The Influence Of Individual And Institutional Factors On Counselors ' Intention To Seek Counselling Supervision Services In Nairobi County, Kenya

Despite the awareness of the benefits of counselling supervision such as reducing counsellor’s burnout, enhancing professional development, increasing competence, and efficiency in counselling, the forces that steer counselors into seeking and adopting counselling supervision have not been largely explored. Failure or reluctance to seek counselling supervision may be caused by many factors, some of which could be individual and institutional factors among others. Consequently, the study objective was to examine the influence of individual and institutional factors on counsellor intention to seek supervision services, in Kenya. Two theories informed the study namely: DiMaggio Powell (1983) Institutional Theory (IT) and Ajzen’s (1991) Theory of Planned Behavior(TPB). The TPB examined the individual level factors namely: attitudes, subjective norms,  and perceived behavioral control, while the IT was used to explore the institutional level factors of coercive pressure, mimetic reinforcement, and normative values, as predictors of counsellor's intention to seek supervision services. The research design is a correlational, cross sectional research design, employing both quantitative and qualitative analysis techniques. The sample of 220 respondents was drawn from a target population of 1205 practicing counselors registered by the Kenya Counselling& Psychological Association in Kenya, in Nairobi County, using simple random sampling method. Data was collected using a questionnaire adapted from items used in TPB and IT research. The Statistical Package for Social Sciences (SPSS) 20.0 was used for data analysis to investigatesignificant relationships between the research variables, to extractdescriptive and inferential statistics. Further, the strength of relationship between the individual and institutional level factors and the dependent variable of intention to seek supervision service, utilized multiple linear regression techniques. The multiple linear regression is significant (R 2 =.577, F (6, 95) =21.556, p