Abstract
Aims.
Identify the prevalence of health psychology use in children with type 1 diabetes (T1D) and evaluate how individual and contextual characteristics are associated with use.
Methods.
Children ages 8 to 16 years with T1D and their parents were recruited from two tertiary diabetes clinics. Cross-sectional data included parent and adolescent surveys and hemoglobin A1c. Parents self-reported the child’s use of health psychology in the last year along with individual factors (e.g., predisposing factors including demographics, enabling factors including health insurance type, evaluated need including mental health diagnoses and perceived need including self-management barriers). Association of health psychology use with individual (e.g., demographics, enabling factors, evaluated and perceived need) and contextual (e.g., clinical site) characteristics was evaluated using logistic regression.
Results.
Of 363 eligible participants, 267 (74%) participated. Health psychology use was reported by only 8.2% (n=22) of participants and was significantly associated with evaluated need factor of mental health diagnosis (OR 5.8; p<0.001) and perceived need factor of parent-reported self-management barriers. Use was not associated with other individual or contextual factors.
Conclusions.
Though infrequent, health psychology use was positively associated with mental health diagnoses and self-management barriers.
Keywords: Diabetes mellitus, type 1; pediatrics; adolescent; mental health services; self-management
1. Introduction
For children with type 1 diabetes (T1D), self-management is complex and requires coordination between a child and his or her family multiple times every day to test blood sugars, determine and administer insulin doses, and adjust as needed. The consequences of suboptimal self-management are a combination of short- and long-term complications, some of which are life-threatening.1,2 Optimal self-management leads to target glycemic control, defined by the American Diabetes Association (ADA) as a hemoglobin A1c (A1c) of less than 7.5% (58 mmol/mol).3 Unfortunately, children with T1D struggle with self-management and only 21–45.7% of children ages 13–18 achieve target glycemic control.4,5 Rates of control vary significantly by age, race, family structure (e.g. number of households), and parent education level.4,5 Both the International Society of Pediatric and Adolescent Diabetes (ISPAD) and the ADA recommend children with diabetes self-management challenges be referred to mental health professionals trained to support children with diabetes.3,6
Mental health problems can contribute to self-management challenges in children with T1D and represent another source of need for mental health services. Though data on prevalence of mental health problems in children with diabetes are limited, one study of 150 adolescents with T1D found positive screen for depression, anxiety or disordered eating in more than one third of participants, with depression alone in 11.3%.7 Depression in this population is associated with higher A1c values and decreased frequency of blood glucose checks.8 Therefore, support for self-management in children with T1D is reliant upon addressing mental health. Indeed, services provided by mental health professionals can help children with T1D improve their glycemic control and quality of life.9–12 Despite demonstrated importance, the prevalence of health psychology use in this population has not been well documented.
Further, the factors that predict use of health psychology resources are not well understood. Understanding factors that may influence health care use is facilitated by applying conceptual frameworks such as the Andersen Behavioral Model (Figure 1).13 This model proposes that use of health services is dependent upon individual and contextual characteristics. Individual characteristics are the attributes that may affect whether a person will seek care and include 3 categories: 1) predisposing, 2) enabling, and 3) need factors. Predisposing factors are those that affect an individual’s propensity to use health services, and in the case of mental health services may include demographics like age, sex, and race.14 Enabling factors are those that affect an individual’s access to services including health insurance, geographic factors, and education level. Need represents how an individual is living with illness and the extent to which illness affects his or her life, and how an individual would gain specific value through health service use. Need can be described using two categories: evaluated and perceived. Evaluated need factors are those that can be observed or realized by a health care team that suggest health service use is indicated. Perceived need factors represent an individual’s functional state and experience of health. Both can include details about illness, illness severity, or self-management. Contextual characteristics describe the environmental factors that may affect an individual’s use of health services and encompass the circumstances of health care access (e.g. the health care system).
Figure 1.
Andersen Behavioral Model of health service use adapted for health psychology service use in children with type 1 diabetes.
Understanding how these characteristics are associated with health psychology use in children with T1D will help identify potential barriers and facilitators of mental health support in this population. Thus, this study evaluated the prevalence of health psychology use in children with T1D and the association of this use with individual and contextual characteristics.
2. Material and Methods
2.1. Subjects
Eligible participants included youth and adolescents ages 8 to 16 years with T1D and their parents recruited from two multi-disciplinary diabetes clinics as part of a large clinical trial.15,16 Other inclusion criteria included T1D diagnosis for at least one year, fluency in English, and ability to provide informed consent (or assent for youth ages 14 years and younger). Human subjects research approval for the study was granted by the lead center’s Institutional Review Board.
2.2. Study design
In this cross-sectional research design, surveys were completed in either paper form or on an iPad upon enrollment. Parents completed survey questions on demographic information, T1D-related characteristics, and an assessment of their child’s health status. Adolescents (ages 13–17 years) and parents of children (8–12 years of age) or adolescents completed a validated instrument to assess self-management barriers specifically for these two age groups.15,17 Each participant’s most recent A1c value was abstracted from the medical record by one of two trained study team members.
2.3. Health psychology use
Parents reported the child’s use of health psychology services in the last year in response to a single yes/no survey item. Positive response indicated use of any health psychology service at least once in the last year.
2.4. Andersen Behavioral Model variables
Following the Andersen Behavioral Model,13 individual and contextual characteristics were defined to represent key constructs that may influence use of health psychology services in this study (Figure 1). Individual characteristics included 3 categories: 1) predisposing, 2) enabling, and 3) need factors. Predisposing factors were represented by demographics including age, constructed as either youth (age 8–12 years) or adolescent (age 13–16 years), sex, and race. Enabling factors were represented by health insurance type (public/private), distance traveled to diabetes clinic (continuous, analyzed as per 50 miles), parent education level (aggregated for analysis as 1=high school or less, 2=some college, 3=college graduate or more), and whether a child lives in multiple households (yes/no).
Need-based factors included both evaluated need and perceived need. Evaluated need was represented by glycemic control (A1c, continuous) as well as by parent report of a child’s diagnosis of depression or anxiety (yes/no). Perceived need was identified by parent and adolescent report of diabetes self-management barriers using PRISM: Problem Recognition in Illness Self-Management.
PRISM is a 32-item scale with demonstrated content, construct and discriminant validity that identifies up to six self-management barriers18 and can be found along with all the survey items for parents and for adolescents at https://www.hipxchange.org/PRISM. Item responses were on a 5-point Likert scale (1=strongly disagree; 5=strongly agree) where higher scores indicate greater perceived barrier. An average of 2 or more on barrier score represents the presence of the self-management barrier, based on prior work suggesting this cutoff is associated with both suboptimal glycemic control and clinically significant quality of life reduction.17,19
In this study, we included data for three self-management barriers as they suggest specific need for mental health support: 1) regimen pain and bother (reported by all parents and by adolescents), 2) denial of diabetes and its consequences (reported by all parents), and 3) family interactions (reported by parents of adolescents and by adolescents). This comprised 16 items from parents of adolescents and 10 items from adolescents and parents of children. An example item for regimen pain and bother is “My child feels that his/her regimen takes a lot of time and work,” and for denial of diabetes and its consequences, “My child tries to forget that he/she has an illness.” An example item for family interactions is “Our family gives my child a lot of support to help him/her follow his/her regimen.”17,19
Contextual characteristics in this study included the multi-disciplinary diabetes clinic in which a patient received diabetes care, or clinical site, because the sites represent different environments. For example, while both sites are academic centers with health psychology providers on their multidisciplinary diabetes teams, they differ in affiliations with insurers and managed care organizations as well as location (one site is located in an urban area, while the other site is situated in a smaller community).
2.5. Analyses
Descriptive statistics were used to examine characteristics of study participants and prevalence of health psychology use. Logistic regression assessed the association between health psychology use and each of the individual and contextual characteristics, reported as odds ratios and p values, with p<0.05 considered statistically significant apriori. Parzen’s median unbiased estimator was used to describe these associations if logistic regression models perfectly predicted relationships.20
3. Results
3.1. Predisposing and enabling factors: participant characteristics
Of 363 eligible participants, n=267 (74%) participated (Table 1) and were between ages 8 and 16 years old. Age groups (youth and adolescents) and sexes were equally represented, and racial minorities represented over 15% of the participants. The majority of participants had private health insurance (75.7%, n=202). The use of health psychology services was low among participants, with only 8.3% (n=22) of participants reporting use.
Table 1.
Participant and Parent Characteristics
| Youth (n = 135) | Adolescent (n = 132) | |
|---|---|---|
| Youth and adolescent characteristics | ||
| Age, years; mean (sd) | 10.8 (1.4) | 15.0 (1.1) |
| Female | 46.7 (63) | 47.0 (62) |
| Non-Hispanic, white | 83.7 (113) | 84.1 (111) |
| Public health insurance | 24.4 (33) | 23.5 (31) |
| Years since diagnosis; mean (sd) | 4.6 (2.7) | 6.1 (3.7) |
| Miles traveled to diabetes clinic; mean (sd) | 40.8 (36.2) | 36.1 (35.0) |
| Lives in more than one household | 20 (27) | 16.7 (22) |
| Insulin pump use | 48.2 (65) | 51.5 (68) |
| % A1c; mean (sd) | 8.6 (1.5) | 9.0 (1.8) |
| mmol/mol A1c; mean (sd) | 70.5 (16.4) | 74.9 (19.7) |
| Depression or anxiety | 11.9 (16) | 14.4 (19) |
| Parent characteristics | ||
| Age, years; mean (sd) | 40.5 (6.5) | 44.1 (5.6) |
| Mother | 88.2 (119) | 84.9 (112) |
| Non-Hispanic, white | 85.9 (116) | 89.4 (118) |
| Education level | ||
| High school or less | 19.3 (26) | 15.9 (21) |
| Some college | 38.5 (52) | 33.3 (44) |
| College graduate or more | 42.2 (57) | 50.8 (67) |
Values are given as % (n) unless stated.
Values may not add up to 100% due to rounding or non-response.
3.2. Evaluated need factors: glycemic control and mental health diagnoses
Only 16.3% (n=22) of youth ages 8–12 years had adequate diabetes control as defined by the ADA-recommended target of less than 7.5% (58 mmol/mol)21 compared to slightly higher proportion of adolescents (21.2%; n=28). Depression or anxiety diagnoses were reported in 13.1% (n=35) participants.
3.3. Perceived need factors: self-management barriers
Self-management barriers were commonly reported by parents and by adolescents, and prevalence varied by respondent group (Table 2). The majority (74%; n=97 of 131) of adolescents reported family interaction barriers, as did the majority of parents of adolescents (60.3%; n=79 of 131). Most parents of adolescents reported regimen pain and bother (70.2%; n=92 of 131). Only 42.7% of adolescents reported regimen pain and bother (n=56 of 131). Finally, most parents of adolescents (80.9%) and most parents of youth (78.5%) reported the barrier denial of diabetes and its consequences (n=106 of 131 and n=106 of 135, respectively).
Table 2.
PRISM self-management barrier prevalence and scores* by respondent type.
| Parents of Youth (n=135) | Parents of Adolescents (n=131) | Adolescents (n=131) | ||||
|---|---|---|---|---|---|---|
| % (n) | Score mean (sd) | % (n) | Score mean (sd) | % (n) | Score mean (sd) | |
| Regimen pain and bother | 68.9 (93) | 2.62 (0.90) | 70.2 (92) | 2.64 (0.80) | 42.7 (56) | 2.11 (0.79) |
| Denial of diabetes and its consequences | 78.5 (106) | 2.87 (0.84) | 80.9 (106) | 2.91 (0.88) | n/a | n/a |
| Family interactions | n/a | n/a | 60.3 (79) | 2.19 (0.55) | 74.0 (97) | 2.70 (0.86) |
Barrier score range 1 through 5. Barrier score ≥ 2 indicates presence of barrier.
3.4. Health psychology use by Andersen Behavioral Model factors
Among individual factors, the use of health psychology services was significantly associated with evaluated need and with perceived need. Specifically, participants with a diagnosis of depression or anxiety were over five times as likely to have used health psychology services in the past year, compared to participants without these diagnoses (OR 5.8; p<0.001). Also, health psychology use was significantly more likely when parents of adolescents endorsed self-management barriers related to family interactions (OR 8.25; p=0.047). Lastly, denial of diabetes and its consequences when reported by parents of youth and by parents of adolescents was positively associated with health psychology use (OR 8.84; p=0.034 and OR 9.32; p=0.020, respectively as calculated using Parzen’s median unbiased estimator20).
Use of health psychology services was not significantly associated with predisposing factors (age, sex, or race) or enabling factors (health insurance type, distance travelled to diabetes clinic, parent education level, or number of households). In addition, use of health psychology services was not significantly associated with contextual characteristics as represented by clinical site (Table 3).
Table 3.
Odds ratios and p values for the association of health psychology use with Andersen model constructs
| Odds Ratio | p value | |
|---|---|---|
| Site | 0.57 | 0.212 |
| Adolescent age group | 1.26 | 0.604 |
| Female | 1.16 | 0.740 |
| Non-Hispanic, white | 0.86 | 0.795 |
| Public health insurance | 1.91 | 0.168 |
| Distance to diabetes clinic | 0.68 | 0.392 |
| Parent education level | 0.82 | 0.482 |
| Lives in multiple households | 2.23 | 0.100 |
| A1c | 1.22 | 0.114 |
| Depression or anxiety | 5.81 | <0.001 |
| Self-management barriers | ||
| Regimen pain and bother | ||
| Parents of youth | 4.39 | 0.167 |
| Parents of adolescents | 2.26 | 0.309 |
| Adolescents | 2.00 | 0.259 |
| Denial of diabetes and its consequences | ||
| Parents of youth | 8.84 | 0.034 |
| Parents of adolescents | 9.32 | 0.020 |
| Family interactions | ||
| Parents of adolescents | 8.25 | 0.047 |
| Adolescents | 1.06 | 0.937 |
4. Discussion
Use of health psychology services was uncommon in this population of youth and adolescents with T1D, with fewer than 10% of participants reporting attending even one health psychology visit in the previous year. Both evaluated and perceived need for services were prevalent in this population, as more than 80% of participants had suboptimal glycemic control and many reported self-management barriers. While this result highlights a discrepancy between health psychology use and need factors, there was a positive association between both evaluated and perceived need and use. Specifically, use was associated with presence of mental health diagnoses (evaluated need), and parent-reported self-management barriers (perceived need). These findings suggest that both provider and parent recognition of need factors supports the delivery of mental health care to this population, as recommended by the ADA and ISPAD.
Perceived need as measured by barriers to self-management was prevalent in this population with the majority of respondents reporting at least one barrier. Although denial of diabetes and its consequences and family interaction barriers reported by parents were associated with use of health psychology services, neither barrier reported by adolescents was associated with use. This suggests that the impact of parental perceived need is greater than the impact of adolescent perceived need in generating use of health psychology services. Therefore, improving provider recognition of perceived need in adolescents, in addition to parents, could be an important step to improve the use of health psychology services.
In addition to perceived need by parents, evaluated need represented by the presence of a mental health diagnosis was positively associated with use of health psychology in the past year. Mental health diagnoses may increase recognition by provider or parent that health psychology services would be beneficial. The association between evaluated need and health psychology use suggests that recognition of need by parent or provider helps connect children with diabetes to mental health services. It may also suggest that routine screening for mental health problems has a role in connecting individuals with services as screening could lead to a mental health diagnosis. This association should be further explored in future studies.
Though mental health services have been shown to be effective in supporting self-management behaviors and quality of life in youth and adolescents with T1D,9–12 results from this study demonstrate low utilization of these services in this population. Few prior studies have evaluated mental health utilization in this population. One population based study from Ontario, Canada found that 40.4% (n=3,432 of 8,491) of adolescents with T1D had at least one mental health service appointment by late adolescence.22 The ADA recommends health psychology support be provided for all youth with behavioral self-care difficulties or frequent hospitalizations for diabetic ketoacidosis,23 yet fewer than 60% of diabetes clinics have regular health psychology services available.24 Access to mental health services is a barrier for many youth and adolescents with T1D, and this study shows that even in a population with health psychology services available in diabetes clinic, utilization rates are still low. In addition, given that many evidence-based psychological interventions to support T1D management require multiple visits, future studies of health psychology utilization could examine the actual number of visits as well. Undoubtedly, an even smaller proportion of our participants accessed multiple health psychology visits in the prior year.
This study has limitations that warrant discussion. Participants for this study were recruited from only two tertiary diabetes clinics, which may represent a limitation. However, the racial makeup, rates of mental health diagnoses, and glycemic control of the participant group is comparable to the national population of children with T1D, suggesting generalizability of study findings.4,5,7,25 Further, our assessment of whether contextual factors are associated with health psychology use was limited by only having one such factor (site) to evaluate in this study using secondary data. Another potential limitation is the use of self-reported data that are not independently verifiable. This method was chosen for health psychology use because these services may not be provided within the health care system making utilization reporting a challenge. Some psychology services are provided through the school district or through private psychology clinics which would not be documented in the medical record. Therefore, self-report was selected to capture any services families considered supportive for mental health. Depression and anxiety diagnoses were also self-reported, but rates were comparable to those previously reported.7 Finally, this study identified associations between factors and health psychology use, however causality cannot be conferred from these relationships due to the cross-sectional study design. Future studies are needed to evaluate causal pathways between such factors and the utilization of mental health services in this population.
5. Conclusion
To improve physical and mental health outcomes in children with T1D, it is important to understand and address the low prevalence of health psychology service use in this population. While many children are not accessing health psychology services at all, even those that do may not receive complete evidence-based health psychology intervention. In addition to mental health diagnoses, the presence of self-management barriers could be used to prompt referrals to health psychology. Future studies will examine how health psychology referrals are associated with use and with individual and contextual characteristics.
Acknowledgements
Funding:
This work was supported by Patient-Centered Outcomes Research Institute (PCORI) Award [IH-1304-6279] and by the National Institutes of Health (NIH) Postdoctoral Fellowship Grant [T32 DK077586-06A1].
Footnotes
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Conflict of Interest:
The authors have no conflicts of interest to declare.
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