Measuring Need Satisfaction and Frustration in Educational and Work Contexts: The Need Satisfaction and Frustration Scale (NSFS)
By Ylenio Longo, A. Gunz, G. Curtis, Tom Farsides. 2016
152 citations recorded by the source corpus.
Abstract The satisfaction and frustration of the psychological needs for autonomy, relatedness and competence predict well-being and ill-being outcomes. However, research within educational and work contexts is stifled by the lack of an exhaustively validated measure. Following extensive preparatory and pilot work, the present three studies (total N = 762) aimed to develop such a measure and validate it against the Basic Need Satisfaction at Work Scale (Deci et al. in Personal Soc Psychol Bull 27(8):930–942, 2001) and an adapted version of the Balanced Measure of Psychological Needs (Sheldon and Hilpert in Motivation Emot 36(4):439–451, 2012). The Need Satisfaction and Frustration Scale demonstrated a better factor structure and internal reliability than its predecessors, and good criterion validity. This improvement was due to the exclusion of ambiguous items and items measuring antecedents of need satisfaction and frustration. The results also strengthen current evidence showing that need satisfaction and frustration are distinct but related constructs, and each better predicts well-being and psychological health problems, respectively.
Subfields: Applied Psychology, Social Psychology
View Paper: https://www.semanticscholar.org/paper/77079ba24f6543db74bdbd5c02c85f709c760701
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Citations in the corpus
- General Need for Autonomy and Subjective Well-Being: A Meta-Analysis of Studies in the US and East Asia (2017, unknown): “…(e.g., Chen et al. 2014), having an undetermined location of data collection (e.g., Schu¨ler et al. 2013), focusing on domain-specific variables (e.g., Longo et al. 2014), not using the SDT measurement of autonomy (e.g., Hollifield and Conger 2015), reporting partial regression weights ( b ) rather…”
- Investigating the Multidimensionality of Need Fulfillment: A Bifactor Exploratory Structural Equation Modeling Representation (2018, methodology): “Some studies have also considered this possibility through the reliance on higher order factor models, or models inspired by the multitrait–multimethod tradition (Cordeiro, Paixão, Lens, Lacante, & Luyckx, 2016; Cordeiro, Paixão, Lens, Lacante, & Sheldon, 2016; Longo et al., 2016; Nishimura & Suzuki”