两岁儿童对母亲的依恋类型

本研究采用实验室观察法,考察122名21-27个月龄的儿童对母亲的依恋类型,实验室程序包括儿童的自由活动、与陌生人的交往、在多种压力情境下的行为表现,与母亲的分离-重聚等.结果发现(1)本研究中使用的实验室观察程序能够有效地测查两岁儿童对母亲的依恋行为.(2)中国两岁儿童对母亲的依恋有四种类型淡漠型依恋、安全型依恋、缠人型依恋、混乱型依恋,分布比例分别为11%,73%,7%,9%.其中安全型和混乱型依恋的表现与国外研究者描述的美国、日本等国家儿童的行为大体相同,但淡漠型和缠人型依恋为我国儿童所特有,其表现特点与国外研究者描述的焦虑-回避型不安全依恋及焦虑-矛盾型不安全依恋有明显区别.     

Interviewing a Therapist in the Presence of a Couple: A Description of the Therapeutic Process

A therapy research team interviewed a therapist in the presence of a couple. Following each of six consecutive sessions with a couple, an interviewer posed questions to the therapist and couple. While one question was standard to each interview, other questions were generated by team members who tracked the entire process via live observation. These questions were directed first at the therapist, then at the couple, and then focused on therapeutic process and outcome. Findings of this process for the therapy system included decreasing the hierarchy within the client/therapist relationship; increasing the client ownership and energy in the therapy process; discovering the presence of parallel processes between the systems; and informing the direction of future therapy sessions. Practical, clinical implications are discussed for a variety of therapy settings.     

Improving an optimization‐based framework for sensitivity analysis in multi‐criteria decision‐making

The framework for sensitivity analysis in discrete multi‐criteria decision analysis developed by Rios Insua and French allows simultaneous variation of all parameters and applies to many paradigms for decision analysis. However, its computational load may inhibit use, particularly in the context of a decision conference where results are required in near real time. In order to improve on the current algorithm and its implementation, we investigate, on the one hand, an opportunistic approach aimed at reducing the number of optimization problems solved in the original framework and, on the other, an alternative framework based on distance analysis. Computational results on linear and bilinear models are reported. Copyright © 2001 John Wiley & Sons, Ltd.     

Assessing risky public investments with MUSTARD

This paper presents a practical implementation of multicriteria methodologies based on the UTA model by Jacquet‐Lagrèze and Siskos and Quasi‐UTA model by Beuthe and Scannella, which are specified with a non‐linear, but piecewise linear, additive utility function. In contrast with the general UTA model, the Quasi‐UTA specification structures the partial utilities as recursive exponential functions of only one curvature parameter. This allows for a reduction of the quantity of information necessary to build the utility function. The software MUSTARD implements different variants of these models. Firstly, it offers the basic deterministic UTA model of disaggregation, but also its first programmed stochastic version. In both cases, the software proceeds stepwise and interactively helping the decision maker to formulate the problem and state preferences between projects; in the stochastic case, the decision maker is even helped to build the criteria distributions. The Quasi‐UTA specification can be introduced in this disaggregation model. Secondly, the software offers an aggregation model whereby the Quasi‐UTA partial utility functions are built separately through specific questioning processes. The questions relating to deterministic criteria are of the ‘direct rating type’, while those of the stochastic criteria are either of the ‘variable probability’ or the ‘variable outcome’ type. The criteria weights can be assessed by the ‘swing weight’ method or by a UTA‐II side‐program. As an example as well as a test of the Quasi‐UTA aggregation approach, the paper presents its application to a real problem of selecting road investment projects in Belgium. Several experts and civil servants were interviewed, and their individual utility functions derived. The projects are ranked according to their rate of return, which is computed on the basis of the projects certain equivalent money value. Copyright © 2002 John Wiley & Sons, Ltd.     

An evaluation of multi‐criteria methods in integrated assessment of climate policy

Those who conduct integrated assessments (IAs) are aware of the need to explicitly consider multiple criteria and uncertainties when evaluating policies for preventing global warming. MCDM methods are potentially useful for understanding tradeoffs and evaluating risks associated with climate policy alternatives. A difficulty facing potential MCDM users is the wide range of different techniques that have been proposed, each with distinct advantages. Methods differ in terms of validity, ease of use, and appropriateness to the problem. Alternative methods also can yield strikingly different rankings of alternatives. A workshop was held in which climate change experts and policy makers evaluated the usefulness of MCDM for IA. Participants applied several methods in the context of a hypothetical greenhouse gas policy decision. Methods compared include value and utility functions, goal programming, ELECTRE, fuzzy sets, stochastic dominance, min max regret, and several weight selection methods. Ranges, rather than point estimates, were provided for some questions to incorporate imprecision regarding weights. Additionally, several visualization methods for both deterministic and uncertain cases were used and evaluated. Analysis of method results and participant feedback through questionnaires and discussion provide the basis for conclusions regarding the use of MCDM methods for climate change policy and IA analyses. Hypotheses are examined concerning predictive and convergent validity of methods, existence of splitting bias among experts, perceived ability of methods to aid decision‐making, and whether expressing imprecision can change ranking results. Because participants gained from viewing a problem from several perspectives and results from different methods often significantly differed, it appears worthwhile to apply several MCDM methods to increase user confidence and insight. The participants themselves recommended such multimethod approaches for policymaking. Yet they preferred the freedom of unaided decision‐making most of all, challenging the MCDM community to create transparent methods that permit maximum user control. Copyright © 2002 John Wiley & Sons, Ltd.     

Analog scale,magnitude estimation,and person trade‐off as measures of health utility: biases and their correction

Subjects judged the disutility of health conditions (e.g. blindness) using one of them (e.g. blindness+deafness) as a standard, using three elicitation methods: analog scale (AS, how bad is blindness compared to blindness+deafness?); magnitude estimation (ME, blindness+deafness is how many times as bad as blindness?); and person trade‐off (PTO, how many people cured of blindness is as good as 10 people cured of blindness+deafness?). ME disutilities of the less bad condition were smallest, and AS was highest. Interleaving PTO with ME made PTO more like ME. AS disutilities were inconsistent with direct judgments of differences between pairs of conditions. ME and PTO judgments were internally inconsistent: e.g. the disutility of one‐eye‐blindness relative to blindness+deafness was larger than predicted from comparison of each to blindness. Consistency training reduced inconsistency, increased agreement between AS and PTO, and transferred from one method to the other. The results support the use of consistency checks in utility elicitation. Copyright © 2001 John Wiley & Sons, Ltd.     

Are absolute frequencies,relative frequencies,or both effective in reducing cognitive biases?

Biases in probabilistic reasoning are affected by alterations in the presentation of judgment tasks. In our experiments, students made likelihood judgments that an event was produced by various causes. These judgments were made in terms of probability, relative frequency or absolute frequency on a full or a pruned list of causes. When they had little personal experience of the event (causes of death), the pruning bias was smaller with relative frequencies than with absolute frequencies or probabilities. When they had more personal experience of the event (missing a lecture), the bias was less with both types of frequency than with probability but still lowest with relative frequency. We suggest that likelihood information is usually stored as relative frequencies when it has been obtained from public sources but that it is based on event counts when it is derived from personal experience. Copyright © 2000 John Wiley & Sons, Ltd.