Deconstructing Cancer Patient Information Seeking in a Consumer Health Library Toward Developing a Virtual Information Consult for Cancer Patients and Their Caregivers: A Qualitative, Instrumental Case Study
Bibliographic record
Abstract
BACKGROUND: Cancer patients and their caregivers want information about their disease and are interested in finding health information online. Despite the abundance of cancer information online, it is often fragmented, its quality is highly variable, and it can be difficult to navigate without expert-level knowledge of the cancer system. The Patient & Family Library at the Princess Margaret Cancer Centre offers a broad collection of high-quality cancer health information and staff are available to help patrons refine their questions and explore information needs that they may not have considered. OBJECTIVE: The purpose of this research study was to deconstruct patrons' information-seeking behaviors in the library to assess the feasibility of replicating the services provided in the library through a Web app, extending the service beyond the walls of the cancer centre. The specific aims of this research were to understand (1) how patrons approach information seeking in the library (interface design), (2) how patrons communicate their informational needs (information categorization and metadata requirements), and (3) what resources are provided to address the patrons' information needs (collection development). METHODS: We employed a qualitative, instrumental case study to deconstruct patrons' health information-seeking behavior. The study population included patients, the librarian, and library volunteers. Ethnographic observation was conducted at the library over 3 days and key informant interviews with library staff were conducted to address the first aim. A closed card-sorting activity was conducted to address the second aim and the library shift logs and Search Request Forms (SRFs) were reviewed to address the third aim. RESULTS: A total of 55 interactions were recorded during the ethnographic observation and nine semistructured interviews were conducted during the key informant interviews. Seven library patron personas were identified: (1) Newbie, (2) Seasoned, (3) Direct, (4) Window Shopper, (5) Collector, (6) Information Seeker, and (7) Distressed. A total of 83 participants completed the closed card-sorting exercise. The participants' conceptual clusters within the similarity matrix overlapped with the groupings created by the librarian, with a few differences. A total of 161 entries in the library shift log and 65 SRFs were analyzed to determine what resources were given to patrons. Most resources that patrons received were available online (61%), although almost half of these required special access (47%). CONCLUSIONS: The study findings suggest it is possible to replicate library functions in a Web app with a few exceptions that cannot be replicated online. These elements include access to journal articles or other content behind paywalls and the librarian's ability to encourage further discussion through empathy and active listening. Discussion with the librarian could serve to refine and predict needs through observing information seekers and to provide immediate connection to spiritual care and psychosocial support for patrons in distress.
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How this classification was reachedexpand
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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.000 | 0.013 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".