Attachment styles and happiness in the elderly: the mediating role of reminiscence styles

Abstract

Background The current study aims to investigate the relationship between attachment styles and happiness through the mediating role of reminiscence styles in the elderly. Methods This was a correlational study of structural equations modelling (SEM) type. The statistical population included all the elderly aged at least 60 years living in Kermanshah province, Iran in 2021, among whom 380 (182 men and 198 women) were selected using convenience sampling method. Participants filled out the questionnaires of Adult Attachment Styles, Oxford Happiness, and Amani et al.’s Reminiscence Styles. Results The results indicated that secure attachment style has a positive and negative relationship with positive reminiscence (PR) and negative reminiscence (NR), respectively. However, the opposite held true for both avoidant and ambivalent attachment styles. It was also found that secure attachment style has a positive relationship, and avoidant and ambivalent attachment styles have a negative relationship with happiness. Moreover, participants’ gender and age had no moderating effect on the mentioned relationships. The results of SEM indicated that secure and ambivalent attachment styles were associated with happiness through both PR and NR, and avoidant attachment style was associated with happiness only through NR. Conclusions The findings emphasize the significance of the development of internal working models based on the kind of parent-child’s reminiscences and narratives, and the lifelong effects of these models.

The mediating role of early maladaptive schemas in the relationship between attachment styles and loneliness

“…The statistical population of the present study included all the college students of Kermanshah, Iran in the academic year 2020–2021, of whom 338 (256 women and 82 men) were selected through convenience sampling. It is worth explaining that Stevens [ 38 ] considered 15 cases for each predictor variable in multiple regression analysis with the standard least squares model as a good rule of thumb. Based on this issue, it can be stated that as SEM is completely related to multivariate regression in some aspects, the number of 15 items for each measured variable in SEM is not unreasonable.…”

“…Based on this issue, it can be stated that as SEM is completely related to multivariate regression in some aspects, the number of 15 items for each measured variable in SEM is not unreasonable. Loehlin [ 39 ] stated that for models with two or four factors, the researcher should plan on collecting at least 100 cases or more, say 200 cases. Therefore, in order to determine the sample size, the calculation based on the number of components of the research variables was used.…”

Does coping with pain help the elderly with cardiovascular disease? The association of sense of coherence, spiritual well-being and self-compassion with quality of life through the mediating role of pain self-efficacy

“…Regarding the sample size, it is necessary to explain that in the analysis of Stevens [ 51 ], 15 cases for each predictor variable in the multiple regression analysis with the standard least squares method are considered a rule of thumb. Accordingly, it can be stated that because path analysis is completely related to multivariate regression in some aspects, 15 items for each measured variable in path analysis is not unreasonable.…”

“…Accordingly, it can be stated that because path analysis is completely related to multivariate regression in some aspects, 15 items for each measured variable in path analysis is not unreasonable. Loehlin [ 52 ] states that for models with two or four factors, the researcher should plan on collecting at least 100 cases or more, about 200. Therefore, taking into account 15 participants for each component and considering that the current research included 18 components, the minimum number of samples required to conduct the study is 270.…”

The Relationship Between Social Anxiety and the Desire for Cosmetic Surgery: The Mediating Role of Body Image and Appearance-Based Rejection Sensitivity

“…In connection with the sample size, it is worth noting that Stevens (39) stated that considering 15 items for each predictor variable in the multiple regression analysis with the ordinary least squares, of the minimum squared standard is a good rule of thumb. Besides, Loehlin (40) states that for models with two or four factors, the researcher must plan to collect at least 100 participants or more of them, for example, 200. Therefore, in order to determine the sample size, the calculation was performed based on the number of components of the research variables.…”