The youth mental health sector is persistently challenged by issues such as service fragmentation and inefficient resource allocation. Systems modelling and simulation, particularly utilizing participatory approaches, is offering promise in supporting evidence-informed decision making with limited resources by testing alternative strategies in safe virtual environments before implementing them in the real world. However, improved evaluation efforts are needed to understand the critical elements involved in and to improve methods for implementing participatory modelling for youth mental health system and service delivery. An evaluation protocol is described to evaluate the feasibility, value, impact, and sustainability of participatory systems modelling in delivering advanced decision support capabilities for youth mental health. This study applies a comprehensive multi-scale evaluation framework, drawing on participatory action research principles as well as formative, summative, process, and outcome evaluation techniques. Novel data collection procedures are presented, including online surveys that incorporate gamification to enable social network analysis and patient journey mapping. The evaluation approach also explores the experiences of diverse stakeholders, including young people with lived (or living) experience of mental illness. Social and technical opportunities will be uncovered, as well as challenges implementing these interdisciplinary methods in complex settings to improve youth mental health policy, planning, and outcomes. This study protocol can also be adapted for broader international applications, disciplines, and contexts.

When determining the score given to candidates in multiple mini-interview (MMI) stations, raters have to translate a narrative judgment to an ordinal rating scale. When adding individual scores to calculate final ranking, it is generally presumed that the values of possible scores on the evaluation grid are separated by constant intervals, following a linear function, although this assumption is seldom validated with raters themselves. Inaccurate interval values could lead to systemic bias that could potentially distort candidates\' final cumulative scores. The aim of this study was to establish rating scale values based on rater\'s intent, to validate these with an independent quantitative method, to explore their impact on final score, and to appraise their meaning according to experienced MMI interviewers. A 4-round consensus-group exercise was independently conducted with 42 MMI interviewers who were asked to determine relative values for the 6-point rating scale (from A to F) used in the Canadian integrated French MMI (IFMMI). In parallel, relative values were also calculated for each option of the scale by comparing the average scores concurrently given to the same individual in other stations every time that option was selected during three consecutive IFMMI years. Data from the same three cohorts was used to simulate the impact of using new score values on final rankings. Comments from the consensus group exercise were reviewed independently by two authors to explore raters\' rationale for choosing specific values. Relative to the maximum (A = 100%) and minimum (F = 0%), experienced raters concluded to values of 86.7% (95% CI 86.3-87.1), 69.5% (68.9-70.1), 51.2% (50.6-51.8), and 29.3% (28.1-30.5), for scores of B, C, D and E respectively. The concurrent score approach was based on 43,412 IFMMI stations performed by 4345 medical school applicants. It provided quasi-identical values of 87.1% (82.4-91.5), 70.4% (66.1-74.7), 51.2% (47.1-55.3) and 31.8% (27.9-35.7), respectively. Qualitative analysis explained that while high scores are usually based on minor details of relatively low importance, low scores are usually attributed for more serious offenses and were assumed by the raters to carry more weight in the final score. Individual drop or increase in final MMI ranking with the use of new scale values ranged from - 21 to + 5 percentiles, with the average candidate changing by ± 1.4 percentiles. Consulting with experienced interviewers is a simple and effective approach to establish rating scale values that truly reflects raters\' intent in MMI, thus improving the accuracy of the instrument and contributing to the general fairness of the process.

暂无摘要。