Journal of Pediatric Psychology, Vol. 25, No. 4, 2000, pp. 257-267
© 2000 Society of Pediatric Psychology
Social Support and Personal Models of Diabetes as Predictors of Self-Care and Well-Being: A Longitudinal Study of Adolescents With Diabetes
University of Surrey
All correspondence should be sent to T. C. Skinner, Research & Development Unit, University Hospital Lewisham, Lewisham High Street, London SE13 6LH England. E-mail: chas.skinner{at}uhl.nhs.uk .
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Abstract |
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Objectives: To examine whether peer support and illness representation mediate the link between family support, self-management and well-being.
Method: Fifty-two adolescents (12-18 years old) with Type I diabetes were recruited and followed over 6 months, completing assessments of self-management, well-being, and social support.
Results: Perceived impact of diabetes and supportive family and friends were prospectively predictive of participants' well-being measures. Although support from family and friends was predictive of better dietary self-care, this relationship was mediated by personal model beliefs. In particular, beliefs about the effectiveness of the diabetes treatment regimen to control diabetes was predictive of better dietary self-care.
Conclusions: Both friends and family are important to support adolescents as they live with and manage their diabetes. Personal models of diabetes are important determinants of both dietary self-care and well-being. In addition, personal models may serve to mediate the relationship between social support and dietary behavior.
Key words: diabetes; adolescents; depression; anxiety; well-being; self-care; adherence; social support; illness representations; family; friends; peers; personal models.
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Introduction |
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The individual with IDDM must assume responsibility for the normally automatic regulation of blood glucose levels, achieved through a complicated, multicomponent treatment regimen that includes daily insulin administration, blood glucose testing, dietary regulation (including timing of meals and snacks with insulin injections), and monitoring of exercise and activity level.
Although those with diabetes can live a relatively normal life, the chronic
complications (neuropathy, myocardial and foot ischemia, renal disease, and
retinopathy) can result in a substantial decline in quality of life. The
Diabetes Control and Complications Trial
(DCCT, 1994
) confirmed that
improved metabolic control was significantly associated with delayed onset and
progression of microvascular complications, with a clear increasing risk
related to poorer metabolic control. This means that the problem of the
decline in blood glucose control seen in many adolescents
(Allen et al., 1992;
Amiel, Sherwin, Simonson, Lauritano, &
Tamborland, 1986; Palta, Shen,
Allen, Kelin, & D'Alessio, 1996) is of even greater
significance, if later complications are to be delayed, reduced, or possibly
avoided. Although this decline in metabolic control is partly attributable to
the physiological aspects of puberty (Amiel
et al., 1986; Bloch, Clemons,
& Sperling, 1987), adolescence is also often a period of
reduced self-management (Anderson,
Auslander, Jung, Miller, & Santiago, 1990;
Johnson et al., 1992;
Morris et al., 1997).
Research on self-management in adolescents has primarily focused on the
relationship between adolescents and their families. A relatively consistent
finding is that adolescents from more supportive and cohesive families have
better metabolic control and adherence (see
Burroughs, Harris, Pontious, &
Santiago, 1997, for a review). Moreover, adjustment to chronic
illness is similarly associated with family characteristics (see
Drotar, 1997, for a
review).
However, in a recent review Glasgow and Anderson
(1995) recommended that
"greater attention be paid to the social context" in which the
adolescent lives. La Greca
(1990,
1992) noted the paucity of
research on the role of the adolescent's peer group, at a time when
friendships develop and peer influence becomes increasingly important. Peers
and friends are an important source of emotional support for adolescents with
diabetes (La Greca et al.,
1995a; Meldman,
1987; Skinner, White,
Johnston, & Hixenbaugh, 1999), and this support is associated
with adherence (La Greca et al.,
1995a) and metabolic control
(Skinner et al., 1999) and may
also be associated with well-being (La
Greca, 1990). In a sample of adolescents with chronic illnesses,
Wallander and Varni (1989)
found that high support from only family or friends was not associated with
better adjustment. Both components—supportive family and
friends—was associated with better adjustment.
Research also needs to examine explanatory models of how the family may
influence the child's adaptation to or coping with diabetes
(Drotar, 1997;
Glasgow & Anderson, 1995).
One possible mechanism is that as part of the process of learning coping
strategies from family members, supportive families may encourage the adoption
of more adaptive illness representation
(Lau, Quadrel, & Hartman,
1990). One model of health behavior that researchers have begun to
examine in this context is the self-regulation model
(Leventhal, Nerenz, & Steele,
1984), which postulates that individuals' personal model of an
illness is a proximal determinant of both their emotional and behavioral
response to a health threat (see Figure
1A).
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This approach differs in at least three ways from other models that concern the role of patient beliefs and attitudes in determining health behaviors. First, personal models are an extension of schema theory from cognitive social psychology. Thus, unlike other social cognition models, personal models are grounded in a general theory of cognition that accounts for the merging of incoming information with past experience. Second, personal models differ by being patient-generated as opposed to researcher-generated. Personal models identify those variables that patients themselves believe to be central to their experience of illness and its management. Third, personal models include the representation of emotional responses to disease and treatment, which is lacking in the other health belief models.
Research using these underlying principles identified five components to
personal models of an illness: illness identity and associated symptoms; its
cause; the consequences of the illness; how long it will last; and treatment
efficacy (Lau, Bernard, & Hartman,
1989; Leventhal et al.,
1984; Meyer, Leventhal, &
Gutmann, 1985). In adults with diabetes, beliefs about the
efficacy of their treatment predicted dietary and exercise self-management
(Hampson, Glasgow, & Foster,
1995; Hampson, Glasgow, &
Toobert, 1990). In a sample of over 2,000 participants, personal
models beliefs about treatment effectiveness proved to be a better predictor
of self-management than either barriers to adherence or perceived seriousness
(Glasgow, Strycker, Hampsom, &
Ruggiero, 1997). In a cross-sectional study of 74 adolescents
(Skinner & Hampson, 1998a,
1998b), individuals' beliefs
in the efficacy of the treatment regimen predicted better dietary self-care.
Similarly for depression and anxiety, the greater the perceived impact of
diabetes on daily life, the more depression and anxiety participants
reported.
If personal models are proximal determinants of individuals' behavioral and
emotional response to illness, they may serve to mediate the association
between demographic variables and outcome measures. Gender differences have
been noted in adolescents with diabetes, with girls having significantly worse
metabolic control and psychological adjustment
(La Greca, Swales, Klemp, Madigan, &
Skyler, 1995b). Furthermore, the gender difference in
psychological adjustment may mediate the association between gender and
metabolic control (La Greca et al.,
1995b). In adults, perceived threat of diabetes partially mediated
the association between demographics indices and depression
(Connell, Davis, Gallant, & Sharpe,
1994). Studies using the personal models approach have reported
associations between illness representations and demographics, and between
demographics and self-care. However, the possible mediational role of personal
models has not been explored (Glasgow et
al., 1997; Hampson et al.,
1995) yet clearly warrants further examination.
Reviewers have been critical of the continued use of cross-sectional
studies (Drotar, 1997;
Glasgow & Anderson, 1995),
which cannot resolve the direction of causal relations underlying associations
between variables. Therefore, a longitudinal study was undertaken with
participants assessed at baseline and at 6-month follow-up, with a view to
testing two models of the relationship between social support, personal models
of diabetes, and outcomes: (1) social support and personal models are
independent predictors of both self-care and well-being (see
Figure 1B); and (2) personal
models mediate the association between social support and both self-care and
well-being (see Figure 1C).
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Method |
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Participants
The sample was recruited from outpatient lists at four regional hospitals in the south of England. Eligibility criteria included age (12-18 years old), a diagnosis of IDDM of at least 9 months, and ability to complete the questionnaire unaided. Further details of recruitment have been reported elsewhere (Skinner & Hampson, 1998b
).
Procedure
Eligible participants were sent a letter introducing the project prior to
their scheduled outpatient appointment, when they were given further details
regarding the project. It was made clear to the adolescents that the clinic
staff would not know who was taking part in the study and that all information
would be strictly confidential. Those individuals who agreed to participate,
and parents of all those under 16 years old, completed consent and demographic
forms. After explanation of the instructions, participants were then asked to
complete the booklet in their own time and return it in the stamped addressed
envelope provided. Recruitment lasted four months at each hospital to ensure
that all eligible patients at each hospital would be approached, as scheduled
appointments were typically every 3 months. Three months after recruitment,
they received a thank you letter. Six months after recruitment, participants
were sent the second questionnaire booklet, which they were asked to complete
and return in the envelope provided. If the questionnaire was not returned
within 3 weeks of posting, a brief reminder letter was sent to
participants.
Measures
All the booklets followed the same format and order of questionnaire
presentation. This started with the two outcome measures, well-being and
self-management, followed by the measures of general social support, personal
models of diabetes, and finally diabetes-specific support measures.
Depression, anxiety, and positive well-being were assessed with the
Well-Being Questionnaire (Bradley,
1994). This is a 22-item instrument, developed specifically for
use in patients with diabetes, that produces four subscales measuring
depression, anxiety, positive well-being, perceived energy, and a summary
well-being score, previously validated on adults
(Bradley, 1994). To date, this
questionnaire has been used only with adolescents as young as 16, so some
pilot interviews were undertaken with healthy 12-year-olds. These indicated
that some participants would have difficulty with one item from the energy and
two from the positive well-being scale. Therefore, these items were removed
and the two scales combined to form one positive well-being scale. Reported
internal consistency (coefficient alpha) of the depression scale was.46-.73
and.65-.80 for anxiety in adult samples
(Bradley, 1994), compared to.63
for depression and.78 for anxiety in this sample. The internal consistency
(coefficient alpha) of the combined positive well-being scale was.87.
Self-management was assessed with the Summary of Diabetes Self-Care
Schedule (Toobert & Glasgow,
1994). This is a validated 12-item self-report instrument that
assessed four areas of diabetes self-management (diet, exercise, blood glucose
monitoring, and injecting) over the previous 7 days. As the care teams
involved did not emphasize exercise as part of diabetes management, this scale
was not included in the analysis. The internal consistency (assessed by
coefficient alpha) was.64 for diet,.80 for blood glucose testing, but only.41
for insulin injecting.
Social support was assessed with four questionnaires. To measure general
support, the Perceived Social Support from Family and Perceived Social Support
from Friends questionnaires were used
(Procidano & Heller,
1983). These each contain 20 items with a "yes,"
"no," or "don't know" response format. These
questionnaires were designed to assess "the extent to which an
individual perceives that his/her need for support, information and feedback
[is] fulfilled." These instruments have an internal consistency of
between.88 and.90, with 1-month test-retest reliability estimated at.83
(Procidano & Heller,
1983). In the present sample, internal consistency was.89 for the
family and.86 for the friends questionnaire.
To measure diabetes-specific support, the Diabetes Family Behavior
Checklist (DFBC) (Schafer, McCaul, &
Glasgow, 1986) was used. The DFBC asks respondents to rate the
frequency of 16 behaviors related to their diabetes care on a five-point scale
(1 = never, 5 = at least once a day), and how helpful/unhelpful they find
these behaviors on a seven-point scale (-3 = extremely unhelpful, +3 =
extremely helpful). For this study the instructions were revised to ask the
respondent "how often family members do several things," instead
of referring to an individual family member. The positive and negative scoring
method used in previous studies was not adopted, as analysis indicated that
there was no consistency between participants as to which behaviors were
helpful or unhelpful. Therefore, a single score reflecting the individual's
perspective of family support was obtained. This was achieved by multiplying
the frequency and helpfulness scores and then summing them to generate a total
support score. The internal consistency of the DFBC is reported as.63 with a
6-month test-retest reliability of.60
(Schafer et al., 1986),
compared to an internal consistency of.73 for the frequency responses,.65 for
the supportiveness ratings, and.83 for the multiplied scores as scored in this
study.
To measure peer support, the Diabetes Inventory of Peer Support (DIPS) was
constructed, using the same format as the DFBC. Items were selected based on
an earlier study examining the supportive and unsupportive behavior of friends
for diabetes care (Skinner et al.,
1999) using the Diabetes Social Support Interview
(La Greca et al., 1995a).
Those behaviors that were reported by at least a third of participants in the
previous study were used to generate 12 items. The questions asked about the
frequency and supportiveness of 10 behaviors related to diet, exercise
injections, and testing and two items related to general diabetes support. As
for the DFBC, the frequency and helpful/unhelpfulness scores were multiplied
and summed to generate a support score. The scale had an internal consistency
(assessed by coefficient alpha) of.75 for the frequency responses,.63 for the
supportiveness ratings, and.69 for the multiplied scores.
Personal model of diabetes was assessed using the Personal Models of
Diabetes Questionnaire, developed from the Personal Models of Diabetes
Interview (Hampson et al.,
1990; Hampson et al.,
1995). This is a brief, eight-item self-report instrument. Each
item has a 5-point Likert scale response option. The instrument has four items
evaluating beliefs about the efficacy of treatment regimen; two of these
assess the belief that self-management will control diabetes (control, 
=.71) and two items assess beliefs that self-management can prevent the
complications of diabetes (prevention, =.45). The remaining four items
relate to the consequences of diabetes; two assess feelings of seriousness and
worry concerning diabetes complications (seriousness, =.60) and two
items assess the impact of diabetes on daily life (Impact, =.68).
Support for the validity of the questionnaire comes from a study of 2,000
adults with diabetes (Glasgow et al.,
1997), which, along with the results of a separate series of
interviews using different measures of self-care and well-being, suggests that
this brief questionnaire taps the key dimensions of interest
(Copp, Skinner, & Hampson,
1998).
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Results |
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Demographics
Of the original 74 (32 girls, 42 boys) participants recruited at baseline, 52 (24 girls, 28 boys) completed and returned the 6-month follow-up questionnaire booklet. Of the 22 who did not complete the 6-month follow-up, 1 died, 1 moved to the United States, 6 decided to withdraw from the study, 4 claimed to have sent the questionnaire in the post in response to the follow-up letter, and the remaining 10 did not return a questionnaire or respond to the follow-up letter. There was no significant gender bias in dropout rates and no significant differences between those lost to follow-up and those returning questionnaires on age (baseline M = 15.2, SD = 1.8: 6 months M = 15.6, SD = 1.9) or duration of diabetes (baseline M = 5.3, SD = 3.7; 6 months M = 5.9, SD = 3.6). The only participant from an ethnic minority at recruitment had moved to the United States by the 6-month follow-up. The sample was biased toward the higher socioeconomic groups, but the distribution did not change significantly from recruitment, (see Skinner & Hampson, 1998b
,
for further demographic details). Neither age, duration of illness, or socioeconomic status was associated with any of the well-being measures. However, better dietary behavior was associated with shorter duration of illness (r = -.34; n = 38; p < 03) and higher socioeconomic status (r = -.32; n = 51; p <.04). There were a number of gender differences, with girls reporting higher levels of depression (t[49] = 2.78, p <.02) and anxiety (t [49] = 3.46, p <.001), and lower levels of positive well-being (t [49] = -2.46, p <.03) and overall well-being (t [49] = -3.00, p <.004) than boys. The girls also reported that their diabetes was more serious (t [49] = 2.53, p <.01) and had a greater impact (t [49] = 2.52, p <.01), but they also reported more support from friends (t [49] = 1.71, p <.05) than boys (see Table I for details).
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Change Across Follow-Up
All predictor and outcome measures at follow-up were significantly
correlated with baseline measures (.49 < r >.82). However,
using paired t tests, perceived seriousness (t [48] = -3.12,
p <.003), perceived efficacy of treatment to control diabetes
(t [49] = 3.07, p <.004), general family support
(t [50] = 3.93, p <.000), and diabetes-specific family
support (t [42] = 2.75, p <.009) at 6-month follow-up
were all significantly different from baseline measures. These changes were
not associated with age, duration, or socioeconomic status. Participants
reported less support from their family, that their diabetes was more serious,
and that their treatment was more efficacious at 6 months than at baseline.
The change scores largely resembled normal distributions, with the exception
of frequency of testing, timing of injections, and family-specific support
(using Shapiro-Wilks tests). This pattern of results suggests that repeat
completion of the questionnaires has not introduced a systematic positive bias
in subject responding.
There were no significant correlations between demographic characteristics and change scores, but there were a number of gender differences. Girls reported a greater decrease in family support both generally (t [49] = 2.08, p <.05) and for diabetes-specific family support (t [49] = 2.52, p <.02) than boys. In addition, girls' injecting behavior got worse over the 6-month follow-up, whereas the boys' injecting behavior improved slightly (t [50] = 2.85, p <.004), and this effect remained when controlling for age, duration, and injecting behavior at time of recruitment (see Table I for details).
Longitudinal Mediator Analysis
For personal models to act as a mediator of social support, three criteria
need to be met: (1) social support and illness representation must be related
to the outcome measures; (2) there must be a relationship between the
predictor (social support) and the mediator (personal models); and (3) after
controlling for the effects of the mediator variable, the relationship between
the predictor and the outcome should be significantly reduced (Baron &
Kenney, 1986).
First, following Varni and Wallander's
(1989) suggestion that it is
the combination of both family and friend support that is important, a
composite measure of social support was computed. The measures of support were
centered (by subtracting the mean) and then summed to produce a composite
general and a composite diabetes-specific measure of support. Using well-being
and self-management measures at 6 months as dependent variables, we conducted
a series of hierarchical regressions entering demographics on step one,
followed by general and diabetes-specific support at baseline on step two, and
change scores as step three. General social support at baseline and change in
general social support were significant predictors of depression, positive
well-being, diet (see Table II)
and total well-being (see Table
III).
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We repeated the same strategy for multiple regressions exchanging the social support measures for the personal model variables. Perceived impact and change in perceived impact were significant predictors of anxiety, depression, positive well-being (see Table II) and general well-being (see Table III). Perceived control of diabetes and perceived seriousness at baseline were significant predictors of dietary self-management. However, the greater perceived seriousness of diabetes, the poorer participants' dietary self-care (see Table II).
Second, as both personal models and social support predicted well-being and dietary behavior, we examined the relationship between personal models and social support in a series of multiple regressions. Using personal model constructs as dependent measures, after entering demographics on step 1, we entered social support variables into a stepwise regression. None of the social support measures was a significant predictor of either perceived seriousness or perceived impact of diabetes. However, general support was a significant predictor of perceived control. General social support with demographics accounted for 28% of the variance, F = 6.58; p <.001, in perceived control at baseline and was the only significant predictor of perceived control at 6 months, accounting for 16% of the variance, F = 6.17; p <.02.
Because the first two criteria were met for a mediating role for perceived control, we examined the effect of personal model beliefs on the relationship between social support and dietary self-care. Using multiple regression, we entered demographic variables (age, duration, socioeconomic status, and gender) first, followed by social support on step two and then perceived control and seriousness on step three (see Table III). This analysis suggests that personal model constructs mediate the association between social support and dietary self-management, as support is no longer a significant predictor when personal model constructs are entered into the equation. It should also be noted that personal model beliefs would appear to mediate the association between socioeconomic status and dietary self-management, as this is no longer a significant predictor in the final equation.
Because perceived impact and social support were not associated with each other, no further mediator analysis was undertaken on this relationship. Therefore, the final equation to predict well-being, (as the results are almost identical for depression, positive well-being, and total well-being, only total well-being is reported) contained gender (boys reporting better well-being), perceived impact, change in impact and social support, and change in support as independent predictors (see Table III and Figure 1B). Again, it should be noted that the lack of significance of gender as a predictor of well-being in the final step suggests that perceived impact is at least partially mediating the relationship between gender and well-being, for girls reported significantly higher impact of diabetes than boys.
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Discussion |
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The results indicate that the more perceived impact of diabetes on day-to-day life, the lower the levels of the participants' well-being. These results almost exactly replicate the baseline data (Skinner & Hampson, 1998b
)
in that not only are the perceptions of the impact of diabetes important but
they also seem to mediate the association between gender and well-being. With
perceived impact and support acting independently to predict well-being, the
results of this study also replicate the results of Connell and colleagues
(1994) using structural
equation modeling to predict depression in adults with diabetes.
Although there were notable gender differences in both support and personal
model constructs, only perceived impact of diabetes, and not social support,
mediated the relationship between gender and well-being. This being the case,
why do adolescent girls perceived that diabetes has a greater impact on their
life? One possible reason is girls' greater concern with body image and weight
gain and the use of insulin manipulation to control weight
(Dunning, 1995;
Khan & Montgomery, 1996).
This hypothesis is partially supported by the increase in insulin skipping we
observed in girls over the follow-up period. The difference in the perceived
impact of diabetes may also be a reflection of girls reporting a greater
decline in the level of family support, with the correlation between change in
impact and change in general and specific family suport just failing to reach
significance (-.36 < r > -.32; n = 22; p
<.07). With psychological adjustment mediating the relationship between
gender and metabolic control (La Greca et
al., 1995b), the mediating role of personal models between gender
and well-being is particularly important and warrants future research.
Social support also predicted the dietary behavior of the adolescents in
this sample. However, it was not the diabetes-specific measures of support,
but the general measure of acceptance and emotional support provided by
friends and family that was important. This is supported by previous studies,
which indicate that peers are seen as primarily a source of emotional support
(La Greca et al., 1995b;
Skinner et al., 1999), which
is most valued (Meldman,
1987).
However, the relationship between this emotional support and dietary
behavior would seem to be mediated by the adolescent's personal models of
diabetes. In particular, beliefs about the efficacy of the treatment regimen
to control diabetes, and perceptions about the seriousness of diabetes, appear
to be more proximal determinants of dietary behavior. Although the results for
treatment efficacy match those in adult studies, the results for perceived
seriousness are inconsistent with previous research
(Glasgow et al., 1997;
Hampson et al., 1990;
Hampson et al., 1995). In
these adult studies, greater perceived seriousness was associated with better
self-care, not with poorer self-care as in this analysis.
Previous studies using the health belief model in adolescents with diabetes
have also found an inverted relationship between seriousness and adherence or
metabolic control (Bond, Aiken, &
Somerville, 1992;
Brownlee-Duffeck et al., 1987).
Do the results of these adolescent studies reflect actual difference in the
types of relationships in the adolescent and adult samples used, or are they a
function of complex, nonlinear relationships between seriousness and
self-management behavior? Perhaps the interaction between treatment efficacy
and seriousness beliefs is important, which would require a larger sample size
to determine. These results may also be a reflection of researchers' different
operationalization of constructs or participants' different interpretations of
questions. Another possibility is that the adolescents' behavior may be
determining their beliefs (i.e., those young people who are managing their
diabetes well perceive their diabetes to be less serious, as they believe
their behavior will prevent complications). Alternatively, the results may be
a consequence of clinicians using ineffective fear communication as a way of
motivating behavior. If the data do represent genuine age differences possibly
caused by differences in perceived invulnerability, denial, planning, and
future concerns (or lack of them), then questions arise as to how, when, and
why the relationship switches direction. This area needs further investigation
if the role of personal models is to be understood and utilized to guide
interventions.
If the adolescent's personal models are mediating the link between social
support and self-care, then, in addition to empirical data, this relationship
needs to be supported by a sound theoretical rationale. Although supportive
families may encourage the adoption of more adaptive illness representation
(Lau et al., 1990) as part of
the process of learning coping strategies, this is unlikely to be the path of
influence for peer support. However, research examining adolescent food choice
suggests that peers may influence dietary behavior, through processes such as
copying the selection of peers, making joint decisions, and making choices
that are normal among their affiliated group (Dennsion, 1996;
Schlundt et al., 1994). Thus,
group affiliation processes may act to provide an environment supportive of
diabetes self-care, with little or no inter- or intrapersonal conflict
experienced by the adolescent. Where the peer group is not supportive,
internal or external conflict may result and consequently affect personal
model beliefs. This would also account for the fact that it is the combination
of family and peer support that is important, for not only does the family
need to encourage the adoption of appropriate personal models but adolescents
then also needs support in day-to-day life to maintain them. This would
explain the results reported by Varni and Wallander
(1989): the combination of
family and peer support is associated with better psychological well-being and
not family or peer support alone, a result replicated in this data.
None of the personal model or social support measures predicted insulin
injecting and blood glucose monitoring possibly because the family is closely
involved in these activities. With only a couple of exceptions, adolescents
were on two-injection-a-day regimens. This means that these injections are
done at home, as is blood glucose testing. If this is the case, parents may
well have direct input initiating or even doing these behaviors, providing no
role for personal model or general support measures. Dietary self-management
takes place both inside and outside the home, so this aspect of
self-management is more likely to be influenced by social support and personal
model constructs. This argument is supported by the negative association
between specific dietary support from the family and age seen in the baseline
data (Skinner & Hampson,
1998b) and the decrease in family support seen over the 6-month
follow-up. This issue can be easily addressed in future research by including
measures such as the Diabetes Family Responsibility Questionnaire
(Anderson et al., 1990). Also,
the inability to predict testing and injecting behavior may be a consequence
of the lack of variability in the reporting of these behaviors, as these
scales used only two items.
Alternatively, the lack of associations between diabetes-specific support and self-care may be a function of the questionnaires used. Although the DFBC has been widely used in diabetes research to predict self-care, the scoring system used here, as a result of the analysis of responses to the helpful/unhelpful scale, is not one reported previously. Furthermore, the measure of diabetes-specific peer support was developed specifically for this study, Although based on responses of adolescents in previous interview studies, which have been replicated in a follow-up study, the diabetes-specific peer support measures' psychometric properties have yet fully to be evaluated. Despite these and the other limitations of the study (e.g., the relatively small sample size, bias toward higher socioeconomic groups, the use of only adolescent self-report measures, and the use of adult, modified questionnaires), these longitudinal data emphasize the importance of friends and family in supporting adolescents with diabetes. Furthermore, this study adds to the burgeoning literature supporting the self-regulation model and emphasizes the importance of personal models of an illness in determining response to health threats. Furthermore, it suggests that, as well as adopting constructive illness representations, adolescents need a supportive peer group, whose lifestyle does not radically conflict with the demands of diabetes, for dietary self-care and well-being to be optimal.
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Acknowledgments |
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This project was partially funded by the British Diabetic Association.
Received May 19, 1998; revision received August 27, 1998; accepted March 17, 1999
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