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Copyright 1998 by the American Psychological Ass

Journal of Abnormal Psychology 1998, Vol 107, No. 3, 497-:in7

Expressed Emotion and Interactional Patterns in the Families of Bipolar Patients Teresa L. Simoneau, David J. Miklowitz, and Rakhshanda Saleem University of Colorado at Boulder

The predictive validity of expressed emotion (EE) may derive in part from its relationship to important interactional processes in families of patients with major psychiatric disorders. The authors examined the relationship between relatives' EE attitudes, assessed during patients' bipolar, manic, or mixed episodes, and the interactional behavior of bipolar patients (n = 48) and their relatives as revealed in problem-solving discussions during the postepisode period. High-EE relatives were more verbally negative than low-EE relatives in these discussions. Patients from high-EE families were more nonverbally negative than those from low-ER families, whereas patients from low-EE families were more nonverbally positive than those from high-EE families. Sequential analyses revealed that high-EE families engage in negative interchanges of up to 3 volleys. Thus, levels of EE are associated with stressful patterns of interaction between bipolar patients and their relatives during the postepisode period.

It is becoming more widely recognized that family socioenvironmental factors influence or at least predict the course of major psychiatric disorders. However, family processes can be examined from a number of different vantage points. For example, they can be understood as the attitudes different members of a family hold toward each other or as the interactions between family members when they discuss and try to solve family problems. Expressed emotion (EE) refers to critical, hostile, or emotionally overinvolved attitudes that relatives hold toward a family member with a psychiatric illness (Vaughn & Leff, 1976). The operational definitions of these attitudes originally derived from observations of the family interactional processes accompanying episodes of schizophrenia (Brown, Birley, & Wing, 1972). EE attitudes have been found to predict the course of schizophrenia and major depressive disorder (for reviews, see Hooley, Rosen, & Richters, 1996; Miklowitz, 1994; Parker & Hadzi-Pavlovic, 1990). More recently, the predictive validity of EE has been extended to bipolar affective disorder (Miklowitz, Goldstein, Nuechterlein, Snyder, & Mintz, 1988; Miklowitz, Simoneau, Sachs-Ericsson, Warner, & Suddath, 1996; O'Con-

nell, Mayo, Flatow, Cuthbertson, & O'Brien, 1991; Priebe, Wildgrube, & Muller-Oerlinghausen, 1989). EE attitudes, assessed from an interview with a patient's caretaking relative during an acute episode of the patient's disorder, are associated with certain interactional processes in the families of schizophrenic and depressed patients. In families of schizophrenic patients, high-EE parents are more critical than low-EE parents when engaged in problem-solving interactions with their schizophrenic offspring during the postepisode period (Miklowitz, Goldstein, Falloon, & Doane, 1984; Miklowitz et at, 1989). Similar findings are seen with spouses interacting with a depressed partner: High-EE spouses are more verbally critical and disagreeable than low-EE spouses when interacting with their partner about differences in opinion on an attitude survey (Hooley, 1986). The EE research has focused mainly on relatives' behavior, but some studies have shown that patients' interactional behaviors are also associated with relatives' EE attitudes. Strachan, Feingokl, Goldstein, Miklowitz, and Nuechterlein (1989) found that schizophrenic patients interacting with low-EE parents during a postepisode problem-solving discussion made more statements of autonomy and fewer statements of criticism toward their relatives than schizophrenic patients interacting with highEE parents. Likewise. Hooley (1986) found that depressed patients interacting with high-EE spouses were less positive and less self-disclosing than depressed patients interacting with lowEE spouses.

Teresa L. Simoneau, David J. Miklowitz, and Rakhshanda Saleem, Department of Psychology, University of Colorado at Boulder. This research was supported in part by National Institute of Mental Health

Grants

MH43931,

MH42556,

and

MH55101;

by

Grant

9009473A from the John D. and Catherine T. MacArthur Foundation Network on the Psychobiology of Depression; and by a Faculty Fellow-

The results of these studies may suggest an interactional process in high-EE families characterized by "reciprocal negativity" between patients and relatives. Indeed, using sequential analysis techniques, Hahlweg ct al. (1989) showed in a schizophrenic sample that reciprocally negative sequences of nonverbal behavior were longer in high-EE families than in low-EE families when schizophrenic patients and their parents engaged in problem-solving discussions during the postepisode period. Patients and relatives in high-EE families engaged in negative

ship to David J. Miklowitz from the University of Colorado. This study is based on the doctoral dissertation of Teresa L. Simoneau. We thank Kara Allen, Elizabeth George, Kristin Powell, Jeffrey Richards, Natalie Sachs-Ericsson, and Maryann Tucker for their input. Correspondence concerning this article should be addressed to Teresa L. Simoneau, who is now at the Department of Medicine, University of Colorado Health Sciences Center, Campus Box A021-210, 4200 East 9th Avenue, Denver, Colorado 80262. Electronic mail may be sent to [email protected].

497

498

SIMONEAU, MIKLOWITZ, AND SALEEM

nonverbal behaviors for up to 20 consecutive parent-patient exchanges, compared with an average of only 6 negative behavioral exchanges in low-EE families. Hooley (1990) extended these findings to patients with major depression interacting with their spouses. While patients were hospitalized for a depressive episode, spouses were interviewed for assessment of EE, and couples were videotaped discussing a topic on which they had differing opinions. High-EE couples were found to have longer negative sequences of verbal (5 vs. 3) and nonverbal (10 vs. 2) behaviors than low-EE couples during these interactions. Low-EE couples had longer sequences of positive verbal (9 vs. 6) and nonverbal (14 vs. 9) behavior than high-EE couples. Do the associations between EE and family interactional processes observed among families of patients with schizophrenia and major depressive disorder generalize to families of patients with bipolar disorder? Differences in the symptomatology of these disorders could lead to important behavioral and functional differences between diagnostic groups, which could influence the interactional behavior of the patient as well as individuals with whom the patient is interacting. For example, bipolar disorder is usually associated with better between-episode remissions than is schizophrenia, so less family stress and conflict might be expected among the families of bipolar patients during the postepisode period. Indeed, studies have found interactional differences when comparing schizophrenic and bipolar patients. For example, Miklowitz, Goldstein, and Nuechterlein (1995) found that relatives of schizophrenic patients were more critical and intrusive than relatives of bipolar patients during a problem-solving interaction conducted during a posthospital period. In addition, bipolar patients were more verbally supportive of their relatives than schizophrenic patients, whereas schizophrenic patients were more self-denigrating than bipolar patients. Using a subset of Miklowitz et al.'s (1995) sample, Simoneau, Miklowitz, Goldstein, Nuechterlein, and Richards (1996) found that differences between these groups extended to the nonverbal realm as well. The relatives of schizophrenic patients were less nonverbally engaged (e.g., poor eye contact, fewer smiles and head nods) during interactions with their schizophrenic offspring than the relatives of bipolar patients, whereas the relatives of bipolar

in which a certain verbal or nonverbal behavior (e.g., criticism) occurs. In attempting to understand the interactions of families containing an ill member, one must examine whether these interactions are primarily attributable to features of the patient's disorder or to his or her current level of symptoms. For example, bipolar patients with a more chronic type of illness who do not return to baseline functioning between episodes may be more irritable and negative during interactions. Alternatively, relatives could become more frustrated with, and thus respond more negatively to, a patient who has had frequent episodes. Thus, a second objective of this study was to examine patients' symptomatic states and illness characteristics as predictors of the interactional behaviors of bipolar patients and their relatives in problem-solving discussions.

Method Participants Recruitment.

The participants were part of the Colorado Family

Treatment/Outcome Project, a randomized, controlled clinical trial assessing the comparative efficacy of two psychosocial treatments for patients with bipolar disorder: family-focused psychoeducational treatment versus crisis management with naturalistic follow-up, both administered with standard medications (Miklowitz, Frank, & George, 1996). For this study, we included all patients who entered the treatment project by March 1993 (N = 61). Of the 61 patients, 12 dropped out of the study before a baseline family interactional assessment was completed. For the purposes of this study, 1 participant was dropped from consideration because her key relative was a sibling, whereas all other participants had a parent or a spouse. Therefore, 48 bipolar patients and their family members were available for this study. Identification of participants appropriate for participation in the larger treatment study was conducted through weekly chart screening at four sites in the Denver, Colorado area: (a) the University of Colorado Health Sciences Center, (b) Centennial Peaks Hospital, (c) Boulder Community Hospital, and (d) the Boulder County Mental Health Center's Cedar House, a transitional living residence for patients with nonacute disorders. Participants were approached if (a) they were experiencing a bipolar manic or a bipolar mixed episode, as judged by the attending psychiatrist, and (b) they met the inclusionary criteria outlined below. Most of the patients (n = 4 3 ) were hospitalized during the index episode. An additional 5 were referred to the project by community psychiatrists during or shortly after an acute bipolar manic or mixed episode that did

patients showed comparatively more nonverbal affiliation with their patient offspring. In addition, bipolar patients tended to

not require inpatient treatment.

show more nonverbal engagement in interactions with their rela-

research diagnosis of manic or mixed bipolar disorder (according to

tives than schizophrenic patients did. The main objective of the present study was to assess whether relatives' attitudes toward patients with bipolar disorder (i.e., their EE status), assessed during a manic or mixed episode, are related to the interactional behavior of relatives and patients in problem-solving discussions conducted during a postepisode assessment (i.e., a period of relative clinical remission). A subsidiary goal was to assess whether bipolar patients or relatives in high-EE family units are more likely than those in low-EE family units to reciprocate negative behaviors during family interactions, as revealed in lag sequential analysis (Gottman & Roy, 1990). Rather than just assessing individual behavior, lag sequential analysis assesses reciprocal dependencies among behaviors during a family interaction to better elucidate the context

Inclusionary criteria.

Participants met the following criteria: (a) a

criteria from the Diagnostic and Statistical Manual of Mental Disorders, 3rd ed., rev.; DSM-HI-R; American Psychiatric Association, 1987) in the 3 months leading up to and including the month of study entry, as judged from an independent research interview, the Structured Clinical Interview for DSM-///-fi-Patient Version (SCID-P; Spitzer, Williams, Gibbon, & First, 1988), (b) age between 18- and 60-years-old, (c) no evidence of organic central nervous system disorder or mental retardation, (d) no evidence of drug or alcohol abuse that was considered significant or habitual in the 6 months prior to the acute episode and no prior use that clouded the primary diagnosis of bipolar disorder, (e) living with or in significant contact with a key relative or relatives for a minimum of 1 month out of the 3 months prior to entry into the study, and ( f ) the willingness, as well as the ability, to give written informed consent to participate. If participants met all criteria fur entry into the study, their significant relatives (parents, siblings, spouses) were contacted about participation.

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EXPRESSED EMOTION AND INTERACTIONAL PATTERNS

Trained SCID-P interviewers diagnosed patients either

tive's emotional reactions to the patient's interpersonal behavior and

while they were hospitalized for their index episode or shortly after

symptoms, particularly during the 3 months prior to an acute episode

hospital discharge. If the patient had not been hospitalized, interviewers

of illness. A trained EE rater coded audiotapes of the interviews for

Diagnosis.

administered the SCID-P at the patient's home within 1 month after the

critical, hostile, or overinvolved attitudes. The criteria used to classify

onset of the acute episode. Raters first attended training sessions on the use of the SCID-P. Then,

a relative as high EE were (a) six or more criticisms during the interview,

they rated standardized videotapes and had individual supervision on

5 (high) on emotional overinvolvement (Vaughn & Leff, 1976). A

administration of the instrument until they reached adequate reliability

family was considered high EE if one or both of the relatives (in dual-

with a criterion rater. Interrater reliability (Cohen's, 1960, kappa) for

relative households) were rated high EE. Otherwise, the family was

SCID-P items (each rated on a 0, 1, or 2 scale), calculated after training,

considered low EE. In single-parent or single-spouse families, the EE

averaged .71 (p < .001; calculated on a minimum of seven cases per

rating of the family was equivalent to the individual relative's EE rating.

(b) the presence of hostility, or (c) ratings of 4 (moderately high) or

rater).

Of the 48 families, 30 (63%) were low EE, 12 (25%) were high EE

Pharmacological treatment. Community psychiatrists pharmacologically managed study patients with standard medications for bipolar

critical, and 6 ( 1 2 % ) were high EE emotionally overinvolved. The mean

disorder. At the time of hospital discharge or entry into the treatment

number of criticisms was 3.6 (SD = 3.4), and the mean emotional overinvolvement rating was 1.6 (SD = 1.3). Of the 59 relatives, 4 were

study, 26 were on lithium, 10 were on an anticonvulsant (carbamazepine

rated as hostile, but all 4 were also rated high EE because they expressed

or divalproex sodium), 7 were on a combination of lithium and an

six or more critical comments.

anticonvulsant, and 5 were on other combinations of mood-regulating

The CFI audiotapes were coded by a rater who had successfully

medications for their bipolar illness. In addition, 24 were taking antipsy-

completed an EE-rating workshop and had attained, by the end of the

chotic medications, 11 were taking antianxiety medications, and 10 were

workshop, agreement levels of .80 or higher (using the phi coefficient)

taking antidepressants, Demographic variables.

Table 1 shows demographic and illness his-

of interrater agreement in the current study, calculated between the

tory characteristics of the study patients. The sample was diverse in age (M = 35.4 years) and characteristics of the illness (mean years since

trained rater and a second trained rater, were .82 (p < .001) for critical

illness onset — 10). Patients were well-educated (M - 14.0 years), and

for emotional overinvolvement ratings (intraclass correlation coeffi-

the median socioeconomic class was 3.0. The majority of the patients

cients were based on 10 randomly selected sample tapes).

with a criterion rater for judgments of high- versus low-EE status. Levels

were female (n = 31, 65%). Of the 48 families, 28 (58%) included spousal relatives, and 20 (42%) included parental relatives. There were 11 "dual-relative" families: 7 dual-parent families, 2 parent-sibling combinations, 1 parent-spouse combination (mother-wife),

and 1

spouse-relative combination (husband-son). The rest of the families consisted of the patient and either 1 parent (n = 11) or a spouse (n = 26).

statements, .93 (p < .0001) for hostility ratings, and .80 (p = .001)

Family interactional assessment.

The core assessment for this study

was an evaluation of the family's communication and problem-solving skills, as revealed in a laboratory setting. Families participated in a family-interaction procedure after the patient's resolution of the acute phase of the index study episode. This procedure was conducted, on average, 28 days (SD = 32 days) after the CFI interview and 48 days (SD = 48 days) after discharge from the hospital, if a hospitalization had occurred. During individual interviews with the patients and separate

Procedure EE ratings.

interviews with their relatives, research staff members identified two Trained interviewers evaluated the level of EE among

key relatives (parents or spouses) by using the Camberwell Family Interview (CFI; Vaughn & Leff, 1976) while the patient was still hospitalized or while he or she was acutely ill and being treated on an outpatient basis. The CFI is a semistructured interview focusing on the rela-

family-conflict issues. The patient or relative verbalized each issue while being audiotaped (e.g., "When you don't talk to me, I feel lonely"), and the relative or patient to whom this issue was directed responded to the issue on the same audiotape, recorded contiguously (e.g., "Sometimes I just need some space before I can talk to you"). The experimenters chose one conflict topic from the patient and one from the relative as stimuli for the family discussions. Examples of problems included communication difficulties, issues regarding sensitivity to other family members' feelings, and responsibility for self-management, such as

Table 1 Demographic and Illness Characteristics of 48 Patients With Bipolar Disorder

household cleanliness or getting a job. To initiate these family discussions, an experimenter played the audiotape of one of the problem topics (i.e., a participant's statement of a

Variable

M

SD

Range

10.0

18-56

problem and the target person's response) to the family or couple. After listening to the topic, the participants were asked to discuss it for 10

Age (years)

35.4

Sex Male Female Age at onset (years) Duration of illness (months) Years since illness onset Social class" Education (years) No. of prior hospitalizations Family composition Parental Spousal a

min and try to solve it. Theiy were left alone to do this. The same procedure was followed for the second family problem. Both discussions

17 (35%) 31 (65%) 26.0 14.5 10.0

2.6 14.0

2.6

were audio- and videotaped. The order of presentation of the problem

9.9 13.5

8.4 1.2 2.3 3.1

13-56 1-52 0-28

stimuli was counterbalanced across families, according to whether problems were generated by patients or relatives. Interactional coding system.

The core question addressed in this

1-5

study concerned the degree to which high- and low-EE couples and

10-20 1-16

families could be distinguished on patterns of interactional behavior

20 (42%) 28 (58%)

Socioeconomic status was calculated with the Amherst modification (Watt, 1976) of Hollingshead and Redlich's (1958) two-factor index of social position. Median = 3.0 for social class.

and particularly on sequences of negative point-counterpoint verbal exchanges. We used the KPI (Category System for Partners Interaction; Hahlweg et al., 1984) to measure interactional behavior from videotapes of the family discussions. The KPI assesses speaker and listener skills of couples or dyads (both verbal and nonverbal behaviors) to assess the larger constructs of communication and problem-solving skills. Evidence for the discriminant validity of the KPI has been shown by its ability

500

S1MONEAU, MLKLOWITZ, AND SALEEM

to distinguish between high- and low-EE relatives of depressed or schizo-

reliability between trained-rater/criterion-rater pairs. The ICC reliabili-

phrenic patients (Hahlweg et al., 1987, 1989; Hooley, 1986). The coding unit for the KPI is a block of speech by a given person

ties for the positive and negative summary categories were as follows:

that contains statements of similar content. The KPI has 29 verbal codes

(range = .80-.91); positive nonverbal behavior, M = .78 (range =

that can be collapsed into 12 (self-disclosure, positive solution, acceptance, agreement, criticism, negative solution, justification, disagree-

.77-.79); and negative nonverbal behavior, M = .68 (range = ,67-.68;

ment, problem description, metacommunication, rest category, and lis-

tended to vary (ICC = .61-.79; for all, p < .0001), with some codes

tening) or 3 (positive, negative, and neutral) summary codes (Table 2). Every statement by a relative or patient is coded in alternating fashion

negative solution, and justification; ICC < .50). Therefore, analyses

positive verbal behavior, M = .94; negative verbal behavior, M = .84

for all, p < .0001). Interrater agreement for the individual verbal codes having very low agreement because of low base rates (positive solution,

(i.e., a relative's statement followed by a patient's statement followed

were conducted at the level of the positive and negative verbal and

by a relative's statement), allowing for the use of sequential analytic techniques.

nonverbal summary categories.

Each verbal code also receives a positive, a negative, or a neutral nonverbal code. Nonverbal codes are assigned using hierarchical decision rules. Facial expressions are assessed first, then voice tone, and finally body movements, A judgment is made at each level of the hierarchy as to whether the nonverbal behaviors exhibited are positive or negative. If a positive or negative code is not assigned after assessing all three levels, then a neutral code is assigned. Teresa L. Simoneau learned this system by reading the KPI manual and practicing the coding procedures with sample videotapes and transcripts of the 10-min problem-solving interactions. She then served as the criterion KPI coder and trained two undergraduate psychology students on the use of the system. Training lasted a total of 50 hr. Coding units were marked on the transcripts by the criterion rater to obtain

Whereas the ICC coefficients demonstrated that the raters agreed on the number of positive and negative KPI codes applied to the 10 family interactions, they did not establish whether the raters agreed on an occurrence-by-occurrence basis. We felt that point-by-point agreement should be demonstrated before sequence analyses were justified. Therefore, we used Cohen's kappa statistic to calculate point-by-point reliability between the trained-rater/criterion-rater pairs for positive and negative verbal and nonverbal KPT behaviors. Kappas for the verbal summary codes were high (K = .82- .87, p < .0001). Kappas for the nonverbal codes were only fair (K = .61-.72, p < .0001), but we felt they were adequate for certain exploratory analyses of nonverbal behavioral sequences among high- and low-EE families. Patient symptomatology.

Family interactions may be influenced by

more accurate point-by-point ratings. The KPI manual was used as a

the patient's level of residual symptoms following an episode of psychi-

guide for decisions about which blocks of speech constituted a coding

atric disorder. We assessed patients' symptoms at the time of the family

unit. The raters were asked to classify each codable unit with a KPI

interactional assessment by using the Schedule for Affective Disorders

verbal code and nonverbal code while watching each videotaped 10-

and Schizophrenia-Change Version (SADS-C; Spitzer &, Endicott,

min interaction (two per family). All trained raters and the criterion rater were unaware of the EE status of the families.

sessing the severity of depressive, manic, and psychotic symptoms. In-

1978). The SADS-C is a well-validated structured interview for as-

We obtained interrater reliability ratings from a random selection of

terrater reliabilities (intraclass rs) for SADS-C items across 11 indepen-

10 family discussions (videotapes and transcripts) that were indepen-

dent raters, assessed from audiotapes of randomly selected SADS-C

dently rated by trie two trained judges and compared with the criterion

interviews, averaged .92 (SD = .08) for depression items, .81 (SD =

rater's judgments. An analysis of variance (ANOVA) intraclass correla-

. 1 1 ) for mania items, and .81 (SD = .10) for psychosis items (for all,

tion (ICC) approach (Bartko & Carpenter, 1976) was used to assess

p < .001; rs were calculated on a minimum of 10 cases per rater).

Table 2 Category System for Partners Interaction (KPI) Code Categories and Code Definitions Category Positive Self -disclosure Positive solution Acceptance of other Agreement Negative Criticize Negative solution Justification Disagreement Neutral Problem description Metacommunication Rest Listening Nonverbal codes Positive Negative Neutral

Definition

Direct expression of feelings, wishes, or needs Specific, constructive proposals or compromise Paraphrase, open question, or positive feedback Direct agreement, acceptance of responsibility, or assent A negative remark or judgment about the partner's behavior such as insults, criticisms, or accusations Remarks having a destructive influence on the problem- solving process such as demands for the partner not to do something or unacceptable suggestions Excuses for one's own behavior or denying responsibility Direct disagreement, "yes, but" statements, or short disagreeing statements such as "no" Neutral descriptions of the problem Clarification requests or process comments related to the topic Statements not fitting other verbal categories (i.e., comments irrelevant to the topic or statements the coder could not understand because of poor tape quality) When double coding of a speaker occurred this code was used Hierarchical decision rules were used to code nonverbal behavior Positive behavior was assessed from the face first, then from voice tone, then from body movement Negative behavior was assessed in the same way as positive behavior A neutral code was assigned if no other code applied

ICC .94 .79 < .50 .61 .97 .84 .72 < .50 < .50 .79 .99 .94 < .50 .64 .99 .78 .68 .55

Note. ICC = intraclass correlation. From Coding Manual for the KPI (Kategoriensystem far Partnerschaftliche Interaktion), by K. Hahlweg and M. Conrad, 1983, University of California, Los Angeles. Unpublished manuscript. Adapted with permission.

EXPRESSED EMOTION AND INTERACTIONAL

Results Data Reduction and Analyses For all of the statistical analyses, verbal statements by patients or relatives were collapsed into positive, negative, and neutral summary categories. The positive verbal category consisted of statements of self-disclosure, acceptance, agreement, and positive solutions to problems. The negative verbal category consisted of statements of criticism, justifications, disagreements, and negative solutions. The neutral verbal category consisted of problem descriptions or other types of utterances that were neutral in tone. The authors of the KPI coding system delineated these a priori groupings (Hahlweg et al., 1984) and used them in a study of families of schizophrenic patients (Hahlweg et al., 1987). We assessed the relationship between relatives' EE status (low vs. high) and the interactional behavior of relatives and patients during the family interactional assessment by using ANOVAs with the EE status of the family as the independent variable. The total number of positive and negative statements and the total number of positive and negative nonverbal behaviors shown by relatives and patients over the two 10-min family interactions were used as the dependent variables. We did not consider differences in neutral verbal and nonverbal behavior because we did not have hypotheses about these behaviors. ANOVAs were conducted separately for relatives and patients. Whereas the majority (« = 37) of the families consisted of a patient with a single relative, 11 had 2 participating relatives, each of whom produced individual KPI scores (number of positive, negative, and neutral KPI statements summed across the two 10-min interactions). There are many ways to handle dualrelative data, including summing or averaging scores, retaining individual scores, or forming family profile scores (Baucom & Sher, 1987). To reduce the number of univariate comparisons between high- and low-EE family units and to be consistent with the methods of our prior studies (Miklowitz et al., 1989, 1995), we summed the KPI scores of the 2 participating relatives in the 11 dual-relative families. When only 1 relative participated, that relative's KPI scores served as the dependent variable in the univariate comparisons. We summed rather than averaged the scores of the 2 relatives to capture the total amount of emotionally toned expression to which the patients in these families were exposed. With this method, total relative KPI scores (i.e., the sum of all positive, negative, and neutral KPI codes) were found to be somewhat higher in dual-relative (M = 183, SD = 86) than in single-relative (M = 127, SD = 36) families, as might be expected. However, this difference did not achieve statistical significance, t(l, 46) = 2.12, p < .10.

501

PATTERNS

Table 3 Relationship of Expressed Emotion (EE) to Relatives' and Patients' Interactional Behavior High EE (n = 18) KPI category Relative Positive verbal Negative verbal Patient Positive nonverbal Negative nonverbal Note.

Low EE (n = 30)

M

SD

M

SD

P

31.72 25.67

22.64 17.15

31.73 14.97

20.67 10.70

ns < .02

34.61 62.50

30.03 67.41

62.77 27.80

51.39 42.01

< .05 < .05

KPI = Category System for Partners Interaction.

number of positive and negative nonverbal behaviors displayed by high- and low-EE relatives, F(l, 46) = 0.76, p > .10 and F(l, 46) = 2.08, p > .10, respectively. We invpJtigated whether the negative interactional behavior of relatives with high emotional overinvolvement (n = 6) differed from that of relatives with a high number of critical comments (n = 12), as some studies of relatives of schizophrenic patients have shown (e.g., Miklowitz et al., 1984; Strachan, Leff, Goldstein, Doane, & Burtt, 1986). Although high-EE critical relatives made more negative statements (M = 29.6, SD = 18.9) than high-EE emotionally overinvolved relatives (M = 17.8, SD = 10.3) during the interactions, this difference was not significant, / ( 1 , 1 6 ) = 1.7,/» . 10. The comparison between high-EE emotionally overinvolved and high-EE critical relatives is exploratory because there were only 6 families in the emotionally overinvolved group. We evaluated the possibility that the relationships between relatives' attitudes and interactional behavior differed depending on whether the relative was a parent or a spouse. With a 2 X 2 ANOVA, a main effect was still found for EE, F(3,44) = 5.41, p < .03, when EE and family composition (parental vs. spousal) were entered as independent variables and negative KPI total scores were entered as the dependent variable. Family composition was unrelated to the number of negative KPI statements made by the relatives, f(3,44) = 0.04, p > .10, and the interaction between EE and family composition was not significant, F(3, 44) = 0.02, p > .10. Thus, high-EE relatives—regardless of whether they were parents or spouses—made more negative verbal statements than low-EE relatives during interactions with their bipolar family members.

EE and Interactional Behavior Among Patients EE and Interactional Behavior Among Relatives Table 3 shows the comparisons of high- and low-EE relatives on the total number of positive and negative KPI statements made to their bipolar family member over the two 10-min interactions. As expected, high-EE relatives made more negative statements than low-EE relatives, F(\, 46) = 7.12, p < .02. However, there was no difference in the number of positive KPI statements made by high- and low-EE relatives, F(l, 46) = 0.00, p > .10. In addition, there were no differences in the

If the EE construct taps into a bidirectional interactional process between bipolar patients and their relatives, then a relationship should exist between relatives' levels of EE and patients' interactional behaviors when interacting with these relatives. It is interesting that there were no differences in the number of positive and negative verbal statements made by patients in highand low-EE families, F( 1, 46) = 0.42, p > .10 and F( 1, 46) = 0.02, p > .10, respectively. However, as shown in Table 3, there were differences in the bipolar patients' nonverbal interac-

502

SIMONEAU, MIKLOWITZ, AND SALEEM

tional behaviors as a function of whether they were interacting with high- or low-EE relatives. Bipolar patients in high-EE families displayed more negative nonverbal behaviors during problem-solving interactions with their relatives than bipolar patients in low-EE families, F(l, 46) = 4.85, p < .05. In addition, bipolar patients in low-EE families displayed more positive nonverbal behavior than those in high-EE families, F(l, 46) = 4.46, p < .05. Thus, patients' nonverbal behaviors rather than their verbal behaviors discriminated between those interacting with high-EE versus low-EE relatives.

Illness History Variables and Patient Symptomatology We evaluated the possibility that characteristics of the patients' illness accounted for the relationship between EE and the interactional behavior of relatives and patients. First, using ANOVA, we examined differences in the level of depressive, manic, and psychotic symptoms exhibited by patients from highand low-EE families at the time of the laboratory interactional assessment. Data on manic and depressive symptoms were missing for 4 patients, and data on psychotic symptoms were missing for 5 patients. Patients from high-EE families reported more manic symptomatology than patients from low-EE families, F(l, 42) = 4.54, p < .05. Patients from high-EE families also reported more depressive symptoms than patients from low-EE families, but this difference did not reach significance, F( 1,42) = 3.71, p < .10. There was no difference in the level of psychotic symptoms reported by patients from the two groups, F( 1, 41) = 1.03, p > .10. Next, with analysis of covariance, the levels of depressive and manic symptoms experienced by patients at the time of the interactional assessment were entered separately as covariates in the EE KPI interactional behavior analyses. The relationship between relatives' EE status and their negative verbal behavior displayed during interactions with their bipolar relatives remained significant after covarying the effect of patients' depressive, F(l, 41) = 7.28, p < .02, and manic, F(l, 41) = 6.05, p < .02, symptoms. The presence of depressive and manic symptoms also did not significantly influence the relationship between EE and patients' positive or negative nonverbal behavior: EE was still related to patients' positive nonverbal behavior after controlling for depressive and manic symptoms, f (1, 41) = 3.71, p = .06 and F(\, 41) = 5.49, p < .03, respectively. Further, EE still predicted patients' negative nonverbal behavior after controlling for depressive and manic symptoms, F( 1, 41) = 5.67, p = .03 and F(l, 41) = 8.23, p < .01, respectively. Finally, other core characteristics of the patients' illness were entered as covariates in separate analyses of the relationships between relatives' EE and relatives' negative verbal KPI statements, and between relatives' EE and patients' positive and negative nonverbal behaviors. These characteristics were the number of previous manic or depressive episodes, the total number of months a patient had been ill during his or her lifetime, the age of the patient at the onset of the illness, and the number of years since illness onset. In only one case was the EE-KPI relationship affected; the total number of months the patient was ill across the lifespan statistically weakened the relationship between family EE status and patients' positive nonverbal behavior, f (1, 35) = 2.99, p < .10. However, because of missing

data on months of illness, only 38 participants were included in this analysis. Thus, for the most part, variations among patients in manifestations of illness did not significantly affect the relationships between relatives' EE attitudes and the behavior of bipolar patients or their relatives in family interactions.

Interactional Patterns Between Relatives and Patients: Lag Sequential Analysis The above analyses indicate that levels of EE among relatives predict the overall amount of positive or negative affective behavior among both relatives and patients in direct interactions. A different question is whether the behavior of one person in a family interaction is influenced by or reciprocated by another and whether the nature or length of these reciprocal sequences vary with the EE status of the family. Sequential analysis techniques (Bradbury & Fincham, 1991; Gottman & Roy, 1990) enable the examination of dependencies among certain target behaviors when evaluating interactions among dyads or triads. Although there are a number of sequential analytic methods available, lag sequential analysis was chosen for this study because it allows for examination of relatively long sequences of behavior without the prohibitive amount of data required by other methods. The number of data points (one coded unit of speech) needed to use lag sequential analysis in this study, given the number of KPI codes and using Gottman's formula (Gottman & Roy, 1990), was calculated to be 100. All of the 10-min interactions in this study exceeded 100 data points. Lag sequential analysis determines whether the unconditional probability or base rate of a behavior differs from the conditional probability of that behavior given knowledge of a prior behavior (in either the same person or another family member). A Z statistic indicates the degree to which the conditional probability of the behavior exceeds its expected frequency from base rates (i.e., the unconditional probability of the behavior in the family under consideration). Allison and Liker's (1982) revision of Sackett's (1979) Z statistic was used in this study. Z scores with an absolute value larger than 1.96 are significant at the .05 level. Sequence analyses within high- and iow-EE groups. Lag sequential analysis permits a number of questions to be addressed. The first and most basic is whether individual lags are significantly more frequent than base rates within the high- and Iow-EE groups. That is, do the types of interactional behavior displayed by a patient or relative probabilistically depend on a preceding criterion behavior in that patient or a relative, even if other behaviors have intervened? To address this question, high- and low-EE families were examined separately. Negative and positive verbal behaviors of relatives and patients were used as the criterion codes, with the same type of behavior among relatives or patients (negative or positive) as the target codes at different sequential lags (i.e., a relative's negative verbal behavior followed by a patient's negative verbal behavior at Lag 1, a relative's negative behavior at Lag 2, etc.). A lag is a delay in a sequence of behaviors. Thus, in the sequence "relative positive behavior, patient negative behavior, relative negative behavior," the "patient negative behavior" target code is one lag removed from the "relative positive behavior" crite-

EXPRESSED EMOTION AND INTERACTIONAL PATTERNS

rion code, and the "relative negative behavior" target code is two lags removed from the "relative positive behavior" criterion code. Every alternating code in a sequence was a patient code, as required by the KPI coding system. When high-EE relatives' negative verbal statements were used as criterion codes, patients' and relatives' negative verbal behaviors following these criterion behaviors were significant at Lags 1_4 („ = 18; z = 2.56, 2.63, 2.17, and 2.29, respectively; all ps < .05; see Figure 1). When low-EE relatives' negative verbal statements were used as criterion codes, none of the Z scores for Lags 1-4 were significant (n = 30; Z = 1.42, 1.82, 1.27, and 1.26, respectively; all ps > .05). These results suggest that when a high-EE relative made a negative statement, it was statistically likely to be followed by a negative statement by the patient at Lag 1. A negative statement by a high-EE relative at Lag 0 was also likely to be followed by a negative statement by the relative at Lag 2, a negative statement by the patient at Lag 3, and a negative statement by the relative at Lag 4. However, these results do not necessarily indicate that these behaviors occurred in succession. Lag sequential analysis tests each lag individually, so the sequence generated by this analysis does not necessarily reflect actual patterns of interaction. To test whether the sequence of negative verbal behaviors seen at Lags 1 -4 in high-EE families was likely to occur in succession, the criterion code was defined as pairs of codes. For example, a relative's negative statement followed by a patient's negative statement was defined as a criterion code, with the third code in the sequence (a relative's negative statement) serving as the target code at Lag 1. Then, the first three negative verbal codes were used as the criterion code (a relative's negative statement followed by a patient's negative statement and ending with a relative's negative state-

3.0

2.5

2.0

1.5 M N

1.0

—

High EE — Low EE

0.5

LagO-R Figure L

Lag1-P

Lag2-R

Lag3-P

Lag4-R

Lag5-P

Lagged probability profile analysis of negative behaviors

from the Category System tor Partners Interaction in high- and low-EE families. Lines indicate within-group comparisons; asterisks denote Z scores significant at p < .05; and arrows indicate between-group comparisons. R = relative; P = patient; EE = expressed emotion.

503

ment), with the fourth code in the sequence (a patient's negative statement) used as the Lag 1 target code. The results showed that sequences of three negative behaviors were significantly more frequent in high-EE families than would be expected by chance (n = 18, Z= 2.22,p < .05). In other words, the "threevolley" ' sequence of a relatives' negative statement followed by a patient's negative statement and ending with a relative's negative statement occurred more frequently in high-EE families than would be expected by the base rate of negative behaviors in the high-EE cohort. Longer sequences of negative behaviors among high-EE families were not significantly more frequent than chance. When a patient's negative verbal behavior was used as the criterion code, sequential dependencies were still apparent but not as strong. Specifically, sequential negative behaviors by relatives and patients following a patient's negative statement were significant for high-EE families at Lags 1 and 2 (n = 18, Z = 2.48 and 3.35, respectively, p < .05) and for low-EE families at Lag 2 only (n = 30, Z = 2.81, p < .05). That is, in low-EE families, a negative verbal statement by a patient at Lag 0 was statistically likely to be followed by another negative statement by that patient at Lag 2. These results may suggest that a high-EE relative started negative interactional sequences with a negative statement. However, a patient could have displayed a nonverbal behavior that provoked a negative response from a relative. To address this question, we entered patients' negative nonverbal behaviors as the criterion code with relatives' negative verbal statements as the Lag 1 and Lag 3 target codes. The Z scores at both of these lags were nonsignificant in high-EE families (n = 18, Z = 1.77 and 1.23, respectively,p > .10). Thus, negative nonverbal behaviors by patients were not differentially likely to precede negative statements by high-EE relatives. When using positive behaviors as criterion codes, reciprocal dependencies were not as apparent. A relative's positive behavior as the criterion code was significantly more likely to be followed by a positive behavior by the relative at Lags 2 and 4 in both high- and low-EE families (high EE: n = 18, Z = 2.47 and 2.38, respectively, p < .05; low EE: n = 30, Z = 2.67 and 2.38, respectively, p < .05). If a patient's positive behavior was used as the criterion code, it was likely to be followed by positive behaviors of the patient and relative at Lags 1 and 2 in highEE families (n = 18, Z = 2.16 and 2.68, respectively, p < .05) and at Lags 2 and 4 in low-EE families (n = 30, Z = 3.05 and 2.22, respectively, p < .05). These patterns suggest that a family member's positive behavior, whether the patient's or the relative's, predicts future positive behavior in the same family member regardless of the EE status of the family. Differences between high- and low-EE groups. The above analyses describe sequences within high- and low-EE families but do not assess differences between these groups. Do highand low-EE families show group differences in their tendency to reciprocate negative behaviors? To address this question, Z scores indicating the frequency of negative behavioral sequences at different lags were used as the dependent variables in ANO\As, with family EE status as the independent variable. High- and low-EE families differed in the probability that relatives' negative statements would be reciprocated by patients, as shown in Figure 1. When a high-EE relative made a negative

504

SIMONEAU, MIKLOWTTZ, AND SALEEM

statement, a patient was more likely to respond with a negative statement at Lag 1, F(l', 46) = 4.31, p < .05, and the relative was more likely to make another negative statement at Lag 4, F( 1. 46) — 4.57, p < .05, than when a low-EE relative made a negative statement. No differences were seen between highand low-EE families at Lags 2 and 3. Thus, in high-EE families, reciprocal negativity is more apparent: Patients respond to relatives' negative statements with a correspondingly negative statement more often in high-EE families than in low-EE families.

Discussion This study examined differences in the interactional behavior of high- and low-EE families of bipolar patients. Significant relationships were found between the EE attitudes of caretaking relatives (parents or spouses), as measured during a patient's manic or mixed episode, and the interactional behaviors of these relatives and the bipolar patient during face-to-face interactions conducted after the resolution of the illness episode (approximately 4 weeks after the EE interview). Relatives holding highly critical, hostile, or emotionally overinvolved attitudes (high EE) toward a bipolar family member made more negative statements (i.e., criticisms, statements of disagreement, self-justifications, or proposals of negative solutions to problems) when inleracting with the patient than did relatives who did not hold these attitudes. Positive statements (self-disclosures, agreements, statements of acceptance, or proposals of positive solutions to problems) and nonverbal behaviors did not distinguish between highand low-EE relatives. Nonverbal behavior, but not verbal behavior, differentiated between patients from high- and low-EE families. Patients from high-EE families displayed more negative nonverbal behaviors than patients from low-EE families, such as looking away from their relative, having an angry facial expression, or using a sarcastic voice tone. In contrast, patients from low-EE families displayed more positive nonverbal behaviors than those from high-EE families, such as smiling, looking attentive, and using a warm and supportive voice tone. Thus, patients from low-EE families were more likely to engage positively in these face-toface interactions, whereas patients from high-EE families were more likely to be contentious with or disengage from their relative or relatives. This study provides an extension of die previously documented relationship between EE attitudes and family interactional behavior to bipolar patients and their relatives. Prior studies have established this association in schizophrenic patients (Hahlweg et al., 1989; Miklowitz et al., 1984; Strachan et al., 1986) and depressed patients (Hooley, 1986). In addition to providing evidence for the concurrent validity of the EE construct, this association raises the possibility that high-EE attitudes in relatives are leading indicators of stress within the larger family environment, at least as indicated by negative interactions in these families. Moreover, repeated experiences of family stress during the postepisode recovery period may contribute to a bipolar patient's liability to relapse. Indeed, in another sample, Miklowitz et al. (1988) found that EE attitudes and negative interactional behaviors during the posthospital period were interactive in predicting relapse risk among young adult, recentonset bipolar patients.

In both the ANOVA comparisons and the sequential analyses, negative interactional behaviors were better than positive behaviors at distinguishing between high- and low-EE families. Levels of positive verbal and nonverbal behavior did not distinguish between high- and low-EE relatives of bipolar patients, even though these behaviors have distinguished between high- and low-EE relatives of schizophrenic patients (Hahlweg et al., 1989) and depressed patients (Hooley, 1986). Given that the interactional coding system used in this study (the KPI) was also used in Hahlweg et al.'s and Hooley's studies, the failure to replicate these group differences may reflect the different family processes that accompany different forms of psychiatric disorders. For example, using a different sample, Miklowitz, Goldstein, Nuechterlein, Snyder, and Doane (1987) and Simoneau et al. (1996) found that the parents of schizophrenic patients were more verbally and nonverbally negative toward their offspring than the parents of bipolar patients. In addition patients with bipolar disorder were more verbally supportive and nonverbally affiliative with their relatives than patients with schizophrenia. As a way of further illuminating these attitude-behavior correspondences, we examined the relationship of EE to sequential interactive processes between bipolar patients and their relatives. High-EE families were more likely to engage in short volleys of negative statements, usually initiated by a relative. In lowEE families, a negative statement by a patient or relative was just as likely to be followed by a positive or neutral statement by a patient or relative as it was to be followed by a negative statement. These results suggest that within high-EE families of bipolar patients, relatives' or patients' negative behaviors are not isolated occurrences but are part of larger bidirectional transactional processes between patients and relatives. Negative verbal sequences of interaction were more likely to be started by relatives, as opposed to patients, in high-EE families. However, this does not necessarily mean thai the relatives' behavior caused the negative interactions to occur. Negative nonverbal behaviors displayed by patients (e.g., looking bored and disinterested) could elicit negative statements by relatives and begin negative verbal sequences in high-EE families. Although patients' nonverbal behaviors were not found to immediately precede relatives' negative verbal statements in sequential analyses, patients in high-EE families were found to be more nonverbally negative than patients in low-EE families during these same interactions. Thus, relatives may have been responding to nonverbal behaviors in patients that occurred much earlier in the behavioral chain. Using different sequential analytic techniques, Hooley (1990) and Hahlweg et al. (1989) showed similar patterns of reciprocal negativity in the high-EE families of depressed and schizophrenic patients, respectively. Hooley found a pattern of reciprocated negative verbal and nonverbal behaviors that occurred much more often among depressed patienls interacting with high-EE spouses than among depressed patients interacting with low-EE spouses. Hahlweg et al. found even longer sequences of negative nonverbal behaviors in the high-EE families of schizophrenic patients and their parents: Reciprocal negative nonverbal behaviors continued for up to 20 changes in speakers in high-EE families, whereas the negative escalation stopped at

EXPRESSED EMOTION AND INTERACTIONAL PATTERNS

505

6 changes in speakers in low-EE families. Analyses of sequences

tive KP1 statements expressed during the interactions. However,

of verbal behavior were not presented in Hahlweg et al.'s study.

because of the small number of emotionally overinvolved fami-

Thus, it appears that high-EE families are emotionally hotter than low-EE families. Patients and family members in high-

lies (n - 6 ) , we cannot draw firm conclusions about this lack of group differences. Future investigations of how emotionally

EE families are more likely to engage in negative interactional

overinvolved and critical families differ in interactional behavior or attribution patterns seem warranted.

behaviors than those in low-EE families, and once negativity is expressed, other families members respond in kind. What is different in high-EE families that evokes these negative interactional patterns is unclear. Although patients in high-EE families

Future research should focus on two important questions. First, are these negative transactional patterns associated with relapse? Relationships have been shown between certain sum-

reported more manic symptoms and showed a statistical trend

mary measures of family interaction, such as relatives' affective

toward having more depressive symptoms at the time of the interactional assessment, it does not follow that these patients

Falloon, Goldstein, & Mintz. 1985; Miklowitz et al., 1988).

are simply more symptomatic than patients in low-EE families and therefore more prone to generating negative responses from

However, to date, no study has examined whether specific sequential patterns of interaction in families have similar pre-

relatives. The EE-interactional-behavior relationships remained

dictive value.

significant after we controlled for patients' concurrent levels of manic and depressive symptoms.

style, and relapses of schizophrenia or bipolar disorder (Doane,

Second, if these negative family interactional patterns are related to relapse, are they amenable to change with treatment?

Negative sequences of behavior may occur more often in

Psychoeducational family-treatment programs have repeatedly

high- than low-EE families because bipolar patients in these

been found to reduce or delay relapses among patients with schizophrenia (for a review, see Goldstein & Miklowitz, 1994).

families are more physiologically aroused and, therefore, are more sensitive to relatives' criticisms, negativity, or overinvolvement. Studies with schizophrenic patients have shown higher levels of psychophysiological arousal in patients interacting with

However, whether these treatments actually change ongoing family interactional behavior or whether they are effective through different mechanisms deserves further investigation.

high-EE relatives than in patients interacting with low-EE rela-

There are two major limitations to this study. Because of the

tives (Sturgeon, Tlirpin, Kuipers, Berkowitz, & Leff, 1984; Tar-

cross-sectional design, we cannot address whether the interac-

rier, Vaughn, Lader, & Leff, 1979). However, studies of arousal have not been conducted with bipolar patients in family interactional settings, an important direction for future research. Hooley (1987) proposed an attributional model to explain

tional patterns observed in the period immediately following recovery from a manic or mixed episode are stable over time or whether the patterns change with different phases of the ill-

the interactional patterns observed in high-EE critical and low-

ness. In addition, these interactions were conducted in a laboratory setting, and we chose discussion topics that were likely to

EE families. She hypothesized that high-EE critical relatives make internal controllability attributions about the causes of

generate affectively laden interactions. Whether these discussions are representative of the type of interactions these families

patients' negative behaviors, blaming patients' intentions for

engage in outside of the laboratory setting is uncertain. Future research should assess family interactional patterns at several phases of the illness and try to incorporate naturalistic observa-

what may actually be symptoms of the illness. Low-EE relatives, on the other hand, are more likely to attribute negative behaviors by patients to uncontrollable illness factors. Support for this theory has been demonstrated in studies of the families of schizophrenic patients (Barrowclough, Johnston, & Tarrier,

tions of families, to the extent possible. Results of this study have important theoretical implications for the EE construct. Instead of suggesting a unidirectional in-

1994; Brewin, MacCarthy, Duda, & Vaughn, 1991; Weisman,

fluence of the relative on the patient, our findings add to the

Lopez, Karno, & Jenkins, 1993) and of couples with a spouse diagnosed with major depression (Hooley & Licht, 1997). Because symptoms of the illness may be seen by high-EE relatives as under the patient's control, they may try to modify the pa-

growing literature suggesting that EE taps into a complex bidirectional transactional process (e.g., Hahlweg et al., 1987;

tient's symptomatic behaviors and become increasingly angry or critical if symptoms persist. Patients in high-EE families,

negative toward patients and that patients find this type of behavior stressful, thus increasing their risk of relapse. Pother, high-

who in parallel may also blame the critical behavior of relatives

EE families appear to engage in negative, possibly coercive,

on internal, global, and stable traits of these relatives, may corre-

patterns of interaction to which both patients and relatives contribute. The ways in which low-EE families manage to avoid these interactional patterns—despite the fact that patients in

spondingly respond with negativity and defensiveness. Although this model provides a parsimonious explanation for the differences in interactional behavior among high-EE critical and low-EE families, it does not explain how high-EE emotion-

Hooley, 1986; Miklowitz et al., 1989; Strachan et al., 1989). It is not merely the case that high-EE relatives are critical or

these families often have illnesses of similar severity to those in high-EE families—deserves further investigation.

ally overinvolved families might be different. In prior work on family interactional processes, emotionally overinvolved relatives have been characterized by greater frequencies of "intrusive" (mind-reading) statements toward patients than high-EE critical or low-EE relatives, as judged by the affective style coding system (Miklowilz et al., 1984; Strachan el al., 1986). Tn the present study, emotionally overinvolved and critical highEE relatives could not be differentiated on the number of nega-

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fication. Unpublished manuscript, University of Massachusetts at Amherst. Weisman, A., Lopez, S. R., Karno, M., & Jenkins, J. ( 1993). An attributional analysis of expressed emotion in Mexican American families with schizophrenia. Journal of Abnormal Psychology, 102, 601-606. Received July 1, 1997 Revision received March 25, 1998 Accepted March 25, 1998 •

Instructions to Authors Journal of Abnormal Psychology Most of the articles published in the Journal of Abnormal Psychology are reports of original research, but other types of articles are acceptable. Short Reports of replications or of failures to replicate previously reported results are given serious consideration. Comments on articles published in the journal are also considered. Case studies from either a clinical setting or a laboratory will be considered if they raise or illustrate important questions that go beyond the single case and have heuristic value. Manuscripts that present or discuss theoretical formulations of psychopathology, or that evaluate competing theoretical formulations on the basis of published data, may also be accepted. For further information on content, authors may refer to the editorial in the November 1995 issue of this journal (Vol. 104, No. 4, pp. 555-557). Authors must prepare manuscripts according to the Publication Manual of the American Psychological Association (4th ed.). All manuscripts must include an abstract that contains a maximum of 960 characters and spaces (which is about 120 words) typed on a separate sheet of paper. All copy must be double-spaced, and further typing instructions, especially in regard to tables, figures, references, metrics, and abstracts, appear in the Manual. Also, all manuscripts are subject to editing for sexist language. In preparing a Short Report, authors should set the character-space limit at 60 characters per line and should not exceed 410 lines of text and references (exclusive of the title page, abstract, author note, footnotes, tables, and figures). There should be no more than two figures or tables. As for regular manuscripts, the abstract must not exceed 960 characters and spaces. Masked reviews are optional, and authors who wish masked reviews must specifically request them when they submit their manuscripts. For masked reviews, each copy of the manuscript must include a separate title page with the authors' names and affiliations, and these ought not to appear anywhere else in the manuscript. Footnotes that identify the authors must be typed on a separate page. Authors are to make every effort to see that the manuscript itself contains no clues to their identities. Articles, except where other limits are specified, must not be longer than 36 manuscript pages, unless they report an unusually large series of studies or present unusually important detail. Case studies are ordinarily no longer than 16 manuscript pages. Comments ought not to exceed half the length of the original article. For Short

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