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Using an Online Measurement Data Management Platform to Improve Survey Response Rates in a Community Sexual Assault
Gena K Dufour1, Sung Hyun Yun2, Lydia Fiorini3
1Department of Psychology, University of Windsor, Windsor, Ontario, Canada.
Journal of Evidence-Based Social Work (2019)
|December 25, 2024
Summary
Implementing an online measurement data management platform (OMDMP) significantly boosted mental health assessment completion rates at a community crisis center. This digital tool improved client participation in measurement-based care.
Area of Science:
- Mental Health Assessment
- Community Psychology
- Health Informatics
Background:
- Data collection in community organizations is vital for evaluation and therapeutic care.
- Measurement-based care relies on consistent client assessment data.
- Community-based sexual assault crisis centers face unique data collection challenges.
Purpose of the Study:
- To evaluate the impact of an online measurement data management platform (OMDMP) on mental health assessment response rates.
- To compare client assessment participation using OMDMP versus manual data collection methods.
- To determine if OMDMP implementation improves data collection efficiency in a community setting.
Main Methods:
- A pre-post design was employed to analyze data from two distinct periods.
- Manual data collection methods were compared with the implementation of an OMDMP.
- Client mental health assessments using standardized tools (DASS-21, IES-R) were analyzed.
Main Results:
- Client completion of at least one mental health assessment increased significantly from 45% (manual) to 71% with the OMDMP.
- The OMDMP facilitated timely completion of client assessments.
- The platform supported the effective use of assessments in measurement-based care.
Conclusions:
- The OMDMP demonstrated clear benefits for data collection in a community-based sexual assault crisis center.
- Online tools can enhance organizational capacity for self-evaluation and client participation.
- Challenges persist in ensuring complete pre- and posttest data collection, requiring ongoing attention.
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