A Rapid Review of the Reporting and Characteristics of Instruments Measuring Satisfaction with Reference Service in Academic Libraries
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Abstract
 Objective – The objective of this review was to examine research instrument characteristics, and to examine the validity and reliability of research instruments developed by practicing librarians, which measure the construct of patron satisfaction with academic library reference services. The authors were also interested in the extent to which instruments could be reused
 Methods – Authors searched three major library and information science databases: Library and Information Science Technology Abstracts (LISTA); Library Science Database (LD); and Library Literature & Information Science Index. Other databases searched were Current Nursing and Allied Health Literature (CINAHL); Education Resources Information Center (ERIC); Google Scholar; PubMed; and Web of Science. The authors identified studies of patron satisfaction with academic library reference services in which the researcher(s) developed an instrument to study the satisfaction construct. In this rapid-review study, the studies were from 2015 and 2016 only. All retrieved studies were examined for evidence of validity and reliability as primary indicators of instrument quality, and data was extracted for country of study, research design, mode of reference service, data collection method, types of questions, number of items related to satisfaction, and content of items representing the satisfaction construct. Instrument reusability was also determined.
 Results – At the end of the screening stage of the review, a total of 29 instruments were examined. Nearly all studies were quantitative or mixed quantitative/qualitative in design. Twenty-six (90%) of the studies employed surveys alone to gather data. Twelve publications (41%) included a discussion of any type of validity; five (17%) included discussion of any type of reliability. Three articles (10%) demonstrated more than one type of validity evidence. Nine articles (31%) included the instrument in full in an appendix, and eight instruments (28%) were not appended but were described adequately so as to be reusable. 
 Conclusions – This review identified a range of quality in librarians’ research instruments for evaluating satisfaction with reference services. We encourage librarians to perform similar reviews to locate the highest-quality instrument on which to model their own, thereby increasing the rigor of Library and Information Science (LIS) research in general. This study shows that even a two-year rapid review is sufficient to locate a large quantity of research instruments to assist librarians in developing instruments.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.060 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it