A Next-Gen Psychosocial Risk Assessment Example

In this brief psychosocial risk assessment example, I summarise 3 requirements for next generation quantitative psychosocial risk management.

Popular quantitative psychosocial risk assessment approaches tend to overlook crucial truths about the psychosocial environment.

1. Assessing risk based on prevalence x impact
2. Measuring harm and benefit, and
3. Analysing individual variation

I hope you find it helpful 😊

Transcript:

I’d like to give you a quick Mibo psychosocial risk assessment example visualisation. When it comes to quantitative psychosocial risk assessment, one of the most important and often overlooked realities is that due to things like our individual histories, personalities, life circumstances it’s just not possible for two people to be impacted by the very same psychosocial circumstances in the same way. This is where traditional approaches fall short.

For example, Culture and Engagement surveys do capture perceptions of exposure to some factors but not the impact of that exposure. Also models that consider duration, frequency and severity of hazard exposure to assess risk are a step forward, but these methods are still not suitable to complete a psychosocial risk assessment because of the huge variations in how each person experiences that exposure. Instead, to better understand risk we really need to ask the question:

What impact is this exposure having on you?

And the how we go about risk assesssment at Mibo, so if we look at our psychosocial risk assessment example here, we assess and calculate risk based on Prevelance x Impact which is the most appropriate way to assess psychosocial risk on a 0-100 scale (instead of Likelihood x Consequence). For example, if we look at the Change Management factor here with a group of 10 people where 6 people reported experiencing Change, we can see not a very good change management process in ths case with everyone reporting harm. The other thing to point out here is that we must assess both harm and benefit for relevant factors so we can understand the degree of harm minimisation and protection or support for mental health that protective factors are contributing. This is particularly important to help us understand the interrelated nature of the overall psychosocial environment.

And the last thing is that only reporting average scores is not enough for psychosocial environments because they tend to hide the distribution of impacts that group members are experiencing and so in our psychosocial risk assessment example we report the distribution analysis as well, and what you’ll find even in small groups is big variations based on our individual differences. For example, in this group with Incivility we see people reporting varying degrees of both harm and protection.

If you’d like to learn more about our approach to psychosocial risk management at Mibo please reach out through our website…