Problems As Human Concerns John J Grant

What "Problems as Human Concerns" Actually Means in Practice

Most people who run into this idea stumble on it while studying reference work or information retrieval. The basic premise from Problems As Human Concerns John J Grant is straightforward enough, but applying it consistently is where things get messy. Grant, who spent decades as a reference librarian at York University, argued that traditional information-seeking models treat problems as abstract queries. They don't account for the fact that the person asking has context, emotion, urgency, and often a poor understanding of their own actual information gap. I worked a help desk role in an academic library setting for several years. One of the first things I learned is that nearly every reference interaction starts with someone describing their problem in ways that don't map cleanly to any database index or subject heading. A student will say they need "sources on depression" when what they actually need is peer-reviewed research on SSRI effectiveness for adolescents, written within the last five years, for an APA paper. The original request is technically answerable. It's also almost completely useless as given. Grant's framework forces you to sit with that gap. Not dismiss it. Not auto-correct it into a search string and move on. The method is to treat the stated problem as a starting point for investigation, not as the problem itself.

How to Apply the Framework Step by Step

The first step is listening without immediately mapping the query to a known solution path. This sounds trivial until you realize most information professionals do this automatically and then wonder why patrons leave unsatisfied. You spend the first three to five minutes of an interaction just clarifying what's driving the need. Is it academic? Personal? Professional? Deadline-bound? The answers reshape the entire search strategy. Second, identify the real question hidden inside the stated one. Grant emphasized that users rarely articulate their actual concern because they don't know what they don't know. In my experience, this step typically adds five to ten minutes upfront but cuts the overall interaction time in half because you stop chasing tangential leads. I once had someone ask for "information on remote work" who turned out to be drafting a policy for a small nonprofit with twelve employees. Searching for remote work studies aimed at Fortune 500 companies would have wasted everyone's time. Third, formulate a response that addresses the human concern, not just the information gap. This means sometimes the answer isn't a list of sources. It might be explaining why the information they want doesn't exist yet. It might be redirecting them to a counselor, a career advisor, or a different department entirely. Grant's model acknowledges that information professionals are not just search engines. They're filters between human need and available knowledge.

The practical workflow goes like this: hear the request, clarify the context, identify the underlying concern, determine whether the library or another service is the right venue, then deliver either sources or a redirect with a brief explanation of why. Most training programs skip the second and fourth steps because they're harder to standardize. That's a mistake.

What This Framework Gets Wrong

It doesn't scale well in high-volume environments. If you're processing twenty reference queries an hour in a busy public library, spending eight minutes per interaction on context-gathering isn't feasible. I've worked in settings where the metric was average handling time, and the Problems as Human Concerns approach got compressed into a thirty-second triage that mostly amounted to asking "what's this for?" before being pointed at a database. It still helped, but the depth Grant envisioned disappears under those pressures. The framework also assumes the information seeker is cooperative and capable of reflecting on their own needs. That's not always true. I encountered a case where a patron insisted they needed medical advice from journal articles and became hostile when I explained that wasn't what the library does. The framework doesn't give you a good tool for dealing with someone who actively rejects the clarification process. You just have to know when to disengage and refer them elsewhere. There's also a blind spot around digital self-service. Grant wrote before search algorithms became as sophisticated as they are now. A lot of the contextual work he described librarians doing manually is now partially handled by Google's understanding of intent, personalization, and query expansion. That doesn't make his approach obsolete, but it does mean some of the original motivation — bridging the gap between human language and indexed vocabulary — has been partially automated away. The deeper part, the human concern component, hasn't.

When Problems As Human Concerns Actually Fails

The model breaks down in situations where the concern is illegible or deliberately obscured. I once dealt with someone asking for "everything on immigration policy" who was clearly looking for ammunition for a political argument rather than balanced information. The framework gives you tools for honest confusion but not for bad faith requests. In those cases, a standard reference interview protocol with clear boundaries works better than trying to dig for a hidden human concern that may not be worth finding. Another limitation is the time investment. A full application of Grant's approach can add ten to fifteen minutes to a single reference interaction. In a queue-based system, that's significant. The workaround I used was to apply it selectively — full depth for complex, multi-step research needs, abbreviated version for straightforward factual queries. You learn quickly which requests deserve the extra time and which just need a direct answer. The core insight remains useful regardless of the medium. Whether you're a librarian, a UX researcher, a customer support agent, or anyone who fields requests from people who don't fully understand what they need, treating the stated problem as a surface symptom of a deeper concern usually produces better outcomes. The tradeoff is time and patience. Grant knew that. He just thought it was worth it.