Validation of a McKinney-Vento Act Implementation Scale

Abstract

Objective: The McKinney-Vento Act (MVA) is the primary federal policy addressing homelessness in America with specific mandates designed to ameliorate the effects homelessness has on educational attainment for school-age children. The extent to which this policy is implemented may have far-reaching effects for homeless children. The MVA Implementation Scale (MVAIS) was developed for the purpose of providing a tool for assessing school-based social services personnel’s perceived knowledge and awareness of implementation of the MVA within their service areas. This study tests the factor structure, reliability, and validity of the 26-item instrument. Method: Data were collected from a purposive sample of school social workers (N = 201) attending a Mid-Western regional conference in order to examine the reliability and the validity of this measure. Results: The hypothesized factor structures were confirmed. Findings also indicated high levels of reliability among items, as well as initial evidence of instrument validity. Conclusion: Findings from this study indicate that the MVAIS adequately measures participant’s perceived implementation of the MVA. Future implications for research and practice are discussed.

Keywords

homelessness field of practice poverty psychometric study factor analysis instrument development validity study reliability study

Children account for 40% of the homeless population in the United States (Rukmana, 2008), and their number is expected to increase due to worsening economic trends throughout the country. Homelessness is often characterized as an experience of transience, moving from one location to another, which leads to a high rate of unplanned school movement accompanied by a host of educational problems (Julianelle & Foscarinis, 2003). School children experiencing homelessness perform poorly academically (Rafferty, Shinn, &Weitzman, 2004) along with being at high risk of attendance and behavioral issues (Miller, 2009).

The McKinney-Vento Act (MVA) is the major federal policy addressing homelessness in the United States. Since its incarnation in 1987, the policy has been expanded to include such disparate provisions as funding for shelters and veteran’s work programs (Biggar, 2001). However, at its core, the policy is designed to address the educational needs of homeless school-age children by upholding the right to equal educational opportunities for children and youth experiencing homelessness. To do this, the MVA contains provisions to ameliorate the barriers homeless children face in maintaining school enrollment while experiencing unstable living conditions (Biggar, 2001).

As a policy mandate, the MVA reduces challenges that homeless children face in maintaining school attendance due to high levels of mobility. This policy plays an important role by eliminating difficulties homeless children experience when returning to school after an extended period of absence or enrolling in a new school. Primarily the legislation allows children to remain in the school of origin during their homeless experience regardless of their families’ living arrangements or location. Because of the MVA, homeless children are further able to enroll in a new school without initially providing necessary documentation such as proof of immunization or previous school records. These and other necessary school enrollment items can be obtained at a later date. The MVA requires school districts to employ liaisons to serve as gatekeepers between a homeless child and the school, improving access to educational opportunities. Miller (2009) posits that school districts heavily rely on liaisons to provide services under the MVA. School social workers often serve as the designated school liaison for the policy’s implementation; they play an important role in the facilitation of provisions under the MVA at both micro and macro levels (Jozefowicz-Simbeni & Israel, 2006). Part of the duties of the homeless liaison includes posting information on the rights of homeless children to an education in places where those experiencing homelessness congregate. This is done to educate homeless families of the policy and their rights to education with the intention of creating awareness of the school. The dedicated liaison should also educate homeless families regarding the MVA’s provisions and their rights to educational access.

Because of the multiple challenges that homeless children face in attempting to attend school, the MVA is often cited within research literature as a reference to public policy that addresses the needs of homeless school children (Biggar, 2001; Jozefowicz-Simbeni & Israel, 2006; Rukmana, 2008). However, there is a dearth of information on the extent to which the MVA is being implemented. While provisions spelled out in the MVA are clearly delineated within the policy, awareness, implementation, and enforcement of its provisions are absent from the research literature.

We found no investigations examining the roles and responsibilities of school social workers who, at the local level, often serve as liaisons for implementation of the MVA. Of existing research, it appears that knowledge of and compliance with provisions within the MVA is lacking. For example, one study reported that levels of awareness concerning the MVA remain low among those designated as liaisons for the homeless (e.g., school social workers; Julianelle & Foscarinis, 2003). Evaluation of the MVA as a policy may hinge on appropriate understanding and assessment of the implementation of its provisions. Ascertaining the level of implementation for the MVA is necessary both for the fidelity of future evaluations, and more importantly, in facilitating our understanding of how well the policy works for homeless children.

Currently, no method exists to measure the implementation of the MVA. Given the growing ranks of homeless school-age children, investigations are needed to understand the extent to which the MVA has been implemented and to gauge the level of compliance with the policy’s provision. Understanding levels of compliance is important because it will give researchers some idea of how well the implementation of the MVA measures up to its intended purpose and/or how well the policy is working. Moreover, it will help determine whether funding levels are appropriate in making school-based social service personnel aware and knowledgeable of the policy’s provisions and in facilitating its enforcement.

Studies are also needed to determine the levels of implementation based on a given school district or geographic location. Systematic evaluations studies using a standardized instrument can be conducted within different regions allowing contrast and comparison across geographical locations. Inner-city, urban, suburban, and rural studies should be conducted to see how knowledgeable school-based social service workers are concerning the MVA. Such studies are particularly needed, given that scholars have referred to the MVA as an unfunded mandate (Biggar, 2001). Thus, initial studies can provide benchmarks for assessing levels of implementation. Finally, the development of a valid and reliable instrument for assessing perceived levels of implementation may facilitate our understanding of how the MVA as a policy affects school social work practice with regard to facilitating educational well-being among homeless children.

Thus, given the need to address the multiple challenges that homeless school-age children face, the research team examined the MVA’s policy provisions and developed an instrument that assesses related school services personnel’s knowledge of the policy’s implementation. The purpose of this article is to validate an instrument designed to measure the perceived implementation of the MVA through three hypothesized core constructs: preparation, accessibility, and collaboration.

Defining Core Constructs of the MVA

We contend that the MVA as a policy has three clear conceptual domains that spell out its implementation: preparation, accessibility, and collaboration. The proposed instrument, the MVA Implementation scale (MVAIS), aims to measure school services personnel’s perceptions of how well their service area adheres to or implements these three main constructs. This section provides conceptual definitions of each proposed domain of the MVA as a policy and as constructed in the MVAIS.

Preparation

Within the MVA, preparation is defined as having appropriate resources necessary to enact specific policies and procedures for working with homeless children made available to school personnel. Commenting on this policy provision, Johnston et al. (2005) contend that preparation is defined as taking steps to mitigate a circumstance that can be viewed as a risk to school attendance and effort for homeless school children (Johnston et al., 2005). In other words, preparation means the reduction of risk factors that impede the opportunity to attend school for homeless youth. To properly implement the MVA, each state and school district must prepare a documented plan for enrolling and preparing for the needs of homeless school-age children. Because homelessness can place children at risk of poor academic performance, delayed development, truancy, and a host of other academic challenges, the preparation component of the MVA is highly important to appropriate implementation of the policy in meeting the unique needs of homeless school-age children and youth.

Accessibility

Within the MVA, accessibility is defined as the extent to which a school makes education available to homeless children through geographic, economic, administrative, cognitive, and psychosocial means. Bertrand, Hardee, Magnani, and Angle (1995) posit that there are five aspects of accessibility: geographic, economic, administrative, cognitive, and psychosocial. The MVA addresses each of these areas. Geographic accessibility can be thought of as how a school makes itself physically available to homeless children. As necessitated by the MVA, compliance in this area is achieved through transportation assistance and residential requirement waivers (42 U.S.C. §§11432(g)(1)(I), (g)(7)). Economically, service areas must strive to eliminate cost barriers by providing free transportation or waiving enrollment fees. Initially, the legislation was designed to eliminate barriers stemming from administrative requirements to school enrollment. Administrative accessibility is achieved by eliminating requirements such as proof of residency or providing previous school records (42 U.S.C. §11432(g)(3)(C)). Provisions within the MVA mandate that schools allow homeless school-age children to enroll without proof of immunizations and that homeless children can remain in their school of origin without proof of residency. Cognitive accessibility refers to the extent to which a service area provides awareness to the rights and services available to homeless children. The extent to which a school decreases stigma and other negative psychosocial stressors defines psychosocial accessibility. As a whole, these measures are designed to increase educational accessibility among homeless school children (42 U.S.C. §11432(g) et seq.) and are thus embedded within the MVAIS.

Collaboration

Within the MVAIS, we defined collaboration as the extent to which service personnel’s agreement that their service area has policies and procedures that allow permit interaction with outside agencies. Because the primary function of the school is to socialize and educate, it often has to collaborate with social service agencies and organizations to provide services to children and youth in order to prepare them for school readiness (Hudson, Hardy, Henwood, & Wistow, 1999). The MVA specifically states that local school districts must collaborate with outside agencies to take care of homeless children’s school needs. Within the scale’s context, collaboration is contacting and utilizing outside agencies, ranging from homeless shelters to other programs that aid homeless children in obtaining an education. The policy requires schools to act in the best interest of children and to work with other organizations in serving homeless school children. This places the onus on school districts to seek services for homeless school-age children (42 U.S.C. §11432(g)(1)(J)(ii)). Including parents in the decision-making process in the best interest of the child is likewise a part of the collaboration and therefore strongly encouraged by the MVA.

Collaborative tasks related to school social service outreach are typically undertaken by school social workers (Jozefowicz-Simbeni & Israel, 2006). Their role is important in coordinating and collaborating services for homeless students who often lack resources, particularly when a given service area may not be equipped to address the needs of homeless children (Buckner, 2008). Contacting and utilizing other agencies, mental health referrals, and working with parents of homeless school children in order to coordinate services are responsibilities normally carried out by school social workers (Jozefowicz-Simbeni & Israel, 2006).

Method

Scale Operationalization and Development

The MVAIS was developed to measure policy implementation among a group of school social workers based on three constructs: preparation, accessibility, and collaboration. Items developed for the instrument stem from a review of the MVA and are therefore designed to measure perceptions of adherence to the policy based on respondents’ level of agreement with each item. Policy provisions were used to outline the core constructs in the development of an item pool. A list of provisions was created and an item pool was developed drawing from mandates in the legislation itself. Therefore, each item corresponds with different provisions described in the policy. Several social work and education researchers reviewed the item pool for content validity and duplication. For instance, Item 8, that is, “It is easy for a homeless child in my service area to: enroll in school without proof of immunization,” corresponds with the mandate to eliminate administrative barriers such as immunization records homeless children face when enrolling in school (42 U.S.C. § 11431, et seq.). Item 14 asks “How much do you agree with the following statements: My service area’s policies and procedures allow a student who became homeless in the middle of a school year to remain enrolled in the same school even if the student moved out of the service area,” which is intended to correspond to the provision allowing a homeless child to remain in his or her school of origin during his or her (use matching tense) experience of homelessness (42 U.S.C. §11432(g)(3)(G). Response options are the same across all items, and measured on a 5-point Likert-type scale: 1 = strongly disagree, 2 = somewhat disagree, 3 = neutral, 4 = somewhat agree, and 5 = strongly agree.

The instrument includes 26 items, divided into three sections to measure the proposed constructs of preparation, accessibility, and collaboration. The first section, Items 1–5, is designed to measure preparation. Because accessibility was thought to be the main aspect of the MVA, two subsections were devoted to this construct (see Items 6–13 and 14–19 in Appendix A). The first subsection used the stem “it is easy for a homeless child to:” and focused on accessibility for the homeless child. The second subsection dealt with actions that school homeless liaisons take to improve school accessibility for the homeless child. The final section, hypothesized to capture collaboration, included Items 20–26. When combined, these three constructs are hypothesized to measure perceived implementation of the MVA among school social workers.

Sampling

A purposive sample of individuals who self-identify as school social workers was obtained at the 2009 Illinois Association of School Social Workers (IASSW) annual conference held in October at a hotel in Arlington Heights, Illinois. As the largest organization of school social workers in the country, the IASSW annual conference provided an opportunity to recruit many school social workers in one setting. Conference attendees were school social workers from the State of Illinois who attended the conference as part of their professional development. Institutional review board approval was obtained prior to the commencement of this study. Two cash prize raffles of $100 and $50 were used as an incentive to improve participation. Each participant who completed the questionnaire received a raffle ticket. A drawing was held at the conference banquet and both prizes were awarded.

Results

Demographics

Two hundred one (201) completed questionnaires out of 497 distributed were returned for a 40% response rate. Each item used in the analysis had less than 2% missing data; casewise deletion was utilized because of the low amount of missing data. On average, each participant served 9.6 years in their service area (SD = 7.976). The respondents were predominantly female (92%) and had an MSW (97.5%; see Table 1). Licensure was divided across four response categories: none (30.8%), beginner (8%), intermediate (21.9), and advanced (37.8%). Three respondents (1.5%) left this question blank. The participants were mostly Caucasian (75.6%) followed by Black/African American (16.4%), Hispanic/Latino (6.5%), Other (1%), and Asian (0.5%).

Table 1.

Demographic Information

Gender (n = 201)	Percentage
Female	92
Male	8
Race (n = 201)
Asian/Pacific Islander	0.4
Black/African American	16
Hispanic/Latino	6
Caucasian	76
Other	21
Education (n = 201)
BSW	1
MSW	98
PhD in social work	0.4
Other	1
Licensure (n = 198)
None	31
Beginner	8
Intermediate	22
Advanced	38
Missing	1.5
Location (n = 199)
Urban/Inner City	23
Suburban	47.5
Rural	29.5
Missing	1
Years in service area	9.6 (SD = 7.976)

Note. BSW = bachelor of social work; MSW = master of social work.

Reliability

To assess the reliability of items developed for the instrument, a Cronbach’s α was calculated for each subscale area. Cronbach’s α provides an aggregate score of internal consistency to see how reliable items hold together that represent each proposed construct. The coefficients for each construct are as follows: implementation (α = .940), preparation (α = .870), accessibility (α = .906), and collaboration (α = .924, see Table 2). These scores were all above an accepted cut score of .8, indicating high levels of internal consistency (Abell, Springer, & Kamata, 2009).

Table 2.

Reliability Scores

	α	SEM
Preparation	.870	.322
Accessibility	.906	.262
Collaboration	.924	.257
Global	.940	.186

Note. SEM = standard error of measurement.

To assess the influence of individual items on the overall internal consistency and strengthen the argument for item inclusion, an alpha-if-item deleted score was also calculated. These scores indicate what the α score for a construct would be if the item were removed. If an alpha-if-item deleted score is above the original α, the item is considered for elimination. Two scores met this criteria, Item 1 in the preparation construct (Δ = .006), and Item 15 in the accessibility construct (Δ = .001). Because both items conceptually fit each construct, and the impact on the overall α was minimal, both items were kept.

Standard error of measurement (SEM) is also reported in Table 2. Ideally, SEM scores are less than 5% of the range (SEM/Range). The range for the global scale and three subscales was four, indicating that the three subscales are slightly higher than the 5% threshold, while the global scale SEM is less than that threshold. The coefficient α scores in addition to the relatively low SEM scores indicate the MVAIS and its subscales are reliable measurements for their respective constructs.

Confirmatory Factor Analysis

A confirmatory factor analysis (CFA) using LISREL version 8.8 was used to test the hypothesized model. We hypothesize that implementation of the MVA is made up of the three core constructs as identified in the policy: preparation, accessibility, and collaboration. Following conceptual definitions within the MVA, our goal was to see whether the constructed measures for each area were indeed representative of factor structures within the instrument. Thus, a CFA was initially selected because of our preconceived notion of the structure of conceptual domains forming the core constructs for the instrument. Using a CFA in this manner is consistent with the work of Abell, Springer, and Kamata (2009). The three-factor model included all 26 items separated into three constructs: preparation (5 items), accessibility (14 items), and collaboration (7 items).

Five fit indices, chi-square goodness-of-fit statistic, comparative fit index (CFI), Tucker Lewis Index (TLI), root mean square error of approximation (RMSEA), and standardized root mean square residual (SRMR), were used to evaluate the overall fit of this model. Initially, the three-factor model was determined to have a reasonable fit (See Table 3). A respecified model, created by correlating 23 error variances as recommended by the modification indices, improved model fit (see Table 3). There was acceptable fit with the initial model, but the respecified model improved model fit. Error variances were only correlated between items within a construct. For example, the error variance for a preparation item was not correlated with an item from accessibility. Because of the reliability evidence from both Cronbach’s α and alpha-if-item-deleted, we felt items within each concept were measuring the same construct and thus error variances would be related.

Table 3.

Model Fit Indices for Three-Factor Model

	Initial Model	Respecified Model*
Df	272	249
χ²	994.53**	497.45**
χ²/df ratio	3.656	1.998
RMSEA	.12	.06
TLI	.92	.97
CFI	.92	.97
SRMR	.1	.09

Note. CFI = comparative fit index; RMSEA = root mean square error of approximation; SRMR = standardized root mean square residual; TLI = Tucker Lewis Index.

*23 Error covariances are correlated.

**Significant at the .05 level.

The chi-square goodness-of-fit statistic tests the null hypothesis that both the covariance and the reproduced covariance matrix are the same (Abell et al., 2009). In order to reject this null hypothesis, therefore indicating a good fit, the ratio of the chi-square statistic and degrees of freedom should be small, around 2 or 3 (Abell et al., 2009). The initial model had 272 degrees of freedom and a chi-square statistic of 994.53 for a ratio of 3.66 (994.53/272 = 3.66). Through correlating error variances, the chi-square statistic and degrees of freedom were lowered to 497.45 and 249, respectively. This lowered the ratio to approximately 2 (497.45/249 = 2). Therefore, the null hypothesis that this model was a poor fit was rejected.

CFI and TLI are similar statistics. Values range from 0 to 1 for both indices, with higher scores indicating better fit. The two indices have the same cut scores, .9 for an acceptable fit, and .95 for an excellent fit (Hu & Bentler, 1999). For our initial model, a CFI value of .92, indicating a good fit, was improved to .97, an “excellent” fit in the respecified model. The TLI scores mirrored the CFI values, .92 for the original model, improved to .97 in the respecified model.

RMSEA values closer to 0 indicate better fit. The cut score of .08 is considered acceptable, while a score of .05 or below is considered a good fit (Hu & Bentler, 1999). The RMSEA was reduced from .12 to .06 through respecification, indicating an acceptable fit. The final index used, SRMR, assesses the difference between the data and a reproduced covariance matrix (Abell et al., 2009). Smaller scores for SRMR are desired. The respecified model resulted in a reduced SRMR score from .1 to .09, meeting the cut score of .1 (Abell et al., 2009).

Evidence of Convergent Construct Validity

The MVAIS is a novel scale for which we could find no counterpart in the literature. Consequently, evidence of convergent construct validity was examined using single-item indicators directly expressing the core definition of the target construct. The assumption is that single-item indicators measure on some level, the theoretical core construct. Therefore, the statistical significance of the relationship between single-item indicators and scale scores is used to confirm a convergent construct validity hypothesis rather than assessing the strength of the relationship. This study used three single-item indicators, one each for preparation, accessibility, and collaboration, on the same 5-point Likert-type score as the rest of the measure. Several other variables thought to be related to implementation of the MVA were also examined for convergent construct validity, including years in service area, frequency of policy involvement, awareness of the needs of homeless children, awareness of homeless policy, frequency of interaction with homeless children, and magnitude of homelessness in the service area. Hypothesized relationships between these single-item indicators, other variables, and the mean scores for each construct were tested using Pearson’s r correlations. For these hypotheses, the strength of the relationship is not necessarily as pertinent as the significance.

Preparation

For preparation, respondents were given the statement: My service area is prepared for the needs of homeless children, and asked to rate their level of agreement. When examined, the scores for the single-item indicators and the preparation construct were positively correlated (r = .500, p < .05, see Table 4). The single-item indicator accounted for 25% of the variance in the preparation score (r ² = .25). Years in service area, awareness of the needs of homeless children, awareness of homeless policy, frequency of interaction with homeless children, and magnitude of homelessness in the service area were all significantly correlated with the preparation mean scores; however, the frequency of policy involvement was insignificantly related to preparation.

Table 4.

Evidence of Convergent Construct Validity: Preparation

	Preparation
	r	r ²
Years in service area	.145*	.021
Frequency of policy involvement	−.083**
Awareness of the needs of homeless children	.407*	.166
Awareness of homeless educational policy	.383*	.147
Frequency of practice interaction with homeless children	.236*	.056
Magnitude of homelessness in service area	.212*	.045
Preparation single-item indicator	.500*	.25
Accessibility single-item indicator	.536*	.287
Collaboration single-item indicator	.469*	.22
Mean convergent hypothesis correlations	.330	.133

Note. r ² not calculated for insignificant r.

*p < .05. **p > .05.

Accessibility

The accessibility single-item indicator used the statement: My service area has policies and procedures to make school accessible for homeless children with the same Likert-type scale response options as the items for the construct. This was significantly correlated with accessibility (r = .611, p < .05). The other variables used for convergent construct validity (see Table 5), except for awareness of the needs of homeless children, were significantly correlated (p < .05) with the accessibility subscale.

Table 5.

Evidence of Convergent Construct Validity: Accessibility

	Accessibility
	r	r ²
Years in service area	.164*	.03
Frequency of policy involvement	−.154*	.02
Awareness of the needs of homeless children	.297*	.09
Awareness of homeless educational policy	.310*	.09
Frequency of practice interaction with homeless children	.257*	.07
Magnitude of homelessness in service area	.234*	.06
Preparation single-item indicator	.523*	.27
Accessibility single-item indicator	.611*	.37
Collaboration single-item indicator	.410*	.17
Mean convergent hypothesis correlations	.329	.11

Note. *p < .05.

Collaboration

Collaboration was examined for convergent construct validity using the item: My service area has policies and procedures to collaborate with outside agencies. The single-item indicator, along with several other variables, was significantly correlated with this construct (p < .05, see Table 6). Years in service area and magnitude of homelessness were insignificantly correlated with collaboration (p > .05).

Table 6.

Collaboration Concurrent Validity

	Collaboration
	r	r²
Years in service area	.083	.01
Frequency of policy involvement	−.174*	.03
Awareness of the needs of homeless children	.148*	.02
Awareness of homeless educational policy	.157*	.03
Frequency of practice interaction with homeless children	.121**
Magnitude of homelessness in service area	.07**
Preparation single-item indicator	.436*	.19
Accessibility single-item indicator	.270*	.07
Collaboration single-item indicator	.460	.21
Mean convergent hypothesis correlations	.213	.05

Note. r ² not calculated for insignificant r.

*p < .05. **p > .05.

Implementation

The global construct, implementation, was examined for convergent construct validity. The 26 items across the three constructs were summed, and these scores were examined using the same variables and each single-item indicator as the three previous subscales. Each relationship (see Table 7) was significantly correlated with the global implementation construct (p < .05). Overall, the significant Pearson scores demonstrate predicted associations between the indicators and the constructs, thus providing initial evidence of convergent construct validity.

Table 7.

Global MVAIS Concurrent Validity

	Global
	r	r ²
Years in service area	.154*	.024
Frequency of policy involvement	−.164*	.027
Awareness of the needs of homeless children	.334*	.112
Awareness of homeless educational policy	.335*	.112
Frequency of practice interaction with homeless children	.241*	.058
Magnitude of homelessness in service area	.201*	.04
Preparation single-item indicator	.577*	.333
Accessibility single-item indicator	.556*	.309
Collaboration single-item indicator	.532*	.283
Mean convergent hypothesis correlations	.343*	.153

Note. MVAIS = McKinney-Vento Act Implementation scale.

*p < .05.

Evidence of Discriminant Construct Validity

Considered the counterpart to convergent construct validity, discriminant construct validity also examines hypothesized relationships. However, discriminant construct validity hypotheses examine relationships among variables proposed not to correlate significantly with target construct scores to further display that the instrument is measuring the intended constructs. That is, if the included items are measuring what they are intended to measure, they should not be significantly correlated with variables that are theoretically unrelated to them. Table 8 displays the results of this analysis. Number of grades, schools, and students served were all insignificantly correlated with the three subconstructs and the global implementation construct. This analysis gives further preliminary evidence that the MVAIS is measuring the intended concepts. Our hypotheses on factor structure and reliability and validity were confirmed, providing initial evidence that the MVAIS is a valid and reliable instrument.

Table 8.

Discriminant Construct Validity Evidence

	Preparation	Accessibility	Collaboration	Global
Number of grades served	.103	.001	.039	.058
How many schools do you serve in your service area?	.057	.014	.060	.052
Approximately how many students do you serve per week?	.017	.019	−.014	.009
Mean discriminant hypothesis correlations	.11	.011	.0	.029

Note. All scores are correlation (r).

Discussion

The psychometric properties reported here provide initial evidence that the MVAIS measures perceived implementation of the MVA policy provisions with regard to preparation, accessibility, and collaboration. Our hypotheses on reliability, factor structure, and construct validity were confirmed, and provide evidence that the MVAIS is a sound instrument for use by school social workers for understanding their perceptions of the MVA implementation in their services areas.

Scale Scoring and Interpretation

This study presents the psychometric analysis and findings for the MVAIS. For eventual use in practice, scale scoring ranges must be determined. It is intended that mean scores should be used in an assessment of global scale scores and for the assessment of each of the three subscales. Because of the differing number of items in each scale there is a need to standardize the scores across the three subscales. Once mean scores are established for each subscale, the range would be 1–5, with higher scores indicating higher levels of implementation, preparation, accessibility, or collaboration. Patterns may then form providing information for review and analyses concerning the dynamics of respondents’ perceptions of the MVA’s implementation.

Limitations of the Study

There are several limitations to this study. First, the purposive sample used for the study is from one geographical location and therefore does not fully represent school social work personnel. Furthermore, the use of survey methodology limits our understanding because it only provides information on respondents’ perceptions of their experiences and knowledge. Thus, the findings from this investigation reflect the perceptions of self-identified school social workers who returned the survey, all assumed to be from one state. Those who did not attend the conference, those who did not receive a survey, or those who did not return a survey may have different perceptions of the MVA as policy implemented in their workplace. Second, because this is the initial validation study, normative cut scores could not be established to determine the meaning of a given respondent’s scores in relation to a known comparison group. At this point, mean scores are intended to be used for each subscale, as well as for the global scale. Higher scores indicate higher levels of preparation, accessibility, collaboration, or implementation. Future research within diverse geographical locations (and objective indicators of the MVA’s implementation) will help solve both of these challenges.

Future research studies evaluating the implementation of the MVA should include further reliability and validity testing of this instrument, including studies using nonsocial work samples. This instrument is intended to measure perceptions of policy implementation for related service personnel in addition to school social workers. Different, but related services personnel such as guidance counselors, school psychologists, or even school administrative staff may all play a role in enrolling homeless school children. This scale may have utility with those serving in related fields. As such, testing should be conducted to confirm these results with those populations. Additional indicators of construct validity must also be sought. However, to do so, program evaluation studies that use this measurement tool will be necessary in order to identify levels of policy implementation.

Implications for Research and Practice

The findings from this study provide initial evidence of reliability and validity for the MVAIS. Future studies should continue the validation efforts initiated by this investigation. The MVAIS can be used as a predictor variable in future studies using outcomes such as truancy rates, number of absent days from school, declaration of homelessness, and days between school enrollment and other intended outcomes of the MVA. For example, areas with higher levels of compliance with provisions within the MVA should have lower rates of days absent from school for homeless youth. The MVAIS may allow researchers to determine policy compliance and enforcement within a given school district. This may facilitate answering some burning public policy questions by researchers: Is the MVA being implemented appropriately at current funding levels? Or, is the MVA an underfunded policy mandate? (Biggar, 2001).

This study demonstrates constructs related the implementation of the MVA in practice with homeless children in schools. Preparation, accessibility, and collaboration are aspects of the MVA’s implementation that must be addressed by school districts with homeless school children. The relationship between these constructs and how they relate to real-world consequences is important in developing future theories and practice models for school social work practice with homeless school children. Potentially, continuation of research on the MVAIS will better facilitate the design and development of school-based services for homeless children and youth. While this study may not provide findings which confirm or test theory, given that its design is tailored to the conceptual provisions outlined within the MVA, findings from the use of the MVAIS will help policy makers and practitioners understand the underlying concepts that are key to implementation of the MVA. Thus, the MVAIS may be instrumental in the policy evaluation process.

The development of this tool could have important utility both in practice evaluation and in understanding how the MVA as a policy influences practice with homeless school-age children. The intended use of this measure is to provide a tool for understanding social service practitioner’s perceptions on implementation of the MVA and core policy provisions as they pertain to school access for homeless children and youth. We intend this measure to be used by school district administrators, teachers, and related service personnel to assess individual and group levels of readiness, preparation, and knowledge of challenges related to educational access for homeless children and youth. Furthermore, the instrument may facilitate collaborative efforts and guide in-service training and professional development for related service personnel to facilitate the development of knowledge concerning the of policy’s provisions.

The MVAIS may be used on a larger scale to determine implementation of the MVA across states and geographical regions. Though further study is needed to confirm these findings across different regions, this measure may provide a standardized method to gauge the perceived level of implementation across geographical locales and different school types (public, charter, etc). Because most studies on the MVA are descriptive in nature, instruments that measure levels of policy implementation would drastically improve both the knowledge base, and more importantly, inform professional development for school social worker. Future studies should focus on barriers and facilitators to implementation of the MVA. Determining this will improve a practitioner’s ability to serve this population. A richer picture of practice with homeless children can be developed as well as future suggestions for research and policy analysis.

Footnotes

Appendix A

The authors declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

The authors received no financial support for the research, authorship, and/or publication of this article.

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