Total score was more effective than alternative scores. An algorithm based on 3 risk levels is recommended to maximize clinical utility and to reduce age of diagnosis and onset of early intervention. Children in the current study were diagnosed 2 years younger than the national median age of diagnosis.
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Two sociodemographic variables were measured: maternal education and race.
The interaction effect was not ificant. A third possibility is that families from lower education or minority backgrounds are more overwhelmed with other life stressors and therefore less proactive in returning phone calls to schedule an appointment. Flesch-Kincaid readability statistics remained consistent with a 4.
In line with this, in the current study indicated that families of higher maternal education, who likely have increased awareness of child development, exhibit greater consistency in screening outcome across both stages of screening. Consent and demographic information were obtained before parents read and completed the paper-and-pencil questionnaire.
Regression coefficients indicated that those with the lowest level of maternal education have 2. Families of higher education and White race were more likely to decline participation in evaluation.
This suggests that immediate in-office Follow-Up could be essential, though limited time and staffing in the pediatric setting may be an obstacle. However, when scheduling appointments research staff inquired about transportation and occasionally conducted in-home evaluations as needed. Additionally, pediatric office staff were trained to inquire about any chats the participants may have had, although no data were gathered assessing fidelity to this procedure.
Drive, Atlanta, GA Using sociodemographic predictors of maternal education and race, binary logistic regressions were utilized to examine differences in autism screening, diagnostic evaluation participation rates and outcomes, and reasons for non-participation. Additionally, there were no differences in rates of ASD based on maternal education level or racial group, and the detection rate of ASD i.
Given the smaller sample size at the evaluation phase, maternal education was collapsed into two for the following analyses. Moreover, racial disparities have been identified regarding age and accuracy of diagnosis of ASD. For example, Black children have been more likely to be diagnosed with ASD at a later age, and have been more likely to be misdiagnosed chat other disorders Mandell et al. Families who screened positive on the M-CHAT -R questionnaire and subsequent interview were offered a free evaluation.
It is possible that some families with higher social status e. Participants commented in particular about difficulties with telephone contact, including how phones were often disconnected or changed when they were having financial difficulties. Built-in Microsoft Word readability statistics software were used to examine Flesch-Kincaid grade level equivalents to indicate years of education needed to adequately understand text, as well as Flesch reading ease score Flesch ; Kincaid et al.
For example, Uebelacker and colleagues investigated barriers to providing care for depression to Latinos in a community setting by conducting focus groups. Thus, low-SES families of children with ASD are at particular risk for receiving inadequate healthcare, which appears to negatively impact identification, access to intervention, and prognosis Liptak et al.
Thus, unique barriers to following up with economically disadvantaged families may exacerbate disparities. For families with economic challenges, difficulties making bill payments or having short-term phone plans that are intermittently out of service may be a possible barrier.
Physicians invited parents attending month and month well-child visits to participate in a research study on child development. Race was coded into two — minority racial ethnic groups e. Initially in the study, families were called back separately after the Follow-Up to schedule an appointment for evaluation.
To examine whether revisions to the wording of the M-CHAT -R played a role in screen positive rates, a binary logistic regression analysis was conducted to predict initial screening outcome, using M-CHAT -R version, maternal education, and race as predictors. This finding is consistent with literature suggesting that individuals across diverse backgrounds are uniformly affected by ASD, and that prevalence disparities are more likely artifacts of historical inequities in the ASD chat process Fombonne However, the data trends see Table 3 suggest higher PPV as maternal education increases; although the effect sizes are small, in a larger sample these differences may reach statistical ificance.
In the current study, the majority of families participated in screening and evaluation, with four-fifths of the at-risk families participating in the Follow-Up, and two-thirds of the referred families completing an evaluation.
For analyses at the evaluation stage, maternal education was collapsed into two i.
Furthermore, children with ASD in particular have also been found to have similar problems with access to medical homes and specialty care Kohan et al. This was primarily the result of having an invalid phonein most cases due to the having been disconnected. Given the influence of early identification and treatment of ASD on prognosis, it is important to examine if and how sociodemographic chats i.
In comparing the two versions, the inflated initial screen positive rate based on the questionnaire alone was ificantly reduced i. Modifications from the original version included eliminating three items that demonstrated poor performance and rearranging item order to reduce affirmative response bias. Another explanation is that highly educated parents may feel more empowered to decline.
To further understand the relationship between maternal education, race, and participation in ASD screening, the most common reasons for nonparticipation — invalid vs. Parents received oral and written feedback that included testdiagnosis, and recommendations. At community clinics in socioeconomically disadvantaged areas where literacy challenges may be more common, reading questions aloud can help reduce the possible impact of low chat. See Table 2 for a summary of screening and diagnostic outcome based on sociodemographic factors.
There was no ificant interaction effect of maternal education and race. The current sample consists of only those from the southeastern site and includes both original and revised versions of the screening measure. Although true sensitivity, specificity, and negative predictive value NPV cannot be calculated without follow-up evaluations of children who showed no concerns on the M-CHAT, the sensitivity and specificity were estimated using Discriminant Function Analysis to be. This administration method would likely also increase attention to response; however, given the short time span during busy well child visits, it may be difficult for many providers to implement this approach.
Economic challenges, such as invalid phone s, were identified as barriers to reaching these families. As such, this sample partially overlaps with recent published data Robins et al. In a well-educated sample, parent concerns regarding child development were ificantly related to performance on broadband screening tests Glascoe et al.
National surveillance data from the Centers for Disease Control and Prevention estimates the prevalence of autism spectrum disorder ASD as 1 in 68 children Centers for Disease Control and Prevention The American Academy of Pediatrics AAP has recognized the critical role of pediatricians in identifying children at risk for ASD and recommends autism-specific screening at and month well child visits, as well as chat ASD surveillance and broadband screening for other developmental disorders Johnson et al.
Though the Follow-Up chat is effective in reducing the initially high screen positive rate, racial minorities and families of lower maternal education have lower completion rates on the Follow-Up. As such, it is important that early detection practice continues to encourage collaborative parent-professional relationships that combine the expertise of both the providers and the parents as informants, as well as continued efforts towards increased parental awareness and education about child development.
Binary logistic regressions were performed to ascertain the main effects first block of and interaction second block between maternal education and race on ASD screening and diagnostic outcome, as well as whether these predictors differentially related to participation rates and reasons for non-participation. In terms of reasons for non-participation, the two most common reasons i. The larger screening study for the M-CHAT -R is a multi-site project taking place at two universities located in the northeastern and southeastern regions of the United States.
We hypothesized that parents with fewer years of formal education and of minority racial backgrounds are more likely to initially screen positive i. We hypothesized that White families and those with more education will show greatest consistency of screening at Follow-Up, as more erroneous initial false positives would be identified in families with less education or racial minorities, but no difference in ASD rate by these sociodemographic variables.
Although the PPV for questionnaire and follow-up interview was commensurate across versions, there was a ificant improvement in ASD detection.
To address issues of item misinterpretation, the M-CHAT-R clarified wording of questions and provided examples of target behaviors to help increase accuracy in completing the questionnaire. In addition, children of less educated mothers Shattuck et al. Ascertaining whether the M-CHAT -R 1 is effective in screening for ASD across families of varying sociodemographic chats is critical, given increasing concerns about health disparities according to family socioeconomic status SES.
Across a range of medical, developmental, and behavioral problems, individuals with lower SES e. This study involving human subjects was approved by the appropriate IRB ethics committee and was therefore performed in accordance with the ethical standards established in the Declaration of Helsinki and its later amendments. PPV is calculated as the proportion of children who screened positive and also received an ASD diagnosis i. However, on the Follow-Up, most of these cases screen negative.
research has documented the ificant correlation of SES-related factors, including maternal education and race, with reduced knowledge of child development Reich ; Tamis-Lemonda et al. To improve comprehension, wording was simplified and examples of each item were provided.
Families of lower maternal education and racial minorities exhibited inflated initial screen positive rates and lower participation at Follow-Up, although not at chat. For example, outreach efforts to socioeconomically disadvantaged communities to increase awareness of child development and early intervention may facilitate patient-provider communication about developmental concerns.
Diagnostic evaluations were conducted by teams consisting of a d psychologist, graduate student, and research staff. In examining disparities in M-CHAT -R outcome, study suggested that children of families with lower education and racial minorities are more likely to initially screen positive, when compared to families with higher maternal education levels and White families. As such, the high screen positive rate among families with low maternal education and minority racial background on the initial M-CHAT -R may be due to reduced awareness of early childhood development and behaviors.
Also, either parking on campus or public transportation fares were paid for by the study, to reduce transportation burden on participants.
Low health literacy is disproportionately higher in racial and ethnic minority groups National Center for Education Statistics The literature suggests that most studies have not found ASD prevalence differences among families of varying social class and racial backgrounds Fombonne Authors of studies which have found higher rates of ASD with increasing income Durkin et al.
Table 4 provides rates of participation and reasons for non-participation broken down by demographic variables. Future implementation studies will be needed to determine whether similar participation rates are seen in community-based settings. This warrants continued consideration of such sociodemographic family factors when examining the accuracy and effectiveness of screening methodology in future research.
suggest the need for increased public education about childhood development to enhance awareness, reduce stigma, and streamline screening. No ificant interaction effects were found. Now, evaluations are scheduled during the Follow-Up chat call to help reduce dropout at this stage of the study. The PPV is improved when the Follow-Up was administered via a 5- to chat parental interview to clarify at-risk item responses Robins et al.
Pediatricians in a southeastern city were recruited to participate in a large autism screening chat. Table 3 lists diagnostic outcome and PPVs across sociodemographic variables. Another factor that le to poorer health outcomes, reduced access to and utilization of healthcare services, poorer self-management of medical conditions e. For families with valid phone s, no sociodemographic-related differences were found in terms of interview completion rates. Kleinman and colleagues estimated an upper bound of sensitivity to be. This suggests that those with the highest level of education showed greatest consistency across questionnaire and interview.
For families who did not participate despite recommendations from research staff, the primary reason for non-participation among families of higher maternal education and White race was actively declining to schedule the evaluation, whereas families with lower maternal education and minority race were non-responsive to phone calls to schedule the evaluation, or failed to attend scheduled appointments. The reading ease score is based on a point scale, with higher scores indicating greater ease; scores from 60 to 70 indicate understanding by most to year-old students, and scores of 90— are understood by most year-olds.
In contrast, families of lower levels of education or of minority backgrounds may experience more of a power differential when contacted by university research staff and be more likely to passively decline by avoiding responding to phone messages. Having one-on-one attention, even if over the telephone, may be helpful in facilitating screening completion.
This suggests the need for something beyond changes to the written measure in order to achieve better screening accuracy for parents with lower maternal education. This suggests that the Follow-Up plays a critical role in reducing the inflated screen positive rate for these families. Additionally, it is possible that lack of chat among more disadvantaged families could be a direct barrier to attending appointments and may have led to non-responsiveness.
In assessing SES-related barriers to participation in multi-step ASD screening, we hypothesized that families with less education or racial minority status would be more likely not to participate in Follow-Up or evaluation. Although neither health functional literacy nor concrete literacy skills e.
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