Year: 2025
Type: article
Study design: Observational Study
Abstract: Background: Because of the importance of marital adjustment among couples and its effects on physical and mental health, the current study was conducted to determine predictors of marital adjustment among wives based on the beliefs, attitudes, subjective norms and enabling factors (BASNEF) model. Methods: This cross-sectional study was conducted on 300 married women aged 18 to 49 referred to health centers of Torbat Heydariyeh (a city in the northeast of Iran) from April to July 2023. They were selected using a multi-stage cluster sampling method. Data were collected using demographic characteristics and researcher-made BASNEF model constructs. Then, the obtained data were analyzed using descriptive and analytical statistics, including the Pearson correlation and structural equation modeling (SEM), using SPSS software, version 26 and Mplus software, version 6. Results: Most samples were between 30 and 40 years old (37%), had diplomas (39.3%) and were housewives (69.1%). Behavioral intention (ρ=0.635, P<0.05) and enabling factors (ρ=0.335, P<0.05) were directly effective on behavior and the effect of behavioral intention was stronger compared to enabling factors. However, the enabling factors were also indirectly effective on the behavior via the behavioral intention (ρ=0.196, P<0.05). Subjective norms indirectly influence behavior through behavioral intention (ρ=0.175, P<0.05). Knowledge (ρ=0.082, P<0.05) and attitude indirectly (ρ=0.142, P<0.05) affected behavioral intention through subjective norms. Conclusion: BASNEF model constructs are suitable predictors for marital adjustment. Therefore, educational interventions based on the BASNEF model are suggested to be designed and implemented to promote marital adjustment among couples.
Source: Journal of Research and Health
Institution: Torbat Heydarieh University of Medical Sciences
Language: English
Subfield: Social Psychology
Field: Psychology
Domain: Social Sciences
Open Access status: diamond
OpenAlex ID: W4411965781