Multiple-Goal Approach Among Indonesian University Students

A total of 1006 students from three public and two private universities in Indonesia participated in the study of multiple goals profiling in the Indonesian context. Four multiple-goal clusters, with learning, performance approach, performance avoidance, and work avoidance goals as clustering variables, were educed. Learning goals correlated positively with both performance approach and performance avoidance clusters, and negatively to work avoidance goals. Performance goals correlated positively with both performance avoidance and work avoidance goals. Learning, performance approach and performance avoidance goals correlated positively with self-efficacy. These clusters were further examined in relations to attributions, self-efficacy, theories of intelligence, religiosity, racial/ethnic identity, and academic performance.

Moving Beyond Two Goals: An Integrative Review and Framework for the Study of Multiple Goals

Historically, the study of multiple goals has focused on the dynamics between two goals as the prototypical example of multiple goals. This focus on dyadic relations means that many issues central to the psychology of more than two goals are still unexplored. We argue that a deeper understanding of multiple-goal issues involves moving beyond two goals. Doing so not only reveals new insights about goal relations (e.g., how one dyadic relation affects another) but also introduces goal structure (how goals and goal relations are positioned relative to each other) as a variable in its own right worthy of study. In our review, we discuss current knowledge gaps, review methodologies both in terms of existing techniques and novel techniques we propose, and highlight new directions from moving beyond two goals—what new questions emerge and what dynamics, including intersectional issues (e.g., between goal properties and goal structure), become possible to explore.

Moving Beyond Two Goals: An Integrative Review and Framework for the Study of Multiple Goals

Historically, the study of multiple goals has focused on the dynamics between two goals as the prototypical example of multiple goals. This focus on dyadic relations means that many issues central to the psychology of more than two goals are still unexplored. We argue that a deeper understanding of multiple goal issues involves moving beyond two goals. Doing so not only reveals new insights about goal relations (e.g., how one dyadic relation affects another), but also introduces goal structure (how goals and goal relations are positioned relative to each other) as a variable in its own right worthy of study. In our review, we discuss current knowledge gaps, review methodologies both in terms of existing techniques and novel techniques we propose, and highlight new directions from moving beyond two goals—what new questions emerge and what dynamics, including intersectional issues (e.g., between goal properties and goal structure), become possible to explore.

Self-control from a multiple goal perspective of mixed reward options

We introduce a distinct type of choice that has yet to be addressed by self-control research: Choosing between activities that offer both delayed and immediate rewards. We describe when and why such mixed-reward choices pose challenges to self-control, and suggest that self-control in mixed-reward choices may be supported (rather than undermined) by delay discounting.

Optimization of CV.Amanda Makassar Production Planning in the Time of Covid-19 Using Multiple Goal Linear Program Model

A research has been conducted on the use of multiple-goal linear program model to solve multi goals by taking the case of optimization of production planning at CV. Amanda Makassar during the Covid-19 period. In this research, four goals were formulated, that were (i) the fulfillment of the number of market demand, (ii) maximizing income, (iii) minimizing production costs, and (iv) maximizing working hours. Then for the optimal solution using LINGO 18 software. Based on the research results, the optimal production plan during the Covid-19 period resulted from the two different models for original brownies products where the results of the dual-purpose linear program model without target priority produced 16.118 original brownies and 32.400 packages from the dual-purpose linear program model with priority target with weight. For cream cheese brownies, there are 3.000 packages, 18.000 packages of sarikaya pandan brownies, 3.600 packs of choco marble brownies, pink marble brownies, tiramishu marble brownies, roasted brownies, and 1.800 packs of cappuccino marble brownies. Chocolate bananas bolen, pineapple molen, and chocolate ganache in 840 packages. Then for 15.000 packs of blueberry brownies, 960 packs of strawberry brownies, 360 packs of dry brownies, 2.400 banana cheese brownies, 300 packs of cheese bananas bolen, 600 packs of peanut butter, and 9.000 packs of pandan cake for a month. The maximum revenue obtained by the company with a multiple-purpose linear program model without target priority is Rp.628.602.000.- and the minimum production cost that the company must pay is Rp.495,048,300,-. Then for the multiple-purpose linear program model with target priority accompanied by a weight of Rp.4.299.480.000.- and the minimum production cost is Rp.3.394.366.000. The result shows that optimization using a multiple goal linear program model with goal priority provide optimal production which results in greater profit compared to the process (optimization) carried out by the company so far, which is only based on the number of demand.

Impact of Lifestyle Interventions on Quality and Consumption of Hyper-Palatable Foods Within Gestational Diets: Single-Goal vs Multiple-Goal

Objectives Examine the impact of a multiple-goal (MG) vs single-goal (SG) lifestyle interventions on gestational diet quality and hyper-palatable food consumption. Methods Pregnant women were randomized in two pilot trials to MG (n = 21) or SG (n = 16) vs usual care (UC; combined trials, n = 18). The 18-week MG intervention included lifestyle modifications, and the 12-week SG intervention focused only on increasing fiber (≥30 g/day). Interventions included weekly instruction by a registered dietitian, and primary aims were appropriate weight gain. Diet recalls were performed at baseline and study end. Diet quality was scored with three versions of the alternative healthy eating index, including adaptations for pregnancy (AHEI 2010, AHEI-P, and AHEI-P 2010). Foods were classified as hyper-palatable based on fat, carbohydrate, sugar, and sodium content using previously defined criteria, and reported as percentage of total calories (%HPF). One-way ANOVA, paired t-tests, and Pearson's correlations were performed. Results At baseline, no between group differences for diet quality were found. By the end of the study, all diet quality scores increased for SG (P < 0.009) and two increased for MG (AHEI 2010 & AHEI-P-2010, P < 0.041). UC diet quality remained unchanged (P > 0.05). At baseline, %HPF was different between groups (MG > UC > SG, 82%, 57%, and 26%, respectively; P < 0.001). By study end, UC and SG increased %HPF (P < 0.033), while MG remained unchanged (P > 0.05), leaving MG and SG similar in %HPF (80% & 74%, respectively) and higher than UC (65%, P = 0.024). The %HPF was negatively correlated with all diet quality scores at baseline (r = −0.37 to −0.42; P < 0.005) and two at the end of study (AHEI 2010 & AHEI-P 2010 r = −0.39, −0.30, respectively, P < 0.040). Changes in diet quality and %HPF were not related (P > 0.05). Conclusions Interventions aimed to prevent excessive gestational weight gain showed improvements in diet quality. Hyper-palatable food consumption was negatively related to diet quality, yet neither intervention decreased %HPF. Focusing on increasing dietary fiber may allow for a targeted message with broad implications for diet quality, but more research is needed. Funding Sources NIH Clinical and Translational Science Award and the Kansas City Area Life Science Institute.