Evaluation of the 215GO! Child Obesity Program in the Philadelphia Health Centers

Abstract. Background: Early identification and appropriate referral services are priorities to prevent suicide. Aims: The aim of this study was to describe patterns of identification and referrals among three behavioral health centers and determine whether youth demographic factors and type of training received by providers were associated with identification and referral patterns. Method: The Early Identification Referral Forms were used to gather the data of interest among 820 youth aged 10–24 years who were screened for suicide risk (females = 53.8%). Descriptive statistics and binary logistic regressions were conducted to examine significant associations. Results: Significant associations between gender, race, and age and screening positive for suicide were found. Age and race were significantly associated with different patterns of referrals and/or services received by youths. For providers, being trained in Counseling on Access to Lethal Means was positively associated with number of referrals to inpatient services. Limitations: The correlational nature of the study and lack of information about suicide risk and comorbidity of psychiatric symptoms limit the implications of the findings. Conclusion: The results highlight the importance of considering demographic factors when identifying and referring youth at risk to ensure standard yet culturally appropriate procedures to prevent suicide.

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Optimal Experimental Design With Nesting of Persons in Organizations

Zeitschrift für Psychologie ◽

10.1027/2151-2604/a000143 ◽

2013 ◽

Vol 221 (3) ◽

pp. 145-159 ◽

Cited By ~ 1

Author(s):

Gerard J. P. van Breukelen

Keyword(s):

Repeated Measures ◽

Optimal Number ◽

Health Centers ◽

Randomized Experiments ◽

Optimal Sample ◽

Treatment Conditions ◽

Sampling Cost ◽

Nested Designs ◽

Simple Equations ◽

Number Of Individuals

This paper introduces optimal design of randomized experiments where individuals are nested within organizations, such as schools, health centers, or companies. The focus is on nested designs with two levels (organization, individual) and two treatment conditions (treated, control), with treatment assignment to organizations, or to individuals within organizations. For each type of assignment, a multilevel model is first presented for the analysis of a quantitative dependent variable or outcome. Simple equations are then given for the optimal sample size per level (number of organizations, number of individuals) as a function of the sampling cost and outcome variance at each level, with realistic examples. Next, it is explained how the equations can be applied if the dependent variable is dichotomous, or if there are covariates in the model, or if the effects of two treatment factors are studied in a factorial nested design, or if the dependent variable is repeatedly measured. Designs with three levels of nesting and the optimal number of repeated measures are briefly discussed, and the paper ends with a short discussion of robust design.

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