Studies show that attendance at orthodontic appointments affects treatment outcomes, treatment duration, and the probability of side effects. The aim of this study was to predict factors that influence patients’ attendance at orthodontic appointments.
We conducted a face-to-face guided interview survey of 153 participants from orthodontic clinics in the Greater Boston area. Attendance at scheduled orthodontic appointments was self-reported as always, sometimes, or rarely. Participants’ characteristics, including demographics, dental insurance, and oral hygiene practices, were self-reported. Moreover, from dental records, we collected the time that the participants spent undergoing active orthodontic treatment. Multivariable ordered logistic regression was used to report proportional odds ratios and attendance probabilities. A likelihood ratio test was performed to ensure that the proportional odds assumption held.
For overall appointment attendance, 76% of the participants reported always attending, 16% reported sometimes attending, and 8% reported rarely attending. Based on multivariable logistic regression (adjusted for age, race, and sex), the participants with optimal oral hygiene practices were almost 6 times (5.9) more likely to attend appointments than those who did not ( P = 0.002). The odds of attending appointments decreased significantly (by 23%) for every 6-month increase in treatment duration ( P = 0.008). Participants covered by non-Medicaid insurance were 4 times ( P = 0.018) more likely to attend appointments than were those with Medicaid insurance.
Our findings indicate that adherence to orthodontic treatment follow-up visits was strongly correlated to insurance type, treatment duration, and oral hygiene practices. Unlike previous studies, sex was not a significant predictor of adherence.
We surveyed patients in private practice clinics about their attendance.
Patients with optimal oral hygiene were more likely to attend appointments.
Medicaid-insured patients had higher “no-shows” than non-Medicaid patients.
Oral hygiene, insurance type, and estimated treatment duration are good predictors of attendance.
A challenging task facing a dental team is supporting patients in changing their oral health behaviors and maintaining those changes. According to the American Association of Orthodontists, because orthodontic treatment is seldom finished rapidly, the assumption would be that patients who want good-looking smiles and healthier occlusions would attend every appointment and comply with every treatment instruction to accomplish the desired outcome as rapidly as possible. In orthodontics, adherence means attending appointments, maintaining good oral hygiene, wearing elastics or functional appliances as instructed, and avoiding foods that can loosen the brackets.
In 2003, Trenouth found that the failure rate of patients who completed orthodontic treatment was 10.3%, and the failure rate of patients who discontinued orthodontic treatment was 21.4%. Therefore, we could say that attendance affected treatment success. In other studies, “no-show” rates for orthodontic appointments ranged from 13.6% to 23.3%. Patients who neglected orthodontic appointments during active treatment were likely to prolong their treatment durations ; as a result, they might experience more harmful side effects. Missed appointments decrease the possibility that orthodontic treatment will be completed successfully.
The American Association of Orthodontists Insurance Company suggests the following possible causes for a patient’s failure to keep orthodontic appointments: teenaged patients who are less than passionate about treatment; an unexpected illness or a crisis in the family; and adults who report interferences with work schedules and emotional pressures. An additional cause, probably the most critical and frequent cause, is that the patient simply forgot. Forgetting indicates patient behavioral attitudes and oral health literacy.
Although previous behavioral epidemiologic studies have tried to establish a connection between a patient’s compliance with treatment, missed appointments, and oral hygiene, we could not find a study performed in private orthodontic offices in the United States. Although it is commonly thought that there is a correlation among elastic wear, showing up for appointments, and oral hygiene level, studies have shown contradictory results. Moreover, because of a lack of consensus about factors affecting attendance and the high percentage of malpractice claims against orthodontists who have frequent no-show patients, the American Association of Orthodontists Insurance Company recommends paying close attention to patient attendance deficiencies and addressing them as early as possible. Therefore, in this study, we predicted that attendance through a set of variables collected during the first visit would help to predict possible future attendance behavior, improve outcomes, and reduce the percentage of malpractice claims associated with no-show patients.
Material and methods
The study population was orthodontic patients in the Greater Boston area of Massachusetts. The participants were recruited from 3 private orthodontic offices in Boston, Cambridge, and Somerville. One hundred fifty-three participants were invited to participate in the study, and none refused or was unable to complete the questionnaire because of literacy problems. The subjects included 81 girls (53%) and 72 boys (47%). Their mean age was 14.7 years (SD, 3.9 years), and the mean average treatment time was 21 months (SD, 16 months). Demographics and participants’ characteristics are shown in Table I . Overall, there were 54 African Americans (34.6%), 44 whites (28.8%), 41 Hispanics (27.6%), and 14 (9%) participants from other ethnic backgrounds. Medicaid insurance was used by 93 of the participants (60.9%). Patients with severe dentofacial deformities were excluded. Parents’ consents and children’s assents were obtained.
|Characteristic/answer to the question||Always (n = 116)||Sometimes (n = 25)||Rarely (n = 12)||Total (n = 153)||P value (X 2 )|
|Age category (y)||0.309|
|<12||21 (81%)||5 (19%)||0||26 (100%)|
|12 to <16||58 (77%)||9 (12%)||8 (11%)||75 (100%)|
|>16||37 (71%)||11 (21%)||4 (8%)||52 (100%)|
|Male||48 (67%)||17 (24%)||7 (9%)||72 (100%)|
|Female||68 (84%)||8 (10%)||5 (6%)||81 (100%)|
|White||37 (84%)||2 (5%)||5 (11%)||44 (100%)|
|Black||37 (69%)||15 (28%)||2 (3%)||54 (100%)|
|Hispanic||31 (76%)||6 (15%)||4 (9%)||41 (100%)|
|Other||11 (79%)||2 (14%)||1 (7%)||14 (100%)|
|Medicaid||64 (69%)||18 (19%)||11 (12%)||93 (100%)|
|Non-Medicaid||52 (87%)||7 (12%)||1 (1%)||60 (100%)|
|Yes||101 (81%)||15 (12%)||8 (7%)||124 (100%)|
|No||15 (52%)||10 (34%)||4 (14%)||29 (100%)|
|Mean time of active treatment (SD) ∗ (mo)||8.8 (6.7)||7.3 (5.8)||10.8 (7.2)||21 (16)||0.322 ∗|
|Mean age (SD) ∗ (y)||14.6 (4)||14.8 (2.6)||15.4 (3.5)||14.7 (3.9)||0.740 ∗|
This was a convenience sample of patients who agreed to take the surveys and signed the consent form. The study was approved by Committee on Human Studies of Harvard University Faculty of Medicine.
The participants completed self-administered questionnaires guided by a face-to-face interview. The questionnaire was divided into 8 parts: (1) demographic data, (2) oral hygiene practices, (3) payment method, (4) attendance history, (5) patients’ and parents’ perceptions about the importance of braces, (6) treatment duration (actual time that the participant was undergoing active orthodontic treatment), (7) Oral Impact on Daily Performances scores, and (8) Peer Assessment Rating scores.
Before the actual data collection, the questionnaire sets were validated in a pilot study, conducted in waiting rooms of the Harvard dental clinic. This article will report and predict patients’ attendance history.
Patient attendance history was addressed by the question “Have you visited the orthodontist after having an appointment?” with possible responses of always, sometimes, and rarely.
The data collection procedure had 2 main stages. First, the participants completed questionnaires that included questions about the parents’ perceived need for orthodontic treatment, behavioral attitude, and sociodemographic information. An interviewer was available to clarify any questions. Second, the Oral Impact on Daily Performance and Peer Assessment Rating scores were calculated from the Oral Impact on Daily Performance questionnaire and the study casts, respectively.
A descriptive analysis was performed for the demographic data to summarize the overall distribution of the characteristic variables, and bivariate analyses (chi-square and analysis of variance [ANOVA]) were performed to assess the associations between independent variables and attendance history.
The first model used the multivariable ordered logistic regression to predict attendance history and examine the simultaneous association of independent and outcome variables. The associations between the independent and outcome variables were adjusted for age (continuous), sex, and race. To determine which additional variables needed to be adjusted, we used the purposeful selection method. The estimated attendance probabilities and odds ratios were reported. Finally, a likelihood ratio test was performed to ensure that the proportional odds assumption held.
The second model used the multivariable logistic regression with the binary outcome attendance history (always vs sometimes or rarely) while adjusting for age (<12, 12 to <16, >16 years) to determine whether teenaged participants driving themselves attended their orthodontic appointments differently from other participants.
We tested whether there were any significant differences in patient characteristics between the 3 orthodontic offices. Moreover, we added the variable of the 3 offices to our models. However, it was not significant and did not change the coefficients of other predictors. Consequently, to have a simpler model, easier interpretations, and better understanding by readers, we removed it from all models.
All analyses were conducted using a statistical package (version 12.0; Stata, College Station, Tex). All statistical tests were 2-sided, and a P value of <0.05 was deemed to be statistically significant.
Among the girls, the proportions who reported they always, sometimes, and rarely attended were 84%, 10%, and 6%, respectively. On the other hand, the boys reported always, sometimes, and rarely attending at 67%, 24%, and 9%, respectively. Overall, the girls were more likely to attend than the boys ( P = 0.038; chi-square test).
Among the Medicaid participants, the proportions who reported they always, sometimes, and rarely attended were 69%, 19%, and 12%, respectively. Among the non-Medicaid participants, the proportions who reported they always, sometimes, and rarely attended were 87%, 12%, and 1%, respectively. Overall, non-Medicaid participants were more likely to attend than Medicaid participants ( P = 0.022; chi-square test).
Among participants with good oral hygiene practices, the proportions who reported they always, sometimes, and rarely attended were 81%, 12%, and 7%, respectively. In contrast, of the participants with suboptimal oral hygiene practices, the proportions who reported they always, sometimes, and rarely attended were 52%, 34%, and 14%, respectively. Those who practiced brushing and flossing daily were more likely to attend than were those who did not brush and floss daily ( P = 0.003; chi-square test).
Overall, there was no statistically significant difference in attendance history among the different race or ethnic categories ( P = 0.075; chi-square test) or among the different age categories ( P = 0.309; chi-square test). Moreover, there were no statistically significant associations between attendance history and the duration of active orthodontic treatment ( P = 0.322; ANOVA) or age of the participants ( P = 0.74; ANOVA).
The results of the multivariable analyses examining the simultaneous associations between attendance (dependent variable) and insurance type, oral hygiene behavior, and treatment duration are summarized in Table II . For non-Medicaid participants, the odds of always attending vs sometimes and rarely attending combined were 4 times higher than for Medicaid participants, adjusted for age, race, and sex ( P = 0.018).