Examining barriers and strategies for effective professional or interagency collaboration in secondary transition

Abstract

BACKGROUND:

For young adults with disabilities, post-high school outcomes in employment, higher education, and independent living are markedly worse than for peers without disabilities. As a result, legislation and research aimed at supporting transitioning students with disabilities has increased. Further, numerous initiatives that better support youth and families have been implemented at the state and local level. Collaboration within and across service delivery systems has been identified as a critical aspect of transition planning and supports; however, evidence-based research related to the implementation and effects of collaborative partnerships is limited.

OBJECTIVE:

In the current study, we identify transition professionals’ perceptions of collaborative factors that facilitate and inhibit collaboration.

METHOD:

This study utilizes a single-state survey research design to examine the viewpoints of people in transition professions, specifically educators, Vocational Rehabilitation professionals, and community supports providers.

RESULTS:

Variances in perceptions were found among participant role groups. Specifically, educators as a whole report that time and workload barriers affect their ability to collaborate effectively. Further, findings indicate that ensuring individual collaborative team member responsibility is perceived as an effective strategy.

CONCLUSIONS:

These findings may be applied to technical assistance providers when developing team-level evaluations to monitor current levels and support needs of collaborative transition planning teams.

Keywords

Secondary transition interagency collaboration

1 Introduction

Schools and education systems play a significant role in preparing youth to obtain and maintain employment and to enroll in postsecondary education. Young people with disability, however, are less likely than their peers without a disability to obtain a high school diploma, to pursue postsecondary education, and to remain in stable employment through their adult lives (Luecking & Luecking, 2015; U.S. Department of Labor, 2017). Findings from the National Longitudinal Transition Study of Special Education Students 2 (NLTS2) show that youth with disability are less likely to be enrolled in or to have completed postsecondary education, less likely to live independently, and are shown to earn lower wages/salary than their non-disabled peers (Newman et al., 2011; Erickson et al., 2016). These less than desirable outcomes for students with disability underscore the critical nature of secondary transition planning. While research of evidence-based practices and promising programs targeting the improvement of these outcomes is growing, the disparity in outcomes continues to exist, and continued work is needed to improve transition planning efforts (Test et al., 2016).

As students with disability move through the public school system, they are provided rights and legal protections safeguarding their education, including access to and development of an Individualized Education Program (IEP). The IEP process is driven by a team of stakeholders (including a special educator, general educator, district representative, parent, related service providers, the student, and any additional advocates or support personnel as needed) who meet annually to review students’ progress and goals to ensure services are based on students’ individual strengths and needs (Yell, 2012). When students exit public schooling, however, states and school districts have recognized gaps for students and families as they move from the special education entitlement model of services to an adult services eligibility model (Brown et al., 2017; Plotner et al., 2012). Planning for the transition from secondary school settings to post-school life involves multiple stakeholders from a number of agencies (Brown et al., 2017). Ideally, stakeholders collaborate to ensure that students have the skills and supports necessary to achieve their goals.

The U.S. Department of Education Office of Special Education Programs, (OSEP) Vision for Targeted and Intensive Technical Assistance (2015) defines collaboration as “entities, projects, or stakeholders working together to achieve a common goal through shared resources and responsibilities.” The National Technical Assistance Center on Transition (NTACT) further specifies components of this definition relevant to the field of special education transition, adding that interagency collaboration efforts seek to cross agencies, programs, and disciplines to lead to tangible transition outcomes for youth (Rowe et al., 2015). Essentially, collaboration consists of team members or agencies working together toward a stated goal or vision (Oertle & Seader, 2015). Collaboration and coordination among stakeholders are recognized as promising practices and predictors of improved outcomes (Kohler et al., 2016; Trainor et al., 2020; Test et al., 2016), however, no clear directive or outline for implementing interagency collaboration exists.

Any agency that could support or be responsible for providing relevant transition services for the student(s) should be invited to participate in transition planning meetings (Plotner , 2017). Typically, members on interagency teams include representatives from local education agencies (LEAs) such as special educators, transition specialists, and special education administrators. Additionally, special education students and their families are integral members of the individual student-level transition planning team (Plotner , 2017). Vocational Rehabilitation (VR) counselors, or Transition VR Counselors, whose caseloads are at least 50%transition-age youth, are also integral members of the student and district level transition planning teams, as they provide links to post-high school vocational services such as career preparation experiences and resource allocation (Plotner, Trach, & Shogren, 2012).

Further highlighting the need for effective collaboration between VR and schools is the implementation of the Workforce Innovation and Opportunity Act of 2014 (WIOA). This act provides for strategic coordination among employment training services for adults and youth through the Department of Labor, as well as VR state grants to assist individuals with disabilities through the Department of Education (U.S. Department of Labor, 2018). WIOA mandates that state VR agencies set aside 15%of their funding to provide transition services such as pre-employment training services to youth with disabilities (U.S. Department of Labor, 2018). To effectively allocate this funding requires active involvement between VR and school districts in order to identify funding needs and potential training and/or supports for transitioning students.

Additional community agencies that are less frequently included in transition collaboration research, but which can provide guidance for transition services at the state, district, or individual student level, are representatives from Centers for Independent Living (CILs). WIOA mandates that CILs implement youth transition services for school-aged individuals with disability. Additionally, CILs can aid in providing individual and system advocacy, peer mentoring, independent living training, and information and referral services (Plotner , 2017). Effective interagency collaboration, among VR, CILs, school districts, and individuals with disability, can seek to maximize these services for youth.

While components of various collaboration models address the importance of developing and allocating resources from multiple stakeholders, there is little research on the effectiveness of teams examining their collaborative activities and applying evaluation results (Erickson et al., 2015). Perceptions of barriers and strategies for collaboration can vary depending on the design and make-up of the collaborative group, the stakeholders’ levels of experience, and the perceived roles of each member and agency. Although various strategies designed to simplify the collaboration process exist, the current research in effective implementation and evaluation of interagency collaboration for secondary transition planning is limited. In addition to establishing a working model of interagency collaboration, research has also shown professionals have difficulty maintaining effective interagency collaboration among stakeholders responsible for helping plan for successful post-high school student outcomes (Lueking & Lueking, 2015; Plotner et al., 2012).

Collaboration strategies include working to learn about other agencies’ terminology, regulations, and members’ respective roles and responsibilities. Additional studies identify strategies such as joint trainings for VR and school, and training for teachers on the transition process and specific role of VR professionals (Taylor et al., 2016). A collaborative team’s capacity is influenced by both the skills and knowledge brought by its individual members, as well as the members’ attitudes and willingness to grow in their collaborative abilities through targeted technical assistance and other professional development. Through an extensive literature review of studies focused on collaborative teams with multiple stakeholders, Foster-Fishman et al., (2001) present a framework for targeted skill-development in areas including (a) building team-member collaboration capacity (e.g. technical assistance training, orientations, logistical support for meeting attendance) (b) relational capacity (e.g. effective communication systems, access to human and financial resources), and (c) program or organizational capacity (e.g. strong leadership roles, formal meeting processes, defined member roles, plan for team evaluations).

Oertle and Trach (2007) discuss barriers to effective collaboration, such as poor relationship-building at the school team level, lack of communication between teachers and VR professionals, poor meeting preparation, lack of coordinated referrals, lack of knowledge of the needs of young adult clients, and little collaboration on student goals or instructional plans between special educators and VR providers. These barriers can lead to confusion among stakeholders, missed opportunities, and a loss of valuable transition preparation time for students. When this lack of collaboration occurs, “special education and community rehabilitation, parallel systems, operate independently rather than interdependently,” (p. 40), and youth are less informed and prepared to receive the services they need for successful transitions (Oertle & Trach, 2007).

There has also been discussion around how roles affect collaboration efforts. Oertle, et al. (2013) found that VR professionals report a need for more than their current interagency collaboration levels in order to effectively support youth who are still receiving educational services. They identify the need for involvement in transition planning beyond participating in goal-setting and job matching activities with youth. Perhaps most compelling was the consistent response from all providers of their view that special educators were the most appropriate people to distribute materials, invite rehabilitation professionals to meetings, and provide meeting management. However, a subsequent relevant study found that teachers report having unclear understanding of transition agency/stakeholder roles and report not taking the lead in accomplishing transition tasks or coordinating services as often as VR counselors or district transition specialists (Plotner , 2017). In sum, rehabilitation professionals indicate the need for more active participation, yet rely on educators to initiate that participation (Oertle et al., 2013), while teachers report that they do not typically take the lead in coordinating transition plans (Plotner , 2017).

In a review of the literature relating to interagency collaboration of teams working with transition age youth, Moore & Lammert (2017) report that of the limited empirical research in this area, what does exist is mostly qualitative. This research, they report, is typically focused on internal team dynamics rather than studies of collaboration and any resultant outcomes at the individual or systems level (Moore & Lammert, 2017; Noonan et al., 2012). Additionally, research on the effectiveness of specific collaboration models or interventions to increase collaboration at various levels of teaming is also scarce (Noonan et al., 2012).

While components of various collaboration models address the importance of resource development and allocation of multiple stakeholders, there is little research on the effectiveness of teams examining their collaborative activities with commensurate evaluative activities. The perceptions of strategies and barriers of collaboration can vary depending on the design and make-up of the team, stakeholders’ levels of experience, and the perceived roles of each member and agency. Although various strategies designed to simplify the collaboration process exist, the current research in effective implementation and evaluation of interagency collaboration for secondary transition planning is limited. In fact, a number of states have transition collaboration initiatives aimed at facilitating greater collaboration, thus, minimizing inhibitors of collaboration; however, the structure and goals of these initiatives vary. It is important that new research examines collaboration under these current initiatives, as published details of current practices are lacking. Therefore, the purpose of this study is to explore professionals’ perceptions of factors that contribute to effective interagency collaboration in transition planning for individuals with a disability. The current study utilizes survey research to examine the viewpoints of transition professionals in one southeastern state. The research questions for this study are as follows:

What do transition professionals indicate as the foremost barriers to effective collaboration?

What do transition professionals indicate as the most effective strategies for successful collaboration?

Do transition professionals’ perceptions of the components of collaboration vary based on their professional roles?

2 Methods

2.1 Sample and procedures

South Carolina (SC), the participating state for this study, has approximately 763,000 students across 85 public school districts. Thirteen percent of students in SC have an identified disability (U.S. Department of Education, 2018). South Carolina supplements federal Individuals with Disabilities Education Improvement Act (2014) regulations by requiring that students receive transition planning services and a transition-focused Individualized Education Program (IEP) by their 13th birthday. Federal regulations require transition programming by the age of 16 (Yell, 2012). In addition to federally mandated transition planning for individual students, SC has developed The Transition Alliance of South Carolina (TASC), a state-funded initiative to help districts develop and sustain effective interagency transition planning teams through various trainings and conferences focused on promoting effective collaboration strategies. At the time of this study, 59 of the 85 districts in SC participated in TASC programming. As such, the impact of these trainings should be noted. TASC is mentioned here because their training focus aligns with much of the content and direction of this study, and the impact of this program on transition programs in SC may be unique from other states.

To be included in this study, participants must have self-identified as working directly or indirectly serving transition-age youth with disability (ages 13–21). Potential participants in the survey included: special educators, special education administrators, special education transition specialists, state Vocational Rehabilitation (VR) professionals, Department of Disabilities and Special Needs (DDSN) representatives, community agency representatives (such as case management providers and adult service providers), and Centers for Independent Living (CIL) representatives. Sampling techniques consisted of direct contact sampling and snowball sampling (Mertens & Wilson, 2012). Special education district administrators, state VR coordinators, DDSN transition coordinators, the state Council for Exceptional Children, and CIL representatives were directly contacted through their email addresses listed on their agency websites, and were requested to forward the survey link to individuals in their agencies who currently serve transition-aged youth (ages 13–21), or who serve on district-level transition planning teams. The last method of participant recruitment consisted of direct email contact of district interagency team members identified from contact lists submitted to the TASC with a request to forward the survey to others in their agency serving transition-age youth with disability. Potential participants received an emailed description of the study and explanation of the linked survey. After a two-week period, participants received a reminder email and survey link to further encourage participation in the survey (Dillman, 1978) and after eight weeks, the survey window closed.

These methods sought to reach most transition professionals within the state; however, due to the use of multiple methods, precise response rates were challenging to determine. A previous study targeting like participants in South Carolina, which used similar sampling methods, obtained response rates near 55%(Plotner , 2017). A total of 240 survey responses were submitted through the online tool, of which 210 were found to be usable based on the completeness of the submission. Before analysis, the participants were grouped into categories based on the roles selected within the Demographics section. Participants were grouped by field (education, VR, and Community Providers) in order to more easily aggregate groups’ responses for analysis. Special education teachers, special education district personnel, and special education administrators were grouped together into an Educators category; VR counselors, transition specialists, and other personnel were grouped together into a VR category; DDSN representatives, Centers for Independent Living (CIL) representatives, and other community-based providers were grouped together into a Community Providers category. Detailed demographic information organized by respondent group is presented in Table 1.

Table 1
Survey participants role groupings (N = 210)

Role n Percent

Educator Group (n = 158, 75.2%)

Middle School Special Education Teacher 25 11.9

High School Special Education Teacher 63 30.0

Special Education Transition Coordinator 16 7.6

Special Education Administrator 54 25.7

VR Group (n = 29, 13.8%)

VR Counselor 16 7.6

VR Transition Specialist 13 6.2

Community Provider Group (n = 23, 11.0%)

DDSN Representative 7 3.3

CIL Representative 6 2.9

Community Agency Representative 10 4.8

Total Participants 210 100.0

Role	n	Percent
Educator Group (n = 158, 75.2%)
Middle School Special Education Teacher	25	11.9
High School Special Education Teacher	63	30.0
Special Education Transition Coordinator	16	7.6
Special Education Administrator	54	25.7
VR Group (n = 29, 13.8%)
VR Counselor	16	7.6
VR Transition Specialist	13	6.2
Community Provider Group (n = 23, 11.0%)
DDSN Representative	7	3.3
CIL Representative	6	2.9
Community Agency Representative	10	4.8
Total Participants	210	100.0

Note: VR = Vocational Rehabilitation, DDSN = Department of Disability and Special Needs, CIL = Center for Independent Living.

2.2 Instrumentation

The survey instrument was developed specifically for this study. First an initial draft of the items was compiled from the relevant literature of research specific to barriers and strategies for effective collaboration in secondary transition, as well as survey design and development literature (e.g., Johnson & Morgan, 2016; Oertle & Trach, 2007; Plotner , 2017; Plotner & Shogren, 2012). Second, ten special education and transition professionals were asked to utilize a review rubric to provide general feedback on the readability and organization of the survey tool. After edits were made, another content review was conducted where three Master’s and PhD level transition experts were asked to review and provide a critique of the survey items, item organization, and presentation of items. Throughout each stage, suggestions for changes were considered and applied as necessary based on input from the identified reviewers. Combined, these review phases aimed to increase the usability of the instrument for the participants, and the data applications for the researcher (Haladyna & Rodriguez, 2013).

Based on the feedback from the three review phases, the final instrument, Interagency Collaboration for Transition Planning Survey, was disseminated to participants through Sampling Methods described above. The survey consisted of 42 question items organized within the following sections and subsections: 1. Personal and Professional Demographics and 2. Collaborative Components (Strategies, Barriers).

2.2.1 Section 1: Demographic items

The Personal and Professional Demographics section of the survey included 11 total items aimed at gathering personal demographic information (age, gender, education level, professional certifications, current professional role, years of experience with transition-age youth with disability), and professional demographics (number of districts and schools served, primary work setting, approximate portion of their work time that is spent with transition-age youth with disability).

2.2.2 Section 2: Collaboration components

The Collaboration Components section consisted of a total of 31 survey items across the two subsections: Strategies for Successful Collaboration and Barriers to Collaboration.

Strategies for successful collaboration. This subsection asked participants to complete Likert-like scale rankings indicating levels of agreement with 13 statements related to strategies for effective collaboration. Participants rated their opinions on the importance of collaboration strategies using the selection options of Not at all important, Minimally important, Moderately important, Significantly important. Strategies assessed included: use of an agenda, discussing agreed-upon topics, ensuring leadership, maintaining focus, pooling of resources, ensuring common values, accountability, understanding of member roles, minimizing turn-over, ensuring adequate work time, effective communication among partners, and ensuring group goals align with agencies’ goals.

Barriers to collaboration. This subsection consisted of items on participant perceptions of barriers to effective collaboration. Participants utilized a Likert-like scale response (Significant barrier, Moderate barrier, Minimal barrier, Not a barrier at all) to indicate their perceptions of barriers described in 18 item statements. Barriers assessed included issues such as: scheduling conflicts, lack of agenda, lack of leadership, poor focus, lack of resource-sharing, lack of common values, lack of collaborator availability, poor follow-through on tasks, lack of accountability, lack of knowledge of own or other agencies’ services, lack of training in collaboration, turn-over of collaborative partners, lack of work time, poor communication among partners, lack of agency support, and lack of alignment with agencies’ goals.

A value for Cronbach’s alpha was calculated to indicate the internal consistency for survey items (Cronbach, 1951) in the Strategies and Barriers subsections. The Strategies subscale consisted of 13 items (α= 0.90), while the Barriers subscale consisted of 18 items (α= 0.96). This indicates that the survey may be viewed as reliable.

2.3 Data analysis

Survey participant role groupings are presented in Table 1. Survey response data was uploaded into the Statistical Package for Social Sciences (SPSS) software program which was utilized for all analyses described below. Missing data points equaled fewer than 15%of all data. Therefore, missing values were replaced using the SPSS procedure for continuous data replacement, utilizing the mean scores from all other participants for the missing survey item data (George & Mallery, 2014).

In order to answer research questions 1 and 2, descriptive statistics were used. To simplify and analyze data at the domain level, an exploratory factor analysis (EFA) was performed. The purpose of EFA is to flag correlations among measured variables and reduce them to a set of parsimonious representations, known as domains or factors, based on the mea-sured variables (Fabrigar et al., 1999). For the purpose of this study, EFA was appropriate as the data obtained from the Barriers and Strategies subsections are categorical-level data (Norris & Lecavalier, 2010). Reducing this data into factors based on patterns of correlations reduced the number of analyses required among the dependent variables (survey responses), and the independent variables identified in the research questions. The resulting factors identified from each of the EFAs were further examined using a scree-plot to confirm that the appropriate number of factors had been identified from each subsection. A scree-plot results in a graph of the eigenvalues from each of the identified factors in descending order, allowing for a visual analysis of the data. The last sharp drop in values (the “elbow”) represents the number of factors that should be retained (Norris & Lecavalier, 2010). Finally, depending on the resulting total variance represented by the identified factors from each subsection, various rotations were attempted to maximize the variance. Inclusion criteria was based on the following decision rules: factors loading lower than 0.40 can be removed or moved from a domain; factors loading 0.40 on more than one domain can be removed or moved from a domain; factors not identified within a domain but considered a key defining construct can be considered for inclusion in a domain (Beavers et al., 2013). Once the EFA was conducted and relevant factors were identified for each subsection, the resultant factors were utilized to address the research questions as discussed in the following sections.

In order to answer research question three, an analysis of variance (ANOVA) was performed. Specifically, to determine whether transition professionals’ perceptions of the components of colla-boration vary based on their professional roles, the resultant factors from the previously performed EFAs were analyzed using a Kruskal-Wallis one-way ANOVA, with the Barriers and Strategies domains as dependent variables and the role groups (Educators, VR, and Community Providers) as the independent variable. Kruskal-Wallis was selected because the dependent variable, perceived impacts of Barriers and Strategies, was ordinal level.

3 Results

3.1 Research question 1: What do transition professionals indicate as most prevalent barriers to effective collaboration?

Participants reported the prevalence of barriers through a Likert-like scale response (Not a barrier at all- 4, Minimal barrier-3, Moderate barrier- 2, Significant barrier- 1). The most challenging barriers to successful collaboration were indicated by the lowest scores.

3.1.1 EFA: Barriers

The data within the Barriers subsection was determined adequate and appropriate for EFA as the Kaiser-Meyer-Olkin Measure of Sampling Adequacy was 0.939 (above the recommended 0.60 threshold), and the Bartlett Test of Sphericity determined a significance value of < 0.05. Principal components analysis was used to identify and reduce the variables (18 survey question items) into underlying factors usable for further inferential testing. Initially, extraction was set for four factors; however, upon review of the resulting scree plot showing an “elbow” between two to three factors, extraction for this number of factors was also programmed. Following manual review of the resulting matrices for logical item placement and parsimony, it was determined that the four-factor output still produced the most meaningful organization of items. The four-factor outcome accounted for 74.33%of the variance. Due to instances of dual-loading of four items, it was necessary to determine appropriate item placement based on manual review of items. This review resulted in two items being placed within factors which were not their highest loading value, but were still above the 0.40 criteria and were viewed as the most logical placement based on content. Upon review of the content of the corresponding items, the four resulting factors relating to Barriers were labeled Member Traits, Meeting Components, Agency Issues, and Time/Workload. Table 2 shows the resulting defined components and included variables with factor loadings.

Table 2
Factor loadings from principal components analysis for18 Barriers to Collaboration items

Member traits Meeting components Agency issues Time/workload

Turn-over of personnel 0.72

Lack of knowledge of other agencies 0.66

Lack of resource-sharing 0.65

Lack of training in collaboration 0.65

Absence of needed members 0.63

Lack of communication 0.62

Lack of common values 0.58

Lack of accountability 0.61

Lack of follow-through 0.58

Lack of leadership 0.76

Lack of focus 0.76

Lack of clear agenda 0.72

Lack of agency support 0.83

Lack of knowledge of own agency 0.81

Lack of alignment of goals 0.76

Lack of collaboration time 0.83

Scheduling difficulties 0.83

Lack of work time 0.51

	Member traits	Meeting components	Agency issues	Time/workload
Turn-over of personnel	0.72
Lack of knowledge of other agencies	0.66
Lack of resource-sharing	0.65
Lack of training in collaboration	0.65
Absence of needed members	0.63
Lack of communication	0.62
Lack of common values	0.58
Lack of accountability		0.61
Lack of follow-through		0.58
Lack of leadership		0.76
Lack of focus		0.76
Lack of clear agenda		0.72
Lack of agency support			0.83
Lack of knowledge of own agency			0.81
Lack of alignment of goals			0.76
Lack of collaboration time				0.83
Scheduling difficulties				0.83
Lack of work time				0.51

The item-level responses within the Barriers section of the survey were reported using descriptive statistics mean and standard deviation. Results indicated that at the item-level, the most challenging Barriers (lowest means) included difficulty scheduling convenient collaborative opportunities. ( $\underline{x}$ = 1.98), turn-over, attrition, or changes in collaborative personnel ( $\underline{x}$ = 2.19), and lack of knowledge of the services of other agencies ( $\underline{x}$ = 2.20). The least challenging Barriers (highest means) included lack of knowledge of own agency’s policies ( $\underline{x}$ = 2.66), lack of support from my own agency to collaborate ( $\underline{x}$ = 2.63), and lack of alignment between one’s agency goals and a team’s collaborative goals ( $\underline{x}$ = 2.63). At the factor level, mean scores and standard deviations showed Time/Workload as the most challenging barrier factor ( $\underline{x}$ = 2.20) and Agency Issues as the least challenging barrier factor ( $\underline{x}$ = 2.63). Table 3 presents descriptive statistics by factor and item-level.

Table 3

Barriers to Collaboration by factor: All participants (N = 210)

Factor, survey item	Mean	Standard deviation
Member traits	2.28	0.78
Turn-over, attrition, changes in collaborative personnel	2.19	0.91
Lack of knowledge of the services of other agency(ies)	2.20	0.96
Lack of resource-sharing from collaborative partners	2.32	1.00
Lack of training in collaboration techniques	2.23	0.96
Essential collaborative partners not available as needed	2.30	0.96
Lack of effective communication among collaborators	2.20	1.00
Lack of common values among collaborators	2.50	1.00
Meeting components	2.32	0.86
Lack of accountability for progress toward group goals	2.24	1.04
Lack of follow-through on agreed-upon tasks	2.25	1.02
Lack of effective leadership during collaboration	2.34	0.99
Lack of focus during collaboration	2.42	1.01
Lack of clear agenda for collaborative activities	2.37	0.96
Agency issues	2.64	1.00
Lack of support from my own agency to collaborate	2.63	1.17
Lack of knowledge of my own agency’s policies	2.66	1.09
Lack of alignment between my agency and team goals	2.63	1.04
Time/workload	2.20	0.70
Difficulty scheduling convenient collaboration options	1.98	0.75
Not enough time in collaboration activities	2.23	0.83
Lack of work time between collaboration	2.38	0.96

Note: Lower means indicate that the barrier is viewed as “more challenging”; Higher means indicate a barrier is “less challenging”.

3.2 Research question 2: What do transition professionals indicate as the most effective strategies for successful collaboration?

Within the Strategies subsection, participants were asked to indicate their perceived importance of various strategies relevant to promoting successful collaboration. Likert-like scale responses for questions within this section of the survey were assigned numerical values as follows: Significantly important-4, Moderately important- 3, Minimally important- 2, Not at all important-1, therefore items with highest resultant means were those identified by participants as most important.

3.2.1 EFA: Strategies

Using SPSS, the data within the Strategies subsection was determined adequate and appropriate for EFA as the Kaiser-Meyer-Olkin Measure of Sampling Adequacy was 0.92 (above the recommended 0.60 threshold), and the Bartlett Test of Sphericity determined a significance value of less than the 0.05 recommended level. Principal components analysis was selected in order to identify and reduce the variables (in this case, 13 survey question items) into underlying factors usable for further inferential testing. Initially, extraction was set for four factors; however, upon review of the resulting scree plot showing an “elbow” between two to three factors, extraction for both three and two factors was also programmed. Following manual review of the resulting matrices for logical groupings of items and parsimony of placements, the two-component outcome was selected, which accounted for 57.21%of the variance. Manual review of the items did not result in any item shifts; all items remained within their highest loading factor. Upon review of the content of the corresponding items, the two resulting factors were labeled Member Responsibilities and Meeting Organization. Table 4 outlines the resulting defined factors and component items.

Table 4
Factor loadings and communalities based on a principal components analysis for 13 Collaboration Strategy items

Member responsibility Meeting organization

Effective communication 0.78

Alignment between agency’s/team’s goals 0.77

Understanding roles of other agencies 0.73

Understanding of my own agency’s services 0.73

Collaborators pool resources 0.69

Collaborators accountable for goal progress 0.68

Collaborators share values 0.64

Adequate work time 0.60

Minimized member attrition 0.54

Collaboration reflects agreed-upon topics 0.86

Collaboration utilizes agenda, objectives 0.85

One collaborator serves as leader 0.56

Collaborative time is focused 0.51

	Member responsibility	Meeting organization
Effective communication	0.78
Alignment between agency’s/team’s goals	0.77
Understanding roles of other agencies	0.73
Understanding of my own agency’s services	0.73
Collaborators pool resources	0.69
Collaborators accountable for goal progress	0.68
Collaborators share values	0.64
Adequate work time	0.60
Minimized member attrition	0.54
Collaboration reflects agreed-upon topics		0.86
Collaboration utilizes agenda, objectives		0.85
One collaborator serves as leader		0.56
Collaborative time is focused		0.51

Domain and item-level descriptive statistics are presented in Table 5. Strategies with the highest mean scores included: ensuring collaborative time is focused and well spent ( $\underline{x}$ = 3.79), ensuring effective communication ( $\underline{x}$ = 3.78), and ensuring understanding of one’s own agency services and policies ( $\underline{x}$ = 3.74). Strategies with the lowest means included ensuring one collaborator serves as a leader ( $\underline{x}$ = 3.25), minimizing collaborator turn-over rate ( $\underline{x}$ = 3.37), and ensuring adequate work time between collaborative sessions ( $\underline{x}$ = 3.51). Mean scores and standard deviations for the domain-level strategies indicated that the domain Member Responsibility was identified as the most effective strategy for collaboration, with a mean score of 3.63. The Meeting Organization domain had a slightly lower mean at 3.59.

Table 5

Strategies for Collaboration by factor: All participants (N = 210)

Factor, survey item	Mean	Standard deviation
Member responsibility	3.63	0.40
Ensuring effective communication	3.78	0.43
Alignment between agency and team goals	3.67	0.49
Understanding roles of other agencies	3.73	0.48
Understanding my own agency services, policies	3.74	0.47
Collaborators pool resources to address issues	3.68	0.53
Collaborators are accountable goal progress	3.63	0.56
Collaborators share common values	3.54	0.64
Adequate work time between sessions for tasks	3.51	0.59
Minimizing member turn-over or attrition	3.37	0.65
Meeting organization	3.59	0.42
Collaborative time reflects agreed-upon topics	3.62	0.52
Collaboration utilizes agenda, clear objectives	3.71	0.50
One collaborator serves as leader	3.25	0.76
Collaborative time is focused, well-spent	3.79	0.42

3.3 Research question 3: Do transition professionals’ perceptions of the components of collaboration vary based on their professional roles?

This research question aimed to identify any associations among professional role and perceptions of Barriers and Strategies for collaboration through inferential statistics (i.e., ANOVA). In order to determine any association between role group and perceptions, each factor from the Barriers and Strategies domains were disaggregated by role. Within the Barriers domain, Educators indicated the Time/Workload factor as the most challenging ( $\underline{x}$ = 2.12), while VR representatives indicated Member Traits as the most challenging ( $\underline{x}$ = 2.29) and Community Providers scored Meeting Components as most challenging ( $\underline{x}$ = 2.14). The Agency Issues factor was indicated as the least challenging barrier when disaggregated by role group with Community Providers scoring 2.92, VR representatives scoring 2.86, and Educators scoring 2.56. Within the Strategies domain, the Member Responsibility factor was indicated as the most effective by both Community Providers ( $\underline{x}$ = 3.62) and by VR representative ( $\underline{x}$ = 3.74). Educators scored both factors equally ( $\underline{x}$ = 3.61). VR representatives indicated Meeting Organization factor as a less effective strategy ( $\underline{x}$ = 3.62) as did Community Providers ( $\underline{x}$ = 3.45). Descriptive statistics of all domains and factors disaggregated by role are presented in Table 6.

Table 6
Descriptive statistics for Barriers and Strategies factors by role

Educators n = 158 VR n = 29 Comm. providers n = 23 Total N = 210

Mean SD Mean SD Mean SD Mean SD

Barriers factors

Member traits 2.29 0.81 2.29 0.80 2.15 0.51 2.28 0.78

Meeting components 2.34 0.88 2.36 0.88 2.14 0.63 2.32 0.86

Agency issues 2.56 1.02 2.86 0.97 2.92 0.84 2.64 1.00

Time/workload 2.12 0.69 2.45 0.78 2.46 0.54 2.20 0.70

Strategies factors

Member resp. 3.61 0.42 3.74 0.32 3.62 0.31 3.63 0.40

Meet. org. 3.61 0.43 3.62 0.38 3.45 0.39 3.59 0.42

	Educators n = 158	VR n = 29	Comm. providers n = 23	Total N = 210
Barriers factors
Member traits	2.29	0.81	2.29	0.80	2.15	0.51	2.28	0.78
Meeting components	2.34	0.88	2.36	0.88	2.14	0.63	2.32	0.86
Agency issues	2.56	1.02	2.86	0.97	2.92	0.84	2.64	1.00
Time/workload	2.12	0.69	2.45	0.78	2.46	0.54	2.20	0.70
Strategies factors
Member resp.	3.61	0.42	3.74	0.32	3.62	0.31	3.63	0.40
Meet. org.	3.61	0.43	3.62	0.38	3.45	0.39	3.59	0.42

Note: Comm. Providers = Community Providers, VR = Vocational Rehabilitation, SD = Standard Deviation, Member Resp. = Member Responsibility, Meet. Org. = Meeting Organization.

The results of the one-way ANOVA only showed significant difference among groups for the Time/Workload factor from the Barriers section (χ² =9.12, df = 2, Sig. of χ² = 0.01). A Mann-Whitney U procedure indicated that Educators view this barrier domain as more challenging ( $\underline{x}$ = 2.12) than both VR ( $\underline{x}$ = 2.45; U = -2.12, p = 0.034) and Community Providers ( $\underline{x}$ = 2.46; U = -2.44, p = 0.015). No other factors yielded significant differences based on individual role. For these factors (Member Traits, Meeting Components, Agency Issues, Member Responsibility, Meeting Organization, Knowledge of Options, Exit Supports, and In-School Supports), professionals’ perceptions did not vary significantly based on professional role.

4 Discussion

4.1 Summary of findings

Results revealed participants’ perspectives on the Barriers and Strategies for collaboration. Item-level data from each of these domains were then reduced into factors based on an exploratory factor analysis (EFA). The 18 items from the Barriers domain were reduced to four factors (Member Traits, Meeting Components, Agency Issues, and Time/Workload), and the 13 Strategy items were reduced to two factors (Member Responsibility, and Meeting Organization). Review of the data revealed the most challenging Barrier factor as Time/Workload, while the most effective Strategy factor was Member Responsibility. The Barrier factor Time/Workload was determined to be the only Barrier or Strategy factor to show statistically significant differences of means across the three role groups. Specifically, Educators viewed Time/Workload as a more challenging Barrier than both VR representatives and Community Providers.

4.2 Impact of role on collaboration

The present study sought to identify participants’ perceptions of various mechanisms (strategies, barriers) that impact interagency collaboration. To simplify and organize the components of collaboration, exploratory factor analysis (EFA) was used to reduce the number of Barriers and Strategies variables into factors. Review of the data revealed the most challenging Barrier factor indicated by participants as Time/Workload which includes variables such as lack of collaboration time, difficulty scheduling convenient options, and lack of work time between collaborative meetings. Participants indicated that they perceived Member Responsibility as the most effective collaboration Strategy factor.

Studies relating to member roles, perceptions, and expectations of collaboration effectiveness can further increase understanding of collaborative practices (Oertle & Trach, 2007), and align with the present study. For example, to study perceptions based on team member role, Plotner , Rose et al. (2017) surveyed educators, VR counselors, transition specialists, and other community agency professionals (all active members of school district interagency transition teams) to determine correlations among perceptions/expectations of collaboration, time on the committee, and role. Findings indicate that teachers report having unclear understandings of stakeholder roles relating to transition planning. Teachers also report not taking the lead in accomplishing transition tasks or coordinating services as often as VR counselors or district transition specialists (Plotner , 2017). These findings combine to indicate incorrect role assumptions which can lead to glaring gaps in service planning. Plotner , Rose et al. (2017) suggest additional teacher preparation, as well as targeted technical assistance to purposefully facilitate collaboration to increase understanding of roles and responsibilities.

Findings from the present study allude to variances in role assumptions as well. The Educators group indicated noticeably lower perceived levels of collaboration with members of outside agencies than the levels indicated by VR and Community Providers. Additionally, Educators identified that Time/Workload as their greatest barrier to collaboration, significantly higher than other role groups. Perhaps Educators simply have fewer opportunities within their work time for collaborative activities than the other role groups, and they therefore do not perceive their collaborative levels as Extensive or Moderate. Other role groups may actually participate in collaboration activities at a higher level simply because of the increased opportunity to do so. For instance, VR and Community Providers may be members of several district collaborative teams, or may be responsible for overseeing transition services for an entire region or state, and therefore may participate in multiple interagency collaborative teams. While Educators implement the services, which may be results of collaborative planning, the time spent in implementation would not be considered collaborative time. Perhaps more often the Educator role in collaboration may be viewed as actually a reflection of the results of effective collaboration. This is not to say that VR or Community Providers have more time in general, just that they have a larger percentage of their work time in which they are expected to engage in collaborative activities. The differences in perceptions of collaborative levels may vary among roles simply because the job descriptions and expectations are different. This raises the discussion for how to best facilitate enhanced collaboration for groups of professionals when some members actively collaborate at high levels and some do not actively collaborate in formal meetings at all.

4.3 Time/workload as an inhibitor to collaboration

The Barrier factor Time/Workload was determined to be the only factor to show statistically significant differences of means across the three role groups. Specifically, Educators viewed Time/Workload as a more challenging Barrier than both VR representatives and Community Providers. Because Educators make up the largest percentage of respondents, Time/Workload was shown as the most challenging Barrier overall; however, when examining the perceived Barriers disaggregated by role, each group identified different factors as most challenging. VR identified Member Traits as most challenging, while Community Providers identified Meeting Components as most challenging. The finding that Educators view Time/Workload as a significantly more challenging Barrier than other role groups is notable as this is the only factor where role perceptions differed this considerably.

Study participants identified Time/Workload as the most challenging Barrier to effective collaboration. This finding indicated a different prioritization of challenges than those identified in previous research. For instance, Oertle and Trach (2007) identified through a review of the literature that collaborators identify barrier issues such as poor-relationship building, poor communication, poor meeting preparation, and lack of coordination among agencies as frequent barriers. Pfeiffer and Cundari (2000) identified barriers such as variations in terminology, eligibility criteria, and regulations across agencies. Benz et al. (1995), and Plotner , (2017) identified barriers including a lack of knowledge of VR services and, as well as gaps in understanding the needs of transition-age adults. These findings indicate a concerning combination of knowledge deficits as well as lack of agency understanding and coordination, which can continuously affect collaboration initiatives.

Training in interagency collaboration may provide tools and methods for effectively navigating many aspects of team dynamics, however, the Time/Workload factor encompasses issues that may not fall within the scope of group member trainings. This factor could be viewed as more closely related to work responsibilities, the values and focus of the agencies, and agency expectations for prioritization of duties. Interestingly, the present study indicated that participants viewed Agency Issues as the least challenging Barrier, a finding which could be capitalized when addressing the more hindering Barriers. Agencies whose goals align with the collaborative teams’ may be more likely to provide increased work time and/or considerations for adjusting workload to help address the Time/Workload factor. Supportive agencies may be more apt to respond to requests of their workers for more time to focus on collaborative goals in order to benefit all transition-related stakeholders and students. Presenting meaningful evaluation results indicating the individual teams’ needs could provide agencies with ideas for how to continue supporting and shaping the growth of effective collaborative teams. As for the results of this study, agencies may recognize the need to provide more time for collaborative activities and collaboration-related work of team members.

4.4 Alignment of roles, expectations, and workload of collaborators

An additional consideration for teams who indicate that Time/Workload is the most prominent Barrier may be a reexamination of the team members participating in collaboration. As discussed previously, because of the recognized importance of the VR counselor role in planning for postsecondary transition and interagency, many states have gone so far as to develop a Transition VR Counselor role designated to provide services specifically to transition-age youth. These Transition VR Counselors, whose caseloads are at least 50%transition-age youth, report higher levels of preparation in facilitating services for this age group, and assign a higher importance to interagency collaboration than typical VR counselors (Plotner et al., 2014). This adjustment in role and job description within VR was a result of a recognition of the need for more targeted services for the transition population, a concept that perhaps should be implemented among other participating agencies, particularly school districts. While some school districts have designated Transition Specialists or Coordinators dedicated to planning and implementing services for youth and families preparing for postsecondary settings, many districts do not provide for this role. Results of the present study, in which Time/Workload is identified as a significantly challenging Barrier among Educators, may affirm the need for dedicated transition professionals within districts, rather than assigning interagency collaboration as an additional duty for special education teachers or administrators to manage.

5 Limitations

Recruitment of participants was based on convenience sampling within one state, therefore poten-tially limiting the generalization of these results. Determining precise response rates was not possible due to the snowball sampling method, as there was no tracing of who received a survey invitation and who actually completed a survey. Additionally, varying agency protocols within school districts and other agencies hindered the snowball sampling option as some employers disallowed the forwarding of surveys to other employees.

The survey design relied on self-report measures and perceptions of effects of interagency collaboration. Verification of this information was not possible due to the subjective nature of the Likert-like scale rankings. Self-response data is susceptible to influence of social desirability, such as answering questions based on what would be perceived to be favorable by others, and should be considered as a limitation of this study (Mertens & Wilson, 2012). Before dissemination, the survey was reviewed by content experts for clarity and alignment to the identified constructs, however, survey participants were not provided opportunity to review the survey for readability, clarity, or comprehensiveness. As noted throughout the study, survey items asked participants to report their perceptions of the barriers to, and strategies for interagency collaboration. The results reported indicate perceptions of these components. This study does not imply that the findings are actually the most challenging barriers or the most effective strategies for collaboration, but simply that these are the perceptions of this sample group; no claims of correlation or causation among these findings and transition outcome data are appropriate based on this study design.

6 Conclusion

The findings from the present study indicated several potential implications for practice regarding interagency collaboration. These include the importance of aligning training tools and agency systems to team needs as revealed through collaboration assessments, while recognizing that team member perceptions may be affected by their role and expectations of collaborative activities.

6.1 Implications for practice

Mandates from WIOA legislation require that VR provide transition services through pre-employment training programs for high school-aged youth with disability (U.S. Department of Labor, 2018). As noted in previous research, rehabilitation professionals indicate the need for more participation in transition planning, yet rely on educators to initiate that participation (Oertle et al., 2013). In the present study, educators express that time and workload constrain them from maximizing collaboration, perhaps implying that to increase participation VR professionals could seek to initiate involvement without relying on educators. Examining present systems used for interagency communication, particularly between school districts and VR, may indicate the need to increase interagency access, such as shared calendars, combined planning meetings, joint professional development, data-sharing agreements, and coordinated service-delivery (Kohler et al., 2016). Identifying and addressing these deficits aims to streamline collaboration opportunities for all, and ensure essential team members are present and efficient without adding to the workload of educators.

Another implication may be the potential impacts that collaboration training tools can have on addressing common barriers to interagency collaboration, including gaps in team member knowledge of agencies, communication skills, and misaligned values among team members. Recognizing potential benefits of collaborative training may be valuable for states not currently employing a state-wide interagency collaboration assistance model and may encourage them to consider implementation. For states with such programs, this finding may be helpful in encouraging district teams to utilize technical assistance to evaluate and address knowledge barriers through joint trainings with their interagency teams. For instance, technical assistance supports (such as TASC) facilitate team-level evaluations followed by targeted interventions to improve collaboration. Practical applications such as standardized training manuals and state or district-specific team-level assessment tools generate findings regarding specific barriers or strategies utilized by teams and indicate effective practices (Oertle & Seader, 2015).

Another potential implication is the use of team collaboration assessment data as a tool for documenting needs that supporting agencies may be able to address. Results of collaboration evaluations can be used to justify readjustments of time or workload constraints to better support the collaborative initiatives. Utilization of valid team-level assessment tools to gauge current collaboration levels can assist in pinpointing the areas of support needed, as well as techniques for utilizing additional time/work resources to best support collaboration. Targeted evaluations of needs would validate a team’s request for these assets from agency heads, and may lead to an increased likelihood of these resources being granted. While the individual team’s results may indicate any number of deficit areas, the practical application is consistent: teams can evaluate their collaborative functioning and identify where further support (in the case of the present study, time and workload allowances) may be requested from supporting agencies.

Finally, to further address team members’ preparation for interagency collaboration, professional degree or certification programs may consider preservice experiences in interagency collaboration. Oertle et al. (2017) have identified that preparation programs for professionals in transition-related fields (i.e. special education, rehabilitation counseling, etc.) are often housed in different academic departments with independent discipline-specific standards and accreditation bodies, preventing any collaborative opportunities among students in these training programs. As training in collaboration has been shown to reduce common barriers to collaboration (Benz et al., 1995; Oertle & Trach, 2007; Taylor et al., 2016), future research in collaboration training at the university level may lead to a reimagined preservice curriculum in which collaboration is expected among various professional areas.

Footnotes

Acknowledgment

None to report.

Conflict of interest

The authors declare that they have no conflict of interest.

Ethical declarations

Ethical approval for this study was waived by The Office of Research Compliance the administrative office that supports the University of South Carolina Institutional Review Board (USC IRB) because the information obtained is recorded by the investigator in such a manner that the identity of the human subjects cannot readily be ascertained, directly or through identifiers linked to the subjects.

Funding

None to report.

Informed consent

Participation in this survey was strictly voluntary. If at any time participants felt uncomfortable, or wished to end the survey, they could cease completion and exit the survey platform as noted in the introduction letter.

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