on alliance in couple therapy. Conclusion This literature review has examined preference, perception, individual therapy, and couple therapy studies pertaining to the effect of age, sex, ethnicity, income, and education on therapeutic alliance. Research on demographic variables and therapeutic alliance within couple therapy is fairly underdeveloped. Of the existing research, the results are often conflicting and do not suggest a clear pattern. Age. Age is a demographic variable that has received support within the research. Three studies within this review found a significant relationship between age and the therapeutic alliance. However, two studies contradict these findings. In a preference study (Atkinson, et al., 1998), perception study (Robiner and Storandt, 1983) and individual therapy research (Luborsky, et al., 1983), similar age consistently appears as a significant variable. Based on the consistency of this finding across multiple studies and methods, more needs to be done to further ascertain the relationship between age differences and therapeutic alliance in couple therapy. There is contradictory evidence 23 for the effect of matching clients with a therapist of a similar age based on preference studies. Atkinson, et al. (1998), Robiner and Storandt (1983), and Luborsky, et al. (1983) found that clients prefer or report higher alliance levels when the therapist is similar in age. However, Atkinson, et al., (1986; 1989) found participants preferred an older therapist, and Schneider and Hayslip (1986) found no effect of age. No studies have examined the effect of age on alliance within couple therapy. Sex. Preference studies provide contradictory evidence about the effect of matching the therapist and client based on sex. Atkinson, et al. (1989) found that participants preferred a therapist of the same sex, but Atkinson, et al. (1998) found that participants, regardless of the sex, consistently preferred a female therapist. Within the perception literature, there is no evidence that matched sex therapist-client pairs have higher alliance levels. However, there is support for the argument that the client?s sex affects the alliance with female clients reporting higher alliance levels (Campbell & Johnson, 1991). In an individual therapy study, Wintersteen, et al. (2005) found matched sex pairs reported the highest alliance levels, and there was also a significant effect for client sex with females reporting higher alliance than men. Again, no existing studies could be located that analyze the effect of sex as a demographic variable within couple therapy. Ethnicity. In a preference study by Atkinson, et al. (1986), participants preferred a therapist of the same ethnicity, but an individual therapy study found no significant effect with same ethnicity therapist-client pairs reporting similar alliance as different ethnicity pairs (Wintersteen, et al., 2005). There are no research findings regarding the 24 effect of client ethnicity independent of the therapist?s ethnicity. There are also no perception or couple therapy studies regarding ethnicity and alliance. Education and income. Research is sparse on the effect of education with only one study to date examining this variable. Mamodhoussen, et al. (2005) in a couple therapy study, reported that the alliance varied depending on the client?s education with more educated clients reporting lower alliance. The need for research findings on client income and alliance are also striking. No studies have examined how the level of alliance is affected by the client?s income. While previous research provides support for a connection between demographic variables and the client?s reported alliance level, there is a need for couple therapy studies that analyze the demographic variables of the client, as well as the demographic similarities and differences between the therapist and client while controlling for symptom distress and relationship adjustment. Introduction of the Research Questions Based on the findings presented in this literature review and feminist theory, the current study explores a possible relationship between demographic predictors and the client?s rating of therapeutic alliance. The predictors include demographic variables of the clients (sex, age, income, education, ethnicity) which are examined in Questions 1-5 and the difference between the therapist and client demographic variables (sex, age, ethnicity) which are examined in Questions 6-8. Because therapist demographics are not independent they will not be included in the present study. However, the study will 25 analyze the difference between therapist and client demography and therapy alliance ratings. Question 1: Are there differences in therapeutic alliance scores of husbands or wives based on the client?s sex? Feminist theory hypotheses that the female is generally the partner that encourages the couple to enter therapy. Therefore, the theory assumes that the female will report a higher alliance level as she is, most likely, the more motivated partner (Silverstein, 2003). Previous researchers have also found the female to report a higher alliance level compared to the male partner (Campbell & Johnson, 1991). Question 2: Are there differences in therapeutic alliance scores of husbands or wives based on the client?s age? Previous studies have found that younger clients rated therapy more favorably than older clients (Atkinson, et al., 1986; 1989; 1998). Question 3: Are there differences in therapeutic alliance scores of husbands or wives based on the client?s income? Because no research has been conducted on this demographic variable, income will be included in the current study as an exploratory variable. Question 4: Are there differences in therapeutic alliance scores of husbands or wives based on the client?s educational level? Mamodhoussen, et al. (2005) found client?s with high educational levels generally reported lower therapy alliance levels. Question 5: Are there differences in therapeutic alliance scores of husbands or wives based on the client reporting a minority or non-minority ethnic status? Feminist theory hypothesizes that clients reporting a minority ethnicity will have 26 significantly lower alliance formation levels as they often view therapy as a ?white institution? (Silverstein, 2003). Question 6: Are there differences in therapeutic alliance scores of husbands or wives based on sex differences with the therapist? Feminist theory suggests that clients form a better therapy alliance with a therapist who is of the same sex (Bischof, Lieser, Taratuta, & Fox, 2003). Previous researchers also found support for the hypothesis that clients prefer a therapist of the same sex, and therapist-client pairs of the same sex report higher alliance levels than non-matched pairs (Atkinson, 1989; Wintersteen, et al., 2005) Question 7: Are there differences in therapeutic alliance scores of husbands or wives based on age differences with the therapist? Feminist theory hypothesizes that clients report a stronger therapy alliance when the therapist and client have similar demographic characteristics (Silverstein, 2003). However, age is not mentioned specifically as an important demographic variable to consider. Research findings from Robiner and Storandt (1983) and Luborsky, et al. (1983) found evidence that alliance values were higher when the therapist and client were close in age. Question 8: Are there differences in therapeutic alliance scores of husbands or wives based on ethnicity differences with the therapist? Again, feminist theory hypothesizes that therapy alliance will increase when the therapist and client report similar demographic characteristics (Silverstein, 2003). The theory also hypothesizes that the minority clients will have increased trust in therapy when the therapist is also of a minority ethnicity. 27 METHODS Procedure The current study used data from the Auburn University Marriage and Family Therapy Center (MFT Center), which is located on the Auburn University campus and serves clients from east Alabama. The facility is a training clinic and is accredited by the Commission on Accreditation for Marriage and Family Therapy Education. The center is staffed by student therapists in training who receive supervision from the Center?s faculty of Ph.D. level, licensed marriage and family therapist. This study used data provided by adults in committed relationships who were seeking therapy with their partner. Couples who attend therapy at the MFT Center are required to complete self- report questionnaires regularly for clinical, administrative, and secondary data research purposes. Clients were made aware of these purposes from the onset of therapy. Prior to the first session, demographic information, symptom distress assessment, and marital adjustment of each individual was gathered by self-report questionnaires. At the fourth session, and every four sessions thereafter, each member of the couple completed a battery of surveys including the therapy alliance measure used in this study. Measures This section describes the measures that will be analyzed in the current research project. The therapy alliance of each couple member was measured using the Couple Therapy Alliance Scale (CTAS). The Outcome Questionnaire (OQ-45.2; Lambert, 28 Hansen, Umpress, Lunnen, Okiishi, Burlingame, et al., 1996) and Revised Dyadic Adjustment Scale (RDAS; Spanier, 1976) were included in the analysis in order to control for varying levels of symptom distress and relationship adjustment at the onset of treatment. The demographic variables were analyzed using categories created from the multiple choice and fill-in-the-blank self-report answers of previous clients and therapists? at the MFT Center. Therapeutic Alliance. Therapy alliance was measured using the Couple Therapy Alliance Scale (Pinsof & Catherall, 1986). This measure is a self-report questionnaire of 40 statements that both members of the couple rate independently on a 7-point Likert- type scale. These statement ratings assess the client?s view of their relationship with the therapist. The measure has three subscales based on Bordin?s (1979) suggested model of therapeutic alliance which includes: developing bonds, assigning tasks, and agreeing on goals. The measure is worded with half of the statements being positive and half of the statements being negative in order to avoid any experimental bias (Pinsof & Catherall, 1986). The bonds subscale refers to the quality of the therapist-client relationship. For example, one statement from this subscale is, ?The therapist cares about me as a person.? The tasks subscale examines the methods and techniques used by the therapist, and ?The therapist and I are in agreement about the way in which therapy is being conducted,? is a statement from this subscale. While this subscale is concerned with the client?s feelings about the effectiveness of the techniques used, it also measures the client?s beliefs regarding the therapist?s ability to help. The goals subscale measures the client?s view of 29 how much agreement exists between the therapist and client on the goals of therapy. A sample statement for this subscale is, ?The therapist and I are not in agreement about the goals of therapy.? Pinsof and Catherall (1986) found a test-retest reliability of r =.84, and the reported internal consistency is an overall alpha level of .93 with alpha levels of .85, .88, and .70 for the bonds, tasks, and goals subscales, respectively (Heatherington & Friedlander, 1990). The alpha for the CTAS among the participants of this study was approximately .96 for both males and females. Symptom Distress. Individual therapy studies have shown that alliance is related to the severity of the individual symptoms. In various studies, individuals with lower levels of depression and anxiety report significantly higher alliance levels, on average (Eaton, Abeles, & Gutfreund, 1988; Raue, et al., 1993). Because of this relationship, the current study controlled for symptom distress of each individual in the couple. Clients completed the Outcome Questionnaire (OQ) as part of their intake paperwork and after every fourth session. This self-report scale measures each client?s perceptions of his or her ability to function and includes measurements for anxiety and depression on a 5 point Likert-type scale (Lambert, et al., 1996). The OQ has been shown to reliably control for demographic differences such as ethnicity, age, and sex. This measure is based on the idea that there are three important dimensions of life and individual functioning. Therefore, the three subscales, symptom distress (intrapsychic difficulties), interpersonal relationship (level of connection to family and friends), and social role relationships (level of functioning in school or work), are based on these dimensions. The measure 30 includes 45 items, and scores can range from 0 to 180 with higher scores signifying higher distress levels. The questionnaire has adequate test-retest reliability (? = .71 to .93) and findings show there is concurrent validity of the subscales. This measure had an alpha of .93 for males and .94 for females in the current study. This measure was included in the current project as the control measure for varying symptom levels prior to the first session. Relationship Adjustment. Several studies have found that, on average, high levels of marital distress predict poor therapy alliance (Mamodhoussen, et al, 2005; Knobloch- Fedders, et al., 2004). The relationship adjustment of each couple member was measured using the Revised Dyadic Adjustment Scale (RDAS), which is based on the original Dyadic Adjustment Scale created by Spanier (1976). The three subscales of this measure are consensus, cohesion, and satisfaction, and the subscales include six, three, and four questions respectively. There is a possible range of 0-79 for the total score with 79 representing the highest possible level of consensus, cohesion, and satisfaction within the couple from the reporting individual?s perspective. This measure is an established and well-reported assessment that has been shown to have criterion and construct validity, internal consistency, and split-half reliability. The reported Cronbach?s alpha is .90, and the Spearman-Brown split-half reliability is .95. The alpha of this measure in the current study was .87 and .86 for males and females respectively. Demographic Variables. Each client was required to complete a demographic questionnaire before beginning treatment at the MFT Center. The questionnaire includes ethnicity, income, current age, sex, and education level. Couples were assigned to a 31 therapist based on the therapists? availability and the clients? schedule. In the demographic questionnaires, total household income is divided into $5,000 brackets. For example, choices include: less than $5,000, $5,001 - $10,000, and so on. The largest bracket is labeled ?above $50,000.? For highest educational level, clients are asked to choose from the following categories: grade school or some high school, high school diploma, Bachelor?s degree, Associate?s or other two year degree, Master?s degree, or Other. Clients were asked to write their ethnicity and current age. Demographic variables of the therapists? were acquired by matching the therapist?s identification number, which is included on all paperwork that clients complete with the administrative program data which is kept on file in the program office. Therapist?s age when treating clients, ethnicity, and sex were used in the current study. Based on these measures, therapeutic alliance, demographic variables, symptom distress, and marital adjustment, the current study aimed to uncover and explain a possible link between demographic variables of both the therapist and clients and the reported therapeutic alliance of couple members. 32 RESULTS Plan of Analysis This analysis explored the possible connection between therapy alliance and demographic variables of the client controlling for symptom distress and relationship adjustment. This study also investigated the possible relationship between therapy alliance and demographic similarities between the therapist and client. Therapist and client ethnicity was coded as a dichotomous variable to represent Caucasian and minority ethnicities. This step was necessary for the ethnicity variable because the sample did not contain a sufficient amount of minority clients or therapists to allow for more detailed analysis. Client education level and income was examined as categorical data based on the categories included in the client questionnaire. Two outcomes, female alliance and male alliance, were analyzed, and symptom distress and relationship adjustment prior to the first session were control predictors for each outcome. Using this model, the study explored a possible effect of the client?s sex, age, income, education, and ethnicity on the alliance reported by each client. Also, this study examined how alliance is affected by the similarity or dissimilarity of the therapist and client?s sex, age, and ethnicity. Initially, a Pearson correlation matrix was used to assess which variables were correlated with therapy alliance for both males and females. A paired samples t-test was used to analyze the effect of client sex on therapy alliance 33 formation. The variables that were significantly correlated with therapy alliance were then entered into two multiple regression models separated by client sex. Participants Only participants who attended couple therapy with their partner for at least four sessions were included in the current study. Clients were considered dropouts if they completed four or more sessions but did not complete the fourth session paperwork due to client refusal or therapist noncompliance. Independent samples T-Test, which analyze differences in continuous variables, and Chi-Square tests, which analyze similarities in categorical variables, were used to compare completers and dropouts. An independent samples T-Test showed that the dropouts were not significantly different from completers based on age, relationship adjustment, or symptom distress (Table 1). The results of the Chi-Square analysis were not statistically significant, meaning dropouts and completers were similar in ethnicity, education, and income (see Table 2). In several cases, one partner completed 4 th session paperwork, but the other partner did not. This led to a total sample of 95 males and 100 females. Because only a minority of individuals indicated an ethnicity other than Caucasian when completing the initial paperwork, only two broad categories are used to indicate ethnicity. These two categories are Caucasian, and ?minority,? which includes all other ethnicity categories. The minority category included participants who indicated their ethnicity as African- American, American Indian, or other. Using two broad categories increased the ?minority? sample size and allowed for further analysis. Of the males, 69 (72.6%) were Caucasian, 19 (20%) were a minority ethnicity, and 7 (7.4%) did not provide an answer. Of the females, 76 (76%) were Caucasian, 19 (19%) were a minority ethnicity, and 5 (5%) did not provide an answer. Table 1 Independent samples T-Test for differences in age, relationship adjustment, and symptom distress Variable T df p-Value Male age -1.78 133 .08 Male relationship adjustment -0.93 126 .36 Male symptom distress -0.03 124 .97 Female age -0.59 130 .56 Female relationship adjustment -1.18 125 .24 Female symptom distress 0.13 127 .90 Table 2 Chi-Square test for similarities in ethnicity, education, and income for male and female dropouts and completers Variable Pearson Chi-Square df p-Value Male ethnicity 0.41 1 .52 Male education 4.86 3 .18 Male income 4.76 3 .19 Female ethnicity 0.03 1 .87 Female education 1.56 3 .67 Female income 3.30 3 .35 34 35 The male participants ranged in age from 18 to 53 years old. Twenty-four (25.3%) male participants were between 18 and 24 years old, 50 (52.6%) males were between 26 and 40, and 16 (16.8%) males were between 41 and 53. Five male participants declined to answer the question. The female participants ranged in age from 19 to 50 years old. Thirty-seven (37%) female participants were between 18 and 24 years old, 51 (51%) females were between 26 and 40, and 8 (8%) females were between the ages of 41 and 59. Four (4%) women did not provide their age. Client education was grouped into four categories, and the percentage of males and females were fairly equal across these groups. Twenty-eight (29.5%) of the males and 28 (28%) of the females reported having a high school diploma or less, 13 (13.7%) males and 17 (17%) females reported having a two year degree, 27 (28.4%) males and 26 (26%) females reported an undergraduate degree, and 19 (20%) males and 23 (23%) females reported having an advanced degree. Eight men and 6 women did not provide their educational level on the intake paperwork. The client?s reported household income was also grouped into four categories. Eighteen (18.9%) of the males and 22 (22%) of the females reported an income of less than $15,000, 32 (33.7) males and 30 (30%) of the females reported an income between $15,000 - $30,000, 15 (15.8%) males and 19 (19%) females reported an income between $30,001 - $40,000, and 23 (24.2%) males and 24 (24%) females reported an income above $40,000. Seven males and five females did not provide their income level on the first session paperwork. Therapists consisted of thirty-two MFT graduate students from seven cohorts who saw clients between 2002 and 2008. Twenty-five (23.8%) couples were seen by a male 36 therapist, and 80 (76.2%) couples were seen by a female therapist. Twenty-six (24.8%) couples were paired with a minority ethnicity therapist while 79 (75.2%) couples were paired with a Caucasian therapist. The therapists? birthdates were used to calculate their age at the time of the couples? first session. The therapist ages ranged from 21 to 45, with a mean age of 25.3 years old. The mean age for male and female therapists was 26.3 and 25 years old, respectively. There was a slight age difference between the Caucasian (24.6 years) and minority therapists (27.6 years). Univariate statistics were analyzed for all continuous variables included in the study in order to verify that each variable exhibited normal distributions. Several of the variables were slightly skewed. However, all measures utilized for this study were normally distributed according to the Kolmogorov-Smirnov statistic. The means, standard deviations, skewness coefficients, kurtosis coefficients, and Kolmogorov- Smirnov statistic for each measure are reported for both males and females in Tables 3 and 4. Correlation analysis Correlations were necessary in order to determine which variables were related to therapy alliance and should be included in the multiple regression model. Separate correlation analyses were completed for female and male participants. Tables 5 and 6 contain the complete correlation tables that show all significant and non-significant relationships between the original variables of interest in this study. Table 7 includes all significant correlation coefficients, p-values, and the corresponding research questions. Table 3 Statistic analysis of distributions for males on measures of relationship adjustment, symptom distress, therapy alliance, and age Statistic Male Relationship Adjustment Male Symptom Distress Male Therapy Alliance Male Age Mean 40.42 57.34 222.00 31.41 Std. Dev. 9.55 22.07 40.67 8.59 Skewness -0.50 0.31 -0.76 0.88 Kurtosis 0.78 0.05 1.46 0.19 Kolmogorov- Smirnov .06 .07 .07 .09 Table 4 Statistical analysis of distributions for females on measures of relationship adjustment, symptom distress, therapy alliance, and female age Statistic Female Relationship Adjustment Female Symptom Distress Female Therapy Alliance Female Age Mean 37.78 68.84 223.12 29.45 Std. Dev. 9.67 22.75 34.60 8.15 Skewness -0.50 -0.21 -0.09 1.37 Kurtosis -0.78 -0.45 -0.89 2.09 Kolmogorov- Smirnov .07 .07 .07 .10 37 Table 5 Pearson correlation coefficients for female variables Variable 1 2 3 4 5 6 7 8 9 10 1. (F) TA 1.00 2. (F) Rel. Adjust. .24* 1.00 3. (F) Symptom Distress -.19 -.49** 1.00 4. (F) Age -.31** -.14 .06 1.00 5. (F) Ethnicity -.21* -.07 .05 -.03 1.00 6. (F) Income .04 -.01 -.09 .36** -.07 1.00 7. (F) Education .02 .15 -.22* .08 .01 .26** 1.00 8. (F) Age Diff. -.25* -.19 .03 .87** -.08 .38** .12 1.00 9. (F) Ethnicity Diff. .01 -.01 -.11 -.08 .66** -.10 -.02 .06 1.00 10. (F) Sex Diff. .01 .12 -.14 .01 -.03 .01 -.06 -.03 .02 1.00 * p < .05. **p < .01. 38 Table 6 Pearson correlation coefficients for male variables Variable 1 2 3 4 5 6 7 8 9 10 1. (M) TA 1.00 2. (M) Rel. Adjust. .23* 1.00 3. (M) Symptom Distress -.48** -.50** 1.00 4. (M) Age -.30** -.15 .27** 1.00 5. (M) Ethnicity -.10 -.06 .10 -.03 1.00 6. (M) Income -.01 -.08 -.01 .36** -.25** 1.00 7. (M) Education .08 .11 -.06 .13 -.01 .20** 1.00 8. (M) Age Diff. -.33** -.16 .19* .86** -.05 .37** .17 1.00 9. (M) Ethnicity Diff. .05 -.11 -.03 -.05 .69** -.18* -.04 .12 1.00 10. (M) Sex Diff. .02 -.15 -.06 .06 .03 -.03 -.06 -.02 .01 1.00 * p < .05. **p < .01. 39 Table 7 Statistically significant Pearson correlation coefficients and p-values, as directed from the research questions Research Question Significant Correlations from the Specified Research Question Correlation Coefficient p-Value Question 2 Male therapeutic alliance formation with client age -.30 <.01 Question 2 Female therapeutic alliance formation with client age -.31 <.01 Question 5 Female therapeutic alliance formation with client ethnicity -.21 <.05 Question 7 Male therapeutic alliance formation with age difference between therapist and client -.33 <.01 Question 7 Female therapeutic alliance formation with age difference between therapist and client -.25 <.01 Each research question will be reviewed and the support or lack of support for each question will also be discussed. Of the eight research questions in the current study, five questions examined the effect of client demographic variables on therapy alliance scores. The other three questions examined the effect of demographic similarity between the therapist and the client on the reported therapy alliance. A paired samples t-test was employed in order to determine if there was a significant relationship between therapy alliance and client sex (Question 1). Male therapy alliance scores were correlated with female therapy alliance scores (r = .42, p < .001), and the two variables were not significantly different from each other (t = -.31, df = 89, p = .76). Therefore, Question 1, which examines the effect of client sex and therapy alliance scores, was not supported by the results of the paired samples t-test. Question 2 was supported since client age was significantly correlated with therapy alliance scores for both couple members (r for males 40 41 = -.30, p < .01, r for females = -.31, p < .01). The Pearson correlation coefficient found no significant relationship between therapy alliance and client income (Question 3) and therapy alliance and client educational level (Question 4) for males or females. Question 5 referred to the relationship between therapeutic alliance and client ethnicity and was significant for females only (r = -.21, p < .05). Questions 6 and 8, which referred to sex and ethnicity differences between the therapist and client, were not supported by the Pearson correlation coefficients. However, Question 7 was supported since there were significant correlations between therapy alliance and the age difference of the therapist and clients (r for males = -.33, p < .01, r for females = -.25, p < .05). As expected, relationship adjustment and symptom distress were correlated for males (r = -.50, p < .001) and females (r = .49, p < .001), and relationship adjustment and therapy alliance were also correlated for males (r = .23, p < .05) and females (r = .24, p < .05). Male symptom distress was strongly correlated with male therapy alliance (r = -.48, p < .001), which means that, on average, high symptom distress scores were associated with low therapy alliance scores, and vice versa. However, female symptom distress at intake was not correlated with female therapy alliance (r = -.19, p = .07). Regarding the research questions, the correlation coefficient findings showed that additional analyses was warranted for the relationship between age, ethnicity, age difference between the therapist and client, and therapeutic alliance formation. Multiple Regression Analyses Based on the original research questions and the Pearson correlation coefficient statistics, multiple regression analyses was conducted on two hypothesized models. These models are shown graphically below in Figures 1 and 2. Female Relationship Adjustment Female Symptom Distress Female Age Female Therapy Alliance Formation Female Ethnicity Female Age Difference Figure 1. Hypothesized model 1: Female relationship adjustment, symptom distress, age, ethnicity, and age difference between client and therapist predicting female therapy alliance formation Male Relationship Adjustment Male Symptom Distress Male Age Male Therapy Alliance Formation Male Ethnicity Male Age Difference Figure 2. Hypothesized model 2: Male relationship adjustment, symptom distress, age, ethnicity, and age difference between client and therapist predicting male therapy alliance formation Results from Multiple Regression Analysis on model 1: The effect of Female Age, Ethnicity, and Age Difference on Female Therapy Alliance Formation controlling for Relationship Adjustment and Symptom Distress. For the variables included in model 1, there were six outliers according to the univariate analysis previously conducted. Female relationship adjustment contained one outlier, female symptom distress contained two outliers, and female age contained three outliers. A sensitivity analyses was conducted by removing each outlying score individually in order to test the effect of the value on the findings of the model. Only one outlier, a female age value, had a significant effect on the results of the model. Therefore, this was the only value removed from the model. 42 The regression coefficients for model 2 before conducting the sensitivity analyses are shown in Table 8. Table 8 Regression Coefficients for model 1 prior to the sensitivity analyses Variable b T p-Value Female Relationship Adjustment -0.81 1.88 .06 Female Symptom Distress -0.11 -0.64 .53 Female Age -1.89 -1.93 .06 Female Ethnicity -12.74 -1.43 .16 Female Age Difference 0.95 1.12 .27 For model 1, the multiple regression analysis indicated that the overall R 2 value was .17 and the standard error of the estimate was 31.90. Overall, the model was significant (F(5, 85) = 3.37, p < .01). However, the relationship between therapy alliance and several predictor variables were not significant when examined individually (see Table 9). After including both control variables, only one variable, female age, was significantly related to therapy alliance (b = -1.97, t = -2.02, p = .01). When all other variables in model 1 were controlled for, the female client?s age was negatively related to her report of the therapy alliance. This means that, on average, for every two years increase in client age there was one point decrease in the female therapy alliance score. 43 Table 9 Regression Coefficients for model 1 after the sensitivity analyses Variable b t p-Value Female Relationship Adjustment 0.81 1.89 .06 Female Symptom Distress -0.10 -0.57 .57 Female Age -1.97* -2.02 .05 Female Ethnicity -10.03 -1.10 .27 Female Age Difference 1.04 1.23 .22 *p < .05. Results from Multiple Regression Analysis on model 2: The effect of Male Age, Ethnicity, and Age Difference on Male Therapy Alliance Formation controlling for Relationship Adjustment and Symptom Distress. The variables included in model 2 also contained several outliers. Male relationship adjustment and male symptom distress each contained two outliers, and male therapy alliance contained one outlier. Unlike model 1, none of the outliers in the male model had a significant impact on the model results. Therefore, none of these values were removed. For model 2, the multiple regression analysis indicated that the R 2 statistic was .27 and the standard error of the estimate was 36.82. Like the female model, the regression results indicated that the male model was significant (F(5, 80) = 5.54, p < .001). Although the model was significant according to the F statistic, only one variable, male symptom distress, was significantly related to therapy alliance (b = -.89, t = -3.67, p < .001). When controlling for all other variables included in model 2, symptom distress was negatively related to therapy alliance (see Table 10). This means that, on average, 44 for a one unit difference in the male therapy alliance score, there was a negative difference of a .88 unit of symptom distress reported by the male client. Table 10 Regression Coefficients for model 2 b t p-Value Male Relationship Adjustment -0.54 -1.01 .31 Male Symptom Distress -0.88*** -3.67 .001 Male Age 0.23 0.21 .84 Male Ethnicity -4.95 -0.49 .63 Male Age Difference -1.21 -1.24 .22 *p < .05. **p < .01. ***p < .001. 45 46 DISCUSSION This study explored the relationship between therapy alliance in couple therapy and demographic variables. Although research findings are limited, multiple theoretical approaches, including feminist theory, presume demographic variables affect therapy alliance formation, which has been shown to be an important factor in therapy (Johnson, et al., 2006; Werner-Wilson, et al., 1999; Silverstein, 2003). Specifically, feminist theory includes assumptions that suggest male clients, minority clients, and clients that have different demographics than the therapist will have poor relationships with the therapist. The theory proposes that the female couple member generally makes the effort to bring the couple to therapy, and therefore, the female is the more invested partner. The theory expects minority clients to have lower alliance levels since these groups have suffered oppression and racism from health care providers in the past. Finally, the theory suggests that when the therapist and client share commonalities in demography, they are likely to have similar values which foster alliance formation (Silverstein, 2003). Based on findings from existing literature and the theoretical hypotheses above, research questions in this study were aimed at discovering if certain demographic variables were connected to the reported therapy alliance scores. Client sex, age, ethnicity, income, and educational level were included in the analysis. The effect of differences in client-therapist sex, age, and ethnicity were also investigated. In this study, relationship adjustment and individual symptom distress were controlled for, as previous 47 researchers found that these variables were significant predictors of therapy alliance scores (Garfield, 2004; Knobloch-Fedders, et al., 2004; Mamodhoussen, et al., 2005; Eaton, et al., 1988; Rau, et al., 1993). This discussion will provide a summary of the significant results. Implications and benefits of these findings will be presented in order to explain the clinical and research significance of the current findings. Limitations of the study will be addressed, followed by future research possibilities that can extend on the current research. Summary of Results Pearson Correlation coefficients. Results from the correlations found relationship adjustment, age, and age difference between the therapist and client to be significantly correlated with therapy alliance for both female and male couple members. While symptom distress and therapy alliance were quite strongly correlated for males, symptom distress was not significantly correlated with therapy alliance for females. On the other hand, the female client?s ethnicity was significantly correlated with her therapy alliance formation, but the male client?s ethnicity was not significantly correlated with his therapy alliance formation. This indicates that different factors affect male and female therapy alliance formation. However, these correlations provided evidence for three of the original eight research questions, and a multiple regression analysis was then employed to analyze these three questions which included client age, ethnicity, and client-therapist age difference. These results provide partial evidence for two of the hypotheses included in feminist theory. For example, the assumption that therapy alliance increases as 48 demographic commonalities increase between the therapist and client was partially supported since the age difference between the therapist and client was correlated with the therapy alliance values for males and females. However, ethnicity difference and sex difference between the therapist and client was not correlated with therapy alliance values. Second, the theory suggests that non-minority clients will report higher therapy alliance than clients who report a minority ethnicity. Again, this hypothesis was partially supported by the findings in the current study. Ethnicity and therapy alliance formation were correlated for females, but these two variables were not correlated for males. Female model. The results from model 1 indicated a negative relationship between the female client?s age at intake and the female therapy alliance formation following the fourth session. Therefore, younger female clients, on average, reported higher therapy alliance scores than older female clients. On average, for every one unit difference in therapy alliance, there was a negative difference of 1.96 years in the female client?s age. Basically, for the current sample, for each two year increase in female age there was a one point decrease in reported alliance formation. While this finding was statistically significant, the clinical significance is debatable. When this finding is considered over a time period of several years, this difference seems rather minute. However, when this finding is considered over the life-span, a one point difference over approximately two years seems to increase in clinical relevancy. For example, the difference between alliance formation in a twenty year old compared to a sixty year old would be an alliance score of approximately twenty points lower, on average. 49 Although age was a significant predictor of alliance with younger clients reporting higher therapy alliance scores, on average, the age difference between the therapist and female client was not a significant predictor. However, this could be due to the lack of sufficient variability in therapist age. The female model predicted 17% of the variance in therapy alliance formation, with female age as the only significant predictor. While this is not an extremely large amount of the variance to be predicted by a model, it is adequate within the social sciences field. It is interesting that most of the predicted variance is due to a demographic variable while the control predictors, which were expected to predict a significant amount of variance, did not. The findings of this model did not provide support for the hypotheses of feminist theory. Of the demographic variables included in this model, age difference was not a significant predictor of therapy alliance scores for females. This finding goes against the hypothesis that therapy alliance scores will vary depending on the similarity or dissimilarity of demographic variables between the therapist and client. Because feminist theory does not specifically include a hypothesis regarding client age, this finding does not strengthen or lessen the arguments made by the current theoretical framework. However, the theory does include a hypothesis on client ethnicity, which was not supported in the female model since this variable was not a significant predictor of therapy alliance for females. Male model. Interestingly, findings for model 2, which included the male sample, were not similar to the female model. For male clients, their age was not related to the therapy alliance formation. The results showed symptom distress at intake to be the only 50 significant predictor of therapy alliance formation. The measure of symptom distress includes items that address the client?s levels of anxiety and depression. Therefore, this indicates that male clients with higher levels of anxiety and/or depression had poorer therapy alliance formation compared to male clients with lower levels of anxiety and depression. Altogether, the male model accounted for 27% of the variance in therapy alliance, of which symptom distress accounted for the majority of this amount since it was the only significant predictor in the multiple regression model. It is interesting that the variance in the male model was mainly predicted by symptom distress which is a pre- treatment measure of the client?s anxiety and depression. Yet, of the variables included in the current study, female therapy alliance was predicted by age which is an unalterable demographic variable. Also, compared to the female model, the male model predicted a markedly larger amount of the variance, which suggests that key variables predicting the female?s therapy alliance have yet to be uncovered. This is partially support by research on feminist theory suggesting that men and women value different things about therapy. Bischof, et al. (2003) found males were more goal-oriented by focusing on solving the symptoms of a specific problem, whereas females were more process-oriented by focusing more on how discussions over the course of therapy created change. Using the idea presented by Bischof, et al. (2003), the current study found pre-treatment symptoms to predict therapy alliance for males suggesting that therapy alliance for males may be based on the problem that the male presents with and the improvement, or lack thereof, in these symptoms during therapy. Predictors of female therapy alliance are less obvious, based on the 51 hypothesis of Bischof, et al. (2003) this could be due to the difficulty in measuring the therapy ?process.? Implications and Benefits of Research Findings These findings provide evidence that, overall, demographic variables are not especially important in therapy alliance formation. Of the eight variables included in the correlation analysis, only three variables, age, ethnicity, and age difference, were significantly correlated with therapy alliance scores. However, once these variables were entered into a multiple regression model, only one variable, female age, was significantly related to therapy alliance. Therefore, the variables included in the model must have contained a large amount of shared variance. When taking multiple variables into consideration simultaneously there was not enough leftover variance to make individual variables significantly impactful. In order to determine the relationship(s) between the shared variance, it is important that future research study the interactions of these demographic variables as the connection between demographic variables and therapy alliance may not be as straightforward as researchers have previously suspected. These findings are contrary to the three main assumptions of feminist theory related to demography (Silverstein, 2003). First, feminist theory predicts that, on average, non-minority individuals will report higher therapy alliance scores because minority individuals are generally mistrustful of mental health services. Client ethnicity was correlated with the therapy alliance score for females but not for males. In the multiple regression models, ethnicity was not a significant predictor of therapy alliance for males or females. Since therapy alliance was related to ethnicity before including 52 other variables in the models, it appears that shared variance between multiple predictor variables nullified the individual effects. Second, male therapy alliance scores and female therapy alliance scores were correlated and were not significantly different when compared using a paired samples t-test. Put another way, males and females report similar therapy alliance scores, which contradicts the hypothesis of feminist theory that females will have higher alliance levels than males. Third, overall, demographic variables, when considered individually, appear to be essentially unimportant in therapy alliance formation while feminist theory proposes that alliance will be higher when the therapist and client have similar demography. However, this final assumption is based on the premise that similar demography signals similar life experiences which in turn could lead to similar values. To fully examine this assumption, it would be necessary to collect data on the therapist and client?s values, which the current study did not take into consideration. The two control predictors, relationship satisfaction and symptom distress, were included in the current study because of the strong empirical evidence showing the relationship between these two variables and therapy alliance. Interestingly, relationship satisfaction was not predictive of therapy alliance formation in either model. This study contradicted most of the published literature on couple?s formation of therapy alliance which found relationship satisfaction to be an important predictor (Knobloch-Fedders, et al., 2004; Madmohoussen, et al., 2005). However, Knobloch-Fedders, et al. (2004) measured therapy alliance after the first and eighth session, while the current study measured therapy alliance following the fourth session. Knocloch-Fedders, et al. (2004) 53 suggested that marital adjustment acts as a ?sleeper variable? meaning that its effect on therapy alliance is not evident in measures of therapy alliance that are conducted early in treatment. The authors argue that in order to examine the effect of relationship satisfaction on therapy alliance formation, therapy alliance must be measured later during the course of therapy. Therefore, if their hypothesis is true, the different findings between this study and the current study may be due to the timing of the data collection. However, Mamodhouusen, et al. (2005) found relationship satisfaction predicted therapy alliance when measured after the third session. Another possible reason for why the current study contradicted other studies is the different populations used in conducting the studies. For example, the study by Mamodhousen, et al. (2005) was conducted in Quebec, Canada, using a French speaking population. Another noteworthy finding is the difference between females and males. Since the same predictors were included for males and females, this study assumed that therapy alliance formation occurs similarly for female and male couple members. While the sexes are generally much more similar than different, it is possible that different factors affect the therapy alliance of females and males. For example, as hypothesized by feminist theory, if males and females come to couple therapy for different reasons, symptom distress may affect the male?s therapy alliance formation because the male, on average, may attend therapy for symptom relief. As discussed previously, Bischof, et al. (2003) found that men are more commonly focused on the problem at hand and how to ?fix it.? Therefore, males may seek therapy to reduce symptoms, and alliance may be higher when he feels confident that this goal will, or is, occurring in therapy. 54 However, if males seek therapy to fix their symptom distress, why do females seek therapy? The current study results do not appear provide an answer to this question as neither relationship distress nor symptom distress at intake affected therapy alliance. Women may be more interested in the process of therapy rather than a specific problem that the female wishes to change (Bischof, et al., 2003). Feminist theory hypothesized that females would report higher alliance levels since females are generally the catalyst for the couple entering therapy, which was unsupported by the current study since males and females reported similar alliance levels. However, this evidence provides support for the idea conveyed in Bischof, et al. (2003). Male and female?s alliance scores may be similar because the dyadic relationship is also a symbiotic relationship since the two members affect each other. When the male?s symptoms change, this is likely to affect the process for the female. Therefore, a change in the male has a carryover effect towards the female?s alliance. This idea is compatible with other existing literature which suggests male pre-treatment predictors of therapy alliance and outcome may be more important than female pre-treatment predictors during the course of conjoint treatment (Stephens, 2006; Brown & O?Leary, 2000; Madmohoussen, 2005). In general, the benefits of this study include a greater understanding of the effect, or lack thereof, of demographic variables on therapy alliance formation as female age was the only demographic variable that affected the reported alliance. Therefore, this research suggests that matching clients and therapist based on their ethnicity, age, or other demographic characteristics is unnecessary. However, because there has not been a great amount of research on demography, this statement is somewhat premature as more 55 studies are needed before a decision is made. This should come as a relief to many therapists and mental health clinics since demographic variables are fairly life-long and stable characteristics that the therapist cannot change. Within couple therapy, the process of matching the therapist and clients based on demographic variables becomes complicated as couples invariably have differences between themselves. For example, all heterosexual couples have a difference in sex, and mismatches in ethnicity, age, and other demographic variables are not uncommon. Therefore, it would be almost impossible to match the therapist and clients on demography. Also, matching clients and therapists based on demographic variables is often impossible because of the general shortage of certain demographic variables within the couple therapy field. For example, the majority of therapists participating in the current study were Caucasian, young females, but the average age of couples presenting for therapy are thirty or older. Based on the current study, therapists and mental health clinics should be relieved that this age difference does not diminish their effectiveness at building an alliance with couples. Limitations Like all research studies, the current study has limitations that should be addressed in future research. Because this study, like many other studies examining couple therapy, did not include a control group, the possibility of a sampling bias must be considered. Using a control group would have eliminated this bias and provided more accurate measurements. The current study did not employ a random sample which makes it impossible to determine whether the intended treatment caused the therapy alliance formation or if the difference resulted from the participants themselves. Also, because 56 the sample was not random and the sample size was fairly small, these results cannot be generalized to the entire population of those who seek therapy services. Therefore, further analysis and replication taking these variables into consideration is necessary before these findings can be generalized beyond East Alabama residents who received treatment at the Auburn University Marriage and Family Therapy Center. It is possible that the small sample size affected the power of the results. If a larger sample was employed, there would be more statistical power to find relationships that possibly do exist within the current study. In other words, a larger sample size would allow for relationships that were approaching significance to reach significance. However, it would still be necessary to examine the clinical significance of these relationships. This study relied entirely on self-report questionnaires which are a less objective means of measurement. Also, each questionnaire was administered at only one time point. For example, the dependent variable, therapy alliance, was measured after the fourth session and both independent variables, symptom distress and relationship adjustment, were measured before the first session. Measuring these variables at multiple time points may provide different findings. The small sample size also failed to provide adequate variability for certain demographic characteristics. For example, as previously mentioned, the majority of the therapists included in the current study are young, Caucasian, and female. A larger sample size, including oversampling of certain categories such as minority therapists and clients, older therapist and clients, and male therapists, would provide a more comprehensive analysis. This lack of variability affects the current results. For example, 57 it is unreasonable to say that the age difference between the therapist and client is not a factor in therapy alliance formation because the current sample did not include enough older therapists to measure age difference on a large scale. In regard to age, the current study was a more accurate analysis of whether young therapists do better with young clients or older clients. At least for females, the current study found that the therapists, who were predominately young, have higher alliance scores with younger female clients. Future Research This study aimed to clarify the relationship between demographic variables and couple therapy alliance formation. The majority of existing literature on demographic variables and therapy is based on simple preference or perception studies with only a few individual and couple therapy studies. While the results of this study explain one more piece of the puzzle, many pieces remain missing. There is much more to be understood about the role of demographic variables in therapy alliance formation. Currently, there is no conclusive evidence in the field to give one possible answer priority over other possible answers. More research is needed to replicate the current study, but also extend on the current findings. As previously mentioned, this study does not explain why female therapy alliance is affected by age while male age does not affect therapy alliance. Future research should aim to clarify this relationship and empirically study reasons for this relationship. Studies should examine the possible interaction between multiple demographic variables. It is possible that demographic variables do not effect therapy alliance just based on age or ethnicity but on a more complex level. For example, age 58 and symptom distress or age and ethnicity may interact with each other to effect therapy alliance formation. In addition, more research is also needed that addresses the interface between males and females in committed relationships. Obviously, couple therapy is affected by each partner as well as how each partner affects the other partner. Research has yet to fully explore this relationship. Because of the lack of variability in therapists? demographic variables, these variables were not analyzed as possible predictors of alliance formation, in the current study. Therefore, future studies should aim to explore these variables as well. 59 REFERENCES Ashby, J. D., Ford, D. H., Guerney, B. G., & Guerney, L. F. (1954). Effects on clients of a reflective and a leading type of psychotherapy. Psychological Monographs, 71, 453-485. 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Psychological Assessment, 1, 207-210. Werner-Wilson, R. J., Zimmerman, T. S., Daniels, K., & Bowling, S. M. (1999). Is therapeutic alliance influenced by a feminist approach to therapy? Contemporary Family Therapy: An International Journal, 21, 545-550. Wintersteen, M. B., Mensinger, J. L., & Diamond, G. S. (2005). Do gender and racial differences between patient and therapist affect therapeutic alliance and treatment retention in adolescents? Professional Psychology: Research and Practice, 36, 400-408. 66 APPENDIX A Therapeutic Alliance Measure Couple Therapy Alliance Scale Instructions: The following statements refer to your feelings and thoughts about your therapist and your therapy right NOW. Please work quickly. We are interested in your FIRST impressions. Your ratings are CONFIDENTIAL. They will not be shown to your therapist or other family members and will only be used for research purposes. Although some of the statements appear to be similar or identical, each statement is unique. PLEASE BE SURE TO RATE EACH STATEMENT. Each statement is followed by a seven-point scale. Please rate the extent to which you agree or disagree with each statement AT THIS TIME. If you completely agree with the statement, circle number 7. If you completely disagree with the statement, circle number 1. Use the numbers in-between to describe variations between the extremes. Completely Agree Strongly Agree Agree Neutral Disagree Strongly Disagree Completely Disagree 7 6 5 4 3 2 1 1. The therapist cares about me as a person 7 6 5 4 3 2 1 2. The therapist and I are not in agreement about the goals for this therapy. 7 6 5 4 3 2 1 3. My partner and I help each other in this therapy. 7 6 5 4 3 2 1 4. My partner and I do not feel the same ways about what we want to get out of this therapy. 7 6 5 4 3 2 1 5. I trust the therapist. 7 6 5 4 3 2 1 6. The therapist lacks the skills and ability to help my partner and myself with our relationship. 7 6 5 4 3 2 1 7. My partner feels accepted by the therapist. 7 6 5 4 3 2 1 67 8. The therapist does not understand the relationship between my partner and myself. 7 6 5 4 3 2 1 9. The therapist understands my goals in therapy. 7 6 5 4 3 2 1 10. The therapist and my partner are not in agreement about the about the goals for this therapy. 7 6 5 4 3 2 1 11. My partner cares about the therapist as a person. 7 6 5 4 3 2 1 12. My partner and I do not feel safe with each other in this therapy. 7 6 5 4 3 2 1 13. My partner and I understand each other?s goals for this therapy. 7 6 5 4 3 2 1 14. The therapist does not understand the goals that my partner and I have for ourselves in this therapy. 7 6 5 4 3 2 1 15. My partner and the therapists are in agreement about the way the therapy is being conducted. 7 6 5 4 3 2 1 16. The therapist does not understand me. 7 6 5 4 3 2 1 17. The therapist is helping my partner and me with our relationship. 7 6 5 4 3 2 1 18. I am not satisfied with the therapy. 7 6 5 4 3 2 1 19. My partner and I understand what each of us is doing in this therapy. 7 6 5 4 3 2 1 20. My partner and I do not accept each other in this therapy. 7 6 5 4 3 2 1 21. The therapist understands my partner?s goals for this therapy. 7 6 5 4 3 2 1 22. I do not feel accepted by the therapist. 7 6 5 4 3 2 1 23. The therapist and I are in agreement about the way the therapy is being conducted. 7 6 5 4 3 2 1 24. The therapist is not helping me. 7 6 5 4 3 2 1 25. The therapist is in agreement with the goals that my partner and I have for ourselves as a couple in this therapy. 7 6 5 4 3 2 1 26. The therapist does not care about my partner as a person. 7 6 5 4 3 2 1 27. My partner and I are in agreement with each other about the goals of this therapy. 7 6 5 4 3 2 1 68 28. My partner and I are not in agreement about the things that each of us needs to do in this therapy. 7 6 5 4 3 2 1 29. The therapist has the skills and ability to help me. 7 6 5 4 3 2 1 30. The therapist is not helping my partner. 7 6 5 4 3 2 1 31. My partner is satisfied with the therapy. 7 6 5 4 3 2 1 32. I do not care about the therapist as a person. 7 6 5 4 3 2 1 33. The therapist has the skills and ability to help my partner. 7 6 5 4 3 2 1 34. My partner and I are not pleased with the things that each of us does in this therapy. 7 6 5 4 3 2 1 35. My partner and I trust each other in this therapy. 7 6 5 4 3 2 1 36. My partner and I distrust the therapist. 7 6 5 4 3 2 1 37. The therapist cares about the relationship between my partner and myself. 7 6 5 4 3 2 1 38. The therapist does not understand my partner. 7 6 5 4 3 2 1 39. My partner and I care about each other in this therapy. 7 6 5 4 3 2 1 40. The therapist does not appreciate how important my relationship between my partner and myself is to me. 7 6 5 4 3 2 1 69 APPENDIX B Demographics Measure Please provide the following personal information. If a question does not apply to you write NA for Not Applicable. All information is confidential. Your age: _____ Your sex: _____ What is your racial/ethnic group? ______________________ (please specify) What is the highest level of education you attained? A. Grade School B. Junior High School C. GED D. High School E. Vocational/Technical School F. Associate Degree/2 Years G. Bachelor degree H. Master?s degree I. Other ________ (specify) Your yearly income is: (Please indicate your combined income with your partner) A. Under $5,000 B. $5,000 to $10,000 C. $10,001 to $15,000 D. $15,001 to $20,000 E. $20,001 to $25,000 F. $25,001 to $30,000 G. $30,0001 to $35,000 H. $35,001 to $40,000 I. Over $40,001 70 APPENDIX C Symptom Distress Outcome Questionnaire (OQ?-45.2) Instructions: Looking back over the last week, including today, help us understand how you have been feeling. Read each item carefully and mark the box under the category which best describes your current situation. For this questionnaire, work is defined as employment, school, housework, volunteer work, and so forth. Never Rarely Sometimes Frequently Almost Always 1. I get along well with others 2. I tire quickly 3. I feel no interest in things 4. I feel stressed at work/school 5. I blame myself for things 6. I feel irritated 7. I feel unhappy in my marriage/significant relationship 8. I have thoughts of ending my life 9. I feel weak. 10. I feel fearful 11. After heavy drinking, I need a drink the next morning to get going. (If you do not drink, mark ?never?) 12. I find my work/school satisfying 13. I am a happy person. 14. I work/study too much 15. I feel worthless. 16. I am concerned about family troubles 17. I have an unfulfilling sex life. 18. I feel lonely 19. I have frequent arguments. 20. I feel loved and wanted 21. I enjoy my spare time 22. I have difficulty concentrating 23. I feel hopeless about the future 24. I like myself 71 25. Disturbing thoughts come into my mind that I cannot get rid of 26. I feel annoyed by people who criticize my drinking (or drug use) (If not applicable, mark ?never?) 27. I have an upset stomach 28. I am not working/studying as well as I used to 29. My heart pounds too much 30. I have trouble getting along with friends and close acquaintances 31. I am satisfied with my life 32. I have trouble at work/school because of drinking or drug use (If not applicable, mark ?never?) 33. I feel that something bad is going to happen 34. I have sore muscles 35. I feel afraid of open spaces, of driving, or being on buses, subways, and so forth. 36. I feel nervous 37. I feel my love relationships are frill and complete 38. I feel that I am not doing well at work/school 39. I have too many disagreements at work/school 40. I feel something is wrong with my mind 41. I have trouble falling asleep or staying asleep 42. I feel blue 43. I am satisfied with my relationships with others. 44. I feel angry enough at work/school to do something I might regret 45. I have headaches 72 APPENDIX D Relationship Adjustment Revised Dyadic Adjustment Scale Most persons have disagreements in their relationships. Please indicate below the approximate extent of agreement or disagreement between you and your partner for each item on the following list. Always Agree Almost Always Agree Occasional Agreement Frequently Disagree Almost Always Disagree Always Disagree 1. Religious matters 5 4 3 2 1 0 2. Demonstrations of affection 5 4 3 2 1 0 3. Making major decisions 5 4 3 2 1 0 4. Sex relations 5 4 3 2 1 0 5. Conventionality (correct or proper behavior 5 4 3 2 1 0 6. Career decisions 5 4 3 2 1 0 All the time Most of the time More often than not Occasionally Rarely Never 7. How often do you discuss or have you considered divorce, separation, or terminating your relationship? 0 1 2 3 4 5 8. How often do you are your partner quarrel? 0 1 2 3 4 5 9. Do you ever regret that you married (or live together)? 0 1 2 3 4 5 10. How often do you and your mate ?get of each other?s nerves?? 0 1 2 3 4 5 How often would you say the following events occur between you and your mate? Every Day Almost Every Day Occasionally Rarely Never 11. Do you and your mate engage in outside interests together? 4 3 2 1 0 Never Less than once a month Once or twice a month Once or twice a week Once a day More often 12. Have a stimulating exchange of ideas 0 1 2 3 4 5 13. Work together on a project 0 1 2 3 4 5 14. Calmly discuss something 0 1 2 3 4 5 From: Busby, D.M., Crane, D.R., Larson, J.H., & Christensen C. (1995). A revision of the Dyadic Adjustment Scale for use with distressed and nondistressed couples: Construction hierarchy and multidimensional scales. Journal of Marital and Family Therapy, 21, 289-308 73