Existential, Relatedness, Growth (ERG) needs’ dimensions of medical students for rural posting – An analytical study
Main Article Content
Abstract
The retention of rural doctors in India is a very big challenge. Despite the mandatory rural postings, year by year rural health statistics indicate an abysmal picture of rural doctors' vacancies and their shortfalls in many states. Various studies stipulate that rural doctors are quitting rural postings. A reliable instrument to identify the motivational needs of doctors towards their rural postings, suitable to the Indian context, which is vital for both policymakers and doctors alike. So, this study aims to acquire the reliability of the Existential, relatedness, and Growth needs of Doctors’ questionnaire and to obtain the dimensions of needs as an initial attempt. An ERG motivational need questionnaire was developed to explain the needs of medical graduates and rurally placed physicians in Indian context. A literature search and pilot study with 64 medical students conducted and relevant items were extracted. This study was conducted in Jaipur, Chennai, and Pondicherry. The reduction of items was done through principal component analysis in SPSS. Cronbach Alpha coefficient is considered to measure for internal consistency reliability of the instrument. The instrument is developed with three constructs namely Existential needs (EN), Relatedness Needs (RN), and Growth Needs (GN) with a 5-point Likert scale. The exploratory factor analysis after three rotations converged to 9 factors with 74.103 total variance and 0.606 Kaiser-Meyer- Olkin index indicating sampling adequacy. The initial scale items (with 58 Items) were reduced to 9 factors with 28 items in the final questionnaire. Overall scale is with Cronbach alpha value of 0.851 for these items. The result obtained has proven that the extracted 9 factors have good reliability to obtain the dimensions of Existential, relatedness, and growth needs. The study results have implications in addressing the problem of Rural doctors’ shortage.
Downloads
Metrics
Article Details
Licensing
TURCOMAT publishes articles under the Creative Commons Attribution 4.0 International License (CC BY 4.0). This licensing allows for any use of the work, provided the original author(s) and source are credited, thereby facilitating the free exchange and use of research for the advancement of knowledge.
Detailed Licensing Terms
Attribution (BY): Users must give appropriate credit, provide a link to the license, and indicate if changes were made. Users may do so in any reasonable manner, but not in any way that suggests the licensor endorses them or their use.
No Additional Restrictions: Users may not apply legal terms or technological measures that legally restrict others from doing anything the license permits.