Measuring wellbeing effectively in universities

Most universities already have wellbeing dashboards, annual staff surveys and an expanding menu of support offers. Yet, as the American College Health Foundation (ACHF) bluntly notes, there is still no “universally accepted definition of well-being” and campuses are not consistently measuring overall wellbeing or the impact of their efforts. UK research on student wellbeing reaches a similar conclusion: studies “lacked consistency in defining and measuring the construct” and leaned heavily on subjective experience. The result is a quiet but serious problem for HR leaders. Numbers travel easily across committees, but the constructs behind them often do not. Before debating which instrument to use – WEMWBS, PERMA, flourishing scales, or the ACHF Emotional Well-Being Survey – the critical question is simpler and more uncomfortable: what, precisely, do you mean by wellbeing in your institution?

Step one: decide what you mean by ‘wellbeing’ before you measure it

In higher education, the word wellbeing flexes to fit whatever conversation it enters. Sometimes it means happiness and life satisfaction (hedonic wellbeing); sometimes growth, meaning and fulfilment (eudaimonic wellbeing); sometimes a catch-all for mental health, belonging and workload. This conceptual elasticity feels inclusive but plays havoc with measurement. The ACHF team responded by building a multi-dimensional emotional wellbeing map for higher education, spanning community and belonging, social connectedness, confidence, safety and trust, coping and stress management, flexibility, anxiety, purpose and meaning, subjective wellbeing, loneliness, depression and institutional environment. This distinction matters. A campus that defines wellbeing as “feeling good” will design very different questions and interventions from one that treats it as “coping well under strain with a sense of purpose”.

UK work with the Warwick-Edinburgh Mental Well-being Scale (WEMWBS) illustrates the risk. WEMWBS has become a popular choice in student studies, yet the scoping review shows researchers used it against a backdrop of divergent definitions, making cross-study comparison fragile. The same danger applies on your own campus. If student services talk hedonic wellbeing, occupational health talks mental ill-health, and HR talks resilience, a single total score can mask deep disagreement about what is actually improving. HR leaders are well placed to break this pattern by forcing a design conversation rather than defaulting to inherited language. A practical move is to adopt a working definition anchored in a small set of dimensions you can defend: for example, belonging, coping, purpose and institutional environment.

From there, instruments become tools rather than philosophies. The ACHF Emotional Well-Being Survey, piloted across several institutions in 2020–2021, is explicit about its emotional wellbeing focus and multi-domain structure. WEMWBS, by contrast, provides a concise global sense of mental wellbeing. Neither is “right” or “wrong”; each answers different definitional choices. The task for HR is to document those choices so that when your wellbeing score moves, you can say what has changed in human terms, not just numerical ones. That is also where preventative mental fitness tools fit in. Digital-first platforms such as Leafyard’s mental fitness model, built on a behavioural science foundation and framed around mental fitness rather than crisis alone, use interactive assessments and structured journalling to operationalise constructs such as coping, motivation and resilience in everyday behaviour.

Because those constructs are made tangible through microlearning and multi-month journeys, they can bridge the gap between abstract scales and lived experience. When staff work through five-day experiments on sleep or stress and report changes in focus, mood or anxiety, HR gains behavioural data that complements global wellbeing scores rather than competing with them. This is not a replacement for formal instruments; it is a way of grounding your chosen definition of wellbeing in observable habits, not just retrospective self-ratings. Definitional clarity, combined with behavioural evidence, turns wellbeing from a vague aspiration into something you can design around.

Step two: design metrics around trade-offs, not wishful thinking

Once definitions are explicit, the next challenge is architectural rather than philosophical. LearningWell’s analysis of college wellbeing measures highlights two unavoidable negotiations: generalisability versus specificity, and complexity versus brevity. The ACHF pilot, with between seven and ten institutions administering the Emotional Well-Being Survey across terms, leans towards generalisability. So do instruments like the PERMA Profiler, Diener’s Flourishing Scale, Human Flourishing measures and the EPOCH measure. They allow cross-campus or cross-country comparison, but inevitably smooth over local nuance in workload models, assessment patterns or staff role identities. Campus-specific questions, by contrast, can surface issues in a particular faculty or staff group but cannot easily be benchmarked.

The second negotiation is familiar to anyone who has watched survey fatigue erode response rates. To capture multiple emotional, mental and psychosocial domains accurately, you need fine-grained items; to respect people’s time, you need brevity. LearningWell is clear: higher specificity improves inclusivity and nuance but may compromise concision and generalisability. In practice, many universities try to dodge this trade-off and end up with bloated, low-response surveys or ultra-short pulse checks that feel easy but tell you little. A more honest design move is to create a two-layer architecture. Start with a stable core of cross-comparable items – for example, a short WEMWBS or flourishing scale, or the common elements of a tool like the ACHF survey – to give you trend lines over time and, where possible, sector benchmarks.

Then add a smaller rotating layer of institution-specific questions tightly linked to current priorities: doctoral supervision for PGRs, civility for professional services staff, assessment bunching for undergraduates. This core-plus-custom model accepts that not everything can be compared, and that is fine. What matters is that everyone understands which numbers serve which purpose. Digital platforms can help here as well. Leafyard’s behavioural analytics and board-ready reporting, for instance, translate engagement in mental fitness journeys into trends in resilience, habit formation and stress management, expressed in both wellbeing terms and pounds-and-pence ROI. Leafyard’s case studies show that such measurable outcomes can sit alongside traditional survey data, giving HR a second lens: how people are actually using support, not just how they say they feel.

Because Leafyard’s human-centred design and mental fitness framing encourage sustained engagement, the resulting data can reveal whether preventative support is reaching the staff groups you most worry about, long before crisis indicators spike. That kind of early signal is valuable when you are negotiating how complex your formal surveys need to be. If behavioural data show that particular departments are struggling with sleep, focus or coping, you can target local questions and interventions without overloading the entire institution with ever-longer questionnaires. The goal is not a perfect metric set; it is a measurement system that is honest about its compromises and fit for the decisions you need to take.

For university HR leaders, this is ultimately a design brief. First, surface and agree a working definition of wellbeing anchored in defensible dimensions. Then, build a metric architecture that balances generalisability with local insight and depth with practicality, supported by behavioural evidence from tools people actually use, including modern EAPs like Leafyard. A useful next step is to audit your current data through this lens. Ask: which conception of wellbeing is silently driving our metrics, and where are our instruments over- or under-engineered for the choices we face? Convene colleagues from student support, academic leadership and analytics to co-design a shared definition and core-plus-custom measurement set. When wellbeing becomes a shared responsibility, backed by intelligent systems rather than wishful thinking, universities can move from counting struggles to strengthening mental fitness across their communities.