Reach Metrics Tell You Who You Missed, Not Whether It Worked

A training programme that reports “94% of participants said they felt more confident afterward” has told you nothing about whether it reached anyone who needed it. A programme that reports “we trained 400 link workers” has told you nothing about whether the training changed what those 400 people did on Monday. Both numbers get written into funder reports as if they were evidence of impact. Neither is.

This confusion is common enough to name: the single-metric trap. A programme picks one number — usually whichever one is easiest to collect — and lets it stand in for the question funders actually want answered, which is “did this work, for the people who most needed it.” Reach and outcome are different questions, and collecting only one leaves you unable to answer either.

What reach measures, and what it can’t

Reach tells you who showed up, relative to who was eligible or intended. For a training programme, that means: how many of the target workforce enrolled, how many completed, and — this is the part most dashboards skip — how the enrolled group compares to the eligible group on the characteristics that predict need.

The AARP Foundation’s 2018 survey of adults 45 and older found that the strongest predictors of loneliness were network size, network diversity, and physical isolation. If a training programme aimed at, say, social prescribing link workers or care coordinators only reaches staff already embedded in well-connected teams, it may post excellent completion rates while never touching the workforce segments most likely to be working with isolated clients. High reach numbers can mask exactly the selection problem the programme was meant to solve.

Reach cannot tell you whether the training changed practice. A 95% completion rate is consistent with a training that was genuinely useful and with one that was mandatory, forgettable, and changed nothing. Completion is a precondition, not a result.

What outcome measures can’t tell you either

Outcome data — confidence scores, knowledge tests, self-reported behaviour change — tells you something about the people who finished the programme. It tells you nothing about the people who didn’t enrol, dropped out at week two, or were never offered a place. Systematic reviews of social prescribing consistently report positive outcomes among participants who completed a link-worker pathway, and a related qualitative synthesis found that people frequently describe benefits going beyond contact itself, toward restored purpose and participation. Both bodies of evidence are honest about a limitation: they describe what happened to people who got as far as being included in the evaluation. They are silent on everyone else.

For training specifically, this matters because training providers can improve their outcome scores simply by tightening who gets in — recruiting more motivated staff, dropping harder-to-reach cohorts, running shorter modules that self-select for the already-engaged. None of that constitutes evidence the training works better. It constitutes evidence the sample changed.

Why you need both, reported together

The fix is not complicated, but it is rarely done. Report reach and outcome as a pair, and be explicit about what each is doing in the argument.

Question	Metric type	What it can support	What it cannot support
Did we reach the right people?	Reach: enrolment vs. eligible population, demographic/role comparison	Claims about equity of access	Claims about effectiveness
Did it change anything for the people reached?	Outcome: pre/post measures, behaviour change, follow-up	Claims about effectiveness for completers	Claims about population-level impact

A funder report that gives only the left column has measured coverage without evidence of value. A report that gives only the right column has measured value without knowing what it was worth to whom.

What this means in practice: before you run a training cohort, decide who was eligible to attend and log that list, not just who signed up. At the end, report completion as a fraction of eligible, broken down by the roles or settings most likely to serve isolated populations — not just an aggregate percentage. Pair it with an outcome measure taken from the same cohort, and say plainly in the report which number answers which question.

The evidence gap this exposes

The wider literature has the same asymmetry. A 2025 protocol reviewing social prescribing for older adults noted that despite growing adoption, only one peer-reviewed randomised controlled trial exists in the area — most of what’s published is uncontrolled programme evaluation, which is well suited to outcome claims among completers and poorly suited to anything about reach or counterfactual effect. The Lancet Healthy Longevity’s 2024 trial of volunteering among lonely older adults in Hong Kong is notable partly because it is one of the few controlled tests in a field otherwise dominated by pre/post designs on self-selected samples. If the underlying intervention evidence is built almost entirely on people who opted in, training evaluations that repeat the same pattern are not adding independent confirmation — they’re adding more of the same blind spot.

Structural access compounds this. Research tracking third-place availability across the United States found closures concentrated in areas with higher social vulnerability and in rural tracts between 2019 and 2021. A training programme’s reach numbers, read against that geography, can reveal whether the workforce being trained even operates in the places where informal social infrastructure has already thinned out.

What this does not solve

Measuring reach and outcome together tells you whether a specific training cohort was appropriately targeted and whether it changed something for those it touched. It does not tell you why the eligible-but-unreached stayed unreached — that requires separate inquiry into referral pathways, scheduling, and trust, none of which a dashboard captures. And it does nothing about the more basic problem: most workforce training, like most social prescribing itself, still reaches the organisations and staff already engaged enough to apply for it in the first place.