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Correspondence: Address correspondence to Victoria B. Mitrani, PhD, Center for Family Studies, Department of Psychiatry and Behavioral Sciences, University of Miami Miller School of Medicine, 1425 N.W. 10th Avenue, Miami, FL 33136. E-mail: vmitrani{at}med.miami.edu
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Abstract |
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Key Words: Alzheimer's • Measurement • Relations • Cohesion
There is mounting evidence that the family plays a role in caregiver distress. Family factors that have been found to be related to the emotional functioning of caregivers include marital cohesion and satisfaction (Rankin, Haut, & Keefover, 2001), cooperative versus competitive communication patterns (Speice, Shields, & Blieszner, 1998), conflict (Semple, 1992), boundary ambiguity (Boss, Caron, Horbal & Mortimer, 1990), and family adaptability (Deimling, Smerglia & Schaefer, 2001; Majerovitz, 1995). Although such studies provide cumulative support for the importance of the family environment, there is no comprehensive theory-based model explaining the mechanisms by which family functioning influences the stress process of caregiving.
The framework that guides the current study is structural family theory (Minuchin, 1974), which views the family as an organism regulated by "structures," that is, repetitive patterns of interaction. Structures determine the manner in which family members communicate, manage disagreements, distribute leadership roles, form alliances, and negotiate distance or closeness. The family's interaction patterns are relatively stable across different situations, and homeostatic processes make them resistant to change. Whereas healthy families adapt their structures in response to the changing needs of family members, others become rigid or disorganized under stress. In dementia caregiving, which requires a realignment of family interactions (Blieszner & Shifflett, 1990), previously adaptive structures may become obsolete. Although some caregiver families eventually reorganize to fulfill newly required roles, others maintain outdated patterns or come apart.
This structural conceptualization is congruent with the stress-process model (Pearlin, Mullan, Semple & Skaff, 1990) in that family functioning is both a secondary stressor and a resource: Stress can disorganize the family and expose individuals to risk, whereas family adaptation can protect individuals from the untoward affects of stress. There is evidence for the disruptive effects of stress on family functioning (McCubbin & Patterson, 1983; Peterson & Hawley, 1998) as well as the family's stress-buffering role (Patterson, 1988). In caregiving, this concept of the family's dual role in the stress process is supported by the work of Fisher and Lieberman (1996; Lieberman & Fisher, 1999).
At the Miami site of REACH (Resources for Enhancing Alzheimer's Caregiver Health; Eisdorfer et al., 2003), we tested the efficacy of a structural family intervention, Structural Ecosystems Therapy (SET; Mitrani, Szapocznik & Robinson, 2000), for reducing distress in caregivers. Our clinical team aimed to strengthen presumably protective structures such as family support, validation of the caregiver's leadership, and the ability to resolve problems; we also aimed to restructure patterns that we believed contributed to caregiver distress such as emotional detachment, negativity, and angry conflicts. Although our intervention strategies were based on structural theory and clinical experience, empirically derived knowledge of the linkages between specific family interaction patterns and caregiver outcomes is needed to develop family interventions that are precisely aimed at those patterns known to affect caregivers. This paradigm has been instrumental in the development of effective family treatments for delinquency and substance abuse (Szapocznik et al., 1988) but has not been applied to caregivers. Such theory-driven and empirically driven treatment-development efforts are recommended in the caregiving literature (Lebowitz, 2004; Pillemer, Suitor, & Wethington, 2003).
The research agenda outlined here requires a method for examining multiple dimensions of interaction in caregiver families. Family assessment is best achieved by observation-based measures (Lindahl, 2001), because they capture processes that are outside of the awareness of family members and are not subject to the reporter biases inherent in self-report. It is also desirable to have theory-based measures to test theoretical precepts that contribute to a comprehensive model and facilitate the translation of research to practice. The Structural Family Systems Ratings (SFSR; Szapocznik et al., 1991) is the only observational measure of family interaction that specifically focuses on multiple structural constructs at the familywide level (Mitrani & Perez, 2003). However, because the SFSR was designed for families of adolescents with behavior problems, its behavioral indicators may not capture some of the family processes that are most relevant for caregivers.
In the current study we adapted the SFSR to assess interactions in dementia caregiver families by integrating structural family theory, clinical experience, and psychometric findings. Our aim in this article is to introduce the SFSR–Dementia Caregiver adaptation (SFSR-DC) and examine the cross-sectional relationship between specific family-interaction patterns and caregiver distress.
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Methods |
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The individuals in the sample for the current study at baseline can be described as follows. Caregivers had a mean age of 69.2 years (SD = 11.3) and had been caregiving for an average of 3.7 years (SD = 3.1). The majority of caregivers were female (71.8%); 43.5% were wives, 24.9% were husbands, 23.2% were daughters, and 8.5% were other relatives of the care recipient. The majority, 62.7%, of the caregivers had more than a high school education; 19.8% completed high school only, and 17.5% had less than a high school education. Their mean score on the Center for Epidemiologic Studies–Depression scale (CES-D; Radloff, 1977) was 17.2 (SD = 11.2), with 48% scoring above the clinical cutoff of 16 (Radloff & Teri, 1986). The mean age of the care recipients was 79.7 years (SD = 7.5). About half were female (51.4%). The mean score on the MMSE was 14.3 (SD = 8.0), with a range of 0 to 29.
Measures
The core battery of measures for REACH is described in Wisniewski and colleagues (2003). The SFSR was administered only at Miami. The measures utilized in the present study are presented here.
Caregiver Depression
We measured caregiver depression by using the CES-D, a 20-item self-report of depressive symptoms that asks about the frequency of depressive symptoms within the past week (4-point scale). Cronbach's alpha in this sample at baseline was 
=.88.
Caregiver Anxiety
We measured caregiver anxiety by using the State Anxiety Inventory (SAI; Spielberger, 1979), consisting of 10 items comprising the state anxiety subscale of Spielberger's State-Trait Personality Inventory (Spielberger, Gorsuch, Lushene, Vagg, & Jacobs, 1983). Respondents are asked how much they agree with statements such as "I feel nervous" (4-point scale). Cronbach's alpha in the current sample at baseline was =.85.
Caregiver Subjective Burden
We measured burden with the Revised Memory and Behavior Problems Checklist (RMBPC; Teri et al., 1992). Respondents indicate which of 24 problem behaviors the care recipient exhibited over the past week, and level of upset regarding each reported behavior, by using a 5-point scale. Subjective burden is calculated by finding the average upset score among all behaviors, assigning a zero to behaviors that were not manifested. Cronbach's alpha in the current sample at baseline was =.83.
Family Interaction Patterns
We assessed family interaction patterns by using the SFSR, which uses a standardized procedure adapted from the Wiltwick Family Task (Minuchin, Rosman, & Baker, 1978) to elicit family interaction on three activities (planning a menu, discussing likes and dislikes about each other, and discussing a recent family argument). The tasks are designed to bring forth family processes that transcend specific presenting problems or content areas but that are nonetheless relevant to the family's management of their problems. Minuchin and colleagues used these tasks in their seminal work to compare the functioning of different diagnostic groups of families.
A trained rater observes videotapes of the family performing these tasks, and the rater codes 63 items on either two or three family tasks to yield a total of 133 indicators. The SFSR yields scores on five subscales: structure, resonance, developmental stage, identified patienthood, and conflict resolution. The range of scores on each subscale is 1 to 5, with higher scores indicating better family functioning. The five subscale scores are summed to determine the total score. Psychometrics with a sample of families of adolescents with behavior problems include alpha reliability of.88 and interrater reliabilities of.89 for total score (Szapocznik et al., 1991).
Procedures
SFSR Rating
A trained rater and V. Mitrani coded 322 videotapes. Mitrani, a developer of the SFSR with 15 years of rating experience, provided the gold standard for rating. The trained rater had more than 5 years of experience rating SFSRs. Rater training for the present study consisted of the two raters' reviewing the coding manual, rating five tapes together, and rating five tapes independently followed by meetings to reconcile discrepancies. Calibration between raters continued throughout the study, and the rating manual was updated to reflect additional instructional details and examples that emerged in these meetings. The raters were blind as to time point and treatment condition.
The average number of participants in the family tasks was 2.80 (SD = 0.75). Although eligibility for the parent study required that a third family member (in addition to the caregiver and care recipient) be available, family tasks were administered even if no others were present. Other family participants included caregivers' daughters (n = 60), sons (n = 44), husbands (n = 32), sisters (n = 17), brothers (n = 14), daughters-in-law (n = 14), sisters-in-law (n = 10), other extended family (n = 46), friends or neighbors (n = 14), and hired aides (n = 6). There were 147 tapes from baseline, 67 from the 6-month assessment, 63 from the 12-month assessment, and 45 from the 18-month assessment. Missing data at the later time points was primarily due to loss to follow-up. However, some family tasks were not administered because of the refusal of the care recipient (n = 8); some were administered but not rated as a result of poor audio or video quality (n = 28) and procedural breaches in family task administration (e.g., when task administrators gave additional instructions or stopped the task too early; n = 16). After the training period, 37 tapes were rated independently by both raters to assess interrater reliability.
We coded all 133 indicators from the SFSR, as well as 60 new indicators (25 items coded on two or more family tasks). A rating form and coding manual are available from V. Mitrani.
Overview of Measure Development Design
Development of the SFSR-DC involved three phases: (a) developing item pools for proposed subscales, (b) refining and conducting a preliminarily cross-validation of the subscales, and (c) developing a multidimensional scale. For the sake of clarity, we report the specific methods with the results of each phase.
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There were three sources of items for each item pool: (a) unmodified SFSR items, (b) items adapted from the SFSR with minor modification to fit the population but without changing the construct, and (c) new items. V. Mitrani developed a list of proposed new items and J. Szapocznik reviewed it to determine whether the items were reflective of the proposed construct and, in the case of the two proposed new constructs, whether they represented adequate coverage of the content area. Revisions to the new items were made on the basis of this feedback. Both individuals involved in item development are developers of the SFSR and of SET and are duly qualified to evaluate the appropriateness of the items for the family task method and their representation of the construct. The items, the family task on which they are rated, and their source are listed in Appendix A. The eight proposed subscales are described in the paragraphs that follow.
1. Problematic caregiver leadership is derived primarily from the SFSR's structure subscale and reflects the extent to which the caregiver is not fulfilling a leadership role in the family. This includes deficits in the caregiver's competence, involvement in decision making, alliances, and others' validation of his or her leadership. Problematic caregiver leadership is rated by noting the amount and quality of the caregiver's contribution toward task completion, how it compares with the contributions of other individuals, how others respond to the caregiver's leadership, and the overall resolution of the task.
2. Enmeshment and 3, disengagement, are derived from the SFSR's resonance subscale. Enmeshment refers to boundaries that are highly permeable, thus allowing for a high degree of closeness or intrusion between family members. Enmeshment is rated by noting the number of instances of boundary-intruding behaviors such as speaking for another person, physically controlling another person, and interruptions. Disengagement refers to boundaries that are highly rigid, thus precluding family closeness. Disengagement is rated by noting the absence of engagement (e.g., an individual does not speak or does not relate to others in an affective manner) or the presence of behaviors that reflect alienation (e.g., refusing to participate) during the course of a task.
The SFSR's resonance subscale sums the absolute value of enmeshed and disengaged indicators to yield one score. For the SFSR-DC, we treated enmeshment and disengagement as two separate subscales because our unpublished findings with adolescent families suggest that they are independent dimensions. Another change was the rating of enmeshment and disengagement at two levels. The first level, which is consistent with the SFSR, is to rate familywide resonance behaviors (e.g., the number of times any individual in the family speaks for any other individual in the family; or whether any individual in the family is never spoken to during the course of the task). The second level involved coding five of the enmeshment items (those most relevant to dyadic functioning) specifically within the caregiver–care recipient dyad (e.g., the number of times the caregiver speaks for the care recipient), and coding all of the disengagement items as they applied specifically to the care recipient (e.g., whether the care recipient is never spoken to during the course of the task). Both levels of coding were tested in Phase II.
4. Family maladjustment to the care recipient's roles is derived from the SFSR's developmental stage subscale, and it reflects the family's failure to adapt to the dementia in that the care recipient is assigned roles that are incongruent with his or her level of functioning. Items consist of noting whether family members assign a role to the care recipient that is either too high (e.g., asking an incapacitated care recipient to lead a task) or too low (e.g., the opinions of a capable care recipient are ignored or not solicited).
5. Identified patienthood is an SFSR subscale that assesses the extent or rigidity of family negativity toward and focus on the identified patient. It is rated by noting the number of times family members focus on or express negativity about the care recipient or the caregiving situation. One new item, "catering to the care recipient," captures one aspect of the family's focus on the care recipient.
6. Conflict resolution is the only SFSR subscale that was unchanged for the SFSR-DC and reflects the manner in which the family manages disagreements and tasks. The resolution of individual differences of opinion and of the overall family task is rated on a 5-point scale. The lowest point on the scale is denial (acting as though a problem does not exist); this is followed by avoidance (the problem emerges but is "swept under the rug"), diffusion (moving on to another problem or conflict without resolving the previous one), and emergence (discussion of the conflict or problem) without reaching a resolution. The highest level is emergence with resolution. We decided not to change this subscale because we observed that caregiver families engaged in all five levels of conflict resolution, and these seemed relevant to caregiver functioning. Further, the scoring of this subscale would not lend itself to factor analysis because items represent mutually exclusive categories and use clinically derived weighting of the different conflict resolution categories.
7. Supportive functioning is a new subscale that, at one end, reflects family support toward the caregiver such as family members' helping with care recipient behavior problems or expressing praise or concern toward the caregiver, and, on the other end, reflects criticism or harsh behavior toward the caregiver. The supportive items were weighted positively and the problematic items were weighted negatively to yield the supportive functioning score. This subscale was proposed in response to our clinical experience as well as research on the relevance for dementia caregivers of family support (Horowitz, 1985; Zarit, Reever, & Bach-Peterson, 1980) and negative exchanges in the social network (Pagel, Erdly, & Becker, 1987).
8. Affective expression reflects the family's overall emotional tone during the family tasks. For each task, the rater assigned a separate score ranging from 0 (not at all) to 4 (extremely) for the extent to which each of four types of affect was expressed by the family: anger or intensity of conflicts, sadness, levity, and positive regard or affection. This subscale was proposed in response to our clinical observation that caregivers in families in which there were expressions of affection or who managed difficulties with a sense of humor seemed to fare better than those in which the overall tone was characterized by sadness or anger.
Phase II
Refining the proposed subscales involved two stages. Stage 1 utilized data collected at the 6-, 12-, and 18-month assessments (n =175) to reduce the item pools to yield reliable subscales. Stage 2 utilized baseline data (n = 147) to perform a confirmatory factor analysis on the subscales that emerged from Stage 1. Conflict resolution was not included in Phase II because it was being accepted without change for the SFSR-DC.
Phase II, Stage 1
We carried out the following four steps for each proposed subscale.
1. We entered indicators in the proposed item pool into an exploratory factor analysis (extraction method: principal component analysis; rotation method: varimax with Kaiser normalization). We compared the factor solutions that were suggested by the scree plot (Catell, 1966) and that had eigenvalues greater than 1 (Kaiser, 1958). The factor solution we selected was the one with the smallest number of factors, that offered minimal overlap of indicators between factors, and in which each factor represented a discernible facet of the subscale construct. We removed indicators that did not load at.30 or above on any factor (Comrey & Lee, 1992).
2. For the multifactor solutions from Step 1, we conducted a factor analysis forcing a single-factor solution to determine if the factors could be aggregated into a single subscale. If a single factor was workable, then we removed indicators with a loading of less than.3 on the single factor. If a single factor was not workable, then we moved each factor forward as a separate subscale.
3. For the indicators that remained after Step 2, we calculated internal consistency by using Cronbach's alpha. We removed indicators that substantially lowered alpha by their inclusion.
4. We conducted interrater reliability analyses (from the entire study sample) on indicators that remained after Step 3 by using intraclass correlation. If the interrater reliability was.7 or above (Hruschka et al., 2004; Landis & Koch, 1977), then we accepted the scale as is. If it was lower than.7, then we calculated interrater reliabilities for each indicator and we removed those that substantially reduced the scale's interrater reliability. We used the intraclass correlation coefficient because the ratings did not form a square n x n table (McGraw & Wong, 1996).
The results of Phase I, Stage 1 were that three proposed subscales emerged as single factors: problematic caregiver leadership (10 indicators), identified patienthood (4 indicators), and supportive functioning (11 indicators). Family maladjustment to the care recipient's roles emerged as expectations of the care recipient that are too high (3 indicators). Affective expression emerged as three subscales: expressed positive affect (6 indicators), expressed sadness (2 indicators), and expressed anger (3 indicators). Enmeshment and disengagement, which were tested at two levels of coding, emerged as familywide enmeshment (12 indicators) and care recipient disengagement (9 indicators). In the case of disengagement, both coding levels resulted in the exact same indicators and were capturing the disengagement of the care recipient from the rest of the family.
Phase II, Stage 2
We entered the indicators from each of the nine subscales that emerged from Stage 1 in a single confirmatory factor analysis by using Mplus Version 2.13 (Muthén & Muthén, 2002), to test whether each subscale was explained by its own single common factor. This procedure serves as a cross-validation of the subscales developed in Stage 1. Note however, that this sample does include the same participants as the sample from Stage 1 (but at different time points), so this is not an independent cross-validation.
Of the 60 indicators that emerged from Stage 1, we removed 14 after preliminary analyses. We removed 4 indicators from problematic caregiver leadership, 6 from supportive functioning, and 2 from expectations of the care recipient that are too high because of the low base rate in the new sample (less than 14 in 147). We removed 1 indicator from problematic caregiver leadership because its loading was not significantly different from zero. Because we dropped 2 of the 3 indicators in the expectations of the care recipient that are too high subscale, we also dropped the subscale's final indicator, thus eliminating this subscale.
The first-order confirmatory factor analysis tested a model with eight hypothesized common factors (subscales) underlying 46 indicators. This model allowed free correlations between subscales and permitted correlations between error variance terms only for indicators that rated the same items on different tasks. We used two indices of fit, the comparative fit index (CFI) and root mean square error of approximation (RMSEA), to evaluate the model. We did not use the chi-square statistic because significance may be due to sample size despite reasonable fit of the model (Bentler & Bonett, 1980; Byrne 2001). The fit indices (CFI =.922, RMSEA =.076) supported this model (Byrne; Tabachnick & Fidell, 1996). Figure 2 shows the factor loadings for each indicator on their respective subscales. The reader should refer to Appendix A for indicator codes. Table 2 presents the estimated correlations between subscales.
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=.62) had composite reliability and interrater reliability above.7.
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Phase III, Stage 1
We examined the correlations between each subscale and caregiver depression, anxiety, and subjective burden. We used baseline data to provide the largest independent sample of family tasks tapes. These correlations are shown in Table 4. We retained those scales that had a significant (p <.05) correlation with at least one distress measure.
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= –.328, p <.001), anxiety ( = –.419, p <.001), and subjective burden ( = –.268, p <.001). In comparison, the total score from the SFSR was only related to depression ( = –.196, p <.019).
Phase III, Stage 3
We tested the factor structure of the SFSR-DC by entering baseline data for each subscale as an indicator loading on a single latent variable in a confirmatory factor analysis using Mplus. The model met criterion for goodness of fit on the CFI index (.918) but not RMSEA (.092). Although these fit indices were somewhat acceptable, an examination of the six scale loadings revealed that identified patienthood and expressed anger had low negative loadings on the latent family-functioning variable, suggesting that a two-factor model might fit the data better. We tested the two-factor model by using confirmatory factor analysis. Fit indices were CFI =.981 and RMSEA =.048, indicating good fit. Factor 1, which we named intimacy–conflict resolution, consisted of enmeshment, care recipient disengagement, conflict resolution, and expressed positive affect. This factor was correlated with depression ( = –.301, p <.001) and anxiety ( = –.409, p <.001). Factor 2, freedom from negativity, consisted of identified patienthood and expressed anger (recall that high scores reflect low negativity). This factor was correlated with subjective burden ( = –.301, p <.001).
Phase III, Stage 4
We tested whether the overall factor pattern in the two-factor measurement model was the same for both ethnic groups (White non-Hispanic American and Cuban American) by using multigroup confirmatory factor analysis. This procedure compares the relative fit of a model that constrains the two ethnic groups to be the same to an alternative model where the two groups are allowed to be different. There was not a statistically significantly difference in fit [
2(df = 3) = 2.03, p <.567] between the two models, suggesting invariance.
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Discussion |
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In addition to measure development, this study provided support for the relevance of family interactions in caregiver distress, and it expanded our knowledge regarding some specific facets of this relationship. First, the use of non-caregiving-related tasks demonstrated that family interactions do not have to be about caregiving to be relevant for caregiver distress. Second, enmeshment, which is typically considered to be problematic (Minuchin, 1974), appears to play a protective function. It is likely that we tapped a moderate level of enmeshment reflecting cohesiveness rather than gross boundary violations, and perhaps it would be more accurate to rename the subscale enmeshment–cohesion. Another finding was that care recipient disengagement was related to caregiver distress. This warranted further analysis because of the possibility that the patient's impairment was driving this relationship. Controlling for MMSE, we found that partial correlations of care recipient disengagement with depression (r =.215, p <.011) and anxiety (r =.228, p <.007) suggest that, regardless of the patient's level of impairment, caregivers are at risk for distress when care recipients are uninvolved in family activities. Finally, we found that it is the manner in which families manage conflicts, rather than the amount of conflict (which we examined in a follow-up analysis) that is related to distress in caregivers.
Limitations
Limitations in this study warrant caution in interpreting results. First, the family members who participated were those who chose to attend after being invited by the caregiver. Therefore, the sample may be overrepresented by family members who were attached to the family. Second, the different phases of measures development did not use independent samples. A further limitation related to sampling is that the pattern of missing data after baseline is likely to represent a bias in the follow-up sample, on which we based our Stage 1 measurement strategy. However, the confirmatory stage and the correlations with caregiver distress were performed with the baseline sample, which had good representation.
Directions for Future Research
Further efforts are needed to cross-validate and examine the SFSR-DC's relationship with other family measures. Although it has been argued that any family activity can be used to assess interpersonal processes (Florsheim & Benjamin, 2001), the choice of family tasks has an impact on the behaviors that are elicited and may have implications for the SFSR-DC's ecological validity. Accordingly, a question that deserves study is whether using family tasks that are directly related to caregiving (e.g., discussing how the family should address some aspect of the patient's care) can tap family processes that are more central to caregiver distress.
Our findings suggest that family closeness and conflict resolution can help protect caregivers from distress, and that family negativity is a risk factor. Longitudinal studies are needed to understand how these and other family structures are changed in response to changes in the stress associated with having a family member with dementia. There are questions about the interaction of family composition and family functioning. Therefore, the use of this measure in a longitudinal design requires documentation of changes in family participation and whether these changes reflect changes in family composition. Clinical follow-up studies also are needed to ascertain whether family structures can be transformed through family therapy and whether such changes in family functioning predict changes in caregiver distress.
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Footnotes |
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1 Department of Psychiatry and Behavioral Sciences, University of Miami Miller School of Medicine, Florida.
2 Department of Education, University of Miami, Coral Gables, Florida.
Decision Editor: Linda S. Noelker, PhD
Received for publication April 9, 2004. Accepted for publication December 17, 2004.
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  V. B. Mitrani, J. E. Lewis, D. J. Feaster, S. J. Czaja, C. Eisdorfer, R. Schulz, and J. Szapocznik The Role of Family Functioning in the Stress Process of Dementia Caregivers: A Structural Family Framework Gerontologist, February 1, 2006; 46(1): 97 - 105. [Abstract] [Full Text] [PDF]
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