Evidence Summary

Demographic Variables Are Associated with Differing Perceptions of a Broad Range of Public Library Benefits

A Review of:

Sin, S.-C. J., & Vakkari, P. (2015). Perceived outcomes of public libraries in the U.S. Library & Information Science Research, 37(3), 209-219. http://dx.doi.org/10.1016/j.lisr.2015.04.009

Reviewed by:

Sara Sharun

Campus Librarian

Okanagan College Library

Penticton, British Columbia, Canada

Email: ssharun@okanagan.bc.ca

Received: 1 Mar. 2016 Accepted: 8 Apr. 2016

2016 Sharun. This is an Open Access article distributed under the terms of the Creative Commons‐Attribution‐Noncommercial‐Share Alike License 4.0 International (http://creativecommons.org/licenses/by-nc-sa/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly attributed, not used for commercial purposes, and, if transformed, the resulting work is redistributed under the same or similar license to this one.

Abstract

Objective – To determine the frequency and nature of perceived beneficial outcomes of public libraries on individuals, and to identify demographic differences in these perceived outcomes.

Design – Self-administered, online questionnaire asking respondents to rate the frequency of benefits they received from public libraries in 22 areas of life including education, work, and business; everyday activities; and leisure activities.

Setting – United States of America.

Subjects – 1010 respondents from 49 states: 50% female, 76% white, 55% urban or suburban.

Methods – Correspondence analysis was used to visualize relationships between demographic variables and perceived outcomes. Exploratory factor analysis was used to identify structures among the outcomes and summarize data into three core dimensions: everyday activities and interests; reading and self-education; and work and formal education. Multiway ANOVAs were used to test the significance of demographic differences on perceived outcomes.

Main Results – The most highly ranked areas of perceived benefits were reading fiction and non-fiction, self-education during leisure time, interest in history or society, and health. Outdoor activities, exercise, and sport ranked the lowest. Respondents in younger age groups reported benefits in “education and work,” as did ethnic minorities and people with lower household incomes. “Everyday life” benefits were reported by male, suburban, White, middle-income respondents. “Reading and self-education” benefits were reported by high-income, older age groups, White, and female respondents. Two demographic groups did not correspond to any benefit categories: those who did not graduate high school and those over age 65.

Conclusion – There are significant differences among demographic groups in how the benefits of public libraries are perceived, and these demographic differences have implications for program planning, marketing, and outreach in public libraries. Specifically, libraries should work to increase and improve service to less-advantaged groups, including low-income earners and ethnic minorities, and make available more services and resources relevant to older people.

Commentary

This study attempts to fill a gap in the LIS assessment literature by defining and examining outcomes, rather than outputs, of public libraries. The authors make an interesting case for the need to measure broader, more inclusive outcomes and their impact on individuals and communities, instead of the more discrete and quantifiable outputs of specific library programs or services. The study, which was based on methods used in a previous study conducted in Finland (Vakkari & Serola, 2012), is well designed. The results are clearly stated (although the terminology used may pose a challenge for readers without a statistical background) and conclusions are accurately reflected in the data.

While the study design and reporting of results are strong, this study’s validity is questionable when the study population and data collection method are considered under critical appraisal criteria (Glynn, 2006). The sample does not seem to be representative of the larger population (i.e., respondents were 76% white). An Internet survey company was used to gather data, and it is not clear how the sample was recruited or selected. These issues may call into question the significance of the sample and the validity of claims made regarding demographic differences. The demographic differences in perceptions may be true for the sample, but the authors do not effectively argue that the sample is representative of the population. The strength of the evidence presented would have been stronger had the authors provided more rationale for their data collection methods. This would not only be helpful for other researchers looking to conduct similar research, but would also have bearing on the comparisons made to the Finnish data, which was collected with different methods from a different population sample.

The authors give due attention to the limitations of surveys and self-reported data, but a stronger case for the reliability of their data could be demonstrated by presenting full details of the questionnaire, which would allow for insight into how respondents might have been influenced by the language of the survey, and how the manner in which categories and examples were presented to respondents might account for differences in responses from people with different demographic backgrounds. More information on category descriptions would also help validate the factor analysis and the establishment of three factors underlying the discussion of demographic differences in perceived outcomes.

So much of LIS research is done at the case-study level, producing results that are usually not generalizable. This study presents an opportunity, in the form of a potentially robust measurement tool, to move beyond case studies and gather comparative data. Information on the reliability and validity of the survey tool, as well as access to the questionnaire, would be welcome by LIS researchers as a tool for benchmarking and comparing data from diverse populations, and would help facilitate the type of research the authors recommend. This way, comparisons made between nations or other large populations might be more reliable, and librarians would have data that they could then triangulate with local data, thereby improving the quality of evidence on the benefits of public libraries to communities.

References

Glynn, L. (2006). A critical appraisal tool for library and information research. Library Hi Tech, 24(3), 387-399. http://dx.doi.org/10.1108/07378830610692154

Vakkari, P., & Serola, S. (2012). Perceived outcomes of public libraries. Library & Information Science Research 34(1), 37–44. http://dx.doi.org/10.1016/j.lisr.2011.07.005