Reducing the prevalence of mothers experiencing recurrent care proceedings
This projects is also known as Pause
Aligned SDGs
- Reducing the prevalence of mothers experiencing recurrent care proceedings
- General overview
- Location
- Involved organisations
- Outcome metrics
- SyROCCo reports
- Spreadsheet of data
- Reducing the prevalence of mothers experiencing recurrent care proceedings
- General overview
- Location
- Involved organisations
- Outcome metrics
- SyROCCo reports
- Spreadsheet of data
General overview
Stage of development: Implementation
Policy sector: Child and family welfare
Date outcomes contract signed: Feb 2019
Start date of service provision: Apr 2019
Anticipated completion date: Mar 2024
Capital raised (minimum): GBP 594.08k (USD 758.18k)
Max potential outcome payment: GBP 1.62m
Service users: 48 individuals
Intervention
Pause is an intensive, relationship-based support programme, delivered over 18 months. The trauma informed support offered is practical (e.g. support accessing and engaging with benefit entitlement, debt advice, stable housing, primary care services – GP, dental, sexual health, etc), behavioural (e.g. development of behavioural regulation techniques, healthy relationships) and therapeutic (e.g. recovery from loss and trauma)
Target population
The target population is women of child bearing age who have experienced (or are at high risk of experiencing) a cycle of recurrent care proceedings leading to removal of their children into local authority care.
Location
Country
- United Kingdom
Service delivery locations
- Plymouth City Council
Involved organisations
Configuration of contracting parties:
- Direct contract between outcome payer and investor
- QBE Insurance Group
- Big Society Capital
- Project Snowball
- Pilotlight
- The Prince of Wales's Charitable Fund
- Guy's and St Tomas' Charity
- Trust for London
- Ceniarth
- Local government pension schemes
- Merseyside
- Global Business Insurer QBE
- Greater Manchester Pension Fund
- Development Bank of Japan
- Bank Workers' Charity
Outcome metrics
- 41 women will engage with 34 women achieving Outcomes 1 (metrics 1 or 2)
- 41 engaging with 40 achieving Outcome 2 (metrics 1 or 2)
Powered by SyROCCo SyROCCo reports
The following articles are taken from the Systematic Review of Outcomes Contracts Collaboration (SyROCCo) Machine Learning tool.
The tool is a collaboration between the Government Outcomes Lab and machine learning experts from the University of Warwick, that allows you to navigate and explore data extracted from nearly 2000 academic and grey literature publications related to outcomes-based contracting.
Spreadsheet of data
Important Notice and Disclaimer on INDIGO Data
INDIGO data are shared for research and policy analysis purposes. INDIGO data can be used to support a range of insights, for example, to understand the social outcomes that projects aim to improve, the network of organisations across projects, trends, scales, timelines and summary information. The collaborative system by which we collect, process, and share data is designed to advance data-sharing norms, harmonise data definitions and improve data use. These data are NOT shared for auditing, investment, or legal purposes. Please independently verify any data that you might use in decision making. We provide no guarantees or assurances as to the quality of these data. Data may be inaccurate, incomplete, inconsistent, and/or not current for various reasons: INDIGO is a collaborative and iterative initiative that mostly relies on projects all over the world volunteering to share their data. We have a system for processing information and try to attribute data to named sources, but we do not audit, cross-check, or verify all information provided to us. It takes time and resources to share data, which may not have been included in a project’s budget. Many of the projects are ongoing and timely updates may not be available. Different people may have different interpretations of data items and definitions. Even when data are high quality, interpretation or generalisation to different contexts may not be possible and/or requires additional information and/or expertise. Help us improve our data quality: email us at indigo@bsg.ox.ac.uk if you have data on new projects, changes or performance updates on current projects, clarifications or corrections on our data, and/or confidentiality or sensitivity notices. Please also give input via the INDIGO Data Definitions Improvement Tool and INDIGO Feedback Questionnaire.