Department of Neuroscience, Psychiatry
Department of Information Sciences, Statistics
Department of Neuroscience, Psychiatry, Uppsala University, Uppsala, Sweden
Correspondence: Erik Wennström, Department of Neuroscience, Psychiatry, Ulleråker, SE-750 17, Uppsala, Sweden. Tel: +46 18 6112219; e-mail: erik.wennstrom{at}neuro.uu.se
Funding detailed in Acknowledgements.
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ABSTRACT |
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Aims To investigate the factor structure of the CAN.
Method Assessments of 741 out-patients (mean age 45.5 years, 50% females) with severe mental illness (68% schizophrenia or other psychotic disorder) were used in an exploratory maximum likelihood factor analysis.
Results Support was found for a three-factor model, comprising 13 of the 22 variables in the CAN, with the factors corresponding to functional disability (7 variables), social loneliness (3 variables) and emotional loneliness (3 variables). The remaining variables did not load on any factor.
Conclusions Exploratory factor analysis revealed three homogeneous dimensions in the CAN that may represent functional disability and two aspects of social health.
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INTRODUCTION |
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METHOD |
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Data-set
The data-set for the study was compiled from a clinical case register at
the University Hospital in Uppsala, set up in 1996 for longitudinal needs
assessment of out-patients with severe mental illness. Needs assessments of
all patients in regular contact with the mental health rehabilitation services
at the Clinic for Psychosis and Rehabilitation are made once a year by
patients' keyworkers using the Swedish version of the CAN
(Ericson et al, 1997).
The results of the assessments are recorded in the case register, along with
each patient's current principal diagnosis according to the DSM-IV
(American Psychiatric Association,
1994). The keyworkers have at least a half-day training in the use
of the CAN, as recommended in the manual
(Slade et al,
1999b). All diagnoses recorded in the case register are
made by a psychiatrist. The rehabilitation services, which have a catchment
area of 225 000 inhabitants 18 years and older, serve the whole of Uppsala
County, including the fourth largest city in Sweden.
For the factor analysis we selected the CAN assessment of each patient recorded in the case register from 1997 through 1999. A CAN assessment was considered incomplete if one or more items were rated not known (i.e. rating 9). Such ratings are thus in practice equivalent to missing values. Generally, cases with missing values are either deleted in the statistical analysis or the missing values are substituted by, for example, group means. Both procedures may have serious drawbacks for multivariate analysis, such as discarding an unacceptably large proportion of subjects or attenuation of important parameters (Little & Rubin, 1987). To avoid such drawbacks, we chose to retain all selected CAN assessments while substituting any missing values by a multiple imputation procedure, using the Expectation-Maximisation algorithm as implemented in LISREL 8.50 for Windows (Jöreskog & Sörbom, 2001; du Toit & Mels, 2002). This algorithm is a general technique for finding maximum likelihood estimates for parametric models when data are not fully observed, which is quite reasonable to use also with non-normal ordinal variables (Schafer, 1997) (see also Schafer & Graham (2002) for an introductory review of available multiple imputation methods). Several simulation studies (e.g. Enders, 2001; Sinharay et al, 2001) have shown that maximum likelihood estimates obtained by multiple imputation in general are robust and unbiased, even when the proportion of missing data is large.
The study was approved by the research ethics committee of the medical faculty of Uppsala University, Sweden.
Factor analyses
We conducted two successive exploratory factor analyses for severity
ratings on the CAN with maximum likelihood extraction estimates using LISREL
8.50 for Windows (Jöreskog &
Sörbom, 2001). Selection of the number of factors to be
extracted was based on the root mean square error of approximation (RMSEA) fit
index (). Browne & Cudeck
(1993) suggest that a value of
0.05 indicates a close fit of the model. Oblique promax rotation of
factor loadings was used, since the factors were found to be correlated
(Fabrigar et al,
1999). Only factor loadings of |0.30| or above were
considered for interpretation (Gorsuch,
1983). Factors comprising fewer than three salient loadings were
discarded (Streiner, 1994;
Floyd & Widaman, 1995). Two-stage least squares (TSLS) estimates and their standard errors were used
to judge whether a model was reasonable
(Jöreskog et al,
1999), controlling the level of significance at
=0.01
(two-tailed). Finally, to check whether a model was preserved using an
alternative common factor analysis technique which does not make the
assumption of multivariate normality, a principal factor analysis
(Everitt & Dunn, 1991) was
made (see also Fabrigar et al
(1999) for a review of the
major design and analytical decisions in exploratory factor analysis).
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RESULTS |
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The distributions of severity ratings, after imputation of missing values, are shown in Table 1. The distributions of ratings before and after imputation of missing values were very similar (data not shown). Most of the variables had just a small percentage of missing values (mean 2.9%, range 0.7-5.3), whereas for intimate relationships, sexual expression and information on condition and treatment the proportions of missing values were higher (24.2%, 44.0% and 8.1% respectively). Psychotic symptoms, psychological distress, company and daytime activities were the most common problems among the patients, whereas problems regarding social benefits, safety to others, access to telephone and drug misuse were uncommon.
We calculated the summary scores on the CAN, although they were not used in any of the analyses. The total number of needs was 6.4 (s.d.=3.4, 95% CI 6.2-6.6), comprising 4.7 (s.d.=2.7, 95% CI 4.5-4.9) met needs and 1.7 (s.d.=2.0, 95% CI 1.5-1.8) unmet needs.
Our maximum likelihood factor analysis included all 22 CAN variables. The
RMSEA goodness-of-fit test indicated a close fit for a four-factor solution
(=0.054), although comprising only 15 of the variables. Seven of the
variables did not load on any factor: psychotic symptoms,
information on condition and treatment, safety to
self, childcare, basic education,
telephone and social benefits.
Factor 1 consisted of six variables, with high loadings (in parentheses) on looking after the home (0.80), food (0.79) and self-care (0.63), moderate loadings on money (0.55) and accommodation (0.49) and a low loading on transport (0.35). Factor 1 appeared to be a personal disability dimension, since all the constituting items are related to functional ability in daily living, and was accordingly labelled Functional disability.
Factor 2 consisted of three variables, with a high loading on company (0.84), a moderate loading on daytime activities (0.51) and a low loading on psychological distress (0.33). This factor appeared to be a social relationships dimension, with variables concerning interpersonal interactions, social participation, and ties to social networks. Factor 2 was labelled Social loneliness.
Factor 3 also consisted of three variables, with high loadings on sexual expression (0.84) and intimate relationships (0.70) and a low loading on safety to others (0.36). Again, this appeared to be a social relationships dimension, although on a more intimate level than Factor 2, with variables related to intimate contact, romantic relationships and satisfaction with sex life. Factor 3 was thus labelled Emotional loneliness.
Factor 4 consisted of four variables: alcohol, physical health, money and drugs. However, all the factor loadings were low (0.39, -0.33, 0.32 and 0.30 respectively), indicating a weak and poorly defined factor. This factor appeared to be associated with substance misuse but was difficult to interpret, and hence not labelled.
All factors except Factor 4 were correlated with each other, with correlation coefficients in the range 0.35-0.50, indicating interdependence to a certain extent among the dimensions of functional disability, social loneliness and emotional loneliness.
To judge whether the four-factor model was reasonable, a TSLS estimation based on the promax-rotated solution was made. The first three factors were replicated by the TSLS estimation, with looking after the home, company and sexual expression respectively set as reference variables. Another two variables, information on condition and treatment, and telephone, also had significant loadings on Factor 1. The weak fourth factor, with alcohol set as reference variable, was not replicated; none of its constituting variables had significant loadings of 0.30.
By comparing the results of the factor analysis with the results of the TSLS estimation, it appeared to be more reasonable to assume the existence of three rather than four common factors, comprising 13 of the 22 CAN variables. Thus, the first of the three presumed factors, Functional disability, would comprise the variables looking after the home, food, self-care, money, accommodation, transport and telephone. The second factor, Social loneliness, would comprise company, daytime activities and psychological distress, while sexual expression, intimate relationships and safety to others would constitute the third factor, Emotional loneliness.
To investigate the reliability of these three factors, the 13 potentially constituting variables were retained and examined in another factor analysis, following the same procedure as in the first analysis. The variable Information on condition and treatment was not retained because of the cross-correlations to Factor 1 and Factor 3, while, at the same time, it was found to fit neither the concept of functional disability nor emotional loneliness.
The factor loadings and factor correlations following the second factor analysis are reported in Table 2. The expected three factors from the first analysis were replicated (RMSEA=0.051). Moderate correlations between Functional disability and Social loneliness as well as between Social loneliness and Emotional loneliness were found, indicating an approximately 20% shared variance in both cases (Table 3). A small correlation was also found between Functional disability and Emotional loneliness, indicating only 3% shared variance between the two factors.
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The three-factor solution was also subjected to TSLS estimation. The reference factor loadings, their standard errors and associated t-values are reported in Table 4. All three factors from the promax-rotated solution were replicated. Functional disability was found to comprise looking after the home (as reference variable), food, self-care, money, accommodation, transport and also telephone, all with significant factor loadings. Social loneliness was found to comprise company (as reference variable), daytime activities and psychological distress, also with significant factor loadings. Likewise, Emotional loneliness was found to comprise sexual expression (as reference variable), intimate relationships and safety to others, with significant factor loadings as well.
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The three-factor solution was preserved in the subsequent principal factor analysis with promax rotation, both in full sample analysis and in analyses when the sample was divided, at random, in halves (data not shown).
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DISCUSSION |
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The first factor, labelled Functional disability, consisted of looking after the home, food, self-care, money, accommodation, transport and telephone. This factor captures difficulties in basic functions and activities in normal living. Functional disability is generally defined as any difficulty, linked to health conditions, in conducting activities of daily living (ADL) (McDowell & Newell, 1996). Activities of daily living may in its turn be subdivided into personal ADL, limited to excretion, cleanliness, feeding, dressing, mobility and communication, and instrumental ADL, comprising household activities, mobility in the wider environment and other basic activities in independent living (McDowell & Newell, 1996). The CAN items comprised in Functional disability seem to be tapping both aspects of ADL; food, self-care and telephone seem to be related to central aspects of personal ADL, whereas looking after the home, money, accommodation and transport are more related to aspects of instrumental ADL. These seven CAN items are also similar to central items in scales used particularly for measuring ADL (McDowell & Newell, 1996).
The other two factors, Social loneliness and Emotional loneliness, seem to be tapping two distinct aspects of social health. Social health has consensually been defined as:
that dimension of an individuals well-being that concerns how he gets along with other people, how other people react to him, and how he interacts with social institutions and societal mores (Russell, 1973: p. 75).
Thus, broadly defined, social health is associated with functioning in social roles and integration in the community, and with affiliation and close relationships on a more intimate level. One obvious sign of problems in either of these aspects of social health is loneliness. The experience of loneliness is, however, according to Weiss (1973), phenomenologically different depending on whether it is stemming from social isolation or from emotional isolation. Whereas social loneliness is a consequence of the absence of meaningful friendships, collegial relationships or linkages to other social networks, emotional loneliness is a result of the absence of romantic relationships or an intimate attachment. Symptomatically, social loneliness is often associated with feelings of boredom, depression, aimlessness and marginality, whereas emotional loneliness rather seems to be associated with apprehension, a sense of utter aloneness and a tendency to misinterpret or to exaggerate the hostile or affectionate intent of others. This typology of loneliness, first described by Weiss (1973), has more recently been supported by a number of studies (e.g. DiTommaso & Spinner, 1997; Russell et al, 1984).
The first of the two social health factors in our study - Social loneliness - may be connected with lack of employment and few social contacts, which can be regarded as prominent elements of social isolation. It is reasonable to assume that problems and discontentment in these areas might indicate a sense of loneliness consistent with the construct social loneliness in Weisss typology. The inclusion of psychological distress in this factor is also consistent with the construct of social loneliness; high levels of psychological distress, particularly depression, have been found to be significantly associated with social loneliness but not with emotional loneliness (DiTommaso & Spinner, 1997).
The second of our two social health factors was labelled Emotional loneliness. Lack of affiliation and intimate relationships are considered by Weiss (1973) to be the essential elements of emotional isolation leading to emotional loneliness. It seems reasonable to assume that the three CAN items sexual expression, intimate relationships and safety to others might indicate loneliness in this sense.
Several variables did not load on any of the factors. This was not unexpected, because the items of the CAN were chosen to reflect the whole range of problems encountered by people with severe mental illness (McCrone et al, 2000). Some might be more related to features of the service systems concerned than to the mental health conditions per se. This might explain why variables such as information on condition and treatment, childcare and social benefits did not load on factors related to personal and social functioning.
Neither psychotic symptoms nor safety to self were associated with a factor, which was perhaps more surprising. In this out-patient population it may not be useful to rate psychotic symptoms globally. In fact, symptoms are known to be highly variable among people with severe mental illness, both cross-sectionally and longitudinally (van Os et al, 1999; Ganev, 2000), and there appears to be only a modest association between current social dysfunction and the characteristic symptoms of psychotic episodes in schizophrenia (Glynn, 1998). Consequently, it has also been recommended that social functioning should be assessed independently from psychopathology (de Jong et al, 1996).
Our results were to a certain extent in accordance with the previous study by Slade et al (1999a) using principal component analysis with orthogonal rotation, but there were also differences. Whereas our results indicate the presence of not more than three common factors, Slade et al found seven principal components, although only four were found to be interpretable. These four appeared to be associated with activities of daily living, relationships, drug and alcohol problems and living conditions. The ADL factor in our study was similar to the corresponding ADL component in the study by Slade et al, sharing the same items except accommodation and food. The two social health factors found in our study were also somewhat in accordance with two components found by Slade et al: the items daytime activities and company loaded on the same factor in both studies, as did sexual expression and intimate relationships. However, in comparison with the results of Slade et al, we seemed to find more clean and conceptually consistent factors, which might be due to differences in methods. Common factor analysis generally provides a better simple structure and results that are more easy to interpret than a principal component analysis, especially when salient loadings are moderate in value rather than high (for a review of the aims and limitations of the different techniques see Fabrigar et al, 1999).
Because our sample was restricted to out-patients with severe mental illness, our findings may not be generalisable to other patient populations or untreated community samples. Our study also has other limitations that should be considered. Some of the variables had many missing values, particularly intimate relationships and sexual expression, which were both related to the emotional loneliness factor. Multiple imputation of missing data, which was used to compensate for this, was made under the assumption that all data were missing at random. However, there is no possibility of knowing whether this is true. Furthermore, the CAN assessments were made in routine clinical care, with many different raters. Regardless of any possible problems associated with such assessment conditions, it is a widely used method of data collection in research on severely mentally ill persons, having the advantage of confidence in long-term patient-staff relationships and naturalistic clinic conditions.
Our findings may have several clinical implications. First, although the results confirm the rather heterogeneous nature of the CAN overall, the summary scores of items corresponding to the more homogeneous dimensions of functional disability and social health might be measures that are more reliable and more sensitive to changes over time than the standard summary scores. This must of course be confirmed in further studies. Second, the three factors might also have a stronger clinical appeal than the standard summary scores and inform the care planning process in a more meaningful way, although individual needs also need to be examined along with any summary score. Finally, since problems in ADL, social interactions and intimate relationships call for different forms of remediation, the factor scores might be more useful as outcome measures in mental health rehabilitation programmes than the standard summary scores seem to be.
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Clinical Implications and Limitations |
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LIMITATIONS
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ACKNOWLEDGMENTS |
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REFERENCES |
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Received for publication November 27, 2003. Revision received April 16, 2004. Accepted for publication June 26, 2004.
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