Tavakoli Taba Seyedamir, Hossain Liaquat, Heard Robert, Brennan Patrick, Lee Warwick, Lewis Sarah
Complex Systems Research Group, Faculty of Engineering & IT, the University of Sydney, Sydney, New South Wales, Australia.
Division of Information & Technology Studies, Faculty of Education, the University of Hong Kong, Pokfulam, Hong Kong.
PLoS One. 2016 Feb 26;11(2):e0150186. doi: 10.1371/journal.pone.0150186. eCollection 2016.
In this paper, we propose a theoretical model based upon previous studies about personal and social network dynamics of job performance. We provide empirical support for this model using real-world data within the context of the Australian radiology profession. An examination of radiologists' professional network topology through structural-positional and relational dimensions and radiologists' personal characteristics in terms of knowledge, experience and self-esteem is provided. Thirty one breast imaging radiologists completed a purpose designed questionnaire regarding their network characteristics and personal attributes. These radiologists also independently read a test set of 60 mammographic cases: 20 cases with cancer and 40 normal cases. A Jackknife free response operating characteristic (JAFROC) method was used to measure the performance of the radiologists' in detecting breast cancers.
Correlational analyses showed that reader performance was positively correlated with the social network variables of degree centrality and effective size, but negatively correlated with constraint and hierarchy. For personal characteristics, the number of mammograms read per year and self-esteem (self-evaluation) positively correlated with reader performance. Hierarchical multiple regression analysis indicated that the combination of number of mammograms read per year and network's effective size, hierarchy and tie strength was the best fitting model, explaining 63.4% of the variance in reader performance. The results from this study indicate the positive relationship between reading high volumes of cases by radiologists and expertise development, but also strongly emphasise the association between effective social/professional interactions and informal knowledge sharing with high performance.
在本文中,我们基于先前关于工作绩效的个人和社会网络动态的研究提出了一个理论模型。我们使用澳大利亚放射医学专业背景下的真实世界数据为该模型提供实证支持。通过结构位置和关系维度对放射科医生的专业网络拓扑结构以及放射科医生在知识、经验和自尊方面的个人特征进行了考察。31名乳腺影像放射科医生完成了一份关于他们网络特征和个人属性的专门设计的问卷。这些放射科医生还独立阅读了一组60例乳腺钼靶病例的测试集:20例癌症病例和40例正常病例。采用留一法自由反应操作特征(JAFROC)方法来衡量放射科医生检测乳腺癌的表现。
相关性分析表明,阅片者的表现与度数中心性和有效规模等社会网络变量呈正相关,但与约束性和层级性呈负相关。就个人特征而言,每年阅读的乳腺钼靶片数量和自尊(自我评估)与阅片者的表现呈正相关。分层多元回归分析表明,每年阅读的乳腺钼靶片数量与网络的有效规模、层级性和联系强度的组合是最佳拟合模型,解释了阅片者表现中63.4%的方差。本研究结果表明放射科医生阅读大量病例与专业技能发展之间存在正相关关系,但也强烈强调了有效的社会/专业互动以及与高绩效相关的非正式知识共享之间的关联。