Contributors to this issue

Geoffrey Blowers
Francis X. Charet
Terence Dawson
David Hewison
John Izod
William E. Kotsch
Patricia Michán
Joe Redfearn
Julieta Besquin Rubinstein
Mara Sidoli     

Seek and ye shall find: test results are what you hypothesize they are

Expert clinicians were given batteries of psychodiagnostic test results (Rorschach, TAT, Draw-A-Person, Bender-Gestalt, Wechsler) to analyze. For half, a battery came along with a suggestion that the person suffers from Borderline Personality disorder, and for half, that battery was accompanied by a suggestion that he suffers from Paranoid Personality disorder. In Study 1, the suggestion was made indirectly, through a background story that preceded the test results. In Study 2, the suggestion was made directly, by the instructions given. The experts saw in the tests what they hypothesized to be there. In particular, the target diagnoses were rated higher when they were hypothesized than when they were not. Copyright © 1998 John Wiley & Sons, Ltd.     

Developing coherence in community and clinical psychology: the integration of idealism and pragmatism

Illustrations of how ideas from community psychology may be integrated with clinical psychological thinking and practice are described from the perspective of a clinical psychologist working in the NHS. The intentions are to consider socially relevant conceptualizations of the causes of people's well-being and distress, and to develop ways of helping individuals and communities to clarify and address these causes. Incorporating an analysis of social power also necessitates a critical awareness of the limited potency of psychological interventions. © 1998 John Wiley & Sons, Ltd.     

医学生临床实习应掌握的几种哲学思维方式

为适应全球卫生事业的迅猛发展,面对医学教育落后于医学发展的现状,转化医学教育迫在眉睫。在第三代“以系统为基础”的教育改革中,培养医学生的哲学思维无疑是其重要环节之一。思维方式必须在医学生步入临床时就要开始正确培养,一旦开始阶段就养成不正确的思维方式、不但会导致医疗过程中的失误,而且再想改变将会有很大难度。本文通过对医学哲学重要性的探讨,剖析医学生哲学思维的不足,阐述了医学生,临床实习过程中应掌握的几种哲学思维方式。旨在提高医学生的哲学理念,促进以岗位胜任能力为导向的医学教育转型发展。     

经皮肺活检对肺部病变的诊断价值

经皮肺活检技术应用已有100多年历史。随着影像技术的不断进步,目前已发展成为肺部疾病的重要诊断技术。本文综述了经皮肺活检对肺部病变的诊断价值。并探讨和比较了不同引导技术的特点,以及适应症、并发症及其处理。     

终末期肾病患者替代治疗方法的临床决策

血液透析、腹膜透析和肾移植是终末期肾病患者替代治疗的主要方法,三种治疗方法各有优缺点。临床上应根据患者原发病因、替代治疗并发症、卫生经济学、生存质量、所在地医疗条件、非医疗因素等作出科学临床决策,最大限度延长患者生命,提高生存质量。     

An empirical Q-matrix validation method for the sequential generalized DINA model

As a core component of most cognitive diagnosis models, the Q-matrix, or item and attribute association matrix, is typically developed by domain experts, and tends to be subjective. It is critical to validate the Q-matrix empirically because a misspecified Q-matrix could result in erroneous attribute estimation. Most existing Q-matrix validation procedures are developed for dichotomous responses. However, in this paper, we propose a method to empirically detect and correct the misspecifications in the Q-matrix for graded response data based on the sequential generalized deterministic inputs, noisy ‘and’ gate (G-DINA) model. The proposed Q-matrix validation procedure is implemented in a stepwise manner based on the Wald test and an effect size measure. The feasibility of the proposed method is examined using simulation studies. Also, a set of data from the Trends in International Mathematics and Science Study (TIMSS) 2011 mathematics assessment is analysed for illustration.     

我国临床药学发展史的回顾及展望

临床药学是一门近几十年发展起来的新兴学科,是近年来我国一个备受关注的领域。它的产生及在我国的发展经历了一个曲折的过程,但却是历史发展的必然结果。纵观整个出现发展过程及现状,让我们思考了很多,对其今后的发展以及我们科学的认识事物有很好的启示。     

Rolling element bearing fault diagnosis using convolutional neural network and vibration image

Detecting in prior bearing faults is an essential task of machine health monitoring because bearings are the vital components of rotary machines. The performance of traditional intelligent fault diagnosis methods depend on feature extraction of fault signals, which requires signal processing techniques, expert knowledge, and human labor. Recently, deep learning algorithms have been applied widely in machine health monitoring. With the capacity of automatically learning complex features of input data, deep learning architectures have great potential to overcome drawbacks of traditional intelligent fault diagnosis. This paper proposes a method for diagnosing bearing faults based on a deep structure of convolutional neural network. Using vibration signals directly as input data, the proposed method is an automatic fault diagnosis system which does not require any feature extraction techniques and achieves very high accuracy and robustness under noisy environments.