Assessing attitudes toward euthanasia: an analysis of the subcategorical approach to right to die issues

PERSONALITY INDIVIDUAL

PERGAMON

AND DIFFERENCES

Personality and Individual Differences 25 (1998) 719-734

Assessing attitudes toward euthanasia: an analysis of the subcategorical approach to right to die issues Robert Ho* School

qfPsychology

and Sociology, Central Queensland University, Bruce Highway, Rockhampton, QLD 4702, Australia Received

6 June 1997

Abstract This study was designed to investigate the way people perceive and respond to the issue of euthanasia. Four models were developed to reflect the subcategorical distinctions of (1) active vs passive euthanasia, (2) voluntary vs involuntary euthanasia, (3) active-voluntary, active-involuntary, passive-voluntary, passiveinvoluntary and (4) a single-factor euthanasia model. In study 1, exploratory factor analysis identified a two-factor structure representing the voluntary-involuntary subcategorical distinction. This two-factor structure of euthanasia was cross-validated with a different sample in study 2, via confirmatory factor analysis. Model comparisons indicated that the two-factor voluntary vs involuntary euthanasia model

offered the best fit to the data relative to the other hypothesised models. These findings suggest that the presence or absence of the wish of the patient to die may be the most important factor influencing attitudes toward life and death issues. 0 1998 Elsevier Science Ltd. All rights reserved. Keybrords:Euthanasia;

Right to die issue; Active euthanasia; Passive euthanasia; Voluntary euthanasia; Involuntary euthanasia

1. Introduction A primary theoretical issue regarding the right to die debate is related to the confusing and uneasy conceptual relationships between the various constructs of euthanasia, e.g. voluntary euthanasia, involuntary euthanasia, active euthanasia, passive euthanasia, assisted suicide, rational suicide, suicide and homicide (Sugarman, 1986; Gostin, 1993; Rogers and Britton, 1994; Shapiro, 1994; Rogers, 1996). As pointed out by Rogers (1996) the lack of specificity in these terms represents a continuing source of difficulty for understanding and study in this area. The major emphasis of this investigation then is to evaluate empirical support for the various sub-

*To whom all correspondence should be addressed. Tel.: +61-79-309-105; Fax: +61-79-309-501; cquednau. SOl91-8869/98/S19.00 0 1998 Elsevier Science Ltd. All rights reserved. PII:SOl91-8869(98)00108-l

E-mail: r.ho@borg.

720

R. Ho/Personality and Individual Differences 25 (1998) 719-734

categorisations of euthanasia, with the view to improving accuracy in assessing public attitudes regarding right to die constructs. Dictionary definitions of euthanasia describe it as “an easy death: the act or practice of killing individuals that are hopelessly sick or injured for reasons of mercy” (Webster’s Dictionary). While this definition has been adequate as an all-encompassing descriptor in the past, the term has now become enmeshed within a whole spectrum of phrases and descriptors such as voluntary euthanasia, active euthanasia, assisted euthanasia, etc. (Foot, 1977; Gostin, 1993; Rogers and Britton, 1994). During the course of the debate over euthanasia, two major subcategorical distinctions have emerged: active vs passive euthanasia and voluntary vs involuntary euthanasia. These distinctions are not definitive (they do not include the other subcategories mentioned above), but they do provide a useful framework for illustrating basic differences in modes of euthanasia. The factorial combination of these two major subcategories further yields four other subcategorical distinctions of euthanasia: active-voluntary, active-involuntary, passive-voluntary, passive-involuntary. These subcategorical distinctions reflect the belief that the term euthanasia does not simply imply that the person concerned has asked for death, but that bringing about death (shortening life) can occur in several different ways (Sanson et al., 1996). Furthermore, it was assumed that using these various subcategorisations in research would contribute to a more concise understanding of current attitudes toward life and death issues. A brief description of these various subcategorisations is presented below. I .I. Active us passive euthanasia Active euthanasia is considered an intentional act that causes death (e.g. a lethal injection of potassium chloride), whereas passive euthanasia is an intentional act to avoid the prolongation of life (e.g. removal of a life support system) (Hunter, 1980). Although both procedures have the same consequences, it is the difference between killing people and merely letting people die that has caused a great deal of controversy. The importance of this subcategorisation has been illustrated by a number of studies that suggest that individuals are significantly more accepting of acts of euthanasia if they are presented as passive in nature as opposed to active (Cappon, 1970; Ostheimer, 1980; Finlay, 1985; Ho and Penney, 1992). 1.2. Voluntary vs involuntary euthanasia On the basis of the presence or absence of the wish of the patient to die, euthanasia can be either voluntary or involuntary. A voluntary act of euthanasia occurs when a patient clearly indicates an expressed wish to die through directives such as verbal statements or living wills; in involuntary euthanasia one causes the death of a person, supposedly in the interests of that person, but disregarding the fact that the person has not requested euthanasia. Some researchers (e.g. Foot, 1977; Buchanan and Brock, 1989) have argued that the distinction between voluntary and involuntary acts of euthanasia is an important subcategorisation in aiding researchers to better gauge public opinion on right to die issues. 1.3. Active-voluntary, active-involuntary, passive-voluntary, passive-involuntary These subcategorical distinctions represent specific conditions of euthanasia yielded by the factorial combination of active vs passive and voluntary vs involuntary euthanasia. Active-

R. Ho/Personality and InditGdualDifferences 25 ( 1998) 719-734

721

voluntary euthanasia can be defined as taking some positive action to terminate the life of a patient (e.g. through the administration of a lethal drug) who has asked for death. In active-involuntary euthanasia, one causes the death of a person who has made no specific request for death or may have expressed a wish to live. Passive-voluntary euthanasia is letting a patient, who has asked for death, die naturally rather than using extraordinary artificial methods (transplant, life-sustaining drugs, etc.) or machines (heart-lung machines, respirators, etc.) to keep him or her alive. Passiveinvoluntary euthanasia is letting a patient die naturally without resorting to extraordinary artificial methods to keep him or her alive, even though the patient has not specifically indicated his or her wish regarding death. Given the perceived complex nature of euthanasia and right to die issues in general, it is assumed that the use of the above subcategorical distinctions in research will reflect more accurately attitudes toward these issues. Past investigations carried out to determine the public’s attitude toward euthanasia have clearly embraced these various subcategorisations and have used questionnaire items that clearly reflect the hypothesised subcategorical distinctions. For example, the 1995 poll carried out by the Roy Morgan Research Centre to tap community support in Australia for euthanasia contained questions that assessed attitudes toward both passive and active-voluntary euthanasia (Roy Morgan Research Centre, 1995). Similarly, studies carried out by Kuhse and Singer (1988, 1992) to assess Australian doctors’ and nurses’ attitudes toward euthanasia employed questions that reflect the subcategorical distinctions of passive vs active and voluntary vs involuntary euthanasia. Recent polls in Canada and the United States also asked questions that differentiate between types of euthanasia (e.g. passive vs active) (Ames, 1991; Gallup Canada, 1995). While the results of these surveys indicate public support for euthanasia in general, the results also show that there is growing acceptance for certain types of euthanasia (e.g. physician assisted), whereas other types are perceived as less acceptable (e.g. nonphysician assisted). Nevertheless, results such as these have been interpreted as indicating firm public support for active voluntary euthanasia (e.g. National Hemlock Society, 1988) and have been used to support the case for affirmative right to die policies. While the data from the above survey studies clearly show an increase in public approval of euthanasia for terminally ill persons over the last decade, it can be argued that without a clear understanding of the way people perceive euthanasia (e.g. either as a unidimensional concept or in categorical format), conclusions regarding the acceptance of euthanasia in the general population based upon these data are, at best, tenuous. For example, while the conceptualisation of the euthanasia concept in a categorical format is assumed to allow for more clarity regarding the terminology related to euthanasia, it is not inconceivable that some people may not consider the right to die issue in the same categorical format. That is, if a person perceives and responds to the issue of euthanasia as an all-encompassing unidimensional right to die issue, then survey questions that reflect a combination of active-passive, voluntary-involuntary categories may not only appear confusing, but may also be regarded as irrelevant by that person. Similarly, if the person perceives and responds to euthanasia solely on the voluntary-involuntary dimension, then survey questions that reflect only the active-passive dimension may not be considered very meaningful by that person. Thus, for data to be both relevant and meaningful and to contribute meaningfully to the debate and development of right to die policies, the questions employed to tap attitudes toward euthanasia must clearly reflect the way the public perceives euthanasia. In sum, a clear understanding of the way respondents perceive and respond to the issue of

722

R. Ho/Personality and Individual Dfferences 25 (1998) 719-734

euthanasia appears to be a prerequisite for continued research and understanding in the area of right to die attitudes. One way toward achieving this understanding is through the development and comparisons of clearly articulated measurement models that empirically define and differentiate between subcategorical distinctions. The purpose of the present study, therefore, is to develop a series of measurement models that reflect the hypothesised classification scheme. Identifying the best fitting model should indicate the primary way people perceive and support euthanasia and should lead to improved accuracy in assessing public attitudes regarding right to die constructs. Ultimately, the obtained results can be an important means of informing public policy decisionmaking. 2. Method 2.1. Subjects and procedure

Respondents were volunteers who were recruited from the Rockhampton metropolitan area (Australia) in February 1997 by the author, with the assistance of graduate psychology students. The total sample consisted of 420 respondents (161 males, 259 females), with an age range of 17 to 60years and a mean age of 31 years. 63% of the respondents were employed (part- and fulltime) at the time of the study. Respondents filled in the study’s questionnaire individually. Prior to filling in the questionnaire, they were informed that any words, phrases, or statements that are unclear would be clarified by the experimenter. 2.2. Materials The questionnaire employed was part of a larger study designed to investigate attitudes toward various aspects of euthanasia. The questionnaire consisted of three sections. Section 1 was designed to elicit information about the respondents’ gender, age, educational level, employment status and current occupation. Section 2, which was not used in the present study, consisted of 18 items designed to tap respondents’ support for euthanasia under three conditions of suffering (physical pain, debilitated nature of the body, impact on family) experienced by oneself, a significant other and people in general. Since this section was not used in the present study (and for the sake of brevity), the items will not be described. Section 3 consisted of 12 items designed to tap the level of support for four types of euthanasia (active-voluntary, active-involuntary, passive-voluntary, passive-involuntary) yielded by the factorial combination of the active-passive and voluntary-involuntary subcategories. Each item was to be rated on a 5-point scale ranging from 1 = strongly not support, to 5 =strongly support. Support for each of the four types of euthanasia was measured by three items. 3. Stage one: exploratory factor analysis and reliability analysis From the initial sample of 420 respondents, 170 respondents were randomly selected for this analysis. This sub-sample consisted of 74 males and 96 females. Exploratory factor analysis and

R. Ho/Personality and Individual Differences 25 (1998) 719-734

123

reliability analysis were carried out to evaluate the factor structure of the 12 euthanasia items and the internal consistency of the extracted factors. 3.1. Results A multivariate analysis of variance (MANOVA) with one between-groups variable (respondents’ gender) was carried out to test for sex differences on the 12 euthanasia variables. Multivariate Pillais F-test showed no significant overall sex difference, F(12, 157)=0.89, p>O.O5; follow-up univariate F-tests yielded no significant sex difference on any of the 12 attitudinal variables (Fratios ranged from 0.01 to 2.34, p > 0.05). Thus, male and female respondents were combined for the subsequent analysis. To test the factor structure of the 12 euthanasia items, a principal components analysis using SPSS for Windows 7.5 (SPSS Inc., 1997) was employed for the initial extraction of factors, followed by oblique rotation. Since the level of measurement for the 12 items was ordinal, polychoric correlations between the items were calculated using PRELIS 2.1 (Jiireskog and S&born, 1989) and the resultant polychoric correlation matrix was used in the factor analysis. Inspection of the results revealed that three factors had eigen-values greater than 1.00. Examination of the items that loaded on these three factors indicated that factor I consisted entirely of items that reflected the “voluntary” dimension of euthanasia, while factors II and III consisted entirely of items that reflected the “involuntary” dimension. In conjunction with results obtained from the scree-plot, these findings suggested a two factor solution. Since the factor correlation matrix showed that the three factors were correlated (0.31 to 0.44), oblique rotation, limited to two factors was then conducted. The obtained pattern matrix showed that the 12 items loaded highly (0.65 to 0.85) on the two factors, accounting for a total of 58.4% of the variance. Factor I, accounting for 44.2% of the variance, consisted of all six items that reflected the voluntary dimension of euthanasia, while factor II, accounting for 14.2% of the variance, consisted of the remainder six items that reflected the involuntary dimension. To test for systematic group differences on the derived factor solution, oblique rotations specifying a two factor solution were then conducted for the subgroups of male and female respondents. Using Tucker’s congruency coefficient as a measure of factor loading similarity (Derogatis and Serio, 1972), no significant differences were found between the subgroups. Different factor analysis methods were employed [principal axis, iterative procedure (maximum likelihood), extraction of factors by Scree test + oblique rotation to maximum simple structure (checked empirically by the +O.lO hyperplane count)], to ascertain whether the factor structure and loadings would remain the same. No significant differences were found. In order to assess the internal consistency of the two factors, the statements representing each factor were item-analysed. The polychoric correlation matrix of item responses derived from PRELIS 2.1 were used in calculating Cronbach’s Alpha (standardised) for each factor. Inspection of the obtained item-total correlations indicated that all coefficients were moderate to high, ranging from 0.49 to 0.76 across both factors. Table 1 presents the two factors of voluntary and involuntary euthanasia, together with the factor loadings (for the three-factor and two-factor solutions) and item-total correlations for the 12 items. Exploratory factor analysis of the 12 items representing the four subcategories of euthanasia (active-voluntary, active-involuntary, passive-voluntary, passive-involuntary) suggested that the respondents perceived euthanasia primarily in terms of the voluntary-involuntary constructs. That

724

R. Ho/Personality and Individual Differences 25 (1998) 719-734

Table 1 Factor loadings and item-total correlations for the two-factor model of voluntary vs involuntary

Factor I: voluntary euthanasia el *a doctors have the right to administer medication that will painlessly end the life of a terminally ill person, if he/she requests it (VA)*b terminally ill patients have the right to decide that life-supporting e2 drugs or mechanisms be withheld or withdrawn, to hasten their death (VP) terminally ill patients have the right to decide about their own lives e5 and deaths (VA) the golden rule requires that we respect the request of terminally ill e6 patients who have asked that life-supporting drugs or mechanisms be withheld or withdrawn, to hasten their death (VP) denying the request of terminally ill patients to “die with dignity” e9 is unfair and cruel (VA) el0 doctors have the right to withhold or withdraw life-supporting drugs or mechanisms for a terminally ill person, if he or she requests it (VP) Cronbach coefficient c(= 0.87 Factor II: involuntary euthanasia e3 it is alright for doctors who attend child-birth to administer medication that will painlessly end the lives of grossly deformed infants (IA) doctors have the right to remove life support system from a patient e4 who is in a state of constant unconsciousness and with no prognosis for recovery, if members of the patient’s family request it (IP) doctors have the right to administer medication that will painlessly e7 end the life of a patient who has been diagnosed to be in a permanent “vegetative” state, if members of the patient’s family request it (IA) the withdrawal of medical treatment to allow death to occur should e8 be permissible in cases where a patient, although biologically alive, has been diagnosed as clinically brain-dead (IP) when a patient is suffering a debilitating terminal disease such as ell Alzheimer’s, it is alright for the doctor to administer medication that will painlessly end the patient’s life, if members of the patient’s family request it (IA) e12 it is alright for doctors who attend child-birth not to resuscitate grossly deformed infants (IP) Cronbach coefficient c(= 0.8 1

euthanasia’

Factor loadings*’

Factor loadings*d

Item-total correlations

0.85

0.85

0.72

0.83

0.84

0.76

0.84

0.84

0.71

0.79

0.80

0.72

0.76

0.76

0.68

0.66

0.67

0.51

0.84

0.65

0.57

0.90

0.79

0.56

0.88

0.74

0.62

0.69

0.67

0.56

0.62

0.72

0.62

0.92

0.67

0.49

“Order of items in questionnaire 1= strongly disagree; 5 = strongly agree. *bVA = voluntary-active euthanasia; VP = voluntary-passive euthanasia; IA = involuntary-active IP = involuntary-passive euthanasia. ‘Three-factor solution. dTwo-factor solution.

euthanasia;

R. Ho/Personality and Individual Differences 25 i 1998) 719-734

125

is, the subcategorical distinctions between active and passive and between the more complex distinctions yielded by the factorial combination of the active-passive and voluntary-involuntary subcategories did not seem to have been differentiated by the respondents in their consideration of the right to die issue. These findings suggest that the decision to support (or not support) euthanasia may be made primarily on the basis of the presence or absence of the wish of the patient to die.

4. Stage two: confirmatory factor analysis The remaining 250 respondents from the original pool of 420 respondents served as the crossvalidation sample for this phase of the study. The sample consisted of 90 males and 160 females with an age range of 17 to 60 years and a mean age of 28 years. Confirmatory factor analysis (CFA) was carried out to evaluate the adequacy of the factor structure identified in study 1. CFA, unlike exploratory factor analysis, allows the researcher to explicitly posit one or more a priori models (e.g. on the basis of the factors identified through exploratory factor analysis) and systematically compare the ability of competing models to fit the observed data. A series of CFA models is considered for this stage of the study. First, based on the factor structure (voluntary vs involuntary euthanasia) identified through exploratory factor analysis, a two-factor model representing these two subcategorical distinctions were posited. For this model, all factor loadings were freed, items were allowed to load on only one factor and the two factors were allowed to correlate. Second, while exploratory factor analysis failed to distinguish between the other major subcategorisations of euthanasia (active vs passive; active-voluntary, active-involuntary, passive-voluntary, passive-involuntary), it was decided (on conceptual and empirical grounds) to also posit a two-factor model representing the active-passive dimension and a four-factor model representing the other four types of euthanasia. Conceptually, the inclusion of these models is consistent with the euthanasia literature that argues specifically for these subcategorical distinctions. Empirically, the inclusion of these models will allow for a more stringent test of the fit of the primary voluntary-involuntary euthanasia model, by allowing for a comparison of its goodness-of-fit with those of the other subcategorical models. For these two models, all factor loadings were freed, items were allowed to load on only one factor and the factors were allowed to correlate. A further model incorporating a single factor was also posited to represent the assumption that the issue of euthanasia may not be perceived and responded to in a categorical format, but simply as a single, unidimensional issue. For this model, all factor loadings for the 12 items were freed. Figure 1 presents the four competing models to be evaluated. 4. I. Statistical analysis The fit of a posited a priori model with the data can be statistically evaluated via a x2 goodnessof-fit test. The null hypothesis initially tested is that a sample covariance matrix is obtained from a population that has the proposed model structure. If the x2 value fails to achieve statistical significance (e.g. p > 0.05), the null hypothesis may be retained; that is one may conclude that the proposed model is consistent with the sample data. However, the x2 statistic is very sensitive to departures from multinormality of the observed variables and increases as a direct function of

726

R. Ho/Personality and Individual Differences 25 (1998) 719-734

Model 1

Model 2

Model 3

Model 4 Fig. 1. Model I =single-factor euthanasia model. Model 2=two-factor passive vs active euthanasia modei. Model 3 = two-factor voluntary vs involutionary euthanasia model. Model 4 = four-factor voluntary-passive, voluntary-active, involuntary-passive, involuntary-active model.

sample size. Therefore, given departures from multinormality or large samples, a proposed model can easily be rejected by a formal test of significance. These limitations have increased the emphasis placed on other goodness-of-fit indices such as the normed fit index (NFI), the comparative fit index (CFI), the incremental frt index (IFI) and the Tucker-Lewis index (TLI). These relative fit indices show the improvement achieved by a posited theoretical structure over the so-called null

R. Ho/Personality and Individual Differences 25 (1998) 719-734

121

Table 2 Means and standard deviations for euthanasia and its subcategories (euthanasia; passive-active euthanasia; voluntary-involuntary euthanasia; voluntary-passive euthanasia, voluntary-active euthanasia, involuntary-passive euthanasia, involuntary-active euthanasia) Deviation

Means

Standard

Euthanasia Passive euthanasia Active euthanasia Voluntary euthanasia Involuntary euthanasia Voluntary-passive euthanasia Voluntary-active euthanasia Involuntary-passive euthanasia Involuntary-active euthanasia

3.17 3.89 3.65 4.17 3.37 4.19 4.15 3.59 3.16

0.69 0.68 0.82 0.11 0.81 0.79 0.91 0.81 0.95

(independence) model (i.e. a model assuming independence among the variables); they range from 0 (a fit that is no better than the null model) to 1 (perfect fit). There are no clearly established rules as to what constitutes a good fit, but a widely applied guideline for these relative indices is 0.90 (Bentler, 1990; Bentler and Bonett, 1980). An index of 0.90 can be roughly interpreted as being able to explain 90% of the covariation among the measured variables (Marsh, 1991). While these goodness-of-fit indices can be used to evaluate the adequacy of fit in CFA, it must be noted that this is only one aspect of model evaluation. As pointed out by Marsh and his colleagues (e.g. Marsh, 1985, 1996; Marsh and Balla, 1994), model evaluation should be based on a subjective combination of substantive or theoretical issues, inspection of parameter estimates, goodness-offit, parsimony, interpretability and a comparison of the performances of competing models. 4.2. Results Table 2 presents the means and standard deviations for the four types of euthanasia. The purpose of this phase of the study was to evaluate the four posited models of euthanasia (see Fig. 1). As all four models are nested, direct comparisons between those models with different degrees of freedom is possible. Separate analyses were conducted to compare the overall fit of the four models. Model 4, positing four factors, fitted the data extremely poorly and even after modification to the model by allowing for correlated uniqueness, the fit of the model did not improve substantively. Because the fit of the model is so poor, it is not considered further. The other three a priori models positing one and two factors fitted the data better, although none reached the 0.90 criterion indicative of good fit. To improve the fit, additional parameters, namely correlated error terms, were added to the models. For all three models, modification indices provided by LISREL 8 (Jbreskog and S&born, 1989) suggested correlation between the error terms of items e3 and e12. Allowing the error terms of these two measurement variables to correlate is theoretically sound, as both items refer to “ending the lives of grossly deformed infants at child-

728

R. Ho/Personality and Individual Differences 25 (1998) 719-734

Table 3 x’ Goodness-of-fit values, normed fit index (NFI), incremental fit index (IFI), Tucker-Lewis index (TLI), comparative fit index (CFI), parsimony normed fit index (PNFI), Akaike information criterion (AIC) and model comparisons’ Model

~‘(N=250)

df

P

NFI

IFI

TLI

CFI

PNFI

AIC

Null model

2189.46

66


0.00

0.00

0.00

0.00

0.00

2213.4

54 53


0.67 0.73

0.69 0.74

0.62 0.68

0.68 0.74

0.54 0.58

766.15 650.36


0.71 0.77

0.73 0.79

0.66 0.74

0.73 0.79

0.57 0.61

679.78 547.57 482.92 387.83

Model 1 (single factor model) a priori 718.15 a posteriori

600.36

Model 2 (two-factor model: passive vs active) a priori a posteriori

629.78 495.57

53 52

Model 3 (two-factor model: voluntary vs involuntary) 432.92 53
a priori a posteriori

335.83

Model comparisons (a posteriori models) Model 2 vs model 1 104.79 Model 3 vs model 1 264.53 Entries under “model comparisons”

52


0.80 0.85

0.82 0.87

0.77 0.83

0.82 0.87

0.64 0.67

1 1


0.04 0.12

0.05 0.13

0.06 0.15

0.05 0.13

0.03 0.09

are differences.

birth” (see Table 1). Table 3 presents the goodness-of-fit indices for the three original (a priori) and modified (a posteriori) one-factor and two factor models of euthanasia. The results show a significant improvement in fit for all three a posteriori models (with 1 degree of freedom, the decrease in x2 values for all three a posteriori models is statistically significant), although no model managed to reach the conventional 0.90 criterion of good fit. However, in the absence of better theories on the factor structure of attitudes toward euthanasia, the analyses carried out allowed for a systematic comparison of the hypothesised models and a rigorous assessment of their relative appropriateness. First, it is evident from Table 3 that of the three models, model 3 (both apriori and a posteriori) offers the best fit to the data relative to the null model. The relative fit indices of NFI, IFI, TLI and CFI for model 3 (a posteriori) all approached the 0.90 criterion (0.83 to 0.87), indicating that this model explained close to 90% of the covariation among its measured variables. These findings suggest that the two-factor model incorporating the subcategorical distinctions of voluntary vs involuntary euthanasia best represents the way the respondents perceive euthanasia, relative to the other hypothesised models. Second, model comparisons indicated that both model 2 (active vs passive euthanasia) and model 3 (voluntary vs involuntary euthanasia) fitted the data significantly better than model 1 (a single-factor euthanasia model), x2(1, N=250) = 104.79, p < 0.001; x2(1, N=250)=264.33, p
R. Ho/Personality and Individual Differences 25 (1998) 719-734

129

Table 4 Standardised measurement model residual and explained variances for (apriori and a posteriori) model 1 (single factor euthanasia model), model 2 (active versus passive euthanasia) and model 3 (voluntary vs involuntary) Model Residual variances Model 1 a priori a posteriori

Model 2 a priori a posteriori

Model 3 a priori a posteriori

Explained variances Model 1 a priori a posteriori

Model 2 a priori a posteriori

Model 3 a priori a posteriori

Euthanasia factors

Euthanasia 0.68 0.68 Active 0.91 0.91 Voluntary 0.69 0.69 Euthanasia 0.32 0.32 Active 0.09 0.09 Voluntary 0.31 0.31

M 0.68 0.68 Passive 0.78 0.79

0.85 0.85 Involuntary 0.33 0.51 0.28 0.49 M 0.32 0.32 Passive 0.22 0.21

0.15 0.15 Involuntary 0.67 0.49 0.72 0.51

freedom used can be evaluated and compared by means of the parsimonious normed fit index (PNFI), a measure that rewards model parsimony. Although there are no recommended levels of acceptable parsimony “fit” when comparing between models, differences of 0.06 to 0.09 are proposed to be indicative of substantial model differences (Williams and Hazer, 1986). Moreover, the fit of such non-nested models can also be compared by using the AIC (Akaike information criterion) measure (Akaike, 1973, 1987). In evaluating hypothesised models, this measure takes into account both model parsimony and model fit. Simple models that fit well receive low scores, whereas poorly fitting models get high scores. Comparing the parsimonious normed fit index (PNFI) for model 2 and model 3 against the PNFI for model 1, it is evident (see Table 3) that model 3 is more parsimonious than model 2 (for the loss of 1 degree of freedom). These results indicated that model 3 has achieved a higher level of fit relative to model 2, per degree of freedom used. Similarly, the AIC measure for model 3 is lower than that for model 2, indicating that model 3 is both more parsimonious and better fitting than model 2. The standardised residual and explained variances for the three models tested are presented in Table 4. The residual variances are reasonably similar for a priori and a posteriori models but vary substantially across the two latent factors in model 1 (active vs passive) and model 2 (voluntary vs

730

R. Ho/Personality and Individual Differences 25 (1998) 719-734

involuntary). Comparing residual variances across all factors, it can be seen that the involuntary euthanasia factor has typically lower residual variances than the other factor, whereas the active euthanasia factor has the largest residual variances. The mean proportion of unexplained variances varies from 0.68 (i.e. 32% of the variance explained) for the single-factor euthanasia model, to 0.85 (i.e. 15% of the variance explained) for the two-factor active vs passive euthanasia model, to 0.49 (i.e. 51% of the variance explained) for the two-factor voluntary vs involuntary model. The large mean proportion of unexplained variances for the two-factor active vs passive euthanasia model is due largely to the residual variance associated with the active euthanasia factor (0.91). The common explained variance for this factor is only 0.09 (i.e. 9% of the variance explained), which indicates that the respondents were typically unsure in their responses to the measures designed to tap this construct. Overall, it must also be emphasised that there are considerable residual variances in the measurement variables that are not explained by the three hypothesised models.

5. Discussion The substantive purpose of this study was to develop and evaluate a series of measurement models that reflect the hypothesised sub-categorisations of euthanasia. Initial exploratory factor analysis identified a two-factor structure of responses to the 12 euthanasia measurement variables, representing the major subcategories of voluntary and involuntary euthanasia. Reliability analysis indicated good internal consistency for both factors. Confirmatory factor analysis confirmed and further clarified the adequacy of this factor structure in representing the way respondents perceived euthanasia. Model comparisons clearly indicated that the two-factor model incorporating the voluntary-involuntary categories offered the best fit to the data relative to the other posited onefactor, two factor (active/passive) and more complex four-factor models (active-voluntary, activeinvoluntary, passive-voluntary, passive-involuntary). Moreover, the voluntary-involuntary model was found to be more parsimonious in achieving goodness-of-fit relative to other models. Together, these findings confirmed those obtained from the initial exploratory factor analysis and point to the importance of the subcategorical distinctions of voluntary vs involuntary euthanasia in influencing attitudes toward life and death issues. These findings suggest that, for the study’s respondents, the decision to support or not support euthanasia is made primarily on the basis of the presence or absence of the wish of the patient to die. This finding is somewhat surprising given that the debate over euthanasia in the last decade has centered primarily around the distinction between active and passive euthanasia. Indeed, it has been argued that it is the difference between killing people (active euthanasia) and merely letting people die (passive euthanasia) that has been the major source of controversy in this debate (Cappon, 1970; Ostheimer, 1980; Ho and Penney, 1992). The present findings suggest that the active vs passive distinction may not be as important a determinant of attitudes toward euthanasia as the literature has suggested. Rather, the decision regarding the termination of life appears to be determined primarily by the perceived morality of a decision made on the basis of whether or not consent has been given by the patient. On the basis of such a decision, it could be argued that people would feel more morally secure about terminating the life of another person if that person had specifically asked to die, or had left specific instructions about when euthanasia was wished.

R. Ho/Personality and Individual Diffrences

25 (1998) 719-734

731

Such steps would move euthanasia from the category of involuntary to voluntary, which may render it more morally acceptable (Darley et al., 1996). The finding that the respondents did not strongly make the distinction between active and passive euthanasia points to the difficulty in drawing the line between these two types of euthanasia. For many people, there may be difficulty in determining whether an act of euthanasia is active or passive. For example, is removal of a treatment procedure, such as a respirator, an active or passive act? On the one hand, it can be argued that the respirator is only maintaining a terminal state, so that if it is removed, patients will die from their inability to breathe on their own, so the act might be a passive method. On the other hand, it can also be argued to be an active step since the death of the patient from asphyxiation is a direct result of the doctor’s action. Indeed, many people believe that any act of euthanasia, regardless of the method that caused the death, is in fact active. The blurring of the lines between active and passive euthanasia could have resulted in the greater reliance by the respondents on the more easily identifiable subcategorical distinctions of voluntary and involuntary euthanasia in their decision making process. It is particularly interesting to note that the most complex four-factor model posited was also the poorest in representing the respondents’ attitudes toward euthanasia. The four-factor model was posited on the belief that people not only differentiate between the two major categories of active vs passive and voluntary and involuntary euthanasia, but also between the subcategorical distinctions yielded by their factorial combination. Such a model is assumed to provide a more detailed approach to, as well as a clearer understanding of the multidimensionality of euthanasia. Indeed, the importance of this subcategorical model has been demonstrated by its use as a major framework for guiding past survey research and in particular, in the design of questionnaire items to tap attitudes toward specific aspects of euthanasia (e.g. Kuhse and Singer, 1988, 1992; Ames, 1991; Gallup Canada, 1995; Roy Morgan Research Centre, 1995). Also, in the continuing debate over euthanasia, the arguments for and against euthanasia have often been based on the perceived moral difference that is assumed to exist between the specific types of euthanasia subsumed under this model. For example, euthanasia that is presented as both involuntary and active exemplifies the basic rationale underlying the opposition to the legalisation of euthanasia in many countries: the concept of the slippery slope (Rogers and Britton, 1994; Lester, 1996). Despite the clarity of interpretation provided by this four-factor model, the results from the present study are not consistent with such a categorical approach to euthanasia. Rather, the decision regarding euthanasia appears to key primarily on the voluntariness of the patient’s decision to die. The emphasis on the voluntary and involuntary aspects of euthanasia appears to reflect the need to ensure that the person requesting euthanasia was in control of the process and that societal support for voluntary euthanasia will not lead to the bottom of the so-called slippery slope, by permitting lessthan-voluntary euthanasia and finally involuntary euthanasia. The finding that inclusion of the correlation between items e3 and e12 (both referring to “ending the lives of grossly deformed infants at childbirth”) significantly improved the fit of the three hypothesised models, suggests that this condition of suffering may be another important factor in the decision to terminate life. Indeed, while the debate on euthanasia appears to key on the moral differences between different forms of euthanasia, the arguments for and against euthanasia may be further complicated by the conditions under which euthanasia is considered an appropriate option. For example, recent studies have shown that conditions such as physical pain (Coyle et al., 1990, 1994), the debilitated nature of one’s body (Davies et al., 1990) impact on the family

732

R. Ho/Personality and Individual Differences 25 (1998) 719-734

(Smith, 1990; Beck-Friis and Strang, 1993) and the person for whom euthanasia is recommended (Wade and Anglin, 1987; Ho, in press), may combine to yield specific conditions which can either increase or attenuate the level of support for euthanasia. As the movement to develop policies around right to die issues strengthens, it will be increasingly important to have an appropriate knowledge base to guide those policies. The development of such a knowledge base relies heavily on empirical research carried out to determine public attitudes toward euthanasia (Clouser, 1991; Koenig, 1993; Conwell, 1994). Given the complex nature of euthanasia and right to die issues in general, it is clear that the assessment approach used in such research must accurately reflect attitudes toward these important issues. The first step in the assessment approach then is to identify the way people perceive and conceptualise the euthanasia concept. A clear understanding of the way people perceive euthanasia can serve as the framework for guiding research that targets relevant constructs of euthanasia for study. Grounded in a clearly articulated model, reliable and valid instruments can then be developed and modified to help empirically define and differentiate those constructs. The present investigation has identified a measurement model that clearly defines and differentiates the voluntary and involuntary subcategorical distinctions in the assessment of attitudes toward euthanasia. Targeting these specific subcategories in future research should lead to improved accuracy in assessing public attitudes regarding right to die issues and should be an important means of informing public policy decision making.

Acknowledgements My thanks to Graham Davidson and Alan Keen for their helpful comments on an earlier draft of this paper.

References Akaike, H. (1987). Factor analysis and AX. Psychometrika, 52, 3 17-332. Akaike, H. (1973). Information theory and an extension of the maximum likelihood principle. In B. N. Petrov & F. Csaki, (Eds.), Proceedings of the 2nd International Symposium on Information Theory (pp. 267-281). Budapest: Akademiai Kiado. Ames, K. (1991). Last rights. Newsweek, August, 40-41. Beck-Friis, B., & Strang, P. (1993). The family is hospital-based care with special reference to terminally ill cancer patients. Journal of Palliative Care, 9, 5-13. Bentler, P. M. (1990). Comparative fit indexes in structural models. Psychological Bulletin, 107,238-246. Bentler, P. M., & Bonett, D. G. (1980). Significance tests and goodness of fit in the analysis of covariance structures. Psychological Bulletin, 88, 588-606.

Buchanan, A. E. & Brock, D. W. (1989). Deciding for Others: The Ethics of Surrogate Decision Making. New York: Cambridge University Press. Cappon, D. (1970). Attitudes on death. Journal of Death and Dying, 1, 103-108. Cherny, N. I., Coyle, N., & Foley, K. M. (1994). Suffering in the advanced cancer patient: a definition and taxonomy. Journal of Palliative Care, IO, 57-70.

Clouser, K. D. (1991). The challenge for future debate on euthanasia. Journal of Pain and Symptom Management, 6, 306-311.

R. Ho/Personality and Individual Differences 25 (1998) 719-734

Conwell, Y. (1994). Physician-assisted

133

suicide: a mental health perspective. Suicide and Life-Threatening Behavior, 24,

326-333.

Coyle, N., Adelhardt, J., Foley, K. M., & Portenoy, K. M. (1990). Character of terminal illness in the advanced cancer patient: Pain and other symptoms during the last four weeks of life. Journal of Pain and Symptom Management, 5, 83-93.

Darley, J. M., Loeb, I., & Hunter, J. (1996). Community attitudes on the family issues surrounding the death of terminal patients. Journal of Social Issues, 52, 85-104. Davies, B., Reimer, J. C., & Martens, N. (1990). Families in support care. Part 1. The transition of fading away: The nature of the transition. Journal of Palliative Care, 6, 12-20. Derogatis, L. R., & Serio, J. C. (1972). An empirical comparison of three indices of factorial similarity. Psychological Reports, 30, 791-804.

Finlay, B. (1985). Right to life vs the right to die: some correlates of euthanasia attitudes. Sociology and Social Research, 69, 548-560.

Foot, P. (1977). Euthanasia. Philosophy and Public Affairs, 6, 85-l 12. Gallup Canada (1995). Majority of Canadians support doctor-assisted

suicide while 50% support child mercy killing.

The Gallup Poll, 55, 1-2.

Gostin, L. 0. (1993). Drawing a line between killing and letting die: The law and law reform, on medically assisted dying. The Journal of Law, Medicine and Ethics, 21, 94-101. Ho, R. (in press). Factors influencing decisions to terminate life: Conditions of suffering and the identity of the terminally ill. Australian Journal of Social Issues. Ho, R., & Penney, R. K. (1992). Euthanasia and abortion: Personality correlates for the decision to terminate life. The Journal of Social Psychology, 132, 77-86.

Hunter. R. C. A. (1980). Euthanasia: A paper for discussion by psychiatrists. Canadian Journal of Psychiatry, 25,439445.

Joreskog, K. G. & S&born, D. (1989). Lisrel8: A guide to program and applications. Chicago: SPSS. Koenig, H. G. (1993). Legalizing physician-assisted suicide: Some thoughts and concerns. The Journal of Family Practice, 37, 171-179.

Kuhse, H., & Singer, P. (1992). Euthanasia: A survey of nurses’ attitudes and practices. The Australian Nurses Journal, 21,21-22.

Kuhse, H., & Singer, P. (1988). Doctors’ practices and attitudes regarding voluntary euthanasia.

The Medical Journal

of Australia, 148, 623-627.

Lester, D. (1996). Psychological issues in euthanasia, suicide and assisted-suicide. Journal of Social Issues, 52, 51-62. Marsh. H. W. (1996). Positive and negative global self-esteem: A substantively meaningful distinction or artifactors?. Journal of Personality and Social Psychology, 70, 810-819.

Marsh, H. W. (1991). Multidimensional students’ evaluations of teaching effectiveness: A test of alternative higherorder structures. Journal of Educational Psychology, 83,285-296. Marsh, H. W. (1985). The structure of masculinity/femininity: An application of confirmatory factor analysis to higherorder factor structures and factorial invariance. Multivariate Behavioral Research, 20,427-449. Marsh, H. W., & Balla, J. (1994). Goodness of fit in confirmatory factor analysis: The effects of sample size and model parsimony. Quality and Quantity, 28, 185-217. National Hemlock Society (1988). The 1988 Roper poll on attitudes toward active voluntary euthanasia. Los Angeles: Author. Ostheimer, J. M. (1980). The polls: Changing attitudes toward euthanasia. Public Opinion Quarterly, 44, 123-128. Rogers, J. R. (1996). Assessing right to die attitudes: A conceptually guided measurement model: Journal of Social Issues, 52, 63-84.

Rogers, J. R., & B&ton, P. J. (1994). AIDS and rational suicide: A counselling psychology perspective or a ride on the slippery slope. The Counselling Psychologist, 22, 171-178. Roy Morgan Research Centre (1995). Australia 1995 support for voluntary euthanasia stands at 78%. The Bulletin, 28 June. Sanson, A., Dickens, E., Melita, B., Nixon, M., Rowe, J., Tudor, A. and Tyrrell, M. (1996). Psychologicalperspectives on euthanasia and the terminally ill. An Australian Psychological Society Discussion Paper. The Australian Psychological Society.

734

R. Ho/Personality and Individual Dfferences 2S (1998) 719-734

Shapiro, R. S. (1994). Liability issues in the management

of pain. Journal of Pain and Symptom Management, 9, 146-

152.

Smith, N. (1990). The impact of terminal illness on the family. Palliative Medicine, 4, 127-135. SPSS Inc. (1997). Statistical Package for the social sciences. Chicago, U.S.A. Sugarman, D. B. (1986). Active vs passive euthanasia: An attributional analysis. Journal of Applied Social Psychology, 16, 60-76.

Wade, C. H., & Anglin, M. D. (1987). Factors influencing decisions to terminate life. Social Biology, 34, 374. Williams, L. J., & Hazer, J. T. (1986). Antecedents and consequences of organizational turnover: A reanalysis using a structural equations model. Journal of Applied Psychology, 71,219-23 1.