Lack of Training and a Self-Service Environment Leaves Staff and Users Uncertain About Health Information in a Public Library Setting
Notice bibliographique
Résumé
Abstract Objective – To explore the role and expectations of patrons and staff about the role of a public library in enabling citizens’ “health information work.” This involves helping citizens take responsibility for their own health care by finding and using health information. Design – Case study. Setting – A single, UK public library with a self-service delivery model based in a city centre in the spring of 2006. Self-service also applies to reference services and is designed to “empower users to locate and use information on their own.” Subjects – 202 library visitors who came to the library specifically to find health information completed a questionnaire, 15 of these visitors were later interviewed; 19 library staff (10 librarians, 6 library officers and 3 senior managers). Methods – Mixed quantitative and qualitative methods. A print questionnaire was administered to adult library users (age 18 and over). Semi-structured interviews were conducted with fifteen randomly selected library users who completed the questionnaire, sixteen library staff who worked directly with library users, and with three librarians in senior management positions in the library. Descriptive statistics were calculated from the questionnaire, recorded interviews were transcribed, and the text analyzed to identify recurring themes. Main Results – While all respondents came to the library to seek health information results from the questionnaire found that half (50%) of respondents came to the library to look for information on a specific health problem; 37% of respondents had tried finding information elsewhere before coming to the library; 40% usually searched the Internet when they needed health information or advice although only 32% reported trusting the Internet somewhat or completely; 67% intended to borrow books; only 4% indicated that they had planned to ask library staff for help; and 59% reported finding what they were looking for by themselves. Results from the interviews found users, front line staff, and managers in general agreement about the role of the library as a starting point for health information, and that the library was a neutral and non-threatening environment. There was also agreement among the three groups interviewed that the public library fills a gap when health care providers, particularly doctors, are unable to meet the information needs of some of their patients. Library staff were concerned about interpreting information as well as the impact of a self-service philosophy on the quality and length of interactions with users, and seemed unclear about their role in relation to health information provision. Library staff had no training in supporting health information and limited or no knowledge of authoritative online health resources and how to use them, and their approach to Internet searching was similar to users. This lack of training and expertise appeared obvious to library users. Users did not identify interpretation of information by librarians as an issue but did reference the impact of self-service and the Internet on the role and morale of the library staff. Neither library users nor library staff identified librarians as a resource to be used when seeking health information. The value of the library for users was the book collection and they saw the library as second only to physicians as a source of trustworthy information. Conclusion – Uncertainty about the role of librarians in health information provision was evinced by both librarians and library users. Both groups were also uncertain about the relationship between self-service and technology, and the way in which librarians and their work are almost invisible. Health policies emphasize personal responsibility for health yet individuals are not enabled to find answers to their questions. The absence of health knowledgeable front line staff in public libraries is “worrisome.” The obvious trust users have in the library suggests that efforts to develop consumer health information in these settings continue to be a worthwhile response to the “pressures on citizens to take responsibility for their health”.
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Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,006 | 0,014 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,001 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,001 | 0,001 |
| Études des sciences et des technologies | 0,008 | 0,004 |
| Communication savante | 0,006 | 0,003 |
| Science ouverte | 0,001 | 0,005 |
| Intégrité de la recherche | 0,001 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,013 | 0,002 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».