Soc. Sci. & Med., Vol. 13A, pp. 715 to 721 Pergamon Press Ltd 1979. Printed in Great Britain
SOCIAL SUPPORT IN CRISIS: QUANTITY OR QUALITY? D. PORRITT School of Community Medicine, University of New South Wales, Australia Abstract--It is suggested that individual differences in reactions to crises depend in part on the variations in social support available to the individual in crisis. A model of the quality of support is derived from research on the effectiveness of interpersonal helping processes. It is predicted that the availability of sources of potential help will be unrelated to crisis outcome, but that the quality of support received will be a determinant of outcome. Different methods of combining measures of the quality of support given by different sources are considered. Data from a controlled trial of crisis interventior with males hospitalised for treatment of road injuries are used to test the predictions and compare the different scoring methods. The results confirm the predictions that source availability is unrelated to outcome, that source quality is related to outcome, and that crisis intervention has a highly significant effect on the reported quality of support received. Problems in determining the causal direction of the relationships found are discussed, and it is concluded that most probably coping behaviour and support influence each other and jointly determine outcome. It is argued that skills in conveying genuine respect and understanding to people in crisis appear to be lacking among professional care givers and inadequate in many individual's social networks. Action to change this situation is recommended, and the measurement methods reported in the paper offered as a basis for further research, as no other simple generally applicable method has been published with data to substantiate its validity.
INTRODUCTION Periods of stress and crisis present individuals with increased demands on their physical, psychological and social resources. There is evidence that such demands can exacerbate and perhaps even precipitate both psychological and physical breakdown for some individuals [1-4]. The effects of such challenges show wide individual differences. Variations in aspects of social support received hold a prominent place among the variables that might explain these differences [2, 5-7]. The proposition that variations in social relationships make a difference for better or for worse at times of challenge is hardly controversial. The relevant empirical studies are, however, so diverse in theoretical conception and measurement procedures that to integrate them is difficult. In particular, little consensus has emerged about the specific types of variation in social network structure or function that are relevant to outcome. To attempt to review or synthesise this literature is beyond the scope of this article. The focus here is on the results achieved in an empirical study which adopted Carkhuff's [8] framework for assessing aspects of social support. This model was an effort to integrate the empirical research into the determinants of the outcome of attempts by one person to be helpful to a n o t h e r - whether by psychotherapists, counsellors, teachers, parents or friends. Carkhuff proposed that development through the life span be seen as moving through a series of choice points or crises. Each crisis offers the opportunity of change for the better while it also threatens change for the worse. Two main classes of variable were suggested in his model as determining the outcome at each crisis point. These were the developmental level of the person and the quality of others' responses to the person. Stated in thesegeneral terms, the model differs little from the common notions typical of most accounts
of crisis theory. The special value of Carkhuff's model is that he suggests specific variables on which the quality of response from others may be assessed. The best validated of the variables are the level of Empathic Understanding (EU), of Respect (R) and of Constructive Genuineness (CG). Thus, a general hypothesis derived from Carkhuff's model would be: the probability of a favourable outcome for an individual faced with a crisis will be greater the higher the levels of empathic understanding, respect and constructive genuineness conveyed to the individual by other people's reactions. It also follows from Carkhuff's model that the mere availability of people from whom assistance might be sought will not affect crisis outcome. Quality is more important than quantity, The general hypothesis is derived largely from studies of dyadic interaction. It thus leaves open the issue of how best to measure the level of response from a social network. At least two approaches could be adopted. (1) Averaging: if the typical level of response is critical, then the average level across all available sources of response is the appropriate measure. This assumes that constructive and destructive responses cancel each other out and that two equally constructive sources are no more helpful than one, other things being equal. (2) Counting: if the number of constructive or destructive sources is important, then each source should be classified as destructive or constructive and the number of sources of each type counted. The issue of whether constructive and destructive reactions cancel each other out could then be explored by comparing the predictive power of three measures: (a) the number of constructive sources; (b) the number of destructive sources; and (c) the difference between (a) and (b). Another issue worthy of empirical investigation is the degree to which a person's social network tends to show a consistent level of response, i.e. whether
715
716
D. PORRITT
each person's sources of response tend to vary within a restricted range of quality or to show a more random scattering of levels. THE STUDY An opportunity arose to investigate these issues as part of an experimental trial of crisis intervention with males hospitalised for road injuries [9, 10].
Design and procedure In the study, 70 males were interviewed 12-16 weeks after being injured on the road and admitted to hospital for at least one week. In this interview, a retrospective assessment was obtained of the subject's perceptions of who was available to him during the period since injury and of the levels of EU, R, and CG conveyed to him by each of the available sources of response. For the purposes of the evaluation trial, the 70 patients had been divided into three groups. All groups reported on their emotional reactions to injury and hospitalisation. The Delayed Contact (DC, n = 30) group gave this data at the follow-up interview. Otherwise they received only standard hospital treatment. None had been referred to the Hospital's Social Work Department. The Immediate Review (IR, n = 10) group and the Full Intervention (FI, n = 30) group were interviewed about these reactions within one week of admission. The iR group received no further contact until follow-up. Patients in the FI group were offered and all accepted the help of a qualified social worker for 2-10 contacts (mean of 5). The social workers were selected to be functioning at or above minimally facilitating levels on a specially prepared Communications Index, based on that developed by Carkhuff [8]. All were experienced in brief action-oriented crisis intervention. Due to practical limitations the research interviews were conducted during the period from April 1973 to January 1974 inclusive. The interviewer had previous experience in a prospective study of recently widowed women. To obtain useable sample sizes, non-random allocation to treatment groups was necessary. Thus, subjects in group D C were all of the eligible consenting patients admitted from December 1972 to April 1973. They were first contacted 12-16 weeks after admission and invited to participate in the study. The outcome interview was then administered followed by the intake assessment which other subjects received in their first week in hospital. Subjects in the IR and FI groups were all of the eligible consenting patients admitted from May 1973 to December 1973. Allocation to these groups was random. Subjects in both groups were interviewed in hospital about their injury and hospitalisation within 1 week of their admission. G r o u p FI subjects were offered and all accepted, intervention by one of the social workers employed for the project as already described.
Measures
back at work at follow-up and reported less than a criterion number of problems at work on Langsley's Work Adjustment Scale), life enjoyment (Bradburn's Positive Affect Scale) and health deterioration (Maddison's Health Change Questionnaire). These measures were described in more detail in previous reports [9, 10]. Social support was assessed by presenting each subject with a list of potential sources of support. The list included Mother, Father, Siblings, Spouse, Children, Friends, Other Relatives, Clergy, Strangers, Doctors or Social Agencies, and Boss. For each potential source, the subject was asked if help was or was not available from that source. If help was available, the subject was asked to rate the Source's reactions on the scales of EU, R and CG presented in Appendix A. Responses were scored with the values shown in brackets beside each response option. In making the ratings, subjects were asked to consider the full period since their injuries. The scales are simplified forms of the scales with the same titles presented by Carkhuff [8].
Intervention The nature of the intervention is important for the interpretation of the results. It involved assessment and intervention as judged necessary on three fronts. Practical support involved such activities as assistance with making contact with families, negotiations with employers about returning to work and obtaining financial and other assistance from government and other welfare agencies. Emotional support was provided by further exploration of emotional reactions to the traumatic events and by exploration and clarification of subsequent concerns as these arose. Constructive, problem-oriented, non-blaming coping behaviour was encouraged. Social support was fostered by encouraging family and friends to keep regular contact and also to listen to, accept and try to understand the patient's concerns. Where a natural support network was not available, community welfare agencies were mobilised to provide any continuing support that it appeared might be needed after the intervention was terminated.
Predictions In this paper, the results of the study are used to test three predictions and to explore some related issues. The predictions are: 1. There will be no differences between groups in the availability of sources. 2. Subjects in the FI group will report more supportive responses, measured on the EU, R and CG scales and subjects in the D C group will report less supportive responses from their available sources. 3. Subjects who show relatively better outcomes when compared to others receiving the same intervention will report their sources of response as equally available, but as more supportive than will subjects with relatively poorer outcomes.
The outcome measures drawn on in this paper were . The results are also used to explore whether the self-reports on standardised questionnaires covering averaging or counting approaches to scoring a supemotional distress (Langner 22-item scale; Langsley port network is more useful, and to test the consistSymptoms Scale; Bradburn Negative Affect Scale), ency in the supportiveness of individual's networks. work adjustment (classed as good if the subject was
Social support in crisis: quantity or quality? Table I. Between group outcome score by treatment group Number of measures with poorer outcome
Treatment group DC IR FI
Table 3. Number of supports available by treatment group
Total
Number available
1 0 2 4 3
18 10 8 6 3
8 7 6 5 4
1 3 8 10 5 2 0 1 0
1 5 15 24 19 5 0 1 0
Total
30
10
30
7O
HI
7 10 13 30
2 4 4 10
12 10 8 30
21 24 25 70
4 1 0 0 0
1
0
2
8
10
3
0
0
3
12
15
2
Total
3O
10
3O
70
0
Poorer Better Total
28 2 30
5 5 10
3 27 30
36 34 70
RESULTS
Chi-square = 4.1, 4 dr, not significant.
Subjects were found to be younger a n d of lower socioeconomic status than the C a n b e r r a population, as would be expected for road injury patients, a n d the outcome measures were found to be sufficiently correlated to justify combining them into a composite index. Bordow 1-9] has reported the relevant data.
Outcome indices Two indices were used here. The Between G r o u p s Outcome Score (BGOS) was obtained by dichotomising each of the six outcome variables a r o u n d its median for the total sample a n d then counting the number of measures on which a subject was in the unfavourable half of the distribution. This c o u n t was the subject's BGOS. The W i t h i n G r o u p s O u t c o m e Score (WGOS) was calculated separately for each group. F o r example, in the F I group, each of the six outcome measures was dichotomised a r o u n d the median score for the 30 subjects in that group. Each subject in group FI then was assigned as his W G O S the n u m b e r of outcome measures on which he was in the unfavourable half of the distribution of that measure in his group. W G O S was derived similarly for the other two groups relative to the median scores for the subject's own group. W G O S can thus be used Table 2. Availability of 11 potential sources of support by treatment group
Mother Father Siblings Spouse Children .Friends Strangers Doctors & agencies Other relatives Boss Clergy n * P < 0.05; t P < 0.01.
26~ 20~ 33~o 63~o 13~ 100~ 20~ 100~o 28~ 90~ 0~ 30
1
MOD LO Total
Chi-square = 40.8, 2 df, P < 0.001.
Total
0 0 2 4 4 0 0 0 0
13 9 6 2 0
DC
Treatment group DC IR FI 0 2 ~ 5 10 10 3 0 0 0
6 5 4 3 2
Source
717
Treatment group IR F]~ 60~ 20~ 40~ 50~o 0~o 100~o 20~o 100~ 0~ 90~o 0~ 10
67~t 60~t 37~ 30~* 3~o 97~ 13~ 100~o 28~o 87~ 0~ 30
as a measure of outcome with experimental effects removed. It is independent of treatment effects. Table 1 presents B G O S by treatment group. The differences in outcome are m a r k e d a n d clearly favour the FI group over the IR group over the D C group. Results for each measure separately were significant a n d have been given previously [10]. Table 2 presents data on the availability of potential sources of support by treatment group. Table 3 presents data on the n u m b e r of available sources by treatment group. In Table 4 the n u m b e r of available sources, with between group differences removed, is presented as a function of W G O S . These tables show as predicted little relationship between availability of sources a n d outcome. The data do reveal one possible confounding factor. The D C group more often reported spouse as available and parents as not available t h a n the F I group, i.e. D C subjects were more often married a n d FI subjects more often single and living with or near parents. Table 5 tests the effect of treatment group on B G O S with marital status controlled. Table 6 tests the effect of marital status on W G O S within treatment groups. These tables show that the differences in marital status c a n n o t account for the differences in outcome between groups and that marital status is not related to out6ome within groups. F o r each available source, the EU, R and C G ratings were summed. Reliabilities of the summed ratings were estimated by C r o n b a c h ' s coefficient alpha as suggested by N u n n a l l y [11]. Table 7 presents means, ns, a n d s t a n d a r d deviations for the three scales Table 4. Within group outcome score by relative number of supports available WGOS
Relative availability Loer Hier
Total
Poorer Better
16 19
19 16
35 35
Total
35
35
70
Chi-Square = 6.5, 1 df, hot significant.
718
D. PORRITT Table 5. Between Group Outcome Score by marital status and treatment group Married treatment group DC IR FI T
BGOS
Single treatment group DC IR FI T
Poorer Better
18 1
4 1
I 8
23 10
10 1
1 4
2 19
13 24
Totals
19
5
9
33
1l
5
21
37
Chi-square
8.80 DC vs IR + FI
'13.99 D C + I R vs FI 1 df, P < 0.001
1 df, P < 0.01
Table 6. Marital status by outcome with treatment effects controlled Marital Status WGOS Poorer Better Total
M
DC* S
T
8 11 19
8 3 11
16 14 30
Treatment Group IR* M S T 4 1 5
1 4 5
5 5 10
M
FI* S
T
All Groupst M S T
3 6 9
11 10 21
14 16 30
15 18 33
20 17 37
35 35 70
* NS by Fisher's Exact Test. t Chi-square = 0.45, 1 dt] NS. and ,coefficient alpha values for the summed ratings for the seven most frequently available sources, viz. Mother, Father, Spouse, Boss, Friends a n d Professionals (Doctors and Social Agencies). Strangers, Siblings, Clergy a n d Children were n o t used in scoring the support network, either because they were n o t sufficiently available or because they were n o t seen by subjects as appropriate sources of support. Table 7 shows that reliabilities for the s u m m e d ratings were high for all sources except fathers. For all of the sources included, the subjects were clearly judging some characteristic c o m m o n to all three scales. There was a wide range of scores on each scale due in part to the large differences between groups reported below. An averaging a p p r o a c h to scoring the overall network for each subject produced n o significant relationships between the score a n d group m e m b e r s h i p and n o significant relationship to W G O S within groups. To conserve space the results are not presented. A counting a p p r o a c h produced quite different results. S u m m e d ratings for each source were highly skewed, with over half falling in the range from three (the most favourable possible total) to five. As a criTable 7. Ratings of emphathy, respect and genuineness for six major potential sources of support Source
n
Means E R
CG
Coefficient Alpha
Mother Father Wife Boss Friends Doctors & agencies
33 33 33 62 69
2.6 2.3 1.7 2.6 2.3
2.4 2.0 2.3 2.6 2,3
2.0 2.4 2.4 1.6 1.3
0.91 0.54 0.79 0.97 0.95
70
2.9
2.8
1.9
0.96
terion for classifying a source as Supportive or Unsupportive, the ratings were divided into those of five or less (Supportive) a n d those of six or more (Unsupportive). Three scores were then calculated for each subject: S, the n u m b e r of sources rated Supportive; U, the n u m b e r of sources rated U n s u p p o r t i v e ; and SB (Support Balance), S minus U. Table 8 shows that the three scores all discriminated significantly between the three treatment groups, as predicted. F o r Table 9, each of the three measures (S, U and SB) was dichotomised within groups a n d the classification of subjects as receiving higher or lower scores on a measure cross-tabulated with W G O S . With treatment effects thus removed the relationship of W G O S to U a n d to SB was significant a n d to S approached significance. Coefficient alpha for S (0.17) and for U (0.29) was low and for SB (0.43) only moderate. The value for SB was probably inflated by the artefactual negative correlation forced between S a n d U by the fact that they must sum to a total of .seven or less. DISCUSSION
Ratings of each source of support were adequately reliable. There was little consistency between the levels of support offered by different sources to the same subject. Apparently these subjects did not select their network members on any basis that was strongly related to supportiveness as measured here. The results with the two different scoring methods clearly favoured the counting approach as the more valid. Thus, it seems that the effects of distinct sources are cumulative. The Support Balance score results give some credence to the notion that supportive a n d unsupportive reactions may cancel each other out, a l t h o u g h this might have been due to the artefactual negative correlation between the two c o m p o n e n t measures. Even so, it appears that intervention which
Social support in crisis: quantity or quality?
719
Table 8. Percentage scoring above median on S, on U and on SB by treatment group Measure S(HI = 3+) U(HI=3+) SB(HI = 1 +) n
DC
Treatment Group IR FI Total
Chi-square*
P
SOCIAL SUPPORT IN CRISIS: QUANTITY OR QUALITY? D. PORRITT School of Community Medicine, University of New South Wales, Australia Abstract--It is suggested that individual differences in reactions to crises depend in part on the variations in social support available to the individual in crisis. A model of the quality of support is derived from research on the effectiveness of interpersonal helping processes. It is predicted that the availability of sources of potential help will be unrelated to crisis outcome, but that the quality of support received will be a determinant of outcome. Different methods of combining measures of the quality of support given by different sources are considered. Data from a controlled trial of crisis interventior with males hospitalised for treatment of road injuries are used to test the predictions and compare the different scoring methods. The results confirm the predictions that source availability is unrelated to outcome, that source quality is related to outcome, and that crisis intervention has a highly significant effect on the reported quality of support received. Problems in determining the causal direction of the relationships found are discussed, and it is concluded that most probably coping behaviour and support influence each other and jointly determine outcome. It is argued that skills in conveying genuine respect and understanding to people in crisis appear to be lacking among professional care givers and inadequate in many individual's social networks. Action to change this situation is recommended, and the measurement methods reported in the paper offered as a basis for further research, as no other simple generally applicable method has been published with data to substantiate its validity.
INTRODUCTION Periods of stress and crisis present individuals with increased demands on their physical, psychological and social resources. There is evidence that such demands can exacerbate and perhaps even precipitate both psychological and physical breakdown for some individuals [1-4]. The effects of such challenges show wide individual differences. Variations in aspects of social support received hold a prominent place among the variables that might explain these differences [2, 5-7]. The proposition that variations in social relationships make a difference for better or for worse at times of challenge is hardly controversial. The relevant empirical studies are, however, so diverse in theoretical conception and measurement procedures that to integrate them is difficult. In particular, little consensus has emerged about the specific types of variation in social network structure or function that are relevant to outcome. To attempt to review or synthesise this literature is beyond the scope of this article. The focus here is on the results achieved in an empirical study which adopted Carkhuff's [8] framework for assessing aspects of social support. This model was an effort to integrate the empirical research into the determinants of the outcome of attempts by one person to be helpful to a n o t h e r - whether by psychotherapists, counsellors, teachers, parents or friends. Carkhuff proposed that development through the life span be seen as moving through a series of choice points or crises. Each crisis offers the opportunity of change for the better while it also threatens change for the worse. Two main classes of variable were suggested in his model as determining the outcome at each crisis point. These were the developmental level of the person and the quality of others' responses to the person. Stated in thesegeneral terms, the model differs little from the common notions typical of most accounts
of crisis theory. The special value of Carkhuff's model is that he suggests specific variables on which the quality of response from others may be assessed. The best validated of the variables are the level of Empathic Understanding (EU), of Respect (R) and of Constructive Genuineness (CG). Thus, a general hypothesis derived from Carkhuff's model would be: the probability of a favourable outcome for an individual faced with a crisis will be greater the higher the levels of empathic understanding, respect and constructive genuineness conveyed to the individual by other people's reactions. It also follows from Carkhuff's model that the mere availability of people from whom assistance might be sought will not affect crisis outcome. Quality is more important than quantity, The general hypothesis is derived largely from studies of dyadic interaction. It thus leaves open the issue of how best to measure the level of response from a social network. At least two approaches could be adopted. (1) Averaging: if the typical level of response is critical, then the average level across all available sources of response is the appropriate measure. This assumes that constructive and destructive responses cancel each other out and that two equally constructive sources are no more helpful than one, other things being equal. (2) Counting: if the number of constructive or destructive sources is important, then each source should be classified as destructive or constructive and the number of sources of each type counted. The issue of whether constructive and destructive reactions cancel each other out could then be explored by comparing the predictive power of three measures: (a) the number of constructive sources; (b) the number of destructive sources; and (c) the difference between (a) and (b). Another issue worthy of empirical investigation is the degree to which a person's social network tends to show a consistent level of response, i.e. whether
715
716
D. PORRITT
each person's sources of response tend to vary within a restricted range of quality or to show a more random scattering of levels. THE STUDY An opportunity arose to investigate these issues as part of an experimental trial of crisis intervention with males hospitalised for road injuries [9, 10].
Design and procedure In the study, 70 males were interviewed 12-16 weeks after being injured on the road and admitted to hospital for at least one week. In this interview, a retrospective assessment was obtained of the subject's perceptions of who was available to him during the period since injury and of the levels of EU, R, and CG conveyed to him by each of the available sources of response. For the purposes of the evaluation trial, the 70 patients had been divided into three groups. All groups reported on their emotional reactions to injury and hospitalisation. The Delayed Contact (DC, n = 30) group gave this data at the follow-up interview. Otherwise they received only standard hospital treatment. None had been referred to the Hospital's Social Work Department. The Immediate Review (IR, n = 10) group and the Full Intervention (FI, n = 30) group were interviewed about these reactions within one week of admission. The iR group received no further contact until follow-up. Patients in the FI group were offered and all accepted the help of a qualified social worker for 2-10 contacts (mean of 5). The social workers were selected to be functioning at or above minimally facilitating levels on a specially prepared Communications Index, based on that developed by Carkhuff [8]. All were experienced in brief action-oriented crisis intervention. Due to practical limitations the research interviews were conducted during the period from April 1973 to January 1974 inclusive. The interviewer had previous experience in a prospective study of recently widowed women. To obtain useable sample sizes, non-random allocation to treatment groups was necessary. Thus, subjects in group D C were all of the eligible consenting patients admitted from December 1972 to April 1973. They were first contacted 12-16 weeks after admission and invited to participate in the study. The outcome interview was then administered followed by the intake assessment which other subjects received in their first week in hospital. Subjects in the IR and FI groups were all of the eligible consenting patients admitted from May 1973 to December 1973. Allocation to these groups was random. Subjects in both groups were interviewed in hospital about their injury and hospitalisation within 1 week of their admission. G r o u p FI subjects were offered and all accepted, intervention by one of the social workers employed for the project as already described.
Measures
back at work at follow-up and reported less than a criterion number of problems at work on Langsley's Work Adjustment Scale), life enjoyment (Bradburn's Positive Affect Scale) and health deterioration (Maddison's Health Change Questionnaire). These measures were described in more detail in previous reports [9, 10]. Social support was assessed by presenting each subject with a list of potential sources of support. The list included Mother, Father, Siblings, Spouse, Children, Friends, Other Relatives, Clergy, Strangers, Doctors or Social Agencies, and Boss. For each potential source, the subject was asked if help was or was not available from that source. If help was available, the subject was asked to rate the Source's reactions on the scales of EU, R and CG presented in Appendix A. Responses were scored with the values shown in brackets beside each response option. In making the ratings, subjects were asked to consider the full period since their injuries. The scales are simplified forms of the scales with the same titles presented by Carkhuff [8].
Intervention The nature of the intervention is important for the interpretation of the results. It involved assessment and intervention as judged necessary on three fronts. Practical support involved such activities as assistance with making contact with families, negotiations with employers about returning to work and obtaining financial and other assistance from government and other welfare agencies. Emotional support was provided by further exploration of emotional reactions to the traumatic events and by exploration and clarification of subsequent concerns as these arose. Constructive, problem-oriented, non-blaming coping behaviour was encouraged. Social support was fostered by encouraging family and friends to keep regular contact and also to listen to, accept and try to understand the patient's concerns. Where a natural support network was not available, community welfare agencies were mobilised to provide any continuing support that it appeared might be needed after the intervention was terminated.
Predictions In this paper, the results of the study are used to test three predictions and to explore some related issues. The predictions are: 1. There will be no differences between groups in the availability of sources. 2. Subjects in the FI group will report more supportive responses, measured on the EU, R and CG scales and subjects in the D C group will report less supportive responses from their available sources. 3. Subjects who show relatively better outcomes when compared to others receiving the same intervention will report their sources of response as equally available, but as more supportive than will subjects with relatively poorer outcomes.
The outcome measures drawn on in this paper were . The results are also used to explore whether the self-reports on standardised questionnaires covering averaging or counting approaches to scoring a supemotional distress (Langner 22-item scale; Langsley port network is more useful, and to test the consistSymptoms Scale; Bradburn Negative Affect Scale), ency in the supportiveness of individual's networks. work adjustment (classed as good if the subject was
Social support in crisis: quantity or quality? Table I. Between group outcome score by treatment group Number of measures with poorer outcome
Treatment group DC IR FI
Table 3. Number of supports available by treatment group
Total
Number available
1 0 2 4 3
18 10 8 6 3
8 7 6 5 4
1 3 8 10 5 2 0 1 0
1 5 15 24 19 5 0 1 0
Total
30
10
30
7O
HI
7 10 13 30
2 4 4 10
12 10 8 30
21 24 25 70
4 1 0 0 0
1
0
2
8
10
3
0
0
3
12
15
2
Total
3O
10
3O
70
0
Poorer Better Total
28 2 30
5 5 10
3 27 30
36 34 70
RESULTS
Chi-square = 4.1, 4 dr, not significant.
Subjects were found to be younger a n d of lower socioeconomic status than the C a n b e r r a population, as would be expected for road injury patients, a n d the outcome measures were found to be sufficiently correlated to justify combining them into a composite index. Bordow 1-9] has reported the relevant data.
Outcome indices Two indices were used here. The Between G r o u p s Outcome Score (BGOS) was obtained by dichotomising each of the six outcome variables a r o u n d its median for the total sample a n d then counting the number of measures on which a subject was in the unfavourable half of the distribution. This c o u n t was the subject's BGOS. The W i t h i n G r o u p s O u t c o m e Score (WGOS) was calculated separately for each group. F o r example, in the F I group, each of the six outcome measures was dichotomised a r o u n d the median score for the 30 subjects in that group. Each subject in group FI then was assigned as his W G O S the n u m b e r of outcome measures on which he was in the unfavourable half of the distribution of that measure in his group. W G O S was derived similarly for the other two groups relative to the median scores for the subject's own group. W G O S can thus be used Table 2. Availability of 11 potential sources of support by treatment group
Mother Father Siblings Spouse Children .Friends Strangers Doctors & agencies Other relatives Boss Clergy n * P < 0.05; t P < 0.01.
26~ 20~ 33~o 63~o 13~ 100~ 20~ 100~o 28~ 90~ 0~ 30
1
MOD LO Total
Chi-square = 40.8, 2 df, P < 0.001.
Total
0 0 2 4 4 0 0 0 0
13 9 6 2 0
DC
Treatment group DC IR FI 0 2 ~ 5 10 10 3 0 0 0
6 5 4 3 2
Source
717
Treatment group IR F]~ 60~ 20~ 40~ 50~o 0~o 100~o 20~o 100~ 0~ 90~o 0~ 10
67~t 60~t 37~ 30~* 3~o 97~ 13~ 100~o 28~o 87~ 0~ 30
as a measure of outcome with experimental effects removed. It is independent of treatment effects. Table 1 presents B G O S by treatment group. The differences in outcome are m a r k e d a n d clearly favour the FI group over the IR group over the D C group. Results for each measure separately were significant a n d have been given previously [10]. Table 2 presents data on the availability of potential sources of support by treatment group. Table 3 presents data on the n u m b e r of available sources by treatment group. In Table 4 the n u m b e r of available sources, with between group differences removed, is presented as a function of W G O S . These tables show as predicted little relationship between availability of sources a n d outcome. The data do reveal one possible confounding factor. The D C group more often reported spouse as available and parents as not available t h a n the F I group, i.e. D C subjects were more often married a n d FI subjects more often single and living with or near parents. Table 5 tests the effect of treatment group on B G O S with marital status controlled. Table 6 tests the effect of marital status on W G O S within treatment groups. These tables show that the differences in marital status c a n n o t account for the differences in outcome between groups and that marital status is not related to out6ome within groups. F o r each available source, the EU, R and C G ratings were summed. Reliabilities of the summed ratings were estimated by C r o n b a c h ' s coefficient alpha as suggested by N u n n a l l y [11]. Table 7 presents means, ns, a n d s t a n d a r d deviations for the three scales Table 4. Within group outcome score by relative number of supports available WGOS
Relative availability Loer Hier
Total
Poorer Better
16 19
19 16
35 35
Total
35
35
70
Chi-Square = 6.5, 1 df, hot significant.
718
D. PORRITT Table 5. Between Group Outcome Score by marital status and treatment group Married treatment group DC IR FI T
BGOS
Single treatment group DC IR FI T
Poorer Better
18 1
4 1
I 8
23 10
10 1
1 4
2 19
13 24
Totals
19
5
9
33
1l
5
21
37
Chi-square
8.80 DC vs IR + FI
'13.99 D C + I R vs FI 1 df, P < 0.001
1 df, P < 0.01
Table 6. Marital status by outcome with treatment effects controlled Marital Status WGOS Poorer Better Total
M
DC* S
T
8 11 19
8 3 11
16 14 30
Treatment Group IR* M S T 4 1 5
1 4 5
5 5 10
M
FI* S
T
All Groupst M S T
3 6 9
11 10 21
14 16 30
15 18 33
20 17 37
35 35 70
* NS by Fisher's Exact Test. t Chi-square = 0.45, 1 dt] NS. and ,coefficient alpha values for the summed ratings for the seven most frequently available sources, viz. Mother, Father, Spouse, Boss, Friends a n d Professionals (Doctors and Social Agencies). Strangers, Siblings, Clergy a n d Children were n o t used in scoring the support network, either because they were n o t sufficiently available or because they were n o t seen by subjects as appropriate sources of support. Table 7 shows that reliabilities for the s u m m e d ratings were high for all sources except fathers. For all of the sources included, the subjects were clearly judging some characteristic c o m m o n to all three scales. There was a wide range of scores on each scale due in part to the large differences between groups reported below. An averaging a p p r o a c h to scoring the overall network for each subject produced n o significant relationships between the score a n d group m e m b e r s h i p and n o significant relationship to W G O S within groups. To conserve space the results are not presented. A counting a p p r o a c h produced quite different results. S u m m e d ratings for each source were highly skewed, with over half falling in the range from three (the most favourable possible total) to five. As a criTable 7. Ratings of emphathy, respect and genuineness for six major potential sources of support Source
n
Means E R
CG
Coefficient Alpha
Mother Father Wife Boss Friends Doctors & agencies
33 33 33 62 69
2.6 2.3 1.7 2.6 2.3
2.4 2.0 2.3 2.6 2,3
2.0 2.4 2.4 1.6 1.3
0.91 0.54 0.79 0.97 0.95
70
2.9
2.8
1.9
0.96
terion for classifying a source as Supportive or Unsupportive, the ratings were divided into those of five or less (Supportive) a n d those of six or more (Unsupportive). Three scores were then calculated for each subject: S, the n u m b e r of sources rated Supportive; U, the n u m b e r of sources rated U n s u p p o r t i v e ; and SB (Support Balance), S minus U. Table 8 shows that the three scores all discriminated significantly between the three treatment groups, as predicted. F o r Table 9, each of the three measures (S, U and SB) was dichotomised within groups a n d the classification of subjects as receiving higher or lower scores on a measure cross-tabulated with W G O S . With treatment effects thus removed the relationship of W G O S to U a n d to SB was significant a n d to S approached significance. Coefficient alpha for S (0.17) and for U (0.29) was low and for SB (0.43) only moderate. The value for SB was probably inflated by the artefactual negative correlation forced between S a n d U by the fact that they must sum to a total of .seven or less. DISCUSSION
Ratings of each source of support were adequately reliable. There was little consistency between the levels of support offered by different sources to the same subject. Apparently these subjects did not select their network members on any basis that was strongly related to supportiveness as measured here. The results with the two different scoring methods clearly favoured the counting approach as the more valid. Thus, it seems that the effects of distinct sources are cumulative. The Support Balance score results give some credence to the notion that supportive a n d unsupportive reactions may cancel each other out, a l t h o u g h this might have been due to the artefactual negative correlation between the two c o m p o n e n t measures. Even so, it appears that intervention which
Social support in crisis: quantity or quality?
719
Table 8. Percentage scoring above median on S, on U and on SB by treatment group Measure S(HI = 3+) U(HI=3+) SB(HI = 1 +) n
DC
Treatment Group IR FI Total
Chi-square*
P
