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Factors that Affect Long Interpersonal Relationships Long-term interpersonal relationships and the factors that keep couples together has been a topic in research that reminds us how these factors come into play as the length of the relationship increases. Rusbult (1983) offered three factors that affect long-term relationships. The first factor was satisfaction, depending on if the individuals in relationship were satisfied (e.g., happy) or dissatisfied (e.g., unhappy) with their relationship it would lead to how long their relationship lasted. The second factor was lack of alternatives, if the individuals felt that they had no alternatives to the present relationship (e.
g., no other person to have a relationship with) or if they did have alternatives this would affect how long the relationship lasted. The third factor was investment of resources, depending on how much the individuals put into the relationship (e.g. money, time, and effort) that would depend on how long the relationship persisted.
Arriaga and Agnew (2001) believed that Rusbult’s three factors dealt with how long relationships last but they believed that there was a fourth factor that affected long-term relationships.
The factor was Psychological Commitment. This factor had three components, which are psychological attachment, long-term orientation and intent to persist. Arriaga and Agnew ‘s model shares similarities with Rusbult’s three factors. According to Arriaga and Agnew, Rusbult’s three factors affect stability indirectly by affecting commitment. The purpose of the current study was to test Arriaga and Agnew’s (2001) model. We had four hypotheses in our study.
The first hypothesis was stability would be positively correlated with commitment. The second hypothesis was commitment would be positively correlated with satisfaction. The third hypothesis was commitment would be positively correlated with Factors that Affect 4 investment. Finally, the fourth hypothesis was commitment would be negatively correlated with availability of alternatives. In this study we used length of relationship as an operational definition of relationship stability.
Method Participants Eighty-one students (47 women, 34 men) ages 18 and above were chosen randomly at Le Moyne College by our class as part of our project. Most of the participants were friends or associates of our class. Out of the eighty-one students chosen, thirty-one women and twenty-one men were presently involved in a relationship. Sixteen women and thirteen men were not presently involved in a relationship. Data from six students were omitted from the analysis. The reason we omitted these students was due to them being married, homosexual or having incomplete data. Due to most of our students being in heterosexual relationships we felt that the six students needed to be omitted to make our results more defined. Materials Survey. We used a 22-item questionnaire that would determine the extent to which satisfaction; alternatives, investment and commitment are related to the length of close interpersonal relationships among Le Moyne students.
Each question was followed by a scale of numbers 1 thought 8 (1 = lowest, you don’t feel very strongly about the question or 8 = highest, you do feel very strongly about the question.) in which the participant had to circle the number they felt in response to the question. The questions were all relationship based. Arriaga and Agnew’s (2001) method measured commitment by using an psychological attachment score, Factors that Affect 5 an longterm orientation score, an intent to persist score, and an psychological commitment score from the questions that pertained to these categories. Rusbult’s (1983) method measured the longevity of relationships by using a quarreling score, a satisfaction with relationship score, an alternatives score and an investment score from questions that pertained to these categories. We also used a method called reverse scoring were we would reverse whatever the participant answered (e.g., 0=8, 3=5, 6=2, 1=7, 4=4, 7=1, 2=6, 5=3, 8=0).
The questions that were reversed in score were number 14 which deals with long-term orientation, number 16 which deals with psychological commitment and number 22 which deals with quarreling. Our commitment score was calculated by taking the longterm orientation score and the intent to persist score and then adding them together. Procedure Students were chosen at random by our class in order to conduct this study. These students were surveyed by themselves or in small groups of four or less. The locations that the surveys took place varied from dorm rooms, the campus cafeteria, and the campus library, ect. All of the locations were on-campus; off-campus surveying was not permitted. Before the surveys were handed to the participants, we read to the participants a brief explanation that stated what the purpose of the survey was. We stated that the survey was completely anonymous so that their anonymity would be protected. We then handed out an informed consent for the participants to read and sign if they agreed to take the questionnaire. After that we handed out the questionnaire and an envelope to each of the participants. We encouraged the participants not to talk while completing the questionnaire. When the participants were finished we reminded them to seal the Factors that Affect 6 questionnaire in the provided envelope and drop it off at the nearest campus mailbox. We were not allowed to take the participants questionnaires due to the promise of the anonymity of the survey.
Results A set of Pearson correlation coefficients was calculated in order to test the four hypotheses. The first hypothesis stated that stability would be positively correlated with commitment. A significant correlation between stability and commitment was found, r = .270, p = .015. In support of the hypothesis, increases in commitment were associated with increases in stability. The second hypothesis stated that commitment would be positively correlated with satisfaction. A significant correlation between commitment and satisfaction was found, r = .666, p < .001. In support of the hypothesis, increases in commitment were associated with increases in satisfaction. The third hypothesis stated that commitment would be positively correlated with investment. A significant hypothesis correlation between commitment and investment was found, r = .570, p < .001. In support of the hypothesis, increases in commitment were associated with increases in investment. The fourth hypothesis stated that commitment would be negatively correlated with availability of alternatives. A significant correlation between commitment and availability of alternatives was found, r = -.436, p <.001. In support of the hypothesis, decreases in commitment were associated with decreases in availability of alternatives.
Discussion in the four hypotheses that were stated above, all of them were supported. These results support Arriaga and Agnew’s (2001) theory on the psychological commitment that there are three Factors that Affect 7 indicators of commitment: psychological attachment, long-term orientation and intent to persist. It also stated that commitment is negatively correlated with availability of alternatives.
I think one of the problems with this study is that we need to have a smaller variation in age groups. For example, instead of having the participants being 18 and above, we should have participants from the ages of 18 to 20, so it deals with a more precise age group. With a smaller age group variation we will get more precise data. Another problem with this study is that it should deal with only one certain type of relationship at a time. For example, have either homosexual relationships or heterosexual relationships then try married or divorced relationships later. If we use these simple techniques we won’t lose as much data and our studies will have more accurate data.
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