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Family Communication Patterns Questionnaire: Development and Validation
Savita Gupta1, Geetika2

1Dr. Savita Gupta, Associate Professor, Faculty of Education, Lovely Professional University, Phagwara (Punjab), India.
2Ms. Geetika, Research Scholar, Lovely Professional University, Phagwara (Punjab), India.
Manuscript received on 15 June 2019 | Revised Manuscript received on 11 July 2019 | Manuscript Published on 17 July 2019 | PP: 542-550 | Volume-8 Issue-1C2 May 2019 | Retrieval Number: A10890581C219/2019©BEIESP
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)

Abstract: Varied case studies and research was conducted to conceptualize the concept of Family Communication Patterns (FCP) and it was introduced first time in the year 1973. It is gaining lot of impetus these days as family structure, family style and communication pattern is altering. Family communication patterns indicate the interaction among family members to arrive at the common principles and decision. The aim of the current study was to simplify the construct of FCP by validating and developing family communication patterns scale in Indian context. For the study 300 respondents from different senior Secondary Schools from different districts of Punjab, India were selected by random sampling technique. Well-sustained and prominent scale development approach was adopted. The findings corroborated that Family Communication Patterns (FCP) can be disintegrated into two dimensions viz Conversational Orientation and Conformity orientation. Furthermore, family communication patterns questionnaire has requisite internal consistency indices that is Cronbach’s alpha came out α =.869, which indicates that questionnaire comprises the substantial psychometric features.
Keywords: Family Communication Patterns, Scale Development, Secondary School Students, Factor Analysis.
Scope of the Article: Communication Architectures for Pervasive Computing