Subjective Self-Mapping in the Mental Health Continuum Model

Background: To complement the Canadian Armed Forces' (CAF) Road to Mental Readiness (R2MR) training program, a mobile application (i.e., "app") was developed to provide users with an online opportunity to review and practice strategies to cope with stress and increase resilience.One of the components of the mobile app is the Mental Health Continuum Model (MHCM), designed to allow users to self-assess on six mental health and well-being domains (i.e., Mood, Attitude & Performance, Sleep, Physical Symptoms, Social Behaviour, Alcohol & Gambling) using a visual spectrum of the continuum that includes four anchors: healthy, reacting, injured, and ill.More specifically, for each functional domain the app involves self-rating on scales guided by different descriptors, which have been grouped to represent the four anchors of the MHCM.The current research was undertaken in order to inform and guide future R2MR mobile app development and training content.Specifically, we sought to understand 1) whether MHCM self-mapping aligns with established validated physical and mental health scales; and 2) how CAF members perceive the MHCM content (i.e., the degree of concurrence or consistency between endorsed anchors and their descriptors).Thus, the current research aimed to examine the concurrent validity of the MHCM compared to validated, well-established measures.Additionally, using a separate matching task, our research assessed if the current wording of the descriptors from the MHCM correspond to the four anchors as well as the in-app visual representation of the continuum.Methods: Data were collected online from 392 Regular Force CAF members.Participants self-mapped onto each of the functional domains of the MHCM, and were randomly assigned to be presented with one of four versions of the MHCM.Participants assigned to Group 1 were presented with the descriptors separately (i.e., without the visual spectrum); they were also presented with the visual spectrum separately (i.e., without the descriptors) and were instructed to self-map onto each of the functional domains of the MHCM.Group 2 were also presented with the descriptors and visual spectrum separately; however, the visual spectrum included the four anchors.Group 3 was presented with the MHCM as is in the mobile app (i.e., the descriptors and spectrum were presented together), and Group 4 was presented with the same version as Group 3, however, the spectrum included the four anchors.All of the participants completed demographic information and validated measures of physical and mental health that assessed similar or the same constructs of each of the functional domains.Finally, all participants completed a matching task to assess the accuracy rates of matching each descriptor to its corresponding anchor.Results: Overall, there was an adequate amount of agreement between MHCM self-mapping and the validated measures providing some support for the MHCM self-mapping approach, although the degree of agreement differed across functional domains.Importantly, of those participants screening positive for clinically significant symptoms of depression/anxiety, suicide ideation, or hazardous and harmful alcohol use, at least one-fifth self-assessed as healthy on the MHCM.Additionally, the rate at which each validated scale predicted group membership to the four MHCM anchors was high for healthy, however, the rates decreased for reacting, injured, and ill.Approximately 15% (Alcohol and Gambling domain) to 45% (Sleep domain) of participants were inconsistent in self-mapping across the functional domains.Similarly, the results of the matching task indicated that accuracy was high for identifying the descriptors that are healthy, but rates decreased noticeably for reacting, injured, and ill.Discussion: The results provide initial support for the MHCM self-mapping approach, such that there was a fair amount of agreement between the MHCM self-mapping task and the validated measures.Moreover, for most of the functional domains, a large proportion of participants' descriptor and spectrum self-mapping ii DRDC-RDDC-2018-R294 were consistent.Nonetheless, our results indicate that there is a noticeable rate of false-negatives on the MHCM self-assessment tool, indicating some participants are underestimating their symptom severity on the continuum.The results of the predicted group membership analyses on the self-mapping task indicate a potential discrepancy between some of the descriptors, particularly the descriptors for the reacting, injured, and ill anchors, and the validated measures.Finally, for most of the functional domains, a large proportion of participants' descriptor and spectrum self-mapping were consistent.However, our findings from the self-mapping task indicate that some of the MHCM descriptors do not accurately reflect how participants self-assess on the visual spectrum and that participants' ability to distinguish and assess symptom severity between descriptors was restricted, especially for reacting, injured, and ill.A similar pattern emerged for the matching task such that accuracy was high for identifying the descriptors that are healthy, but rates decreased noticeably for reacting, injured, and ill.Future research should focus on further assessing the source of inconsistency and discrepancy between self-mapping and between the MHCM and well-established, validated measures. Significance to Defence and SecurityThe psychosocial well-being of CAF personnel is a priority for the Department of National Defence and R2MR training is a primary tool that is employed to promote mental health and well-being in our members, as is the recently developed R2MR app.Overall, our results indicate that self-mapping on the MHCM is consistent, however, it is also associated with some inaccuracies when comparing the self-mapping tool to validated measures.These results are also supported by the results of a separate matching task indicating that discriminating symptom severity between some of the descriptors is hindered.Findings from the current research highlight some of the ways in which the MHCM could be improved upon for the mobile app tool as well as for the R2MR training.

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