The principle of reciprocity in Scharff interviews

Author:

Palena Nicola12ORCID,Granhag Pär‐Anders3,Vrij Aldert4ORCID,Orthey Robin5,Monticciolo Roberto1,Caso Letizia6ORCID

Affiliation:

1. Department of Human and Social Sciences University of Bergamo Bergamo Italy

2. Netherlands Institute for the Study of Crime and Law Enforcement Amsterdam Netherlands

3. Department of Psychology University of Gothenburg Gothenburg Sweden

4. Department of Psychology University of Portsmouth Portsmouth UK

5. Aoyama Gakuin University (Japan) Bestätigte Shibuya‐ku Japan

6. Department of Human Sciences Libera Università Maria SS. Assunta University Rome Italy

Abstract

AbstractStudies on the collection of information (intelligence) show the effectiveness of the Scharff technique and the principle of reciprocity. These two aspects have never been considered at the same time. In the present experiment, we compared the effect of two different forms of reciprocity (intrinsic vs. instrumental) and their combination on the elicitation of information in Scharff interviews. Participants were asked to imagine that an interview took place and were exposed to four reciprocity conditions (no reciprocity, intrinsic reciprocity, instrumental reciprocity, intrinsic and instrumental reciprocity). The results showed that instrumental reciprocity resulted in more information than intrinsic reciprocity.

Publisher

Wiley

Reference38 articles.

1. The Role of Rapport in Investigative Interviewing: A Review

2. Why tough tactics fail and rapport gets results: Observing Rapport-Based Interpersonal Techniques (ORBIT) to generate useful information from terrorists.

3. The efficacy of rapport-based techniques for minimizing counter-interrogation tactics amongst a field sample of terrorists.

4. Blood from a stone: Why rapport works and torture doesn't in'enhanced'interrogations;Alison L.;Investigative Interviewing: Research and Practice, Special Issue,2015

5. Associazione Italiana di Psicologia. (2015).Codice Etico per la Ricerca in Psicologia. Retrieved fromhttps://www.aipass.org/node/11560. Accessed December 15 2022.

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