The Journal of Allergy and Clinical Immunology
Volume 122, Issue 3 , Pages 490-495, September 2008

Negative affect, medication adherence, and asthma control in children

  • Bruce Bender, PhD

      Affiliations

    • Department of Pediatrics, National Jewish Medical and Research Center, Denver, Colo
    • Corresponding Author InformationReprint requests: Bruce G. Bender, PhD, Professor and Head, Pediatric Behavioral Health, National Jewish Medical and Research Center, 1400 Jackson St, Denver, CO 80206.
    • ,
  • Lening Zhang, PhD

      Affiliations

    • Department of Biostatistics and Bioinformatics, National Jewish Medical and Research Center, Denver, Colo

Received 9 January 2008; received in revised form 23 May 2008; accepted 28 May 2008. published online 07 July 2008.

Article Outline

Background

Negative affect including depression is known to be associated with asthma control, but whether and how it influences control in children with asthma is not understood.

Objective

The objective of this investigation was to evaluate whether negative affect and medication nonadherence each predict decreased symptom control, and whether the relationship between negative affect and disease control is explained by children's adherence to asthma medications.

Methods

Participants included 104 children 8 to 18 years old being treated with an inhaled corticosteroid delivered by metered-dose inhaler for asthma diagnosed by their health care providers. Children and parents independently rated asthma symptoms and completed questionnaires assessing sad and anxious affect. Electronic devices were attached to each participant's metered-dose inhaler to measure adherence. At study completion, records were collected to confirm reports of health events.

Results

Both child and parent negative affect scores predicted symptom scores, whether reported by child or parent, and child negative affect scores predicted school absence because of asthma. In a lagged analysis taking into account time sequence, medication adherence predicted prednisone bursts but not subjective symptom scores. Nonadherence did not explain the relationship between negative affect and symptom scores, but parent negative affect predicted prednisone bursts even when controlling for level of adherence.

Conclusion

Although both negative affect and adherence were predictive of asthma control, the relationship of each to asthma control was distinctly different. Accuracy of symptom perception may be influenced by patient and parent affect characteristics.

Key words: Asthma, control, children, affect, adherence

Abbreviations used: CDI, Children's Depression Inventory, CES-D, Center for Epidemiologic Studies Depression Scale, ED, Emergency department, ICS, Inhaled corticosteroid, MDI, Metered-dose inhaler, RCMAS, Revised Children's Manifest Anxiety Scale

 

Both emotional distress and treatment nonadherence can undermine asthma control. Emotional distress is frequently encountered in patients with asthma.1, 2 Increased rates of depression have been reported among children,3, 4 adolescents,5, 6 and adults1, 7, 8, 9 with asthma. Increased anxiety and depression have been linked with decreased quality of life in patients with asthma,6, 10, 11 but only depression has been associated with declining control and increased risk of death in children with asthma.12, 13, 14, 15

Treatment nonadherence is common in patients taking controller medication for their asthma and may also lead to decreased control and increased use of emergent care services.16, 17 Adherence declines further in patients with asthma who are depressed.18, 19, 20 This finding has fostered the hypothesis that depression and negative affect lead to decreased symptom control because distressed patients are less consistent in taking their controller medication.7, 21, 22 However, most studies linking negative affect to nonadherence have not addressed the question of whether an association between patient negative affect and symptom control also exists and is explained by level of adherence. One study found that adherence failed to account for the association between disease severity and depression, although an objective measure of adherence was not included.23 Few investigations have examined the relationship between negative affect and adherence in children. Data included in this report are from a larger study that sought to determine the most accurate methods for assessing adherence to asthma medications.24 The current report examined whether negative affect and medication nonadherence each predict decreased symptom control, and whether the relationship between negative affect and disease control is explained by children's adherence to asthma medications.

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Methods 

Patient visits 

One hundred four participants were recruited through advertising and referrals from multiple practices and clinics in the Denver area and met the following inclusion criteria: age 8 to 18 years with a current diagnosis of asthma by a health care provider who prescribed an inhaled corticosteroid (ICS) delivered by metered-dose inhaler (MDI), otherwise in good general health including no significant learning or psychological problems that might interfere with study participation. One parent from each family was required to participate with the child. Informed consent was obtained from parents and children 18 years of age, and informed assent was obtained from children under age 18 years. Each family attended a baseline visit followed by 4 monthly visits.

Adherence measurement 

The 4-month study period was designed to provide an interval sufficient to document adherence over time. Because inaccurate adherence assessment can bias outcomes, adherence was assessed with an objective, electronic tracking device. An MDILog (WestMed, Englewood, Colo) or Doser (Meditrack, Hudson, Mass), previously determined to provide more accurate assessment of medication adherence than patient self-reports,24 was attached to each participant's MDI as the source of adherence data. All devices were tested for accuracy before and after each monthly visit.

Negative affect measurements 

At the baseline visit, affect questionnaires were completed by parents and children in separate interview rooms. Parents completed the Center for Epidemiologic Studies Depression Scale (CES-D).25 The CES-D consists of 20 items (4 positive and 16 negative) and has been shown to correlate well with interview assessments of depression.26, 27 Children completed the Revised Children's Manifest Anxiety Scale (RCMAS)28 and the Children's Depression Inventory (CDI).29 The RCMAS consists of 28 Anxiety items and 9 Lie (social desirability) items, all of which are answered yes or no. Substantial research confirms the validity of the RCMAS30, 31, 32 as a measure of chronic anxiety in children. The CDI, a downward extension of the Beck Depression Inventory, measures self-rated assessment of depressive symptoms in children and adolescents with 27 items rating depressive symptoms on a scale from 0 (no symptoms) to 2 (definite symptoms). Reliability and validity are well established.33, 34, 35

Healthcare event and symptom monitoring 

At each monthly visit, children and parents were queried separately about health care encounters because of asthma and about asthma symptoms in the past 2 weeks. Six symptom questions commonly used to assess asthma control36, 37, 38 were asked about wheezing, tightness of chest, shortness of breath, coughing from exercising, coughing from other causes, and nighttime symptoms. Parents were also queried about health events in the past month including school absences, prednisone bursts, emergency department (ED) visits, and hospitalizations. At the end of study participation, medical records were collected from the child's physician to confirm reports of health events including prednisone bursts, ED visits, and hospitalizations.

This study was approved by the Institutional Review Board at National Jewish Medical and Research Center.

Data analysis 

All statistical analyses were conducted with the SAS statistical analysis package (version 9.1; SAS Institute Inc, Cary, NC). Individual adherence scores represent the percent of prescribed medication that was taken during the study interval. Percent adherence was determined by dividing the number of puffs taken by the total number prescribed for each day. Each participant's adherence score represented average daily adherence over the previous month.24 Composite symptom scores were calculated by summing the individual symptom scores from the 6 self-report questions from child and parent questionnaires. Individual symptom scores ranged from 0 to 4; hence, the composite symptom scores ranged from 0 to 24. Each participant's score represents a composite of these scores at each time point. The Student t test was used to compare adherence across different age groups. An ANOVA model was used to compare adherence across different sex, race, and smoking groups. Very few hospitalizations occurred during the course of the study, and therefore, this variable was not included in the analyses. When examining the relationships among negative affect, adherence, and asthma control, measures from each of the 4 time points were used with the exception of negative affect, which was measured only at baseline. Two types of regression models were used, each of which can accommodate both the correlations from within a subject because of repeated measurements as well as between different subjects: (1) a mixed effects model was used when composite symptom scores were the outcome variable, with the predictor variable consisting of each of the negative affect scores (parent depression and child anxiety and depression, each tested in separate models); (2) a generalized estimating equation model was used when ED visit, missed school days, or prednisone burst was the outcome variable and negative affect was the predictor variable. A binomial distribution and a logit link function were used for the generalized estimating equation model. To examine whether medication adherence in one 2-week interval can predict symptom scores in the following 2-week interval (Fig 1), a lagged analysis was performed by using a mixed effects model in which symptom scores were used as the outcome variable and adherence as the predictor. Both adherence and negative affect were included as predictor variables in the lagged regression model when testing for the effect of adherence on the relationship between negative affect and indices of asthma control. Numerous studies have demonstrated that child age, smoking in the household, and race are associated with treatment adherence and symptom control.29, 39, 40 Therefore, although adherence differences emerged here only for smoking, all 3 variables were included as covariates in all analyses. For all analyses, 2-tailed tests were used, and P values less than .05 were designated as statistically significant.

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Results 

Demographic and adherence profile of participants 

Age, sex, race, and smoking household frequencies and their associated medication adherence levels are seen in Table I. Mean adherence rates did not differ significantly by age, sex, or race, although trends suggested that white and other participants were more adherent than black or Hispanic participants. Mean adherence was significantly lower for children in households with a smoking adult in contrast with nonsmoking households. The average rate of adherence across all participants was 40% (SD = 23.4%). No children were excluded from this study because of significant learning or psychological problems. Summary statistics on adherence, negative affects, and symptom scores across the four 1-month periods are shown in Table II.

Table I. Demographic and adherence characteristics of participating children
FrequencyMean adherenceSDP value from t test∗ or ANOVA model†
Age (y)
5-115040.923.4.598
12-165438.523.5
Sex
Male5641.823.1.323
Female4837.223.7
Race
White3944.325.8.226
Black2734.219.2
Hispanic2235.223.6
Other1643.922.3
Smoking in household
No7742.425.4.045
Yes2731.914.2
All participants10439.723.4

∗Student t test was performed for age group comparison.

†ANOVA model was used for sex, race, and smoking group comparisons.

Table II. Summary statistics on adherence, negative affect, and symptom variables
VariableMonthMeanSD
Medication adherence (%)
147.3925.56
239.9626.29
337.9127.51
435.9227.96
Negative affect measures
Child depression score (CDI)Baseline8.366.40
Child anxiety score (RCMAS)Baseline10.986.96
Parent depression score (CES-D)Baseline11.879.19
Self-reported symptom scores
Child-reported composite symptom scoresBaseline12.954.43
110.543.71
210.944.29
311.004.18
410.574.26
Parent-reported composite symptom scoresBaseline12.104.17
110.824.33
211.154.45
310.593.92
411.004.40

Negative affect was measured only at baseline.

Negative affect and asthma control 

Child and parent emotional distress may influence the child's asthma morbidity. To determine specifically whether negative affect can predict asthma control, the relationships between affect scores and control measures were examined separately for subjective reporting of symptoms and objective health events including prednisone bursts, ED visits, and school absence. Negative affect scores from the measures of parent and child depression and child anxiety were distributed with a wide range. Less than 5% of the child anxiety (greater than 1830, 31, 32) or depression scores (greater than 1933, 34, 35) were significantly elevated, although 22% of parent CES-D depression scores were elevated into the clinically significant range (scores greater than 1925). Results showed that the measures of child depression and anxiety (CDI and RCMAS) and the parent depression measure (CES-D) predicted the composite symptom score when symptoms were reported by either the child or the parent (Fig 2). Thus, higher negative affect scores were associated with reports of more frequent symptoms. Table III indicates that child anxiety and depression scores were significant predictors of missed school days; as scores increased, children were more likely to miss school. The parent depression score did not significantly predict any of the health event endpoints, although the relationship between CES-D and ED visits was significant at the α = 0.10 level (P = .075; Table III).

  • View full-size image.
  • Fig 2. 

    Associations between negative affects and child or parent self-reported symptom scores. The predictive effect of negative affects on child (A) or parent (B) self-reported composite symptom scores are shown by the regression lines from longitudinal data analyses. In the regression models, one of the negative affects was used as the predictor variable and self-reported symptom score as the outcome variable, controlling for age, smoking status, and ethnicity. Plots shown are for white nonsmokers at the age of 11.75 years (mean age for the study population).

Table III. Prediction of health care events from negative affect scores
95% Confidence limits
Predictor variableOutcome variableOdds ratioLowerUpperP value
Child self-rating
Depression (CDI)ED visit because of asthma1.0340.9361.142.5079
School absence because of asthma1.0651.0061.127.0297
Prednisone burst1.0620.9661.168.2126
Anxiety (RCMAS)ED visit because of asthma1.0800.9611.214.1941
School absence because of asthma1.0681.0041.136.0372
Prednisone burst1.0330.9631.108.3674
Parent self-rating
Depression (CES-D)ED visit because of asthma1.0610.9941.132.0752
School absence because of asthma1.0280.9851.072.2097
Prednisone burst1.0950.9731.231.1317

Medication adherence and asthma control 

One potential explanation for the relationship between negative affect and indices of control is that adherence declines in response to negative affect, which in turn causes a decrease in disease control. To test this possibility, the relationship between adherence and disease control was first examined for symptom reports and objective health events including prednisone bursts, school absences, and ED visits.

Results showed that adherence was not significantly associated with either child-reported (P = .96) or parent-reported symptoms (P = .32). For health event endpoints, lower adherence was significantly associated with increased chance of prednisone burst (odds ratio [95% confidence limit] = 0.976 [0.956, 0.996]; P = .019). Patient reports and medical record indicators of prednisone bursts and ED visits were in 92% agreement.

Adherence was added to the model to test whether an association between negative affect and asthma symptom control was accounted for by level of adherence. Adherence level did not change the significant association between negative affect and subjectively reported symptom control except for the association between the parent depression score and child-reported symptom (P value changed from .003 to .064). Adherence was not a significant predictor in any of these models. For objective measures of asthma control, adding adherence to the model did not change any predictors from significant to nonsignificant. Child depression and anxiety scores continued to predict missed school days when controlling for adherence. Further, decreasing adherence continued to predict prednisone burst even when a negative affect variable was included in the model (data not shown). In summary, adherence predicted prednisone bursts but did not account for the significant correlations between negative affect and subjective and objective symptom controls.

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Discussion 

On average, participants in this study used less than 40% of their prescribed ICS. Although this finding is consistent with other studies using an objective measure of adherence in pediatric patients with asthma,41, 42, 43, 44, 45, 46, 47, 48 most studies of adherence in children with asthma have not tested whether adherence predicts control, and none have directly tested whether an association between affect and control exists and is explained by level of adherence. Recognizing both that adherence can vary over time and that the impact of anti-inflammatory medication on symptom control is not immediate, a lagged analysis was used to examine the relationship between medication adherence in one 2-week period and symptom control in the following 2-week period. This lagged analysis, which has not be used in previous adherence studies but is designed to take into account the time delay between medication use and symptom control, revealed that nonadherence undermined asthma control; as adherence declined, frequency of prednisone bursts increased. A small number of studies have examined the relationship of medication adherence to symptom control in asthma, primarily through administrative databases that did not separate adult and child patient groups. For example, 1 health maintenance organization study demonstrated that decreased prescription refilling was associated with poorly controlled asthma including increased oral steroid use and ED visits.16 In a small study of children with asthma, the mean level of ICS adherence was lower in the group with uncontrolled asthma requiring oral steroid than in the group not requiring treatment escalation.49

In the current study, negative affect consistently predicted increased child-reported and parent-reported symptoms independently of treatment adherence. In adults, depression associated with asthma is common, with lifetime occurrence in as many as half of patients with asthma11, 39, 40 and recent depression in 31% of adolescents with asthma.5 Increasing levels of depression have been associated with greater airway obstruction50 and increased use of EDs, hospitals, and unscheduled appointments for asthma.11, 51 Limited evidence suggests that depression in adults with asthma may produce physiological changes, such as dysregulation of cholinergic pathways52, 53, 54 or neuroendocrine systems,50 that result in worsening of symptoms. A second potential causal explanation for the relationship between negative affect and disease outcomes is that depression may cause medication nonadherence because patients feel fatigued and hopeless and are therefore unable to manage their asthma adequately.55 In 1 study of adults, higher levels of depressive symptoms were associated with an 11.4-fold increase in the risk of low medication adherence.18 However, neither explanation adequately accounts for the findings in this study. Given the relatively infrequent elevated depression scores in the children with asthma in this study, a direct physiological effect of depression on their asthma is unlikely. Further, a behavioral explanation for the connection between emotions and poor outcomes was not supported by the data; medication nonadherence did not account for the relationship between negative affect and decreased symptom control.

An alternative explanation for the association between mood and symptom scores is that subjective reporting of symptoms is influenced by the emotional state of the respondent such that as individuals feel more distressed they are more likely to report asthma symptoms, while those patients whose emotional state is more positive are less likely to perceive their asthma as problematic or burdensome. Patients with diabetes who were also depressed incurred a higher number of physician office visits and hospital/ED visits and filled more prescriptions than patients without depression with similar levels of disease severity.56 Reports of increased asthma burden were more likely to occur when parents reported increased anxious and depressive symptoms and when children reported more anxious symptoms.57 Adults with epilepsy who produced higher scores on a measure of optimism were more likely to perceive their illness as well controlled.58 In the current study, the finding that prednisone burst, an indicator of decreased asthma control that is more objective than symptom perception, was predicted by adherence but not by any measure of negative affect supports the interpretation that negative affect may change perception of symptoms without altering the disease severity itself. Similarly, school absence, an asthma-related event that was associated with the child's affect but not adherence, results from a decision by parent and child that may reflect more about the affective state of both than actual disease activity. That is, distressed children may be quicker to seek to stay home from school even in the face of relatively mild symptoms.

Results from this study must be interpreted with consideration to its limitations. First, the choice of instruments to measure affect or disease activity other than those used here may have produced a different picture of the affect-adherence-symptom relationship. These results cannot determine whether daily diary card recording of asthma symptoms is influenced by negative affect to the same degree as recall of symptoms over a period of days, weeks, or months. Future investigations will be strengthened by the use of standardized asthma control questionnaires, not commonly used at the time this study was reviewed for funding by the National Heart, Lung, and Blood Institute. Second, most patients did not have severe illness, and hence, frequency of hospitalizations was insufficient for analysis. Third, the 2-week interval chosen for the lagged analysis may not have been optimal to evaluate the mutual response between symptoms and medication adherence. Fourth, most of our pediatric participants were not depressed; the relationships between depression, adherence, and disease control may be different in a population of clinically depressed patients. Fifth, β-agonist use is likely affected when ICS adherence declines, but it was not measured here. Nonetheless, results from this study establish that medication nonadherence and negative affect may each contribute to inadequate asthma control in children and that reporting of asthma symptoms may be influenced by parent and child affective states to a degree that introduces significant bias when patient symptom reporting is a primary endpoint in clinical trials. The determination of whether asthma symptoms reported by parents and children are distorted by a perceptual filter determined by their affective state, or are accurate reflections of disease activity triggered by emotions, requires further research with larger samples of patients of varying disease severity. Additional understanding can be gained by investigations that treat depression in patients with asthma, assessing disease-related changes while controlling for level of adherence.

Clinical implications

Nonadherence remains a significant threat to successful asthma treatment and must be addressed in follow-up visits. Accurate reporting of asthma symptoms may be influenced by the emotional state of the child and parent.

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References 

  1. Scott K, Von Korff M, Ormel J, Zhang M, Bruffaerts R, Alonso J, et al. Mental disorder among adults with asthma: results from the World Mental Health Survey. Gen Hosp Psychiatry. 2007;29:123–133
  2. Goodwin R, Jacobi F, Thefeld W. Mental disorders and asthma in the community. Arch Gen Psychiatry. 2003;60:1125–1130
  3. Padur J, Rapoff M, Houston B, Barnard M, Danovsky M, Olson N, et al. Psychosocial adjustment and he role of functional status for children with asthma. J Asthma. 1995;32:345–353
  4. Goodwin R, Eaton W. Asthma, suicidal ideation, and suicide attempts: findings from the Baltimore epidemiologic catchment area follow-up. Am J Public Health. 2005;95:717–722
  5. Bender B, Long A, Parasuraman B, Vu Tran Z. Factors influencing patient decisions about the use of asthma controller medication. Ann Allergy Asthma Immunol. 2007;98:322–328
  6. Goodwin R, Fergusson D, Horwood L. Asthma and depressive and anxiety disorders among young persons in the community. Psychol Med. 2004;34:1465–1474
  7. Bender B. Risk taking, depression, adherence, and symptoms control in adolescent and young adults with asthma. Am J Respir Crit Care Med. 2006;173:953–957
  8. Goodwin R, Olfson M, Shea S, Lantigua RA, Carrasquilo O, Gameroff MJ, et al. Asthma and mental disorders in primary care. Gen Hosp Psychiatry. 2003;25:479–483
  9. Ettinger A, Reed M, Cramer J. Depression and comorbid community-based patients with epilepsy or asthma. Neurology. 2004;63:1008–1014
  10. Annett R, Bender B, Lapidus J, DuHamel T, Lincoln A. Predicting children's quality of life in an asthma clinical trial: what do children's reports tell us?. J Pediatr. 2001;139:854–861
  11. Mancuso C, Peterson M, Charlson M. Effects of depressive symptoms on health-related quality of life in asthma patients. J Gen Intern Med. 2000;15:301–310
  12. Bartlett S, Krishnan J, Riekert K. Maternal depressive symptoms and adherence to therapy in inner-city children with asthma. Pediatrics. 2004;113:229–237
  13. Miller B, Wood B. Psychophysiologic reactivity in asthmatic children: a cholinergically mediated confluence of pathways. J Am Acad Child Adolesc Psychiatry. 1994;33:1236–1245
  14. Strunk R, Mrazek D, Wofson Fuhrmann G, LaBrecque J. Physiological and psychological characteristics associated with deaths from asthma in childhood: a case-controlled study. JAMA. 1985;254:1193–1198
  15. McQuaid E, Kopel M, Nassau J. Behavioral adjustment in children with asthma: a meta-analysis. Devel Behav Pediatr. 2001;22:430–439
  16. Williams LK, Pladevall M, Xi H, Peterson EL, Joseph C, Lafata J, et al. Relationship between adherence to inhaled corticosteroids and poor outcomes among adults with asthma. J Allergy Clin Immunol. 2004;114:1288–1293
  17. Bender B. Nonadherence to asthma treatment and failure of therapy. Curr Opin Pediatr. 1997;9:590–595
  18. Smith A, Krishnan J, Bilderback A, Riekert K, Rand C, Bartlett S. Depressive symptoms and adherence to asthma therapy after hospital discharge. Chest. 2006;130:1034–1038
  19. Cluley S, Cochrane G. Psychological disorder in asthma is associated with poor control and poor adherence to inhaled steroids. Respir Med. 2001;95:37–39
  20. Baiardini I, Braido F, Giardini A, Majani G, Cacciola C, Rogaku A, et al. Adherence to treatment: assessment of an unmet need in asthma. J Investig Allergol Clin Immunol. 2006;16:315–325
  21. Wing R, Phelan S, Tate D. The role of adherence in mediating the relationship between depression and health outcomes. J Psychosom Res. 2002;53:877–881
  22. Ziegelstein R, Fauerback J, Romanelli J. Patients with depression are less likely to follow recommendations to reduce cardiac risk during recovery from a myocardial infarction. Arch Intern Med. 2000;160:1818–1823
  23. Wood B, Millder B, Lim J, Lillis K, Ballow M, Stern T, et al. Family relational factors in pediatric depression and asthma: pathways of effect. J Am Acad Child Adolesc Psychiatry. 2006;45:1494–1502
  24. Bender B, Bartlett S. Impact of interview mode on accuracy of child and parent report of adherence with asthma-controller medication. Pediatrics. 2007;120:e471–e477
  25. Radloff L. The CES-D scale: a self-report depression scale for research in the general population. Appl Psychol Meas. 1977;1:385–401
  26. Hopkinson J, Neuringer A. Modifying behavioral variability in moderate depressed students. Behav Modif. 2003;27:51–264
  27. Radloff L, Locke B. The Community Mental Health Assessment Survey and the CES-D scale. In:  Weissman M,  Myers J,  Ross C editor. Community surveys of psychiatric disorders. Newark (NJ): Rutgers University Press; 1986;p. 177–189
  28. Reynolds C, Richmond B. Revised Children's Manifest Anxiety Scale (RCMAS). Los Angeles: Western Psychological Services; 1985;
  29. Kovacs M. Rating scales to assess depression in school aged children. Acta Paedopsychiatr. 1981;46:305–318
  30. Reynolds C. What I think and feel: a revised measure of children's manifest anxiety. J Abnorm Psychol. 1978;6:271–280
  31. Reynolds C, Richmond B. Concurrent validity of what I think and feel: the Revised Children's Manifest Anxiety Scale. J Consult Clin Psychol. 1980;48:774–775
  32. Reynolds C. Long-term stability of scores on the Revised Children's Manifest Anxiety Scale. Percept Mot Skills. 1981;53:702
  33. Kovacs M, Beck A. An empirical-clinical approach toward a definition of childhood depression. In:  Raskin JGSA editors. Depression in childhood: diagnosis, treatment, and conceptual models. New York: Raven Press; 1977;p. 1–25
  34. Kazdin A, Petti T. Self-report and interview measures of childhood and adolescent depression. J Child Psychol Psychiatry. 1982;23:437–457
  35. Kovacs M. The Children's Depression Inventory. Psychopharmacol Bull. 1985;21:995–998
  36. NHLBI . Expert Panel Report 2: guidelines for the diagnosis and management of asthma. Washington (DC): US Department of Health and Human Services; 1997;
  37. Schatz M, Mosen D, Apter A, Zeiger R, Vollmer W, Stibolt T, et al. Relationships among quality of life, severity, and control measures in asthma: an evaluation using factor analysis. J Allergy Clin Immunology. 2005;115:1049–1055
  38. Nathan R, Sorkness C, Kosinski M, Schatz M, Li J, Marcus P, et al. Development of the asthma control test: a survey for assessing asthma control. J Allergy Clin Immunol. 2004;113:59–65
  39. Brown E, Khan D, Nejtek V, Thomas N, Mahadi S. Depressive symptoms and functioning in asthma patients. Prim Care Psychiatry. 2000;6:155–161
  40. Afari N, Schmaling K, Barnhart S, Buchwald D. Psychiatric comorbidity and functional status in adult patient with asthma. J Clin Psychol Med Settings. 2001;8:245–252
  41. Jonasson G, Carlsen KH, Mowinckel P. Asthma drug adherence in a long term clinical trial. Arch Dis Child. 2000;83:330–333
  42. Bartlett S, Lukk P, Butz A, Lampros-Klein F, Rand C. Enhancing medication adherence among inner-city children with asthma: results from pilot studies. J Asthma. 2002;39:47–54
  43. Bender B, Annett R, Ikle D, DuHamel T, Rand C, Strunk R. Relationship between disease and psychological adaptation in children in the Childhood Asthma Management Program and their families. Arch Pediatr Adolesc Med. 2000;154:706–713
  44. Walders N, Kopel SJ, Koinis-Mitchell D, McQuaid EL. Patterns of quick-relief and long-term controller medication use in pediatric asthma. J Pediatr. 2005;146:177–182
  45. McQuaid E, Kopel S, Klein R, Fritz G. Medication adherence in pediatric asthma: reasoning, responsibility, and behavior. J Pediatr Psychol. 2003;28:323–333
  46. O'Conner S, Bender B, Gavin-Devitt L, Wamboldt M, Milgrom H, Szefler S, et al. Measuring adherence with the Doser CT in children with asthma. J Asthma. 2004;41:663–670
  47. Gibson N, Ferguson A, Aitchison T, Paton J. Compliance with inhaled asthma medication in preschool children. Thorax. 1995;50:1274–1279
  48. Coutts JA, Gibson NA, Paton JY. Measuring compliance with inhaled medication in asthma. Arch Dis Child. 1992;67:332–333
  49. Milgrom H, Bender B, Ackerson L, Bowry P, Smith B, Rand C. Non-compliance and treatment failure in children with asthma. J Allergy Clin Immunol. 1996;98:1051–1057
  50. Allen G, Hickie I, Gandevia S, McKenzie D. A possible link between depression and unexplained ventilatory failure in asthmatic patients. Thorax. 1994;49:881–884
  51. Eisner M, Katz P, Lactao G, Iribarren C. Impact of depressive symptoms on adult asthma outcomes. Ann Allergy Asthma Immunol. 2005;94:566–574
  52. Carr RE, Lehrer PM, Hochron SM, Jackson A. Effect of psychological stress on airway impedance in individuals with asthma and panic disorder. J Abnorm Psychol. 1996;105:137–141
  53. Lehrer P, Hochon S, Carr R, Edelberg R, Hamer R, Jackson A, et al. Behavioral induced bronchodilation in asthma during active and passive tasks: a possible cholinergic link to psychologically induced airway changes. Psychosom Med. 1996;58:413–422
  54. Miller B, Wood B. Influence of specific emotional states on autonomic reactivity and pulmonary function in asthmatic children. J Am Acad Child Adolesc Psychiatry. 1997;36:669–677
  55. Wing R, Phelan S, Tate D. The role of adherence in mediating the relationship between depression and health outcomes. J Psychosom Res. 2002;53:877–881
  56. Kalsekar I, Madhavan S, Amonkar M, Scott V, Douglas S, Makela E. The effect of depression on health care utilization and costs in patients with type 2 diabetes. Manag Care Interface. 2006;19:37–38
  57. Price M, Bratton D, Klinnert M. Caregiver negative affect is a primary determinant of caregiver report of pediatric asthma quality of life. Ann Allergy Asthma Immunol. 2002;89:572–577
  58. Pais-Ribeiro J, da Silva A, Meneses R, Falco C. Relationship between optimism, disease variables, and health perception and quality of life in individuals with epilepsy. Epilepsy Behav. 2007;11:33–38

 Supported by General Clinical Research Centers grant M01-RR00051 and National Heart, Lung, and Blood Institute grant 5R01HL64199.

 Disclosure of potential conflict of interest: B. Bender has received research support from the National Heart, Lung, and Blood Institute, AstraZeneca, and Sepracor. L. Zhang has declared that she has no conflict of interest.

PII: S0091-6749(08)01011-7

doi:10.1016/j.jaci.2008.05.041

The Journal of Allergy and Clinical Immunology
Volume 122, Issue 3 , Pages 490-495, September 2008

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