Validating an Instrument for Assessing Workforce Collaboration

Townsend, Amy; Shelley, Kyna

doi:10.1080/10668920701707813

Cited by 14 publications

(6 citation statements)

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“…The Levels of Collaboration Scale [ 39 ] will be adapted for the purposes of this study and will measure progress over the five levels of collaboration and their characteristics (networking, cooperation, coordination, coalition, collaboration). The Wilder Collaboration Factors Inventory [ 40 ] is a 40-item measure that assesses strengths and weaknesses within organizations shown to be important for successful collaborations. Factors include: collaboration history, organizational climate, mutual respect, definition of roles, adaptability, and shared goal setting.…”

Section: Methodsmentioning

confidence: 99%

Mobile technology intervention to improve care coordination between HIV and substance use treatment providers: development, training, and evaluation protocol

Claborn

Becker

Ramsey

et al. 2017

Addict Sci Clin Pract

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BackgroundPeople living with HIV (PLWH) with a substance use disorder (SUD) tend to receive inadequate medical care in part because of a siloed healthcare system in which HIV and substance use services are delivered separately. Ideal treatment requires an interdisciplinary, team-based coordinated care approach, but many structural and systemic barriers impede the integration of HIV and SUD services. The current protocol describes the development and preliminary evaluation of a care coordination intervention (CCI), consisting of a tablet-based mobile platform for HIV and SUD treatment providers, an interagency communication protocol, and a training protocol. We hypothesize that HIV and SUD treatment providers will find the CCI to be acceptable, and that after receipt of the CCI, providers will: exhibit higher retention in dual care among patients, report increased frequency and quality of communication, and report increased rates of relational coordination.Methods/designA three phase approach is used to refine and evaluate the CCI. Phase 1 consists of in-depth qualitative interviews with 8 key stakeholders as well as clinical audits of participating HIV and SUD treatment agencies. Phase 2 contains functionality testing of the mobile platform with frontline HIV and SUD treatment providers, followed by refinement of the CCI. Phase 3 consists of a pre-, post-test trial with 30 SUD and 30 HIV treatment providers. Data will be collected at the provider, organization, and patient levels. Providers will complete assessments at baseline, immediately post-training, and at 1-, 3-, and 6-months post-training. Organizational data will be collected at baseline, 1-, 3-, and 6-months post training, while patient data will be collected at baseline and 6-months post training.DiscussionThis study will develop and evaluate a CCI consisting of a tablet-based mobile platform for treatment providers, an interagency communication protocol, and a training protocol as a means of improving the integration of care for PLWH who have a SUD. Results have the potential to advance the field by bridging gaps in a fragmented healthcare system, and improving treatment efficiency, work flow, and communication among interdisciplinary providers from different treatment settings.Trial Registration: NCT02906215

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Section: Methodsmentioning

confidence: 99%

Mobile technology intervention to improve care coordination between HIV and substance use treatment providers: development, training, and evaluation protocol

Claborn

Becker

Ramsey

et al. 2017

Addict Sci Clin Pract

View full text Add to dashboard Cite

show abstract

“…The instruments were the Thomson, Perry and Miller Collaboration Instrument [29], the Thomson, Perry and Miller (2007) Collaboration Instrument in the South African Context [30], the Collaboration with Medical Staff Scale of the Nurses Opinion Questionnaire (CMSS-NOQ) [31], the Collaboration and Trust in an Education Context [32], the Wilder Collaboration Factors Inventory [33], the Collaboration Index [34], the Collaborative Culture Scale [35], the Assessment of Inter-professional Team Collaboration Scale [36], the Collaboration Assessment Tool (CAT) [37], the Transdisciplinary Tobacco Use Research Centers (TTURC) Researcher Survey [38], the Index of Interprofessional Team Collaboration for Expanded School Mental Health (IITC-ESMH) [39], the Teacher Collaboration Assessment Survey (TCAS) [40], the Distance Education Learning Environment Survey (DELES) [41], the Index of Interdisciplinary Collaboration (IIC) [42], the Expanded School Mental Health Collaboration Instrument [School Version] [43] and the Collaborative Practice Assessment Tool (CPAT) [44].…”

Section: Step 1: Conceptualizationmentioning

confidence: 99%

Development of a Quantitative Instrument to Measure Mobile Collaborative Learning (MCL) Using WhatsApp: The Conceptual Steps

Nyembe

Howard

2020

Lecture Notes in Computer Science

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It has been reported that WhatsApp, a social media application, had approximately 1.6 billion active users globally as of July 2019, almost one-fifth of the total world's population. Thus, research about WhatsApp's influence in general and especially its influence in education was relevant and significant. While there was much research involving WhatsApp and learning, it was not conclusive about the effects of WhatsApp on student learning. Specifically, research focusing on collaborative learning using WhatsApp was lacking, including research instruments for measuring collaboration on WhatsApp. Consequently, the paper's research problem was the lack of research instruments for measuring collaboration on WhatsApp in relation to academic achievement. To address the research problem, the study followed the important initial and conceptual steps of the instrument development process to develop a research instrument to measure collaboration on WhatsApp in relation to academic achievement. The result of the paper was a developed instrument that provides researchers with a basis to measure the explanatory constructs involved in mobile collaborative learning (MCL) processes on WhatsApp and potentially other social media platforms. Therefore, the paper made an appropriately theoretical contribution, which was grounded in the scientific literature. The study facilitated positivistic research and epistemology for acquiring objective and precise scientific knowledge. Such deductive research promotes theory testing and development and presents educators and students with scientific evidence about learning with MCL applications such as WhatsApp from which both curriculum and learning design can be informed and benefited. In the age of connected mobility this is a necessity.

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“…LOC = level of collaboration. The Wilder Collaboration Factors Inventory measured LOC using the following scale: strong collaboration, LOC ≥ 4.0; collaboration approaching strength, LOC = 3.5 − 3.9; collaboration approaching concern, LOC = 3.0 − 3.4; and collaboration levels that are cause for concern, LOC ≤ 2.9 (Townsend & Shelley, 2008).…”

Section: The Journey: the Partners For Change Studymentioning

confidence: 99%

Navigating Intersecting Roads in a Mixed Methods Case Study: A Dissertation Journey

Walton

Clark

Foote

et al. 2019

Journal of Mixed Methods Research

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Practical guidance for navigating issues associated with combining mixed methods and case study research approaches is in short supply, particularly for novice researchers who may grapple with numerous decision points in planning and conducting such studies. This methodological discussion examines the decision-making process used in a qualitatively driven mixed methods dissertation study with a focus on how mixed methods and case study research approaches can be applied together to enhance case descriptions and interpretations. This discussion contributes to the field of mixed methods research methodology by expanding conversations about the inherent messiness of mixed methods research and by providing practical guidance to researchers interested in applying a mixed methods case study approach.

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Validating an Instrument for Assessing Workforce Collaboration

Cited by 14 publications

References 1 publication

Mobile technology intervention to improve care coordination between HIV and substance use treatment providers: development, training, and evaluation protocol

Mobile technology intervention to improve care coordination between HIV and substance use treatment providers: development, training, and evaluation protocol

Development of a Quantitative Instrument to Measure Mobile Collaborative Learning (MCL) Using WhatsApp: The Conceptual Steps

Navigating Intersecting Roads in a Mixed Methods Case Study: A Dissertation Journey

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