PEDIATRICS Vol. 121 No. 4 April 2008, pp. e961-e966 (doi:10.1542/peds.2007-1690)
ARTICLE |
One-Month Adherence in Children With New-Onset Epilepsy: White-Coat Compliance Does Not Occur
a Department of Pediatrics, Division of Behavioral Medicine and Clinical Psychology
b Department of Pediatrics, Division of Neurology, Cincinnati Children's Hospital Medical Center, Cincinnati, Ohio
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ABSTRACT |
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 TOP ABSTRACT METHODSRESULTSDISCUSSIONREFERENCES |
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OBJECTIVES. Adherence to antiepileptic drug therapy plays an important role in the effectiveness of pharmacologic treatment of epilepsy. The purpose of this study was to use an objective measure of adherence to (1) document patterns of adherence for the first month of therapy for children with new-onset epilepsy, (2) examine differences in adherence by demographic and epilepsy variables, and (3) determine whether treatment adherence improves for a short time before a clinic visit (eg, "white-coat compliance").
METHODS. Participants included 35 children with new-onset epilepsy (mean age: 7.2 years; 34% female; 66% white) and their caregivers. Children had a diagnosis of partial (60%), generalized (29%), or unclassified (11%) epilepsy. Adherence to treatment was electronically monitored with Medication Event Monitoring System TrackCap, starting with the first antiepileptic drug dose. Adherence was calculated across a 1-month period and for the 1, 3, and 5 days before and 3 days after the clinic appointment.
RESULTS. Adherence for the first month of treatment in children with new-onset epilepsy was 79.4%. One-month adherence was higher in children of married parents and those with higher socioeconomic status but did not correlate with child's gender, age, epilepsy type, prescribed medication, seizure frequency, or length of time since seizure onset. Adherence across the entire 1-month period was not different from adherence for the 1, 3, or 5 days before or 3 days after the clinic visit.
CONCLUSIONS. Poor adherence seen for children with new-onset epilepsy during the first month of antiepileptic drug therapy is a cause for concern. Several demographic variables influence adherence to treatment, whereas the proximity to a clinic visit does not. Additional studies are needed to document whether this trend continues longitudinally and determine the clinical impact of poor adherence.
Key Words: compliance • pediatric • electronic monitoring • seizures • longitudinal design • MEMS TrackCaps
Abbreviations: AED—antiepileptic drug • MEMS—Medication Event Monitoring System • SES—socioeconomic status • NS—not significant • TDM—therapeutic drug monitoring
Although adherence to antiepileptic drugs (AEDs) plays an important role in drug response, no study has objectively and reliably measured adherence in a cohort of children with new-onset epilepsy. Poor adherence to the epilepsy treatment regimen is likely one important contributor to continued seizures, which is evidenced by data suggesting that 32% of adults reported having seizures after missing a dose of medication1 and the association of nonadherence with higher seizure frequency in adults with epilepsy.2 Nonadherence estimates in pediatric epilepsy range from 14% to 43% on the basis of the measurement method (eg, self-report, blood levels)3–7; however, these methods have shown to be unreliable compared with more objective measurement methods, such as electronic monitoring.8–12 No studies in pediatric epilepsy have used objective methods, such as electronic monitors, to determine adherence to AED therapy.
Improved adherence to treatment that occurs for a short time before a clinic visit is known as "white-coat compliance," which has been noted in adult chronic populations with illness. For example, Cramer et al 13 reported that adherence was significantly higher 5 days before and after a clinic visit for 20 adults with epilepsy. Mean adherence was 88% for these days and 73% 1 month after the appointment, suggesting that white-coat compliance exists for this population; however, there are no studies to date documenting white-coat compliance in pediatric populations, such as epilepsy. White-coat compliance may be especially salient for patients with epilepsy because blood levels are frequently measured at clinic visits to assist in making clinical decisions. When patients take their AEDs inconsistently during the 3 to 4 days before the clinic visit, the clinician's ability to interpret serum blood levels is compromised. As a result, suboptimal clinical decisions on how to adjust medication dosages can lead to increased adverse effects or seizures.
The purpose of this study was to use an objective measure of adherence, Medication Event Monitoring System (MEMS) TrackCaps, to (1) document patterns of adherence for the first month of therapy for children with new-onset epilepsy, (2) examine differences in adherence by demographic and epilepsy variables, and (3) determine the level of white-coat compliance in this pediatric population. It was hypothesized that adherence would be relatively high (eg, >90%) during the titration period. Previous literature in pediatric adherence14–17 suggested that socioeconomic status would be significantly related to adherence. Finally, it was hypothesized that on the basis of the adult epilepsy literature, white-coat compliance would be observed in pediatric epilepsy.
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METHODS |
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TOPABSTRACTMETHODSRESULTSDISCUSSIONREFERENCES |
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Participants
Study participants included 35 children who had new-onset epilepsy and were between the ages of 2 and 12 years and their parents. Thirty-six consecutive, potential participants were eligible for the study. One eligible participant was not included because the parents declined to participate (eg, too busy). The mean age of children with new-onset epilepsy was 7.2 years (SD: 3.05; range: 2.1–12.5 years); 34% were female; and 66% were white, 23% were black, and 11% were other/biracial. Sixty percent of children had a diagnosis of partial epilepsy, 29% of generalized epilepsy, and 11% of unclassified epilepsy. Sixty percent were initially prescribed carbamazepine and 40% valproic acid. For patients with partial epilepsy, the mean number of seizures before the clinic visit was 3.0 (SD: 1.5). The average amount of time from first seizure to the diagnosis of epilepsy and initiation of AED therapy was 9.7 months (SD: 16.3).
Primary caregivers of children with new-onset epilepsy were predominately mothers (86%), as well as fathers (11%) and aunts (3%). Twenty-nine percent of primary caregivers were single, 60% were married, and 11% were divorced/separated. The mean Revised Duncan score, a measure of occupational attainment,18,19 was 46.5 (SD: 20.5). This score reflects occupations such as sales worker, computer operator, and tool/dye maker.
Procedure
The protocol and consent forms were approved by the institutional review board/human research ethics committee. Potential participants were recruited from a pediatric new-onset epilepsy clinic in the Midwest. Eligibility criteria included (1) new diagnosis of epilepsy, (2) age between 2 and 12 years, (3) no comorbid chronic illnesses (eg, asthma, diabetes) or developmental disorders (eg, autism, Down syndrome), and (4) no previous treatment and initiation of carbamazepine or valproic acid. Parents of children who had a new diagnosis of epilepsy and met inclusion criteria were approached by study personnel during their scheduled clinic visit. After consent was obtained, parents completed a demographics questionnaire and were given a MEMS TrackCap and bottle to begin electronically monitoring adherence to their prescribed treatment (carbamazepine or valproic acid). Parents were made aware that the bottle monitored medication taking. Minimal data were collected from children and their parents during this first clinic visit because they had just received an epilepsy diagnosis. Parents received a $10 gift card for completing the questionnaire and providing information about the child's seizure history.
As a part of routine clinical care, patients returned to clinic 
1 month later for a follow-up appointment. Before this appointment, parents were sent a reminder card to bring their MEMS TrackCaps back to the appointment. During the follow-up appointment, parents and children completed several questionnaires, and the MEMS TrackCaps were downloaded. Participants received a $10 gift card for completion of the questionnaires and an additional $10 gift card for bringing back the MEMS TrackCaps. It is important to note that families who participated in this study are part of a larger longitudinal study examining adherence to AED therapy during a 2-year period.
Measures
Background Information Form
Parents completed a Background Information Form at the initial visit; this asked about the child's date of birth, gender, parent's age, socioeconomic status, occupation, and composition of the family. Data were available to calculate the Revised Duncan19 for each family, an occupation-based measure of socioeconomic status (SES).18 This occupational-based measure is a contemporary indicator of SES.20 Scores range from 15 to 97, with higher scores representing greater occupational attainment. For 2-caregiver households, the higher Duncan score was used in analyses. Information about the child's medical history was also collected from the parent, including number of seizures before initiation of AED therapy, first seizure date, and comorbid diagnoses.
Prescribed Treatment
Each family was provided with verbal and written information regarding the medication prescribed for the child at the initial visit from the clinic nurse, including the name of the medication and a separate full-page 5-week titration schedule. This is standard care in the new-onset seizure clinic. This written treatment plan was obtained from the medical chart to ascertain the prescription for each child in the study.
Electronic Monitoring
The MEMS 6 TrackCap made by AARDEX Corp (Union City, CA), is an electronic monitoring system that measures the dosing histories of patients' prescribed oral medications. It was used to monitor adherence to AEDs for this study. It has 2 components: a standard plastic vial with a threaded opening and a closure for the vial that contains a microelectronic circuit to register the dates and times the bottle is opened and closed. The MEMS TrackCap stores times and dates for more than 3518 events for a period of 36 months, and the data can be transferred to a Windows-based computer. Data from the MEMS TrackCap were downloaded at the follow-up clinic visit. It is important to note that the MEMS cap did not account for the number of capsules taken at each day; it was assumed that patients extracted the correct number of capsules.
Statistical Analyses
The number of treatments performed each day divided by the number of treatments prescribed was multiplied by 100 to determine percentage adherence (ie, percentage of AED taken each day). These percentages were calculated across a 1-month period. There was an average of 2.1 extra bottle openings per patient across the 30-day period for this study; however, truncated adherence rates (maximum of 100%) were used in analyses to reduce inflation as a result of overuse or extra openings that may have occurred as a result of refills. This method has been used successfully in studies that assessed adherence with electronic monitoring.12
Descriptive analyses, including means and SDs, were calculated for AED adherence during the first month of therapy for children with new-onset epilepsy. Student's t tests were conducted to examine differences in adherence on the basis of gender, parental marital status, epilepsy type, and prescribed AED medication. Pearson correlations were used to determine the relation between adherence and age, SES, seizure frequency before the first clinic visit, and length of time since seizure onset. Paired t tests and correlations were calculated between overall 1-month adherence and adherence for the 1, 3, and 5 days before the clinic appointment and 3 days after the clinic appointment to determine white-coat compliance. Significance was identified as P < .05.
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RESULTS |
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TOPABSTRACTMETHODSRESULTSDISCUSSIONREFERENCES |
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1-Month Adherence Data
Longitudinal adherence for the first month of treatment for children with new-onset epilepsy is shown in Fig 1. Mean overall adherence across patients during this 1-month period was 79.4% (SD: 28.2%). Patients were 100% adherent to their medications on 77.1% of days, 50% adherent on 12.7% of days, and 0% adherent on 10.1% of days. For the first month of therapy, only 23% (n = 8) were completely adherent (ie, 100%) to the prescribed regimen each day. The distribution of complete nonadherence over 5-day increments was as follows: 20% of patients for 1 to 5 days, 6% of patients for 6 to 10 days, 6% of patients for 11 to 15 days, 3% of patients for 16 to 20 days, 3% of patients for 21 to 25 days, and 0% of patients for 26 to 30 days.
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Next, differences in adherence were examined for demographic and medical variables. No significant differences were found in 1-month adherence for gender (t33 = –1.2; P = not significant [NS]), epilepsy type (F2,32 = 0.48, P = NS), or prescribed medication (t33 = –0.56; P = NS); however, a significant difference was noted for parental marital status (t33 = –2.1; P < .05), for which adherence was higher for children of married parents compared with unmarried parents. Pearson correlations indicated a significant relation between 1-month adherence and SES (r = 0.44, P < .01) but not child's age (r = 0.20, P = NS). For children with partial epilepsy, no significant relation was found between 1-month adherence and seizure frequency before the first clinic visit (r = 0.15, P = NS) or length of time since seizure onset (r = –0.28, P = NS).
White-Coat Compliance
Paired t test results revealed no significant differences between adherence for the 1 (t34 = 0.16, P = NS), 3 (t34 = 0.99, P = NS), or 5 days (t34 = –1.0, P = NS) before the clinic visit compared with adherence across the entire 1-month period (79%; Fig 2). There were no significant differences between adherence 3 days after the clinic appointment and overall adherence (t19 = 0.14, P = NS). Paired correlations also indicated a significant relation between the 1-day (r = 0.72, P < .0001), 3-day (r = 0.79, P < .0001), and 5-day (r = 0.82, P < .0001) adherence before the clinic visit and overall adherence rates. Similarly, there was a strong correlation between adherence 3 days after the clinic appointment and overall adherence (r = 0.82, P < .0001).
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DISCUSSION |
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TOPABSTRACTMETHODSRESULTSDISCUSSIONREFERENCES |
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This is the first study to document adherence to AED therapy for children with a new diagnosis of epilepsy using electronic monitors, an objective method of measurement. The level of nonadherence,
21%, in the first month of therapy is concerning because children and parents are most likely to adhere to their treatment regimen initially.17,21,22 In fact, research suggests that adherence during the first month of treatment is one of the most powerful predictors of long-term adherence.23 Other studies that examined adherence in pediatric epilepsy found nonadherence rates ranging from 14% to 43%. Although our data fall within this range, it is important to note that previous research used poor measurement methods and examined nonadherence cross-sectionally with varying length of time since diagnosis. The results of this study indicated that, on average, patients did not correctly take their medications on 7 of 30 days of the month. More surprising, patients did not take any of their medication on an average of 3 of 30 days. Studies in adults suggested that even 1 missed dose could prompt more seizures.1,2 Furthermore, nonadherence may affect clinical decision-making resulting from the underestimation of AED efficacy and tolerability and overestimation of dosing requirement for optimal efficacy.23 Results from the general literature suggested that adherence decreases over time for chronic conditions,24 with a strong likelihood that adherence will approach 50% by the end of the first year for these patients. Poor adherence is associated with lower SES and having parents who are not married. This finding is consistent with the broader pediatric adherence literature and evidenced in several conditions, including asthma, cystic fibrosis, diabetes, and renal disease. Specifically, lower SES and parental education levels were associated with nonadherence.14–17 In addition, parental separation/divorce was associated with poorer adherence for children with asthma16 and renal disease.17 It may be that parents with lower incomes have significant competing demands and limited resources, causing them to choose higher priority needs (eg, food, rent) compared with purchasing medications; however, this information remains unknown. It is also important to note that SES and marital status are likely closely linked; however, posthoc analyses indicated a NS relationship between these 2 constructs for the current sample (point biserial r = 0.29, P = .09).
Our data indicated that white-coat compliance did not exist for children with new-onset epilepsy during the first month of AED therapy. This is in contrast to the adult epilepsy literature in which Cramer et al13 reported a significant difference between adherence immediately before and after a clinic appointment (88%) relative to adherence between appointments (73%). Adherence for children with new-onset epilepsy was consistently between 76% and 80%. Differences in duration of AED therapy (eg, new-onset versus chronic therapy) may explain the lack of white-coat compliance in pediatric epilepsy patients compared with adult epilepsy patients. This suggests that future studies need to evaluate longitudinally white-coat compliance in children with epilepsy.
Results from this study have significant implications for burgeoning areas of research, including the development of clinically useful population pharmacokinetic models and its clinical application in therapeutic drug management (TDM). TDM is the proper measurement and interpretation of drug concentrations in a specific patient, which can allow for better individualization of the drug dosing regimen.25 TDM can be useful in clinical situations that require a rapid onset of effect or for patients who manifest a higher or lower effect than expected. For a correct interpretation of drug concentrations, it is imperative to have precise information about the dosage regimen and time of the last dose relative to the time of blood sampling.26 Patient report regarding dosage regimen and missing doses may not appropriately reflect actual adherence to treatment, affecting a correct interpretation of drug concentrations. Missing doses and only taking medications shortly before a clinic visit will result in much lower than expected drug concentration in slowly eliminated drugs.26 Research with adults with epilepsy and other diseases (eg, HIV) has shown that white-coat compliance exists and thus compromises the utility of TDM13,27; however, our data show that in a pediatric population with epilepsy, white-coat compliance did not exist during the first month of therapy, potentially eliminating one factor of uncertainty for TDM.
The strengths of this study include the characteristics of the patient population, method of measuring adherence, and blinding of the clinical team. First, the patient population was a consecutive cohort of previously untreated children who had newly diagnosed epilepsy and were seen in a clinic that services an 8-county region including and surrounding the city of Cincinnati. This clinic's population is considered a representative subset of the general population of children between the ages of 2 and 18 years in the region. Focusing on children with newly diagnosed epilepsy eliminates potential confounding bias of negative experiences with previous antiepileptic medications and their adverse effects. Second, the consecutive nature of the cohort also helps to minimize selection bias. Third, our measurement of adherence, electronic monitors, represents an objective and valid method. This cohort represents the largest sample of prospectively followed children with epilepsy regarding adherence to AED therapy. Last, the adherence research team functions independent from the clinical team; therefore, the clinicians are blinded to the adherence data. Overall, clinical treatment of patients and discussions are not influenced by knowledge of a specific patient's level of adherence.
Although this study represents one of the first to examine white-coat compliance in a pediatric sample, several limitations were noted, including the proxy nature of the electronic monitoring caps, short duration of the study, and small sample size. MEMS TrackCaps serve as a proxy for when the patient actually took the medicine. There is no absolute guarantee that opening the bottle translates into taking a pill from inside the bottle; however, this form of electronic monitoring is the best method currently available to measure adherence to oral medications relative to other measurement methods (eg, self-report questionnaires, pharmacy refill).8,28 Another limitation of the study is its short-term nature. We recognize the importance of following this cohort of patients longitudinally to assess whether this initial snapshot of adherence holds true or changes significantly over time. Finally, the sample size is small but represents nearly double the sample presented by Cramer et al13 for adult white-coat compliance. Our prospective longitudinal study has ongoing recruitment with the hope of ascertaining a large sample size to be reported in the future.
Future studies examining adherence to AEDs in children with new-onset epilepsy should focus on several areas. First, no studies have examined patterns or typologies of adherence over time (eg, longitudinally) to understand whether adherence changes at different points in disease trajectory. For example, it may be that adherence declines after 6 months of therapy, when the initial scare related to the diagnosis has dissipated. In this scenario, identifying predictors or barriers to adherence becomes critical in understanding why adherence has decreased. Second, what remains unknown is the optimal or minimal levels of adherence that are necessary to achieve good health outcomes. For example, adults with chronic conditions, including HIV and hypertension, have identified that 80% to 95% adherence is necessary to reduce viral load and improve blood pressure, respectively.29–31 Finally and most important, we must identify the impact of nonadherence on morbidity in children with new-onset epilepsy, as well as the long-term impact that it may have on the course of the disease itself (eg, development of pharmacoresistance). Combined, future studies can lead investigators to develop adherence interventions that are proactive and personalized on the basis of the needs of the family.
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ACKNOWLEDGMENTS |
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We extend our deepest appreciation to the children with epilepsy and their families who participated in this study. We thank Julie Koumoutsos for recruiting participants and collecting their data. We also thank the health care team involved in the medical and psychosocial care of children with new-onset epilepsy who facilitated the current research, including Sally Monahan, Dee Daniels, Stephen Fordyce, Sondra Weingartner, Amy Hankins, and Lisa Heaton.
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FOOTNOTES |
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Accepted Sep 27, 2007.
Address correspondence to Avani C. Modi, PhD, Division of Behavioral Medicine and Clinical Psychology, Center for the Promotion of Adherence and Self Management, MLC-3015, Cincinnati Children's Hospital Medical Center, 3333 Burnet Ave, Cincinnati, OH 45229. E-mail: avani.modi{at}cchmc.org
The authors have indicated they have no financial relationships relevant to this article to disclose.
| What's Known on This Subject The sparse literature on white coat compliance suggests that adults with epilepsy and hypertension have increased adherence to their medications prior to clinic visits compared to their overall adherence.
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| What This Study Adds This is the first pediatric study examining white coat compliance and longitudinal adherence in children newly diagnosed with epilepsy.
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REFERENCES |
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TOPABSTRACTMETHODSRESULTSDISCUSSIONREFERENCES |
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- Cramer JA, Glassman M, Rienzi V. The relationship between poor medication compliance and seizures. Epilepsy Behav. 2002;3 (4):338 –342[CrossRef][Web of Science][Medline]
- Jones RM, Butler JA, Thomas VA, Peveler RC, Prevett M. Adherence to treatment in patients with epilepsy: associations with seizure control and illness beliefs. Seizure. 2006;15 (7):504 –508[CrossRef][Web of Science][Medline]
- Al-Faris EA, Abdulghani HM, Mahdi AH, Salih MA, Al-Kordi AG. Compliance with appointments and medications in a pediatric neurology clinic at a University Hospital in Riyadh, Saudi Arabia. Saudi Med J. 2002;23 (8):969 –974[Web of Science][Medline]
- Asadi-Pooya AA. Drug compliance of children and adolescents with epilepsy. Seizure. 2005;14 (6):393 –395[Web of Science][Medline]
- Kyngäs H. Compliance with health regimens of adolescents with epilepsy. Seizure. 2000;9 (8):598 –604[CrossRef][Web of Science][Medline]
- Mitchell WG, Scheier LM, Baker SA. Adherence to treatment in children with epilepsy: who follows "doctor's orders"? Epilepsia. 2000;41 (12):1616 –1625[CrossRef][Web of Science][Medline]
- Shope JT. Compliance in children and adults: review of studies. Epilepsy Res Suppl. 1988;1 :23 –47[Medline]
- Modi AC, Lim CS, Yu N, Geller D, Wagner MH, Quittner AL. A multi-method assessment of treatment adherence for children with cystic fibrosis. J Cyst Fibros. 2006;5 (3):177 –185[CrossRef][Web of Science][Medline]
- Milgrom H, Bender BG, Ackerson L, Bowry P, Smith B, Rand C. Noncompliance and treatment failure in children with asthma. J Allergy Clin Immunol. 1996;98 (6 pt 1):1051 –1057[CrossRef][Web of Science][Medline]
- Butz AM, Donithan M, Bollinger ME, Rand C, Thompson RE. Monitoring nebulizer use in children: comparison of electronic and asthma diary data. Ann Allergy Asthma Immunol. 2005;94 (3):360 –365[Web of Science][Medline]
- Bender BG, Milgrom H, Wamboldt FS, Rand C, eds. Measurement of Treatment Nonadherence in Children With Asthma. Hillsdale, NJ: Lawrence Erlbaum Associates; 2000
- Bender BG, Wamboldt FS, O'Connor SL, et al. Measurement of children's asthma medication adherence by self report, mother report, canister weight, and Doser CT. Ann Allergy Asthma Immunol. 2000;85 (5):416 –421[Web of Science][Medline]
- Cramer JA, Scheyer RD, Mattson RH. Compliance declines between clinic visits.
Arch Intern Med. 1990;150
(7):1509
–1510
[Abstract/Free Full Text] - Bobrow ES, AvRuskin TW, Siller J. Mother-daughter interaction and adherence to diabetes regimens. Diabetes Care. 1985;8 (2):146 –151[Abstract]
- Patterson JM. Critical factors affecting family compliance with home treatment for children with cystic fibrosis. Family Relations. 1985;34 :79 –89[CrossRef][Web of Science]
- Radius SM, Becker MH, Rosenstock IM, Drachman RH, Schuberth KC, Teets KC. Factors influencing mothers' compliance with a medication regimen for asthmatic children. J Asthma Res. 1978;15 (3):133 –149[Web of Science][Medline]
- Brownbridge G, Fielding DM. Psychosocial adjustment and adherence to dialysis treatment regimes. Pediatr Nephrol. 1994;8 (6):744 –749[CrossRef][Web of Science][Medline]
- Nakao K, Treas J. The 1989 Socioeconomic Index of Occupations: Construction From the 1989 Occupational Prestige Scores. Chicago, IL: University of Chicago, National Opinion Research Center; 1992
- Stevens G, Featherman DL. A revised socioeconomic index of occupational status. Soc Sci Res. 1981;10 (4):364 –395[CrossRef][Web of Science]
- Hauser RM. Measuring socioeconomic status in studies of child development. Child Dev. 1994;65 (6):1541 –1545[CrossRef][Web of Science][Medline]
- Litt IF, Cuskey WR. Compliance with salicylate therapy in adolescents with juvenile rheumatoid arthritis.
Am J Dis Child. 1981;135
(5):434
–436
[Abstract/Free Full Text] - Bond GG, Aiken LS, Somerville SC. The health belief model and adolescents with insulin-dependent diabetes mellitus. Health Psychol. 1992;11 (3):190 –198[CrossRef][Web of Science][Medline]
- Bosworth HB. Medication treatment adherence. In: Bosworth HB, Oddone EZ, Weinberger M, eds. Patient Treatment Adherence: Concepts, Interventions, and Measurement. Mahwah, NL: Lawrence Erlbaum Associates; 2006:147 –194
- de Klerk E, van der Heijde D, Landewe R, van der Tempel H, Urquhart J, van der Linden S. Patient compliance in rheumatoid arthritis, polymyalgia rheumatica, and gout.
J Rheumatol. 2003;30
(1):44
–54
[Abstract/Free Full Text] - Vinks A, Walson P. Therapeutic drug monitoring. In: Jaffe SJ, Aranda JV, eds. Neonatal and Pediatric Pharmacology. MD: Lippincott Williams & Wilkins; 2005:99 –1103rd ed: Baltimore
- Soldin OP, Soldin SJ. Review: therapeutic drug monitoring in pediatrics. Ther Drug Monit. 2002;24 (1):1 –8[CrossRef][Web of Science][Medline]
- Podsadecki TJ, Vrijens B, Tousset EP, Rode RA, Hanna GJ. White coat compliance patterns make therapeutic drug monitoring (TDM) a potentially unreliable tool for assessing long-term drug exposure. Poster presented at: 13th Conference on Retroviruses and Opportunistic Infections (CROI); February 5–8, 2006; Denver, CO
- Quittner AL, Modi AC, Lemanek K, Ievers-Landis C, Rapoff MA. Evidence-based assessment of adherence to medical treatments in pediatric psychology. J Pediatr Psychol. 2008, in press
- Gifford AL, Bormann JE, Shively MJ, Wright BC, Richman DD, Bozzette SA. Predictors of self-reported adherence and plasma HIV concentrations in patients on multidrug antiretroviral regimens. J Acquir Immune Defic Syndr. 2000;23 (5):386 –395[Web of Science][Medline]
- Liu H, Golin CE, Miller LG, et al. A comparison study of multiple measures of adherence to HIV protease inhibitors.
Ann Intern Med. 2001;134
(10):968
–977
[Abstract/Free Full Text] - Haynes RB, Sackett DL, Gibson ES, et al. Improvement of medication compliance in uncontrolled hypertension. Lancet. 1976;1 (7972):1265 –1268[Web of Science][Medline]
PEDIATRICS (ISSN 1098-4275). ©2008 by the American Academy of Pediatrics
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