Acad Med. Sep;87(9) The relationship between physician empathy and disease complications: an empirical study of primary care physicians and. and one item from Rubin and Campbell's () study (“How passionate was your relationship today?”). Participants rated the items on a 1 (not at all) to 7. The research is part of an effort to better understand the contexts in which some relationships Date: August 2, ; Source: Society for Personality and Social .
Consequently, intimacy steadily builds up during the early stages of a relationship and eventually becomes stagnant Sternberg, Passion, on the other hand, is primarily affective. Unlike intimacy, which takes a certain amount of time to develop, passionate feelings can emerge quickly at the beginning stages of a relationship; however, they tend to decline as time passes Sternberg, ; Acker and Davis, ; Beutel et al.
Several studies show that intimacy and passion are positively associated e. Nevertheless, the causal direction of this association is not clear.
Some studies suggest that intimacy predicts passion Aron and Aron, ; Reissman et al. The current study focuses on a model which proposes increases in intimacy generate passion Baumeister and Bratslavsky, In this formula, P represents passion, I represents intimacy, t represents time, and C represents a constant that accounts for other factors that could moderate the required amount of increase in intimacy to generate passion.
According to the model, increases in intimacy generate passion, and when intimacy levels remain stable no passion is generated. Thus, during the early stages of a relationship when intimacy is increasing steadily, passion levels will be high. However, intimacy will eventually reach its peak and remain stable, resulting in low levels of passion. This model provides a parsimonious framework that can explain the relationship between intimacy and passion, as well as, their time course.
To date, there has been only one empirical study that tested the intimacy change model. In a day diary study with 67 couples it was found that increases in intimacy significantly predicted passion Rubin and Campbell, Researchers also examined the partner effects i.
However, changes in passion also significantly predicted intimacy, but the authors suggested that the support for this opposite direction hypothesis was weaker. Researchers also suggested that intimacy should be conceptualized in an interpersonal framework as it includes mutual self-disclosure, trust, and communication Reis and Patrick, ; Ferreira et al. Materials and Methods Participants Both partners of 75 heterosexual couples who had been in a romantic relationship for at least 1 month participated in the study.
Participants were recruited from undergraduate courses at a large university. Students received extra course credit for their participation in the study. Data from one couple were not included in the analysis because the couple did not follow the instructions. All the couples were in a dating relationship, and three couples were living together. The average age of the participants was Internal reliability was 0.
This measure was used for measurement validity, and it was not included in models testing main hypothesis. Participants rated the items on a 1 strongly disagree to 7 strongly agree scale.
Before daily alphas were computed, items were within-person centered to remove the between-person effects from the ratings. Daily alphas ranged from 0. Participants rated the items on a 1 not at all to 7 extremely scale.
Procedure The study involved three phases: Initially, participants were invited to the lab to receive an orientation session on how to complete the daily records. Participants were instructed to complete the records every day before going to bed.
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The researcher also explained the importance of completing the records independently from each other and told participants to keep their responses private. After the orientation session, each participant received an e-mail providing a link for the baseline questionnaire packet that included demographics and person-level measures 1.
To ensure that participants had sufficient time to complete the questionnaires, they were given 1 week before they proceeded to the diary phase of the study. During the diary phase, participants submitted an online record at the end of each day for 14 consecutive days. The time-stamped data were checked to confirm that the participants followed the instructions and completed the records on-time. The average number of completed records was Two participants completed an extra record and these records were excluded from the analysis.
Data Analytic Strategy The data structure was hierarchically nested as two individuals were nested within 74 couples that were then crossed with 14 days. Because the data consisted of distinguishable dyads, we used a multilevel model with two-intercepts Bolger and Shrout, to adjust for non-independence.
The two-intercept model approach allows separate estimates for females and males. The female dummy-coded variable 1 for females and 0 for males and the male dummy coded variable 1 for males and 0 for females are multiplied by a predictor to have two separate estimates for females and males.
Therefore, we reported the separate estimates for each gender using bf for females and bm for males. This structure allowed the errors to be auto correlated to model the correlation from 1 day to the next Kenny et al. In all of the analyses, day-level predictor variables were within-person centered, and person-level predictors intimacy or passion were controlled.
All of the regression coefficients reported in multilevel analyses are unstandardized. Results Results for Measurement Validity To establish measurement validity for person-level measures, we conducted a confirmatory factory analysis for the person-level triangular love scale, and compared the three factor intimacy, passion, commitment structure with one-factor love structure.
We also conducted an exploratory principal component factor analysis. Results mainly showed a three factor pattern. Out of 15 intimacy items, two of them mainly loaded on the other factors, and another two items cross-loaded on the other factors.
Out of 15 passion items, two of them mainly loaded on the other factors. Next, we conducted confirmatory multilevel factor analyses to establish measurement validity for day-level measures. We created a single factor latent variable model with seven indicators, and a two factor model using four intimacy and three passion items.
However, these findings might not be robust because the sample size was small compared to the number of parameters estimated in the model. We also conducted additional analyses using the other variables in the dataset as outcome variables to examine discriminant validity. First, we had one item measuring whether people wanted to express their love to their partners using physical contact expressions.
We expected that this variable should be more closely related to passion rather than intimacy. Second, we examined whether these variables predicted secrecy from partner. As intimacy is closely related to self-disclosure, we expected that intimacy, compared to passion, should be a stronger predictor of secrecy. Third, we conducted the same analysis for trust in partner. Trust is associated with self-disclosure; thus it should also be more strongly predicted by intimacy.
These meta-analyses report, for example, an effect size of. These effect sizes, though somewhat lower than those that are found for treatment studies, are impressive given that the majority of the studies are prevention studies.
Interestingly, stronger findings emerged for more rigorous designs e. Overall, while the outcome findings were both interesting and important, we feel that the most important set of findings in the past decade emerged from two large-scale projects. First, a study on the effectiveness of the Prevention and Relationship Enhancement Program Markman et al. Army indicated an effect of relationship education for divorce. Divorce is rarely studies in research on relationship education because of the necessity of large samples and long-term data.
Preliminary results from the Building Strong Families study are generally disappointing, with very few positive effects of relationship education and even some negative effects Wood et al. When sites were analyzed separately, only one site showed significant positive findings across many of the relationship quality variables. The results showed that participating couples were more likely to stay together; had higher levels of happiness, support, affection, and fidelity, and were better at parenting than couples in the control group.
This high rate of completion may be partly attributable to the fact that Oklahoma uses material incentives for program participation.
These services included booster sessions as well as planned activities for couples and families, such as a holiday party every December for program participants. Such services should be strongly considered in future relationship education programs and their effects should be evaluated in research over the next decade. In addition, the very strong organizational structure supporting the delivery of Family Expectations likely plays an important part in the outcomes achieved.
Relationship Education Research: Current Status and Future Directions
The program is well-staffed and run professionally. More generally, stronger administration of large scale community-based relationship education efforts will likely be associated with stronger outcomes. For more discussion of the Family Expectations program and findings from the Building Strong Families evaluation specific to Oklahoma, see Devaney and Dion Methodological Strengths and Weaknesses In this section we use the format in Table 1 as much as possible to review the strengths and weaknesses of the studies conducted on relationship education from to Sample characteristics The samples described in Table 1 included a mix of premarital and marital couples, with most studies either not distinguishing between the two or combining the two groups in analyses.
Many of the studies included cohabiting participants, but most did not indicate how many, nor did they look at differences between married and cohabiting participants. More generally, the couples included in the research reflect the increasing diversity of the field. Studies now include evaluations of interventions for couples with low income levels, unmarried couples with a child together, couples in which one partner has a medical problem, military couples, foster and adoptive parents, step-families, and couples with children.
Thus, good progress continues on the aforementioned recommendations by Halford et al. There have been major strides in the last decade to offer and evaluate services to couples with low-income levels, including the large scale, multi-site evaluation mentioned earlier Wood et al. Also consistent with the recommendations from the last review paper, we found evaluations of programs that offer services during transition periods.
Nevertheless, wide gaps exist between the diversity of those who are participating in research and whom we are serving in practice. That is, the participants receiving services are not generally included in the studies we have reviewed.
Many populations exist that are either underserved or not served at all including: Recently, Whitton and her research team have started to evaluate a relationship education program for gay couples e. We hope that the field will continue to reach out to diverse populations in terms of both delivery of research-based services and the evaluation of these services using rigorous research design in the next decade.
Interventions Several different intervention approaches were evaluated in the last decade. Furthermore, many of the studies in Table 1 were evaluated by researchers who developed, and sometimes delivered, their own interventions. These kinds of research designs may lead to bias in the research. One solution to this potential bias is to have other research teams evaluate programs.
In addition, despite the strong recommendation made by Halford et al. A larger problem for this field is that most relationship education services that are delivered are not being evaluated at all. Thus, linkages between practices as defined by Halford et al. Design As indicated in Table 1there is much diversity in the methodological quality of the studies.
On the positive side, there have been several randomized clinical trials RCTs implemented in the last decade. This kind of design is the strongest in terms of establishing effects of an intervention more on RCTs below.
Though we did not examine effect sizes, meta-analyses conducted by others Blanchard et al. The majority of the studies conducted in the last decade used weaker designs. In terms of the type of control group, most studies used a no-intervention control group, and the second most frequently used control group was an alternative intervention. There were no placebo-control group designs to control for attention and expectations, which could provide alternative explanations for positive effects.
In research conducted prior to the studies reviewed in the current paper, several studies used placebo controls such as reading a relationship book e.
In general, relationship education programs have outperformed placebo control groups. Measuring outcomes The majority of the studies revealed positive effects of relationship education on key indicators of relationship quality including communication quality, conflict management skills and relationship satisfaction. In addition, very few studies measured other important dimensions of relationship quality including measures of protective factors, such as commitment, friendship, and passion.
Follow-ups The absence of long-term follow-up is notable.
More studies need to include longer-term follow-ups, as the vast majority of studies assess outcomes only at post-test. This is a major problem, because the goals of prevention programs are by definition long-term in nature.
In addition, there need to be at least three data points to apply state-of-the-art growth curve analyses to evaluate change over time. Without more assessment points, non-linear effects in relationship education cannot be captured.
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In general the data that do exist show that long-term follow-up trajectories display a tendency toward attenuation e. However, these findings require replication with a control group and in a randomized clinical trial.
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In general, although most researchers recommend booster sessions, few programs use them, fewer studies evaluate them, and those that do have trouble persuading couples to participate e.
Suggested Program of Research and Interventions with Diverse Populations Many of the studies reviewed in Table 1 are not incorporated into a systematic program of planned research.
Here, we offer a model for researchers who want to develop a program of research consistent with the best practices for relationship education research. The next step is to pilot the intervention and then use a pre-post, no control group design, to see if there are effects over time and if it is acceptable to the population of interest see Markman et al. Then, research teams can move first to quasi-experimental studies, then to randomized clinical trials, and finally to dissemination trials.
It is also important to have other researchers cross-validate findings to ensure that results are not biased. Some research teams have been successful in moving studies in a laboratory setting i.
While more research is needed, evaluations of dissemination studies have yielded promising findings e.