In search of the mythical ‘typical library user’

Evidence-based library and information practice (EBLIP) brings together three key ingredients: the best available evidence, professional judgement, and knowledge of user needs and preferences.1 The last of these is frequently taken as a given. If anything, librarians might be criticized for privileging assumptions of what users need over and above evidence on effectiveness. Potentially, this has resulted in the persistence of services of questionable value. Adherents of EBLIP have concentrated on the lack of use of evidence in library decision-making when there is arguably an equally legitimate target—the professional mantra that librarians know what their users need. If we are to use evidence in practice effectively, we need to be convinced that we do have the means to identify what our users need. Without this, we are like a doctor targeting a new purpose-designed treatment at an ill-defined collection of signs and symptoms—we may enjoy the occasional fortuitous success, but our average effectiveness will be poor and, furthermore, we risk the danger of collateral damage from inappropriately targeted interventions. As part of an ongoing mission to make a hamburger of ‘sacred cows’ (Mark Twain), we shall examine how confident we may be that we are sufficiently sensitized to the needs of the population we serve. Most practising librarians recognize the importance of making a distinction between users and non-users. Clearly, there is an important difference in how well we perceive that we are meeting the needs of our ‘user community’ if we look simply, either quantitatively or qualitatively, at users of our library compared with the entire eligible population. Indeed, the literature on user needs captures this distinction in differentiating between methodologies that purposively sample library users only, and ‘community studies’ which use random sampling to identify both users and non-users.2 While the inclusion of the latter within a study population may address inequitable provision, within the context of a library survey it can simply become a form of ‘political correctness’. Why do we say this? Well, rather than offering novel insights on what your library ought to be doing to attract this ‘untapped’ population, non-users generally offer very conservative comments along the lines of ‘more of the same’.3 If we are simply trying to report the needs of our actual users, then we will probably be better off surveying only these and explicitly stating that we have not tried to include non-users. Of course, this is not to say that the views of non-users are not important or worth eliciting. If we do wish to capture the opinions of non-beneficiaries from existing services, it is probably best to conduct separate and specific research aimed at this group (such as focus groups or interviews). Needless to say, one of the inherent problems with non-users is that by definition they are less likely to agree to participate in such research anyway! However, some solutions have been suggested.4 Our first take-home message in our search for the mythical ‘typical library user’ is therefore—devise separate research strategies for targeting the needs of users and non-users. Our second area for debate is ‘What exactly do we mean by the term “library user”?’ A library is, at least in most cases, a physical place, an organization, and a virtual provider of services. Working within a university, I make much of the fact that I have not visited the university library to use its services since my appointment as an academic over 8 years ago. I have, of course, visited the physical place of the library on several occasions, principally for meetings. I have a library membership card that gains entry, not least to attend quarterly Faculty Library Committee meetings as a fully eligible member of the organization. Notwithstanding these, I use library services virtually (in both senses of the word) every day of the year. Of course, the term ‘library user’ can be applied equally to any of these three patterns of behaviour. We need to ensure that we pick the most appropriate definition for our purpose and that this then translates into an appropriate methodology of data collection.4 If I am interested in physical use of the library, I will perhaps use entry or exit methodology, being particularly careful to select a wide and indicative range of dates and times within which to capture data. If, on the other hand, I am interested in library members, I will perhaps employ some random sampling based on membership numbers. I may follow this up with specific strategies to make sure that numerically under-represented groups (e.g. the hospital chaplain) are included as well as dozens of junior doctors or scores of nurses. Finally, if my purpose is to survey those who use the library's virtual services, such as databases or electronic journals, I may attach an online questionnaire to these interfaces. I need to decide whether I am more interested in uses (in which case a user may be asked to complete more than one questionnaire) or in users (in which case I would strictly ration one questionnaire per user). The distinction between different definitions of user becomes particularly important if they are used in performance metrics. A ratio of books loaned to a number of users (which we want to be high) will look more favourable if it only uses data on those who physically use the library. In contrast, an attempt to win increased funding would divide resources allocated by the total number of registered users, regardless of how recently, if ever, they have used our services. Finally, for services used virtually, we might choose not to use ‘users’ at all, but some metric that captures multiple use such as number of accesses. Indeed, our main challenge with this latter type of service is not necessarily encouraging use per se, but rather making users aware that the library is the provider and funding source of facilities that they are using almost invisibly—the electronic equivalent of identifying interlibrary loans with a library stamp or sticker. Our second take-home point is—select a denominator that is most appropriate, or even most favourable, for the service being evaluated. Finally, the example of my own use of a library highlights a need to shift our mindset such that we no longer label those who do not use our services as problematic or ‘informationally challenged’. The analogy is with the literature on compliance with medication which crudely divided patients into compliant and non-compliant. Research has identified that a subgroup of those previously labelled non-compliant is actually well informed and make decisions based not on ignorance, but perhaps on a greater level of knowledge than those who comply without questioning.5 A proportion of those whom we have previously labelled as ‘non-users’ may actually have extremely resourceful information behaviour. They may be fully aware of what the library can provide—a group that I have tentatively labelled ‘knowledgeable non-users’. Some evidence for this type of behaviour comes from Palmer's study of biochemists, entomologists, and statisticians working in agricultural research.6 She used semi-structured, in-depth interviews to examine personal and organizational variables, and identified five groups: Non-seekers for whom information was either a problem, because of difficulties in finding it, or ‘was almost disregarded because it was rarely sought for problem-solving’; Lone, wide rangers—longer-serving members of the organization, who subscribed to more journals, and regularly scanned outside their own subject fields; Unsettled, self-conscious seekers—either new to the organization or new to the problem area with which they were concerned—they used the library more heavily than any other group; Confident collectors, who had abandoned regular information-gathering, but who kept personal files and used a variety of ways (including personal networks) to collect information; and Hunters who maintained regular routines to make sure that nothing relevant escaped them. The key point is that many such behaviours (possibly 1, 2, and 4 and some elements of 5) could be carried out, particularly given technological developments in the years since Palmer's study, without a pattern of regular library visits. In line with recent trends towards outreach, our best approach may be to capture this wide range of information behaviours and then to identify how we can help such groups maximize the effectiveness of their pre-existing information habits. A third take-home point thus becomes—we should conduct and use broader studies of the information (some would say communication7) needs of the community we serve and not focus on information that, through historical or geographical accident, has been handled by or located in the library. The next point regarding users relates to the paradox, some would say the curse, of the user representative. Simply speaking, this states that, given our users’ general inertia and indifference to ‘all things library’, as soon as a user volunteers for membership of a library committee, or even a focus group of library users, they cease becoming ‘representative’ of the group from which they were sought. This is a well-observed phenomenon within health services research where patient representatives are often unable to represent more than their own individualized perception of their illness and their associated priorities.8 Furthermore, with increased longevity and exposure to an educational programme that user representatives receive through committee papers and formal presentations, they become ever less representative. Again, this does not mean that there is no place for such persons on the library committee—they can prove invaluable as advocates and product champions. My point again centres on the fact that they are unsuited for the purpose of establishing user needs. Take-home message number 4 is—we should not confuse mechanisms for communication or consultation with mechanisms for capturing user needs. Of course, problems regarding the non- representativeness of our population plague most methods we could use to try to investigate user needs. An average response rate for published library surveys approaches 65%9 (although it could more typically approach 35–40% for surveys that we might conduct that do not make it through to publication). This means that any assessment of user needs misses one-third of potential respondents from the very start. If this missing third is equally distributed, then we could still draw valid conclusions (in fact, we would simply scale up our sample size to compensate). However, what actually causes the problems is the fact that: (i) the respondents present some form of bias and, more importantly (ii) that we do not know what the effects and direction of the likely bias will be. It is unlikely that we could eliminate the actual bias. The suggested response is, therefore, to try to quantify what the likely effect of the bias will be.9 We can do this by obtaining good demographic information on the population we are surveying, and then compare the actual distribution of different user groups with the distribution of responses. If, for example, 18% of hospital staff were consultants and yet only 5% of our respondents are in that staff category, we have every reason to believe that the views of more senior users are under-represented. Take-home message number 5 is—we should seek to establish the extent to which our method of investigation represents our population of interest, the presence of likely biases, and the likely effect of such biases. Recent research using the Customer Value Discovery methodology at venues such as Nottingham Trent University has revealed significant gaps in library staff perceptions of user needs.10, 11 In particular, library staff tended to underestimate the impact/value/frequency of certain sub-optimal features (‘irritants’) of the service and, indeed, failed to predict some irritants at all! Furthermore, we know that use of library services is not normally distributed. A study of users at Shell Research noted that those who made use of the greater number of services tended to be above-average users of each service, and that above-average use was shared by a small number of users: This means that some of those research workers who read more journals than average also read more than the average number of reports, and at the same time ask more than the average number of questions.12 Neither have we stopped to consider the further problem that users may not actually know what they need or that they may not be able to articulate it in a form that a librarian is able to understand and then interpret in terms of available or potential services. All of the above evidence, admittedly collected purposively and not systematically, gives us cause to challenge the myth of the ‘typical’ or ‘average’ user. Indeed, this analysis focuses only on difficulties in characterizing our users at a population level and skirts equally important issues around variations in their individual behaviour.13 For example, if I have significant time to prepare for a meeting or project, I may spend much time gathering extensive information, but if I am operating under time constraints for the same meeting or project, I may ‘satisfice’ with the best available item of information identifiable within the given time.14 If even our ‘average user’ does not behave ‘averagely’, what hope do we have of accurately capturing their needs! Of course, the intention of the above provocative piece is not to induce a form of organizational paralysis by which we conclude that it is not worth targeting the information needs of our users at all. That would hardly advance the paradigm of using evidence in practice, would it? What we are demonstrating, with judicious examples and occasional contributions from the literature, is further evidence of the truth of the statement—‘Fuzzy questions tend to lead to fuzzy answers’.15 EBLIP provides a toolbox from which we all can select, resisting the temptation to carry out a rapid but botched job. We would all do well to remember the caveat—‘to the person with a hammer, everything is a nail!’