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Abstract Background There is considerable expertise in the obesity field in identifying, appraising, and synthesising evidence to develop guidelines and recommendations for policy and practice. The recommendations, while based on evidence, are not formulated in a way that readily leads to implementation. This paper analyses the recent UK recommendations on obesity using a proposed implementation framework. Methods Two bibliographic databases (Medline and Embase) and various health related and government websites were systematically searched for obesity recommendations published between 1996 and 2007. All the documents published on recommendations for either prevention or treatment of obesity in the UK were assessed. A proposed implementation framework was developed for the purpose of this review. All the UK recommendations were critically appraised and results summarised according to the criteria used within the framework. Cross-country applicability of the proposed framework was assessed using the Swedish policy recommendations on obesity. Results Most recommendations on obesity while demonstrating their basis in evidence, fail to meet the implementation standards. They tend to be non-specific in identifying who is responsible for implementation and monitoring, and often no timescale is indicated. The costs of implementation are rarely estimated and those responsible for such funding are not specified. There are some notable exemptions to the general pattern emanating from more operational and locally based groups. The Swedish policy details 79 proposals with responsibility clearly identified and costs are presented for 20 of them. This policy satisfied most of the framework criteria but failed to give details on evaluation, monitoring and the timeframe for implementation. Conclusions Public health has developed skills in appraising evidence and formulating recommendations based on appropriate evidence but these are often not implemented. Different skills are required to translate these recommendations into actions. Public health clearly needs to develop the implementation skills to a level comparable to the ability to synthesise evidence.

This paper documents how an ethically aligned co-design methodology ensures trustworthiness in the early design phase of an artificial intelligence (AI) system component for healthcare. The system explains decisions made by deep learning networks analyzing images of skin lesions. The co-design of trustworthy AI developed here used a holistic approach rather than a static ethical checklist and required a multidisciplinary team of experts working with the AI designers and their managers. Ethical, legal, and technical issues potentially arising from the future use of the AI system were investigated. This paper is a first report on co-designing in the early design phase. Our results can also serve as guidance for other early-phase AI-similar tool developments.