A psychosocial profile of women with premenstrual dysphoria

re

ria

elinda J. Board and Tim P.S. Oei of P.qrhdogy, t Received

The I frrr‘r-ersi?y ofQtceenshd, SrisharteA~tsrruliu

1%:November

1991)

received 4 May 1992) (Accepted I4 M&y 1992)

( Revision

Sixty women from the community were used in this study t ~1 identify a profile of women who experience premenstrual dysphoria. Women with prospectively confirmed premenstrual dysphoria (PMD + ; N = 24) were compared to:women with prospectively unconfirmed premenstrual dysphorla (PMD - ; D ‘control; N = 21). Over one menstrual cycle daily records of ph.jsical, emotional and behavioural symptoms were completed on the Daily Ratings Form. fither self report easures obtained were the Premenstrual Assessment Form, Rotter’s Internal External Locus of Control, the Locke-Wallace Marital Adjustment Scale, and the State-Trait Anxiety Inventory. A psychiatric history was obtained during an in ..,tcrview. Analyses showed that premenstrually, PMD + and PMD - groups cou!d be significantly differentiated from controls on reports of premenstrual dysphoric changes and levels of state and trait anxiety. Postmenstrually, they could be significantly differentiated from controls firstly, by history of affective disorder and locus of control and secondly, by premenstrual dysphoric changes. There were no significant differences between the PMD + and PMD - women on most of the self report measures either at pre or post menstrual assessments. The present findings suggest that the characteristic profile of PMD + and PMD - women is one of being symptomatic premenstrually in relation to dysphoric changes and levels of state and trait anxiety. Postmenstrually these symptoms appear to be superimposed on a background of a history of affective disorder and an exterm.1 locus of control orientation. Key wordy Premenstrual orientation

dysphoria;

Psychosocial;

The concept of cyclical changes in the moods of women has been empirically acknowledged for

Corresporzderzceto: T.P.S. Oei, Psychology Clinic. Department of Psychology, The University of Queensland, Brisbane QLD 4072, Australia.

Diagnostic

markers;

Mood disorder

history; Control

more than five decades (I-lalbreich et al., 1988; Youdale and Freeman, 198’7). While the level of these changes is not usually clinically significant (Johnson, 1987), community surveys indicate that roughly fifty percent of women experience these changes at most or a_llcycles (Slade, 1989) and a small proportion of women are disabled by cyclical fluctuations (Halbreich et al., 1988; Slade, 1989).

Collectively, premenstrual negative mood changes are referred to as premenstrual dysphoria (PMQ) (Endicott 1986; Rosen et al.. 1988). PMD has been defined as a subset of premenstrual changes characterised by fluctuations in a cluster of negative mood states which include tension, irritability, anger, depression and anxiety (Gallant and Hamilton, 1988; Halbreich et al., the dvspho1983). Typically, in women with P he premenric disturbance is prominent dur strual phase, defined here as one to seven days prior to onset of menstruation (Halbreich et al., l988), dissipates within or shortly after the onset of menses (Hamilton et al., 1989) and can produce significant functio 1 and social impairment (I-Ialbreich et al., 1988; For women to be e frequently reported disturbance it is important to gain an understanding of its correlates (Rag,-Byrne et al., 1987). Of continuing interest to us has been the relationship between psychosocial variables and premenstrual dysphoria. The psychosocial variables which will be addressed in particular are level of marital/partner satisfaction, locus of control, anxiety levels and mood disorder history. They were chosen because they have been prominent in the anecdotal reports of women associated with our work, yet have received little empirical attention. These psychosocial variables may be the residual effects of repeatedly suffering ria or perhaps women’s atese variables during particularly severe episodes of premenstrual dysphoria. Conversely, these variables may be catalysts for the development of premenstrual dysphoria i.e., a combination of a deteriorating marital relationship and high trait anxiety may increase vulnerability to premenstrual dysphoria. Theoretically, me have an inadequate conceptualization of the characteristics of premenstrual dysphoria. Turning now to tile variables of interest, anecdotal reports from women associated with our work to date, suggest that the quality of one’s relationship with partner/spouse and one’s perception of extent of control may come into focus for some women during their premenstrual phase. However, the empirical link between marital sat&ction and premenstrual dysphoria remains unclear. Some researchers (Keye, Hammond and Strong,

1986) have reported a negative relationship between level of marital adjustment and general premenstrual physical, behavioural, and mood changes. Conversely, Morse and colleagues (1988) found no evidence of an association between level of marital adjustment and premenstrual changes. This issue requires further clarification. There is some evidence that P port frequent feelings of lacking their impulses and external events al., 1985). In addition, there is some evidence that women with premenstrual syndrome exhibit an external locus of control (LO@) orientation (O’Boyle et al., 1988). It remains unclear which premenstrual changes have this relationship. Of particular interest was the relationship between qremenstrual dysphoric changes and general LQC rather than health-LOC. In the context of the premenstrual phase, dysphoric changes can impact on physical as well as behavioural we11being, thus it was relevant to assess genera1 LOC rather than health LOC. Our previous research suggests that anxiety, depression and cognitive style, may feature in women who experience premenstrual dysphoria (Christensen and Oei, 1989), as PMD women have significantly higher levels of anxiety, depression and negative self verbalisations than eontrols. These findings were derived, however, from a female undergraduate sample and their generality is unknown. Thus, we were interested in whether a similar relationship existed in a community based sample who were seeking treatment. Another factor of interest has been research findings which suggest that approximately sixty percent of women with a disorder have significant changes (Endicott et al Endicott, 1985; MacKenzie et al., 1986). In this study we sought to assess this relationship using the PAF scales and detailing prospective measures of premenstrual change. Hence the current study aimed to identify a profile of psychosocial variables which could separate premenstrual1y dysphoric and nondyspho~ic women. In an attempt to enhance the assessm’ ,!t and conceptualization of premenstrual dysphoria, we sought to clarify which characteristics are as-

253

sociated with this condition. It was hypothesised that women with confirmed premenstrual dysphoe discriminated from others on the of Premenstrual Assessment Form ange sca!es, histo?{ and type of mood disorder, state and trait anxiety, locus of control and level of marital adjustment.

Subjects Sixty women participated in this study. Thirty nine were recruited from the general public who responded to media coverage seeking women who believed they experience .I the premenstrual changes of anxiety, irritability and/or depression (dysphoria) and wanted to participate in a treatment programme at the University of Queensland Psychology Clinic. Women were excluded from the study for violating one or more of the following entry criteria: aged between 25 and 45 years, had not been hysterectomised; not currently pregnant not taking oral contraceptives; antidepressants or antipsychotics; was menstruating regularly; not receiving other treatment for premenstrual dysphoria; not psychotic nor personality disordered (Christensen and Oei, 1989; Rubinow and Roy-Byrne, 1984). A control group of 21 women without PMD were screened in the same way, except that they reported no history of premenstrual dysphoric symptoms. The subjects for the control group were obtained from the community through door knock appeals and word of mouth. For the control group the age range was 25 to 43 with a mean age of 33.3 years. Procedure All women in the clinical group attended an interview at the University of Queensland Psychology Clinic. Written informed consent was obtained from all subjects, as was detailed demographic data. A clinically trained interviewer then completed the Structured Clinical Interview for DSM-III-R - non patient version (SCID-NP) (Spitzer et al., 1987). Following this, a booklet of measures containing the Daily Ratings Form (DRF) (Endicott et al., 1986), the Luteal and Fellicular versions of the Premenstrual Assess-

ment Form (PAF) (Halbreich et al., 19821, StateTrait Anxiety Inventory (STAI-X1 (Spielberger et al., 1970), Locke-Wallace Marital Adjustment Scale @IAS) (Locke and Wallace, 19591, and Rotter’s Internal-External Locus of Control Inventory (LOC) (Rotter, 1954) was distributed. Subjects were asked to complete a menstrual cycle of the DRF, the STAI-X pre and postmenstrually and the PAF Luteal phase and Follicular phase versions of the PAF. The MIS and LOC were completed once during the menstrual cycle. Women in the control group were interviewed at either the Psychology Clinic, University of Queensland, or in their own residence. Using a semi-structured interview, detailed information was collected on demographic data, menstrual and medical historiss. The SCID-NP was completed and a booklet of measures was given to the subject with accompanying instructions for its completion. The same measures and regime for their completion was observed except that the STAI-X, LOC and MAS were completed once. The PAF was scored using the unipolar summary scale system (Halbreich et al., 1982). This approach classifies the 95 items into 18 scales, which provide quantitative summary scores of change on that particular dimension. As the focus of this study was on dysphoric changes, the following summary scales were targeted: Scale l-low mood/loss of pleasure; Scale 2-endogenous depressive features; Scale 3-lability; Scale 4-‘atypical’ depressive features; Scale 5-hysteroid features; and Scale &hostility/anger; Scale 8anxiety (Christensen and Oei, 1989). The PAF-LP and PAF-FP versions were obtained following a personal communication with their author. In the LP version, women rate the severity of change from their usual state when they are having their most severe premenstrual changes or on the first day of menstrual bleeding when they did not have In determining change, noticeable changes. women refer only to the two preceding days. The FP version is completed in the 7-10 days after menstrual bleeding and women rate the severity level of their experienced behaviour, mood and physical condition during the last 24 hours. With regard to the SCID-NP, as the interest of this study was on history and type of mood disorder, the mood disorder section only was ad-

dressed here. The following modules were completed: mood syndromes, psychiatric screening and mood disorders. For the DRF. the seven days prior to and the seven days immediately following menstruation comprised the premenstrual and postmenstrual phases respectively (Halbreich et al.. 1988). Each subject’s daily scores on the five items constituting the dysphoric mood factor were summed and averaged across the seven days for both the premenstrual and postmenstrual phases to yield a premenstrual and postmenstrual mean dysphoric mood score (Endicott et al., 1986). A similar procedure has been used previously (Christensen et al., 1989; Christensen and Oei, 1989). A thirty percent or greater dccredse in the mean DRF dysphoric mood score irr the postmenstrual phase compared to the premenstrual phase was used to determine confirmed dysphoria for the clinical sample, all of whom considered they suffered dysphoric changes premenstrually. Using this criterion women were assigned to either the premenstrual dysphoria confirmed group (PMD + ) or premenstrual dysphoria unconfirmed (PMD - 1 group (Rubinow et al., 1986). The criterion of a thirty percent difference between mean pre and postmenstrual scores is

Premenstrual

group means, univariate

F’s and correlations

Group

PMD +

PMD-

PMD

Predictor

Mean

Mean

Control

Variable

consistent with the operational definition adopted by NIMH PMS Research Workgroup in 1983 (DeJong et al., 1985) and has been employed by others (Christensen et al., 1989; Christensen and Oei, 1989; Rubinow et al., 1986). There were 24 subjects in the PMD + group, with a mean age of 36, and 15 subjects in the PIMD - group, with a mean age of 37. The third group (controls) comprised 21 female volunteers from the community who claimed that they did not experience premenstrual dysphoric changes. Examination of their DRF data confirmed this.

Prior to the discriminant function analyses, data were examined for relevant multivariate statistical assumptions. No violation of assumptions was detected. In addition, several preliminary ANOVAs were conducted on variables measured only once to discern any within or between group effects for the phase in which they were completed. Results were nonsignificant with approxiand PMD - groups. mately half the P 1 error rate the BonferTo protect for onni adjustment was applied to al analyses to reduce the alpha level used to test

of predictor

-

variables with discriminant

function

Univariate

Discriminant

Functions

F. rati

I

2

Mean

Scale 1

52.00

44.00

I.90 *

Ch 40 * *

0.74 *

0.36

Scale 2

28.00

27.73

3.43 *

20:c)l) * *

0.44 *

0.39

Scale 3

64.42

53.53

3.Yl *

60.11 **

il.82 *

0.36

Scale 4

56.46

42.67

KIY

*

42.54 **

0.65 *

0.10

Scale 5

53.17

40.00

5.14 *

47.57 * *

O.hY *

0.13

Scale 6

SK92 *

41.07 *

4.57 *

57 I7 **

0.76 *

0.03

Scale 8

S7.46

46.00

s.71 *

&I

**

0.73 *

0.24

S-l-Al X-l

52.83

5 I .x0

30.h2 *

IbY5

:: 7

0.42 *

O.j.3

STAI

49.13

SO.73

31.29 *

0.47 *

0.52 *

1I.54

10.53 102.53

25.03 * * 9.24 * *

LOC MAS Mood

X-2

90.42

6.76 113.14

5.78 13.92 **

0.29

I

0.10

- 0.24

0.13

- 0.37

G.13

* Indicates loadings for interpretation ( > = 0.4); * * ?mistical significance P < 0.004. As mood was a dichotomous variable no means are reported.

255

their significance (Hertzog and Rovine, 1985). The experiment-wise alpha level (0.05) was divided by the number of predictor variables in the analysis UIertzog and Robine, 1985). Separate discriminant function analyses were performed on the pre and post menstrual data for the three e Statistical Package for the Social Sciences (SPSS-X release 3). Disc~i~ii~a~~tarra1ysi.sof premenstmal data To determine the major variables that distinguish between the PMD + , PMD - and PMD control groups, a stepwise discriminant function analysis (Wilks method), which is based on minimising the overall Wilks Lambda (Norusis, 1988), was performed. Twelve variablcg# were employed as predictors of membership in the three groups. The predictors were the seven PAF scales; (1) loss of pleasure/low mood; (2) endogenous depressive features; (3) lability, (4) ‘atypical’ depressive features; (5) hysteroid features; (6) hostility/ anger; (8) anxiety state (STAI X-1) and trait anxiety (STAI X-2); locus of control (LOCI; marital adjustment (MAS); and history of mood disorder (Affect). Of the two discriminant functions obtained for the premenstrual data, only the first function was significant (x ‘(24) = 96.2, P < 0.0000). The first function accounted for 88.8% of the between group variability and differentiated the three groups, with the PMD - group falling between the other two. The loading matrix of correlations between predictors and discriminant functions, presented in Table 1, suggests that premenstrually the best predictors in descending order for distinguishing between the PMD + , PMD - and PMD control groups are the PAF lability, hostility/anger, low mood/loss of pleasure, anxiety, hysteriod features, atypical depressive features and endogenous depressive features, followed by trait and state anxiety (Function 1). Only loadings of 0.4 or greater magnitude were interpreted (Tabachnick and Fidell, 1989). On each variable (see Table l), apart from the marital adjustment scale, the univariate F-ratio’s are significant at the 0.004 level (0.05 divided by 12 predictor variables). Post-hoc analyses (Scheffe

tests) show that premenstrually, PMD + and PMD - women experience significantly more low mood/loss of pleasure, endogenous depressive features, lability, ‘atypical’ depressive features, hysteroid features, hostility/ anger, anxiety, and state and trait anxiety than PMD control women. Both PMD + and PMD - groups were significantly less internally localised (I/E LOG scale) than controls. The only significant difference between PMD + and PMD -women was on the PAF scale 6 (hostiIity/ anger), with PMD women having lower levels. With respect to the accuracy of the discriminant functions in classifying PMD + , PMD and PMD control women, they resulted in overall correct predictions being made for 86.93% of subjects. Of the seven subjects incorrectly classified, three were from the PMD + and four from the PMD - groups. Analysis of postmenstrual data A stepwise discriminant function analysis was performed on the postmenstrual data. Twelve predictor variables, as for the premenstrual data analysis, were employed. Two significant functions were obtained for the postmenstrual data (x*(24) = 71.45, P < 0.0000 and x’( 11) = 27.244, P < 0.0042). The first and second functions accounted for 66.1 and 33.9% of the between group variability, respectively. Both functions differentiated the three groups, with the PMD - group falling between the other two. The loadings between predictors and the first discriminant function, presented in Table 2, suggest that postmenstrually the best predictors for distinguishing between the three groups are history of affective disorder and lticus of control. On the second discriminant function the best predictors of group membership were trait anxiety followed by PAF scales 2 (endogenous depressive features), 4 (‘atypical’ depressive features), 1 (low mood/loss of pleasure) and 3 (lability). These two functions can predict group membership with 8 1% accuracy. The first discriminant function appears to be related to women’s perception of their general level of control, with history of mood disorder and locus of control distinguishing between the three groups. Dysphoria seems to be the second

Scale 2 Endogenous

Scale 1 Low Mood

Depress1 ve

60 50 40 30 20 IO

Scale Lab1

v-e

post

w-e

post

Scale 4 “Atyprcal”

3

I ity

Depress1

ve

I 60 i

post

Pre

Scale 5 Hysterold

Scale Host

Features

I I I

6 ty/Anger

60-1 501 40 33 20 10 :

post

we

Scale Anxrety

post

8

60 50

Kev

t

= PMD + group

-= =

PMD - group PMC control

group

Fig. 1.

discriminant function, with group membership being predicted by state anxiety, followed by PAF scales 2, 4, 1 and 3. The univariate F-ratios shown in Table 2 indicate overall significant differences (P < 0.004) on PAF scales 1 (low mood/loss of pleasure), 3 (lability), 4 (‘atypical’ depressive features), locus of control, trait anxiety and history of affective disorder.

Post Hoc analyses (scheffe tests) indicate that on PAF scales 4, 6 and 8 (‘atypical’ depressive features, hostility/ anger an anxiety), and trait + and PMD - women have signifir levels than controls. In addition, controls are significantly more internally oriented than the two clinical groups. Table 2 shows a rend in that PMD - women have s than PMD + and controls on all

257

variables. Post HOC analyses however show that the only significant differences were between the PMD - and control group on PAF scales 1, 2, 3 and 5 (low mood/loss of pleasure, endogenous depressive features, lability and hysteroid depressive features) with the P D - group reporting r levels. Differences between PMD + and - groups were nonsignificant. to mood disorder, frequency data D -I- women have a 38% (g/24) incidence of a mood disorder history while PMD - women have a 47% (7/E) incidence. Details of diagnoses indicate that 8 women in the PMD + and 3 women in the PMD - had a lifetime prevaone woman in lence of major depression= the PMD -I- and 3 in the P diagnosis of PEIVPT?~ 3-a P*.a. major one woman had a diagnosis of ne of the women in the control group met criteria for either a current or lifetime prevalence of mood disorder. Group means for the PAF dysphoric scales at pre and postmenstrual phases are presented in Fig. 1 and show that premenstrually, PMD -Iwomen report higher levels compared to the D - or PMD control groups. The PMD + women also show a marked drop in mean levels on these variables from pre to post menses. Women in the PMD - group do not

show the same consistency or magnitude of change across phases. On all variables measured during pre and post menstrual phases the PMD + group show higher mean levels than the PMD group premenstrually but show lower mean levels than the PMD - group postmenstrually. Only slight changes from pre to post menses on these variables are apparent for the control group. iscussion Women with premenstrual dysphoria were able to be significantly discriminated from controls at both the pre and post menstrual phase. Premenstrually PMD + and PMD - women were discriminated from controls on seven PAF mood t__ a3 __ __.-tt -- trait- any -.- 3 state arje&. changes S-ales wc:ll as measures. In the post menstrual phase these clinical groups were significantly distinct from controls firstly on mood disorder history and locus of control, and secondly on four of the seven PAF mood changes scales. Overall, the results indicate that premenstrually the profile of women who seek treatment for premenstrual dysphoria is characterised by high levels of dysphoria and anxiety, which become overshadowed postmenstrually by a history of mood disorder and an external locus of control orientation. Unlike others, such as Keye et al. (1986), these

TABLE 2 Pestmenstrual

group means, univariate F’s and correlations

of predictor variables with discriminant

functions

Group Predictor Variable

PMD+ Mean

PMD Mean

PMD Control Mean

Univariate F-ratio

Discriminant 1

Functions 2

Scale 1 Scale 2 Scale 3 Scale 4 Scale 5 Scale 6 Scale 8 STAI X-l STAI X-2 LOC MAS Mood

13.42 07.33 14.79 14.96 12.83 13.41 14.58 34.71 39.37 11.54 90.41

20.53 17.87 22.47 22.87 16.8 14.87 16.33 39.27 45.53 10.53 102.53

1.52 1.71 1.48 2.14 2.29 0.91 1.43 30.62 31.29 6.76 113.14

6.19 5.64 6.16 7.57 4.86 4.56 4.78 2.5 10.27 8.24 5.78 13.92

- 0.23 -0.10 - 0.23 - 0.25 - 0.23 - 0.27 - 0.27 -0.10 - 0.26 -0.42 * 0.38 0.59 *

0.46 0.52 0.46 0.51 0.37 0.30 0.31 0.32 0.62 0.25 0.04

**

**

** ** *

* Loadings for interpretation ( > = 0.4); * * Statistical significance P < 0.004. As mood was a dichotomous variable no means are reported.

* * * *

*

results suggest that level of marital harmony does not discrimlqate premenstrually dysphoric women from others. This inconsistency between the current study and others may be due to mcthodological differences. The marital adjustment scale would be ideally completed pre and postmenstrually. Turning to the locus of control, PMD + and PMD - women had a more external than internal orientation as compared to the control group, suggesting that they perceive themselves having little power to control both their own actions and external events. This finding is compatible with those of O’Boyle et al. (1988> and taken together suggest that women who experience premenstrual dysphoria have an external locus of control orientation yet in the premenstrual phase this is dominated by the influences of a negative mood state and high anxiety. Our study does not enable us to conclude whether such an orientation resulted from or was caused by repeated episodes of premenstrual dysphoria or major deprcsG)n. As a relatively stable personality characteristic the external orientation shown by the treatment seeking sample is quite consistent with their elevated scores on trait anxiety, another enduring measure. In any future assessment of the relationship between LOC and premenstrual dysphoria it would be desirable to obtain LOC measures pre and post menstrually. These results are inconsistent with the findings of two earlier studies wherein PMD + women were distinguished from PMD - women by their significantly higher levels of state and trait anxiety (Christensen and Oei, 1989, Christensen et al., 1989). However, previous work was with undergraduate women who were not seeking treatmcnt for premenstrual dysphoria and rated their prcmcnstrual changes retrospectively. The present study was based on women from the general community who were seeking treatment and made prospective ratings postmenstrually. The inconsistency could be explained by the fact that the 30% criterion which was sufficient to differentiate between these two groups in the non-clinical sample (Christensen and Oei, 1989) is inadequate for the clinical (treatment seeking) sample. In terms of similarity at the premenstrual phase, the PMD + and PMD - groups were

indistinguishable so far as their seven PAF dysphoric symptoms, apart from hostility/ anger (the PMD - group reported significantly less). Turning to differences at postmenses, the P group did not have the thirty percent reduc emenses levels F dysphoria compared when compared to the he PAF scales appear to be more dysphori and more anxious. However, ese differecces were not statistically significant. T difference between the PMD + groups is that of phase. In view of the fact that there were no statistically significant on frequency of mood disorde nious explanation is that in wo for premenstrual dysphoria. criterion for prospective confirmation may not be sufficiently stringent to separate these groups. This hypothesis is currently under investigation. Another possible explanation is that in view of the overa!! ~-end h..I. hth C’VCnI grc\ups to have ;t histoq of mood disorder, this phenomenon may have masked possible differences between the PMD -Iand PMD - groups. This study suggests a profile of experience premenstrual dysphoria (P PMD - 1 as one of being sympto ity, hostility/anger and anxiety being the prominent features at that time. Postrne~str~a~~y they can be characterised by a history of mood disorder and an external locus of control. Future research would be enhanced by the assess two consecutive menstrual cycles rather t cycle only. Also, as our results reflect, and postmenstrual experience of women sufficiently motivated to seek treatment for their dysphoria, they may be representative of a particularly distressed group of premenstrual sufferers. These results suggest that in conceptualizing women who are premenstrual dysphoria sufferers, the diagnostic markers are likely to be an external locus of control orientation and a history of major depression. In the premenstrual phase in particular, these women are likely to experience mood changes and higher levels of anxiety. However, it seems that premenstrually dysphoric women comprise two distinct groups: women whose mood and anxiety levels deteriorate premenstrually and improve posimenstrually (PMD

259

+ women); and a second group who remain somewhat more dysphoric Froughout their cycle (PMD - women). Our results corroborate others’ findings y suggesting that women whose prospective ratings 0 not confirm premenstrual dysphoria may have a mood disorder history. Therapeutic approaches which impact on mood, anxiety and perception of control orientation may be differentially effective for these two groups, wit being more resistant to treatment. This issue requires further empirical

A.P. and Oei, T.P. (I9891 Correlates of confirmed dysphoria. J. Psychosomat. Christensen. A.P.. Oei. T.P. and C ip between premenstrual dysphoria and daily ratings dimensions. J. Affect. Dis. 16, 127-132. DeJong. R.. Rubinow. D.R., Roy-Byrne. P.. Hoban. M.C., Grwer. G.N. 2nd P&t. R.?.?. (191(41 Premenstrual mood disorder and psychtatric iilness. Am. J. Psychtatty 132. 1359-1361. Endicott. J.. Halbreich, U.. Schacht. S. and Nee. J. f 1981) Premenstrual changes and affective disorders. Psychosomat. Med. 43. Sl9-529. Endicott. J.. Nee. J.. Cohen. 9. and Halbreich. U. (19%) Premenstrual changes: Patterns and correlates of daily ratings. J. Affect. Dis. 10. 127-135. Gallant. S.J. and Hamilton. J.A. (1988) On a premenstrual psychiatric diagnosis: What’s in a name? Prof. Psychoi.: Res. Pratt. 19. 271-278. Halbreich. U.. Alt. I.H. and Paul. L. (1988) Premrnsirual Changes: Impaired hormonal homeostasis. Endocrinol. Metab. Clin. N. Am. 17. 173-19-I. Halbreich. U. and Endicott. 3. (1982) Classification of premenstrual syndromes. In: R. Friedman (Ed.). Behavior and the Menstrual Cycle, Marcel Dekker. New York. pp. 243-265. Jlalbreich, U. and Endicott, J. ( 19XSa) Methodological issues in studies of premenstrual changes. Psychoneuroendocrinology 10. 15-32. Halbreich. U. and Endicott. J. (198Sb) Relationship of dysphoric premenstrual changes to depressive disorders. Acta Psychiat. Stand. 7 1. 33 l-338. Halbreich. U.. Endicott. J. and Nee. J. (1983) Premenstrual depressive changes. Arch. Gen. Psychiatry 40. 53S-542. Halbreich, U. and Endicott. J.. Schacht, S. and Nee. J. (1982) The diversity of premenstrual changes as reflected in the premenstrual assessment form. Acta Psychiat. Stand. 65, 46-65. Hamilton. J.. Alagna. S. and Sharpe, K. (1985) Cognitive approaches to understanding and treating premenstrual depression. In: H. Osafsky and S. Blumenthal (Eds.). Pre-

Christensen.

menstrual Syndrome: current findings and future directions. American Psychiatric Press, Washington pp. 67-8.4. Hamilton, J.A.. Gallant, S. and Lloyd, C. (1989) Evidence for a menstrual-finked artifact in determining rates of depression. J. Nrrv. Ment. Dis. 177, 359-365. Haskett. R.F. (1987) Premenstrual dysphoric disorder: Evaluation Q~OQ~YS~OEO~Y and treatment. Progr. NeuropsychopharmcoE. Biol. Psychiatry f t . t 29- 135. Hertzog. C. and Rovine, M. (1985) Repeated - measures analysis of variance in developmental research: Selected issues. ChiId Develop. 16, 787409. Johnson. S.R. i 1987) The epidemiotogy and social impact of premenstrual symptoms. Chn. Obstet. Gynecol. 30. 367376. Keye. W.R., Hammond. D.C. and Strong, T. (1986) Medical and psychologic characteristics of women presenting with premenstrual symptoms. Obstet. Gynecol. 68, 633-637. Locke. H.J. and Wallace. K.M. (1959) Short marital-adjustment and prediction tests: Their reliability and validity. Marriage Family Living August 25 t -255. MacKenzie, T.B., Wilcox, K. and Baron, H. (1986) Lifetime prevalence of psychiatric disorders in women with premenstrual difficulties. J. Affect. Dis. 10, 15-19. Morse. C.A.. Dennerstein, L., Varnavides, K. and Burrows, G.D. Cl988)Menstrual cycle symptoms: Comparison of a non-clinical sample with a patient group. J. Affect. Dis.. 14, 31-50. Norusis. M.J. (1988) SPSS-X: Introductory Statistics Guide. SPSS Inc. Chicago, IL. O’Boyle. M.. Severino, S.K. and Hurt, SW. (198X) Premenstrual syndrome and locus of control. Int. J. Psychiatry Med. 18, 67-7-t. Rosen, L.N.. Moghadam. L.Z. and Endicott. J. (1988) Psychosocial correlates of premenstrual dysphoric subtypes. Acta Psychiat. Stand. 77, 346453. Rotter, J.B. (195-I) Social Learning and Clinical Psychology. Englewood Cliffs, Prentice-Hall. New Jersey. Roy-Byrne, P.P., Hobart, M.C. and Rubinow, D.R. (1987) The relationship of menstrually related mood disorders to psychiatric disorders. Clin. Obstet. Gynecol. 30, 386-395. Rubinow, D.R. and Roy-Byrne, P. (1984) Premenstrual syndromes: Overview from a methodological perspective. Am. J. Psychiatry 131. 163-172. Slade, P. ll989) Psychological therapy for premenstrual emotional symptoms. Behav. Psychotherapy 17. 135- 151). Spielberger. C.D.. Gorusch, R.L. and Lushene, R.E. (1970) STAI Manual for the State-Trait Anxiety Inventory. Consulting Psychologists Press, Palo Alto, CA. Spitzer. R.L.. Williams, J.B. and Ribbon, M. (1987) Instruction Manual for the Structured Clinical Interview for DSM-III-R. New York State Psychiatric Institute. New York. Tabachnick, B.G. and Fidell, L.S. (1989) Using Multivariate Statistics (2nd ed.). Harper and Row. New York. Youdale, J.V. and Freeman, R.J. (1987) Premenstrual assessment form typological categories: Classification of self-defined premenstrually symptomatic and asymptomatic women. J. Consult. Clin. Psychol. 55. 418-42.