Background

The Digital Capabilities Statement for Social Work is a framework to guide practice . It identifies the knowledge, skills and values social workers need to develop their use of digital technology in practice. It uses a wide definition of ‘digital’, providing an overarching resource for social workers and those managing and employing social workers. It brings together and complements existing work in this area for social workers and provides a framework for planning continuing professional development (CPD). The Digital Capabilities Statement will enable social workers to develop and improve their skills and knowledge in using digital technology and support their critical reflection on related ethical issues.

The Digital Capabilities Statement was commissioned by NHS Digital and Health Education England and has been supported and endorsed by a wide range of leading bodies in social work. It supports social workers to:

  • Meet the regulatory requirements of The Professional Standards (Social Work England, 2019)
  • Develop digital capability throughout career levels in line with the Professional Capability Framework (British Association of Social Work (BASW), 2018)
  • Meet ethical expectations for social workers contained in the UK Code of Ethics (BASW, 2014 (update forthcoming 2020)
  • Fulfil relevant elements of the Knowledge and Skills Statement for adults and children Department for Education, 2018; Department of Health, 2015)
  • Have a wide-ranging, tailored reference document for digital parallel to that available to health colleagues (National Health Service, 2018)
  • Provide a framework for and stimulate interest in further research and resources for social workers in particular areas of digital practice (e.g. the work being developed by the Principal Social Workers for Children and Families (forthcoming, 2020)

The Digital Capabilities Statement is one of several related resources produced as part of this project:

The Digital Capabilities Statement is based on findings from online surveys of social workers, focus groups and practice workshops with social workers.  The work is also underpinned by a literature review of existing research and evaluations and draws on learning from relevant work done with health and care professionals.

The project has been overseen by a cross-sector Advisory Group of people with lived experience of social work services, social work practitioners, social work academics, educators, employers, policymakers, regulators, and digital technology experts.

Definition of digital technologies

The definition of digital technologies adopted in this project is derived from a survey of social workers, a literature review and consultation with sector leaders.

  • Electronic systems (software) to facilitate day-to-day work of and by social workers (e.g. email, electronic case management systems, business software such as email, calendar and collaborative technologies such as SharePoint and instant messaging)
  • Online resources for professionals and people using social work services (e.g. apps and websites)
  • Assistive technologies for people using services (e.g. communication aids and robotics; cognitive assistant robots, physically assistive robots).
  • Social media and social networking interfaces (e.g. Twitter, Facebook, Snapchat, Skype, WhatsApp) used by social workers and other professionals, and used by people of all ages accessing social work services
  • Informatics – how information, including large data sets, is used and analysed through computation, and how data is used strategically to determine aggregate need and to monitor and improve services (e.g. performance management software used by social work managers)
  • Data protection, privacy and the use of personal,  identifiable data – e.g. how social workers access, store and use  information about people who contact services, to improve their direct care or share information with professionals about them
  • Information management (e.g. search, retrieval, data security and access issues)
  • Hardware (e.g. smart phones, mobile devices and web enabled laptops)
  • Online learning (e.g. professional e-learning, online courses, webinars, online communities of practice)
  • Artificial Intelligence and machine learning - for processing large amounts of data about the population to predict their needs