Pediatricians’ Reported Practices Regarding Early Education and Head Start Referral
,
* Robert Wood Johnson Clinical Scholars Program, University of Washington, Seattle, Washington
Departments of Pediatrics
Epidemiology, University of Washington, Seattle, Washington
 |
ABSTRACT |
|---|
 TOP ABSTRACT INTRODUCTIONMETHODSRESULTSDISCUSSIONREFERENCES |
|---|
Background. Early learning programs have proven benefits for impoverished children; Head Start is the most widespread of such programs. The current involvement of pediatricians in the Head Start enrollment process is unknown.
Objectives. 1) To assess the knowledge, attitudes, and reported practices of pediatricians on referring families to Head Start; 2) to assess pediatricians’ receptivity to a potential practice-based intervention to enhance their ability to make Head Start referrals.
Methods. Mail survey to stratified random sample of pediatricians practicing in poor and non-poor US zip codes. Prevalence estimates and logistic regression models were estimated using weighted data.
Results. Of 1000 surveys distributed, 472 of 772 presumed-eligible subjects completed surveys for a response rate of 61%. Respondents and nonrespondents were similar with regard to age, gender, years in practice, and urban/rural practice setting. Eighty percent of pediatricians reported discussing child care arrangements with a majority of their preschool-aged patients’ families, while only 14% reported actually assisting these families in applying to Head Start. Lack of time (77% of pediatricians) and nonphysician office staff (71%) were listed as the most significant barriers to helping families apply to Head Start. Unfamiliarity with early childhood education (10%) was generally not seen as a barrier to this practice. Head Start knowledge (adjusted odds ratio [aOR]: 1.43; 95% confidence interval [CI]: 1.01, 2.02), self-efficacy in advising families how to access local Head Start programs (aOR: 3.49; 95% CI: 1.46, 8.38), and the belief that it is the pediatrician’s responsibility to do so (aOR: 9.98; 95% CI: 3.91, 25.48) were significantly associated with assisting families with Head Start enrollment. The majority of respondents (77%) reported a willingness to participate in a proposed computer-based intervention to aid eligible families in applying to Head Start. Having access to a social worker (aOR: 2.48; 95% CI: 1.17, 5.21) and respondent age (aOR: 0.96 for each year; 95% CI: 0.93, 0.99) were significantly associated with likely participation in the intervention.
Conclusions. Although pediatricians report commonly discussing child care issues, few actively assist patients in the application process for Head Start. An intervention to facilitate Head Start referral from the physician’s office must address time and staff limitations; education of pediatricians is a secondary need.
Key Words: Head Start • early childhood development • early childhood education • education • pediatrician practices • pediatrics
Abbreviations: CI, confidence interval • aOR, adjusted odds ratio
|
INTRODUCTION |
|---|
|
TOPABSTRACTINTRODUCTIONMETHODSRESULTSDISCUSSIONREFERENCES |
|---|
Early childhood development programs can produce lasting benefits for children and society. Longitudinal studies of experimental programs have demonstrated sustained cognitive, social, and educational benefits for both medically fragile1–3 and low-income children. The High/Scope Perry Preschool Project has demonstrated positive effects on income, educational achievement, divorce, and crime rates into adulthood.4 The Carolina Abecedarian Project has demonstrated effects on academic achievement through the midteen years.5 The Chicago Child-Parent Center Program has demonstrated lower rates of juvenile arrest and grade retention, and higher rates of high school completion.6 Programs in Syracuse7 and Houston8 have each demonstrated similar benefits. A Cochrane Collaboration systematic review of these interventions confirms their findings.9
Head Start, a federally funded preschool program for low-income families, is often considered a national model of early educational intervention. Any family at or below the federal poverty level is eligible to enroll their 3- to 5-year-old children in Head Start, and their 0- to 3-year-old children in Early Head Start. Nationally, Head Start serves >850 000 children; its curriculum incorporates child development, school readiness, health, nutrition, and linkage to other social services.10 Head Start outcome data are controversial in part because the program was never implemented as a controlled experiment and because its per capita funding is significantly less than that of the experimental programs cited above. Nevertheless, substantial social and educational benefits have been observed among Head Start graduates,11 and early results of a randomized controlled trial of Early Head Start supports its efficacy across a wide range of outcome parameters.12
Through frequent contact with families during a child’s first few years of life, the pediatrician may be in a unique position to affect Head Start enrollment and ultimately facilitate access. Two important organizations have advocated this concept. The American Academy of Pediatrics has recommended that pediatricians contribute to universal access to early child care and education.13 Most recently, the Centers for Disease Control and Prevention has strongly recommended publicly funded, center-based development programs for impoverished preschool-aged children, and suggested the promotion of such programs as part of routine well-child care.14
The extent to which the medical community plays a role in the Head Start recruitment and enrollment process, however, is unknown, as are pediatricians’ current knowledge and practices with regard to early childhood development programs in general. Therefore, our main goal in this study was to assess the knowledge, attitudes, and reported practices of pediatricians with regard to referring families to early childhood development programs, particularly Head Start. We also sought to assess pediatricians’ receptivity to a potential clinic-based intervention to enhance their ability to assist families in the Head Start enrollment process.
|
METHODS |
|---|
|
TOPABSTRACTINTRODUCTIONMETHODSRESULTSDISCUSSIONREFERENCES |
|---|
Sample
We generated our study sample from the American Medical Association’s Masterfile (Axciom Corporation, Skokie, Illinois), considered the most comprehensive list of all physicians practicing in the United States. In addition to physician names and addresses, it contains information on subspecialty, practice setting, date of birth, and years since completion of medical school and residency. From this list, we selected a national sample of general pediatricians practicing in the United States, limiting eligibility to residency graduates, age 25 to 65, practicing in hospitals, offices, and teaching institutions. We excluded researchers and administrators. A total of 26 833 pediatricians fulfilled these inclusion criteria.
Our intention was to over-sample pediatricians working with low-income, Head Start eligible children, while allowing valid national estimates to be obtained by appropriate weighting. To generate our sample of 1000 pediatricians, we divided the 
f40 000 US zip codes into quartiles based on median household income. We obtained income data from a 1998 Claritas Corporation data set, a validated database derived from the 1990 US Census, but updated to reflect interval changes.15 We randomly chose half of our sample (500) from the pool of 3561 pediatricians practicing in the bottom quartile of zip code incomes (median household income below $25 074). We randomly chose the other half of our sample from the pool of 23 272 pediatricians practicing in the 3 higher zip code quartiles (Fig 1).
|
Sample Size
We estimated that 250 subjects in each zip code stratum were necessary to make prevalence estimates to ±6% precision or better with 95% confidence. We predicted a survey response rate of 50%.
Instrument
The survey was divided into 6 domains representing potential predisposing, enabling, and reinforcing factors theorized in Green and Kreuter’s PRECEDE-PROCEED model to support behavioral or environmental change.16 We assessed knowledge about Head Start with a series of 6 true/false questions. We used a 5-point Likert scale to assess pediatrician self-efficacy and sense of responsibility in performing a number of items involved in early education and Head Start referral. We used the same Likert scale to assess barriers to helping families access Head Start. We scored all survey Likert items positively if respondents "agreed" or "strongly agreed" with the statements.
We assessed reported practices by asking respondents to recall the last 5 preschool-aged children they saw for well-child care, and to report with how many they performed each of 5 items. Although this type of bounded recall procedure is reported to reduce over-reporting,17 we still assumed a social desirability bias, and thus scored items as positive only if respondents reported them with a majority (
3) of patients.
We assessed willingness to participate in a potential clinic-based intervention to promote Head Start referral by asking subjects to respond to the following paragraph: "With a family’s permission, the demographic information of a preschool-aged child is transferred electronically from your clinic database onto a Head Start application. No additional data entry is required. As part of a well-child visit, clinic staff review the application with the family and send it to Head Start." To account for possible social desirability biases in their responses, respondents were considered "likely participants" only if they indicated a willingness to participate and indicated that the program would be "very important" or "important" to their clinic population.
The demographics portion of the instrument comprised a series of questions validated by the American Academy of Pediatrics’ Department of Research.18 Additionally, we assessed the proportion of Medicaid patients seen by each respondent by asking them to estimate on a visual analog scale what proportion of their practice received Medicaid.
We piloted the survey by face-to-face, semistructured interviews with 20 pediatricians in a variety of practice settings in the Puget Sound area. Items were included in the survey instrument only if there was near universal consensus on their meaning. We then piloted the survey by mail with another 20 pediatricians belonging to the King County Medical Society. One of the authors (D.G.) followed up the pilot mailing with brief telephone interviews with a subset of the pilot cohort.
Survey Protocol
Using a modification of Salant and Dillman’s procedures,19 we sent up to 5 mailings to those from whom we received no initial response. Participants received a $1 inducement.
Secondary Data Sources
Zip codes of practice addresses were linked to the Rural-Urban Commuting Area Code database, a validated instrument for rural-urban status generated jointly by the United States Department of Agriculture and the WWAMI (Washington-Wyoming-Alaska-Montana-Idaho) Rural Health Research Center.20 These codes represent continuous variables ranging from 1.0 to 11.0, with lower numbers denoting urban areas. From the Claritas dataset, we obtained an estimate of population and number of pediatricians practicing in each zip code.
Statistical Analysis
We weighted cases based on the size of the pool from which each subject was chosen. With the exception of comparing respondents to nonrespondents, we analyzed all data in their weighted form. Interval data were compared across groups using the Student t test for equality of means. Ordinal and categorical data were compared using the 
2 test. We calculated 2 multivariable logistic regression models: 1 with reported practices as the outcome of interest; the other, with likely participation in the proposed intervention as the outcome. Covariates were included in the base models based on their theoretical relevance as supportive factors for behavioral or environmental change; private practice was added to these base models because of the magnitude of its bivariate association with both outcomes of interest. Statistical analyses were conducted using Stata 7.0 (Stata Corporation, College Station, TX).
The University of Washington granted official exemption from institutional board review.
|
RESULTS |
|---|
|
TOPABSTRACTINTRODUCTIONMETHODSRESULTSDISCUSSIONREFERENCES |
|---|
Response
Of the 1000 surveys mailed, 65 were returned with no forwarding address. A total of 572 of the remaining 935 pediatricians returned surveys. Of the 572 respondents, 100 (17%) were excluded for not providing health supervision to preschool-aged children. Assuming an equal proportion of ineligible pediatricians among respondents and nonrespondents, 472 eligible respondents of 772 presumed-eligible subjects returned surveys, for a response rate of 61% (Fig 1). (In the implausible case that all nonrespondents were actually eligible for the study, our response rate would have been 57%.) There was no significant difference in response rate across zip code sampling strata.
Respondents and nonrespondents were similar in age, sex, and years in practice. The zip codes of their practice addresses were similar in population size, median household income, rural-urban score, and estimated number of pediatricians (Table 1).
|
Demographic Data
Table 1 represents a weighted description of all respondents. The proportion of respondents in private practice was lower in low-income zip codes (48% vs 73%; P < .0001), the mean proportion of patients receiving Medicaid was higher in these areas (53% vs 31%; P < .0001), and the proportion of clinics to employ a social worker was higher (42% vs 22%; P < .0001).
Head Start Knowledge and Self-Efficacy
Pediatricians’ responses to individual knowledge items related to Head Start are represented in Table 2. Of the 6 items, respondents answered an average of 3.5 correctly (95% confidence interval [CI]: 3.3, 3.6). Pediatricians reporting a majority of Medicaid clients answered slightly more questions correctly than those reporting <50% Medicaid participation (3.7 vs 3.4; P = .06). Of note, 44% of respondents were aware that Head Start offers services to children ages birth to 5 years (Early Head Start, birth to 3; standard Head Start, 3–5), and 23% of respondents were aware of Head Start’s eligibility criteria (federal poverty level) relative to their state’s Medicaid eligibility for preschool-aged children.21 A total of 37% (95% CI: 32, 42) of pediatricians expressed self-confidence in their ability to advise families how to access local area preschool programs, including Head Start.
|
Physician Responsibility, Reported Practice, and Barriers to Practice
A total of 36% of all respondents agreed that assisting families with Head Start enrollment was the pediatrician’s responsibility, yet only 14% reported assisting families in applying to Head Start (Table 2). Respondents reporting caring for a majority of Medicaid patients more often agreed that assisting families with enrollment was the pediatrician’s responsibility (57% vs 29%; P < .0001), and were more likely to report assisting families with enrollment (33% vs 8%; P < .0001) than those seeing a <50% Medicaid clientele.
Fig 2 shows the prevalence of reported practices among pediatricians considering such practices their responsibility. Of those considering assistance with Head Start enrollment their responsibility, only 34% reported this practice.
|
The most commonly reported barriers to helping families apply to Head Start were time constraints and lack of office staff (Table 2). Respondents reporting a majority of Medicaid patients were more likely to report as a barrier the perception of full Head Start classrooms (49% vs 26%; P < .0001), but less likely to report difficulty identifying eligible families (36% vs 48%; P = .05) or unfamiliarity with local Head Start programs (45% vs 57%; P = .07) than those reporting a <50% Medicaid clientele.
Controlling for all other covariates in a logistic regression model, considering Head Start enrollment assistance the pediatrician’s responsibility was associated with a nearly 10-fold increase in the likelihood of providing such assistance (adjusted odds ratio [aOR]: 9.98; 95% CI: 3.91, 25.48). Self-efficacy in advising families how to access local preschool programs (aOR: 3.49; 95% CI: 1.46, 8.38) and Head Start knowledge score (aOR: 1.43; 95% CI: 1.01, 2.02) were also significantly associated (Table 3). The model produced similar results when applied to the subpopulation of respondents reporting >50% Medicaid participation (data not shown).
|
Receptivity to Potential Intervention
A total of 77% (N = 354) of respondents indicated a willingness to participate in a potential office-based intervention to assist in the Head Start application process. The majority of respondents felt that the program would need to be free, not disrupt patient flow, and that there be an easy way to identify eligible families. Only a minority (37%) indicated that they would have to feel more comfortable discussing early childhood education. Of the willing responders, 52% (N = 180) indicated that such a program would be important or very important to their clinic population; these subjects were considered "likely participants" in the intervention.
We estimated a multivariable logistic regression model with likely participation in the proposed intervention as the outcome of interest. Significantly associated with likely participation were the presence of a clinic social worker (aOR: 2.48; 95% CI: 1.17, 5.21) and the age of the respondent (aOR: 0.96 for each year of life; 95% CI: 0.93, 0.99; Table 4). When the model was applied to the subpopulation of respondents reporting a majority Medicaid clientele, similar trends remained; however, because of sample size limitations, no single covariate remained statistically significant (data not shown).
|
|
DISCUSSION |
|---|
|
TOPABSTRACTINTRODUCTIONMETHODSRESULTSDISCUSSIONREFERENCES |
|---|
The majority of pediatricians in this national sample considered it their responsibility to discuss child care arrangements with families; of these, nearly 90% reported doing so. By contrast, fewer pediatricians considered it their responsibility to assist families >with Head Start enrollment, and of these, only a third reported this practice. Those who expressed self-efficacy in advising families how to access Head Start and considered it their responsibility to help families do so were more likely to provide assistance with enrollment. In contrast to reported practices, likely participation in the proposed intervention was more strongly associated with the presence of a clinic social worker and the age of the pediatrician.
Over the decades, pediatricians have become increasingly concerned about child care and early childhood education. Scurletis and others22 reported in 1966 that over one third of pediatricians they surveyed had never been asked for their advice about child care, and nearly all had no comment concerning the potential educational value of out-of-home care. By the late 1980s, Guralnick and others23 reported that most pediatricians they surveyed consulted regularly with infant stimulation programs, preschools, Head Start programs, or other such agencies. In 2002, the Centers for Disease Control’s Task Force on Community Preventive Services strongly recommended publicly funded, center-based, early childhood development programs for impoverished preschool-aged children, and suggested that health care providers promote participation in such programs as part of well-child care.12
This study represents a first step in trying to translate such recommendations into programmatic action. In the context of Green and Kreuter’s PRECEDE-PROCEED model of health intervention,16 our study results are noteworthy for a number of reasons. First, the divide between pediatricians’ sense of responsibility and reported practice with regard to providing Head Start enrollment assistance suggests a set of predisposing factors that may facilitate motivation for change, particularly among pediatricians caring for a large proportion of poor families. Second, time and staff limitations—examples of potentially modifiable enabling factors—appear the primary explanations for this divide. Although knowledge and attitude appear to drive current practice, clinic characteristics (ie, presence of a social worker) are strongly associated with likely participation in the proposed intervention. These results suggest that an effective Head Start enrollment intervention should aim to harness the resources and abilities of the clinic more so than the pediatrician him/herself, and that an automated, action-oriented program is a potentially effective method to motivate Head Start referrals from pediatric offices. Pediatrician education is a secondary concern.
Our study was limited by a number of factors. First, as with many surveys, social desirability biases may have compelled respondents to overestimate their attitudes and practices. Although we have dealt with this by defining positive responses conservatively, our cutoff values for certain variables are admittedly arbitrary. Additionally, although our 61% response rate is consistent with norms for survey research,24,25 restricting our survey to pediatricians who provide health supervision to preschool-aged children precludes a precise quantification of response rate attributed to an unknown proportion of ineligible pediatricians among the nonrespondents. However, given the likelihood that the ineligible rate is higher among the nonrespondents (they don’t see the right patient population, so they don’t respond), we have likely estimated our response rate conservatively.
The early education literature shows that experimental, university-based preschool programs with high parental participation are most effective. The Perry Preschool project, Abecedarian project, and Chicago Child-Parent Center program are examples of such meticulously implemented and rigorously tested programs.4–6 Exactly where Head Start lies on the quality spectrum is controversial. However, Head Start is the most widely available, comprehensive development program for low-income children in the United States; and, although its outcomes may be less clear than the university-based experiments, it has been shown to improve vocabulary and writing skills during the Head Start academic year, improve social skills, and enhance school readiness and subsequent academic performance.11 Therefore, implementing a systematic mechanism that enables pediatricians to make effective Head Start referrals would constitute evidence-based practice.
|
ACKNOWLEDGMENTS |
|---|
We thank Gary Hart, PhD, for his expertise in medical geography; Charlotte Lewis, MD, and Karen O’Connor for their experience in survey design; and Nancy Hutchins, PhD, and George Askew, MD, for their knowledge of the Head Start system.
|
FOOTNOTES |
|---|
Received for publication May 17, 2002; Accepted Oct 8, 2002.
Address correspondence to Michael Silverstein, MD, Robert Wood Johnson Clinical Scholars Program, University of Washington, H-220 Health Sciences Center Box 357183, Seattle, Washington 98195. E-mail: msilve{at}u.washington.edu
|
REFERENCES |
|---|
|
TOPABSTRACTINTRODUCTIONMETHODSRESULTSDISCUSSIONREFERENCES |
|---|
- The Infant Health and Development Program. Enhancing the outcomes of low-birth-weight premature infants.
JAMA.1990; 263
:3035
–3042
[Abstract/Free Full Text] - Brooks-Gunn J, McCarton CM, Casey PH, et al. Early intervention in low-birth-weight premature infants: results through age 5 years from the infant health and development program.
JAMA.1994; 272
:1257
–1262
[Abstract/Free Full Text] - McCarton CM, Brooks-Gunn J, Wallace IF, et al. Results at age 8 years of early intervention for low-birth-weight premature infants: the infant health and development program.
JAMA.1997; 277
:126
–132
[Abstract/Free Full Text] - Schweinhart LJ, Barnes HV, Wiekart DP. Significant Benefits: The High/Scope Perry Preschool Study Through Age 27. Ypsilanti, Michigan: High/Scope Press; 1993
- Campbell FA, Ramey CT. Effects of early intervention on intellectual and academic achievement: a follow-up study of children from low-income families. Child Dev.1994; 65(2 Spec No) :684 –698[Web of Science][Medline]
- Reynolds AJ, Temple JA, Robertson DL, Mann EA. Long-term effects of an early childhood intervention on educational achievement and juvenile arrest.
JAMA.2001; 285
:2339
–2346
[Abstract/Free Full Text] - Lally JR, Mangione PL, Honig AS. Long-Range Impact of an Early Intervention With Low-Income Children and Their Families. Far West Lab for Educational Research and Development. San Francisco, CA: Center for Child & Family Studies; 1997
- Johnson DL, Walker T. A follow-up evaluation of the Houston Parent-child Development Center: school performance. J Early Intervention1991; 15 :226 –236
- Zoritch B, Robert I, Oakley A. Day care for preschool children (Cochrane Review). The Cochrane Library 2001; 3, Oxford: Update Software
- United States Department of Health and Human Services, Administration for Children and Families. Head Start Fact Sheet. Available at: http://www2.acf.dhhs.gov/programs/hsb/about/fact2001.htm. Accessed May 8, 2002
- Head Start Program Performance Measures: Longitudinal Findings From the FACES Study. Washington, DC: United States Department of Health and Human Services; 2000
- Love JM, Kisker EE, Ross CM, et al. Making a Difference in the Lives of Infants and Toddlers and their Families: The Impacts of Early Head Start; 2002. Available at http://www.acf.dhhs.gov/programs/core/ongoing_research/ehs/ehs_intro.html. Accessed September 5, 2002
- American Academy of Pediatrics, Committee on Early Childhood, Adoption and Dependent Care. Universal access to good-quality education and care of children from birth to 5 years.
Pediatrics.1996; 97
:417
–419
[Abstract/Free Full Text] - Task Force on Community Preventive Services. Community interventions to promote health social environments: early childhood development and family housing. MMWR Recomm Rep.2002; 51(RR-1) :1 –8[Medline]
- Claritas Corporation Homepage. Available at http://www.claritas.com/index.html. Accessed on May 5, 2002
- Green LW, Kreuter MW. Health Promotion Planning: An Educational and Ecological Approach. 3rd ed. Mountain View, CA: Mayfield Publishing Company; 1999
- Aday LA. Designing and Conducting Health Surveys. 2nd ed. San Francisco, CA: Jossey-Bass Publishers; 1996
- Brotherton SE, Tang SS, O’Connor KG. Trends in practice characteristics: analyses of 19 Periodic Surveys (1987–1992) of fellows of the American Academy of Pediatrics.
Pediatrics.1997; 100
:8
–18
[Abstract/Free Full Text] - Salant P, Dillman DA. How to Conduct Your Own Survey. New York, NY: John Wiley and Sons, Inc; 1994
- Zip Code RUCA Approximation Methodology, WWAMI Rural Health Research Center. Available at: http://www.fammed.washington.edu/wwamirhrc/methods.html. Accessed May 5, 2002
- Medicaid Eligibility. Health Care Financing Administration. Available at: http://www.hcfa.gov/medicaid/meligib.htm. Accessed March 7, 2002
- Scurletis TD, Dehuff Peters A, Robie WA. Attitudes of pediatricians toward day care.
Pediatrics.1966; 38
:44
–47
[Abstract/Free Full Text] - Guralnick MJ, Heiser KE, Eaton AP, Bennett FC, Richardson HB, Groom JM. Pediatricians’ perceptions of the effectiveness of early intervention for at-risk and handicapped children. J Dev Behav Pediatr.1988; 9 :12 –18[Web of Science][Medline]
- Asch DA, Jedrziewski K, Christakis NA. Response rates to mail surveys published in medical journals. J Clin Epidemiol.1997; 50 :1129 –1136[CrossRef][Web of Science][Medline]
- Cummings SM, Savitz LA, Konrad TR. Reported response rates to mailed physician questionnaires. Health Serv Res.2001; 35 :1347 –1355[Web of Science][Medline]
PEDIATRICS (ISSN 1098-4275). ©2003 by the American Academy of Pediatrics
CiteULike 
Connotea 
Del.icio.us 
Digg 
Facebook 
Reddit 
Technorati 
Twitter What's this?
This article has been cited by other articles:
|
|
 |
|
  R. L. Herman-Smith CAPTA Referrals for Infants and Toddlers: Measuring Early Interventionists' Perceptions Topics in Early Childhood Special Education, November 1, 2009; 29(3): 181 - 191. [Abstract] [PDF]
|
|
|
|
 |
|
 C. Kenyon, M. Sandel, M. Silverstein, A. Shakir, and B. Zuckerman Revisiting the Social History for Child Health Pediatrics, September 1, 2007; 120(3): e734 - e738. [Full Text] [PDF]
|
|
|
|
 |
|
 S. Cash Getting ahead in life: Pediatricians can help steer eligible patients toward Head Start program AAP News, March 1, 2006; 27(3): 16 - 16. [Full Text]
|
|
|
|
|
|
N. Sand, M. Silverstein, F. P. Glascoe, V. B. Gupta, T. P. Tonniges, and K. G. O'Connor Pediatricians' Reported Practices Regarding Developmental Screening: Do Guidelines Work? Do They Help? Pediatrics, July 1, 2005; 116(1): 174 - 179. [Abstract] [Full Text] [PDF]
|
|
|
|
 |
|
 M. Silverstein, C. Mack, N. Reavis, T. D. Koepsell, G. S. Gross, and D. C. Grossman Effect of a Clinic-Based Referral System to Head Start: A Randomized Controlled Trial JAMA, August 25, 2004; 292(8): 968 - 971. [Abstract] [Full Text] [PDF]
|
|
|
|
|
|
B. Zuckerman and N. Halfon School Readiness: An Idea Whose Time Has Arrived Pediatrics, June 1, 2003; 111(6): 1433 - 1436. [Full Text] [PDF]
|
|
| ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
