Depressive Cognitions Impact On A Latent Growth Curve Model Of Depressive Symptoms In Caregiving Grandmothers

Grandmothers caring for grandchildren have elevated levels of depressive symptoms compared to grandmothers who do not provide care. While the CES-D measures the somatic, positive and negative affect, and interpersonal strain symptoms experienced with depression, the Depressive CognitionScale © captures the change in cognitive thinking that often precedes depression. Depressive symptoms, on the other hand, are state like in nature and describe depressive symptoms that have happened recently. While depressive cognitions, according to Beck’s theory of depression, are the first negative thought processes to appear, these typically lead to other, more serious symptoms of depression. Specifically, depressive cognitions reflect negative thinking patterns and not depression. Data were collected on 343 participants in a longitudinal nationwide online research study of caregiving grandmothers. A latent growth curve model was used to track the trajectory of depressive symptoms at four time points (baseline, 2 weeks, 12 weeks, and 24 weeks). As depressive cognitions are the precursor to the development of depressive symptoms, a latent growth curve model was tested to gain an understanding of how depressive cognitions impacts the trajectory of depressive symptoms over time. The model fit the data well (Chi Square=21.025; df=9; p=.013; TLI=.976; CFI=.985; RMSEA=.063). Baseline depressive cognitions had a strong impact on the intercept (Standardized Beta=.76, p<.001) and the slope of depressive symptoms (Standardized Beta=-.67, p<.001). The continued impact of depressive cognitions over 24 weeks indicates the need for potential interventions to further address depressive cognitions as a way to decrease depressive symptoms in grandmother caregivers.

Constructing an Adoption Model of Proactive Environmental Strategy: A Novel Quantitative Method of the Multi-Level Growth Curve Model

To fill in the literature flaws that have not been detected in previous studies, this research, therefore, examines the driving factors of proactive environmental strategy (PES). First, this research proposes how corporate social responsibility (CSR) predicts the agricultural company’s PES through the intermediary mechanism of green organization identification (GOI) of the top management team (TMT) according to symbolic context and theory of high-level echelon, to solve the first gap in exploring what factors can drive the PES. Second, this research proposes a multi-level growth curve model (MGCM) to solve how individuals adjust their behavioral intentions over time according to their translation and understanding of their use environment, because past studies consist of almost cross-sectional properties. Third, past research has also neglected the multi-level framework, leading to hierarchical reasoning bias. Therefore, this research believes that the MGCM can fill in the multi-level gap. Finally, this research collected 400 TMT employees from 100 different agricultural companies in Taiwan in three-stage time for six months. The results show that CSR will significantly lead to more growth in GOI, and more growth in GOI will lead to more growth in PES adoption. The research results can not only advance the agricultural sustainability literature but also serve as a guide for agricultural companies to implement PES.

Growth curve model for analyzing the effects of Calcium foliar feed on the wilting rate of post-harvest rose flowers

Cut rose flowers contribute to the economy and development of the export markets for several developing countries. Despite this contribution, profitable production of rose flowers is limited by wilting which leads to lower production. This paper aims to investigate the effects of Calcium foliar feed on the wilting rate of post-harvest rose flowers using the Growth Curve Model. This method was applied to the data consisting of wilting scores on five treatment groups. The Likelihood ratio test was used to test the growth curve and the equality of the growth curves in all groups. Results revealed that the expected growth curves for all groups followed different quadratic functions. The results also revealed that the wilting rate increased with the increase of calcium concentration compared to the control. This leads to a useful model for policy-makers or further analyses.