The evolution of community peer support values: reflections from three UK mental health project teams: The McPin peer support evaluation writing collaborative

OBJECTIVE: To explore emergent values for community-based peer support in three projects and use of peer research methodology. BACKGROUND: Peer support refers to the support people with shared lived experiences provide to each other. Its roots are in the civil rights movement, providing alternatives to clinical treatments. This method of support is delivered in different settings, with varying degrees of structure. In this paper, it includes shared experience of mental health issues. METHODS: We reviewed interview data from two evaluations and one development project - mental health (n = 69), women-only (n = 40), and maternal mental health (n = 24), respectively. Each project used peer research methods. Peer support values from each project were compared, along with reflections from mostly peer researchers who worked on them (n = 11). RESULTS: Six peer support values emerged and were found to be identifiable and applicable in different contexts. Decisions on facilitation and leadership varied across projects and generated some concerns over professionalisation, including non-peer leadership. Frameworks were viewed as broadly useful, but peer support is heterogenous, and peer researchers were concerned about over-rigid application of guidance. DISCUSSION: We propose caution applying frameworks for peer support. Values must remain flexible and peer-led, evolving in new contexts such as COVID-19. Evaluators have a responsibility to consider any potentially negative consequences of their work and mitigate them. This means ensuring research outputs are useful to the peer support community, and knowledge production is based upon methodologies, such as peer research, that complement and are consistent with the values of peer support itself

The evolution of community peer support values: reflections from three UK mental health project teams: The McPin peer support evaluation writing collaborative

Objective: To explore emergent values for community-based peer support in three projects and use of peer research methodology. Background: Peer support refers to the support people with shared lived experiences provide to each other. Its roots are in the civil rights movement, providing alternatives to clinical treatments. This method of support is delivered in different settings, with varying degrees of structure. In this paper, it includes shared experience of mental health issues. Methods: We reviewed interview data from two evaluations and one development project - mental health (n = 69), women-only (n = 40), and maternal mental health (n = 24), respectively. Each project used peer research methods. Peer support values from each project were compared, along with reflections from mostly peer researchers who worked on them (n = 11). Results: Six peer support values emerged and were found to be identifiable and applicable in different contexts. Decisions on facilitation and leadership varied across projects and generated some concerns over professionalisation, including non-peer leadership. Frameworks were viewed as broadly useful, but peer support is heterogenous, and peer researchers were concerned about over-rigid application of guidance. Discussion: We propose caution applying frameworks for peer support. Values must remain flexible and peer-led, evolving in new contexts such as COVID-19. Evaluators have a responsibility to consider any potentially negative consequences of their work and mitigate them. This means ensuring research outputs are useful to the peer support community, and knowledge production is based upon methodologies, such as peer research, that complement and are consistent with the values of peer support itself

ASSESSMENT OF THE QUALITY OF DIGITAL TERRAIN MODEL PRODUCED FROM UNMANNED AERIAL SYSTEM IMAGERY

Production of digital terrain model (DTM) is one of the most usual tasks when processing photogrammetric point cloud generated from Unmanned Aerial System (UAS) imagery. The quality of the DTM produced in this way depends on different factors: the quality of imagery, image orientation and camera calibration, point cloud filtering, interpolation methods etc. However, the assessment of the real quality of DTM is very important for its further use and applications. In this paper we first describe the main steps of UAS imagery acquisition and processing based on practical test field survey and data. The main focus of this paper is to present the approach to DTM quality assessment and to give a practical example on the test field data. For data processing and DTM quality assessment presented in this paper mainly the in-house developed computer programs have been used. The quality of DTM comprises its accuracy, density, and completeness. Different accuracy measures like RMSE, median, normalized median absolute deviation and their confidence interval, quantiles are computed. The completeness of the DTM is very often overlooked quality parameter, but when DTM is produced from the point cloud this should not be neglected as some areas might be very sparsely covered by points. The original density is presented with density plot or map. The completeness is presented by the map of point density and the map of distances between grid points and terrain points. The results in the test area show great potential of the DTM produced from UAS imagery, in the sense of detailed representation of the terrain as well as good height accuracy