Exploring varieties of knowledge in safe work practices - an ethnographic study of surgical teams

<p>Abstract</p> <p>Background</p> <p>Within existing research in health and medicine, the nature of knowledge on how teams conduct safe work practices has yet to be properly explored.</p> <p>Methods</p> <p>We address this concern by exploring the varieties in which knowledge is expressed during interdisciplinary surgical operations. Specifically, the study was conducted in a surgical section of a Norwegian regional general hospital, between January and April of 2010, by means of an ethnographic design combining detailed non-participant observations, conversations and semi-structured interviews.</p> <p>Results</p> <p>Based on an analysis of the gathered data, we identify three particular themes in how knowledge is expressed by operating room personnel: (i) the ability and variety individuals demonstrate in handling multiple sources of information, before reaching a particular decision, (ii) the variety of ways awareness or anticipation of future events is expressed, and (iii) the different ways sudden and unexpected situations are handled by the individual team members.</p> <p>Conclusions</p> <p>We conclude that these facets of knowledge bring different insights into how safe work practices are achieved at an individual and team level in surgical operations, thus adding to the existing understanding of the nature of knowledge in safe work practices in surgical operations. Future research should focus on exploring and documenting the relationships between various elements of knowledge and safe work practices, in different surgical settings and countries.</p

Neurological symptoms among dental assistants: a cross-sectional study

<p>Abstract</p> <p>Background</p> <p>Dental assistants help the dentist in preparing material for filling teeth. Amalgam was the filling material mostly commonly used in Norway before 1980, and declined to about 5% of all fillings in 2005. Amalgam is usually an alloy of silver, copper, tin and mercury. Copper amalgam, giving particularly high exposure to mercury was used in Norway until 1994. Metallic mercury is neurotoxic. Few studies of the health of dental assistants exist, despite their exposure to mercury. There are questions about the existence of possible chronic neurological symptoms today within this working group, due to this exposure. The aim of this study was to compare the occurrence of neurological symptoms among dental assistants likely to be exposed to mercury from work with dental filling material, compared to similar health personnel with no such exposure.</p> <p>Methods</p> <p>All dental assistants still at work and born before 1970 registered in the archives of a trade union in Hordaland county of Norway were invited to participate (response rate 68%, n = 41), as well as a similar number of randomly selected assistant nurses (response rate 87%, n = 64) in the same age group. The participants completed a self-administered, mailed questionnaire, with questions about demographic variables, life-style factors, musculoskeletal, neurological and psychosomatic symptoms (Euroquest).</p> <p>Results</p> <p>The dental assistants reported significant higher occurrence of neurological symptoms; psychosomatic symptoms, problems with memory, concentration, fatigue and sleep disturbance, but not for mood. This was found by analyses of variance, adjusting for age, education, alcohol consumption, smoking and personality traits. For each specific neurological symptom, adjusted logistic regression analyses were performed, showing that these symptoms were mainly from arms, hands, legs and balance organs.</p> <p>Conclusion</p> <p>There is a possibility that the higher occurrence of neurological symptoms among the dental assistants may be related to their previous work exposure to mercury amalgam fillings. This should be studied further to assess the clinical importance of the reported symptoms.</p

Human-Centered Design (HCD) of Personal Decision Support System (PDSS) for understandable individual health management, using Natural Language Processing (NLP) and machine learning

This project addressed the challenges of patients to comprehend typical information (e.g. in the form of ''doctor letters'' or ''patient journals'') about their health condition, and to get understandable and personalized recommendations in a user friendly way to improve their health and well-being, considering their individual and actual health status. The chosen approach has been to explore the possibilities of natural language processing technologies and use of machine learning (particularly random forests), integrated in a Human-Centered Design of a personal decision support system. The project followed a combination of Design Science Research Methodology and Human-Centered Design Methodology. For the initial user needs assessment, 12 interviews with potential users of the target application were carried out, representing varying degrees of experience with the Norwegian health care system. The interviews showed a large gap in the comprehension of the information contained in personal medical journals, and resulted in the problem specification, needs assessment, and a PACT analysis. Further a series of requirements were produced with the use of Volere shells. The project was divided into three main parts, Natural Language Processing (for the data extraction and content summarization), personal health suggestions (with use of machine learning and feature importance determination), and front end design (for an integrated target application). The language processing was largely based on pre-trained transformer based models tuned for downstream tasks. Several models trained with biomedical and clinical text were evaluated on automated summarization, semantic search and assertion detection, and showed promising results. Areas of improvement and future work were summarization of short texts and formal evaluation of medical term explanations. The front end design went trough three iterations, a low fidelity prototype in the for of a paper prototype, and two versions of the high fidelity prototype. The user testing showed an improvement in understanding of medical data in both high fidelity prototypes. The health suggestion were based on the feature importance determination of random forests. Three different determination methods were tested, finding minor variations in results, but with Gini Importance gaining a major advantage in computational speed. The recommendation produced could not be tied to clinical results but would require further study to prove or disprove the effectiveness of the recommendations

Human-Centered Design (HCD) of Personal Decision Support System (PDSS) for understandable individual health management, using Natural Language Processing (NLP) and machine learning

This project addressed the challenges of patients to comprehend typical information (e.g. in the form of ''doctor letters'' or ''patient journals'') about their health condition, and to get understandable and personalized recommendations in a user friendly way to improve their health and well-being, considering their individual and actual health status. The chosen approach has been to explore the possibilities of natural language processing technologies and use of machine learning (particularly random forests), integrated in a Human-Centered Design of a personal decision support system. The project followed a combination of Design Science Research Methodology and Human-Centered Design Methodology. For the initial user needs assessment, 12 interviews with potential users of the target application were carried out, representing varying degrees of experience with the Norwegian health care system. The interviews showed a large gap in the comprehension of the information contained in personal medical journals, and resulted in the problem specification, needs assessment, and a PACT analysis. Further a series of requirements were produced with the use of Volere shells. The project was divided into three main parts, Natural Language Processing (for the data extraction and content summarization), personal health suggestions (with use of machine learning and feature importance determination), and front end design (for an integrated target application). The language processing was largely based on pre-trained transformer based models tuned for downstream tasks. Several models trained with biomedical and clinical text were evaluated on automated summarization, semantic search and assertion detection, and showed promising results. Areas of improvement and future work were summarization of short texts and formal evaluation of medical term explanations. The front end design went trough three iterations, a low fidelity prototype in the for of a paper prototype, and two versions of the high fidelity prototype. The user testing showed an improvement in understanding of medical data in both high fidelity prototypes. The health suggestion were based on the feature importance determination of random forests. Three different determination methods were tested, finding minor variations in results, but with Gini Importance gaining a major advantage in computational speed. The recommendation produced could not be tied to clinical results but would require further study to prove or disprove the effectiveness of the recommendations

Hvordan ble de norske P-3 Orion-flyene anvendt etter den kalde krigen (1991-2008)?

Denne oppgaven skal gjennom å se på endringene i NATOs strategiske konsept, Norges sikkerhetspolitiske situasjon og omstillingen i Forsvaret etter den kalde krigen, forsøke å finne ut hvordan de norske P-3 Orion-flyene ble anvendt, og se om det finnes noen sammenhenger. Problemstillingen valgt for oppgaven er derfor som følger: Hvordan ble de norske P-3 Orion-flyene anvendt etter den kalde krigen (1991-2008)?publishedVersio

Airway symptoms and lung function in the local population after the oil tank explosion in Gulen, Norway

Background: Oil tanks containing a mixture of hydrocarbons, including sulphuric compounds, exploded and caught fire in an industrial harbour. This study assesses airway symptoms and lung function in the nearby population 1½ years after the explosion. Methods: A cross-sectional study included individuals ≥18 years old. Individuals living 20 km away formed a control group. A questionnaire and spirometry tests were completed by 223 exposed individuals (response rate men 70%, women 75%) and 179 control individuals (response rate men 51%, women 65%). Regression analyses included adjustment for smoking, occupational exposure, atopy, infection in the preceding month and age. Analyses of symptoms were also adjusted for stress reactions related to the accident. Results: Exposed individuals experienced significantly more blocked nose (odds ratio 1.7 [95% confidence interval 1.0, 2.8]), rhinorrhoea (1.6 [1.1, 3.3]), nose irritation (3.4 [2.0, 5.9]), sore throat (3.1 [1.8, 5.5]), morning cough (3.5 [2.0, 5.5]), daily cough (2.2 [1.4, 3.7]), cough >3 months a year (2.9 [1.5, 5.3]) and cough with phlegm (1.9 [1.2, 3.1]) than control individuals. A significantly increasing trend was found for nose symptoms and cough, depending on the proximity of home address to explosion site (daily cough, 3-6km 1.8 [1.0, 3.1], <3km 3.0 [1.7, 6.4]). Lung function measurements were significantly lower in the exposed group than in the control group, FEV1 adjusted mean difference −123 mL [95% confidence interval −232, -14]), FEV1% predicted −2.5 [−5.5, 0.5], FVC −173 mL [− 297, -50], FVC% predicted −3.1 [− 5.9, -0.4], and airway obstruction (GOLD II/III). Conclusions: Based on cross sectional analyses, individuals living in an area with air pollution from an oil tank explosion had more airway symptoms and lower lung function than a control group 1½ years after the incident

Validation of a full-shift benzene exposure empirical model developed for work on offshore petroleum installations on the Norwegian continental shelf

Workers on offshore petroleum installations might be exposed to benzene, a carcinogenic agent. Recently, a full-shift benzene exposure model was developed based on personal measurements. This study aimed to validate this exposure model by using datasets not included in the model. The exposure model was validated against an internal dataset of measurements from offshore installations owned by the same company that provided data for the model, and an external dataset from installations owned by another company. We used Tobit regression to estimate GM (geometric mean) benzene exposure overall and for individual job groups. Bias, relative bias, precision, and correlation were estimated to evaluate the agreement between measured exposures and the levels predicted by the model. Overall, the model overestimated exposure when compared to the predicted exposure level to the internal dataset with a factor of 1.7, a relative bias of 73%, a precision of 0.6, a correlation coefficient of 0.72 (p = 0.019), while the Lin’s Concordance Correlation Coefficient (CCC) was 0.53. The model underestimated exposure when compared to the external dataset with a factor of about 2, with a relative bias of −45%, a precision of 1.2, a correlation coefficient of 0.31 (p = 0.544), and a Lin’s CCC of 0.25. The exposure model overestimated benzene exposure in the internal validation dataset, while the precision and the correlation between the measured and predicted exposure levels were high. Differences in measurement strategies could be one of the reasons for the discrepancy. The exposure model agreed less with the external dataset.publishedVersio

Airway symptoms and lung function in the local population after the oil tank explosion in Gulen, Norway

Background: Oil tanks containing a mixture of hydrocarbons, including sulphuric compounds, exploded and caught fire in an industrial harbour. This study assesses airway symptoms and lung function in the nearby population 1½ years after the explosion. Methods: A cross-sectional study included individuals ≥18 years old. Individuals living 20 km away formed a control group. A questionnaire and spirometry tests were completed by 223 exposed individuals (response rate men 70%, women 75%) and 179 control individuals (response rate men 51%, women 65%). Regression analyses included adjustment for smoking, occupational exposure, atopy, infection in the preceding month and age. Analyses of symptoms were also adjusted for stress reactions related to the accident. Results: Exposed individuals experienced significantly more blocked nose (odds ratio 1.7 [95% confidence interval 1.0, 2.8]), rhinorrhoea (1.6 [1.1, 3.3]), nose irritation (3.4 [2.0, 5.9]), sore throat (3.1 [1.8, 5.5]), morning cough (3.5 [2.0, 5.5]), daily cough (2.2 [1.4, 3.7]), cough >3 months a year (2.9 [1.5, 5.3]) and cough with phlegm (1.9 [1.2, 3.1]) than control individuals. A significantly increasing trend was found for nose symptoms and cough, depending on the proximity of home address to explosion site (daily cough, 3-6km 1.8 [1.0, 3.1], <3km 3.0 [1.7, 6.4]). Lung function measurements were significantly lower in the exposed group than in the control group, FEV1 adjusted mean difference −123 mL [95% confidence interval −232, -14]), FEV1% predicted −2.5 [−5.5, 0.5], FVC −173 mL [− 297, -50], FVC% predicted −3.1 [− 5.9, -0.4], and airway obstruction (GOLD II/III). Conclusions: Based on cross sectional analyses, individuals living in an area with air pollution from an oil tank explosion had more airway symptoms and lower lung function than a control group 1½ years after the incident.publishedVersio

Health-related quality of life from 20 to 32 years of age in very low birth weight individuals : a longitudinal study

Background Preterm birth with very low birth weight (VLBW, birth weight < 1500 g) is associated with health problems later in life. How VLBW individuals perceive their physical and mental health-related quality of life (HRQoL) is important to understand their putative burden of disease. Previous studies have shown mixed results, and longitudinal studies into adulthood have been requested. This study aimed to investigate differences in HRQoL between preterm VLBW and term born individuals at 32 years of age, and to study changes in HRQoL from 20 to 32 years. Methods In a geographically based longitudinal study, 45 VLBW and 68 term born control participants completed the Short Form 36 Health Survey (SF-36) at 32 years of age. Data from three previous timepoints was also available (20, 23 and 28 years of age). The SF-36 yields eight domain scores as well as a physical and a mental component summary. Between-group differences in these variables were investigated. We also performed subgroup analyses excluding individuals with disabilities, i.e., cerebral palsy and/or low estimated intelligence quotient. Results At 32 years of age, the physical component summary was 5.1 points lower (95% confidence interval (CI): 8.6 to 1.6), and the mental component summary 4.1 points lower (95% CI: 8.4 to - 0.3) in the VLBW group compared with the control group. For both physical and mental component summaries there was an overall decline in HRQoL from 20 to 32 years of age in the VLBW group. When we excluded individuals with disabilities (n = 10), group differences in domain scores at 32 years were reduced, but physical functioning, bodily pain, general health, and role-emotional scores remained lower in the VLBW subgroup without disabilities compared with the control group. Conclusion We found that VLBW individuals reported lower HRQoL than term born controls at 32 years of age, and that HRQoL declined in the VLBW group from 20 to 32 years of age. This was in part, but not exclusively explained by VLBW individuals with disabilities.Peer reviewe