Search

Background International and national organizations recommend exclusive breastfeeding for the first 6 months of life, but many women stop earlier. Lay and professional persons can support mothers’ efforts to overcome breastfeeding difficulties. Considering breastfeeding support to comprise emotional support, practical help, and information offered to women who desire to breastfeed (by professionals, family members, and others), we developed and tested a scale to measure it in Japan. Methods A total of 31 items were generated by literature review and from the authors’ clinical experiences. Those items were tested with 243 mothers who visited public health centers in Tokyo for their infant’s health check-up 3 months after birth. Breastfeeding support and infant feeding status were then assessed 5 months after birth. All the data were collected by using self-administered questionnaires. Results On the basis of the results of factor analysis, the number of items was reduced to 11. There were three factors: support from breastfeeding peers and from people in specifically named healthcare professions, practical help, and support from people the mother can rely on to help meet emotional needs and address breastfeeding concerns. Internal-consistency reliability (alpha) of scores on the 11-item scale was 0.83 when measured 3 months postpartum and 0.85 when measured 5 months postpartum. Higher scores on the 11-item scale 3 months postpartum were associated with more breastfeeding exclusivity both at that time (Kruskal–Wallis test, chi-squared = 14.871, df = 3, n = 211, p = 0.002, eta-squared = 0.071) and also 5 months postpartum (Kruskal–Wallis test, chi-squared = 8.556, df = 3, n = 159, p = 0.036, eta-squared = 0.054). Further, the area under the Receiver Operating Characteristic curve was 0.73 (95% CI [0.57–0.88]), which indicates that scores on the 11-item scale 3 months postpartum may be useful to predict which mothers will be less exclusive in breastfeeding 5 months postpartum. In conclusion, scores on this 11-item scale were reasonably reliable and valid for measuring breastfeeding support provided by lay and professional persons to mothers in Japan. Further research is required to evaluate this scale’s applicability in other settings.

Background Health education can benefit people with chronic diseases. However, in previous research those benefits were small, and reinforcement to maintain them was not effective. A possible explanation is that the benefits appeared to be small and reinforcement appeared to be ineffective because those analyses mixed data from two latent groups: one group of people who needed reinforcement and one group of people who did not. The hypothesis is that mixing the data from those two different groups caused the true effects to be “diluted.” Methods To test that hypothesis we used data from the Chronic Disease Self-Management Program in Japan, focusing on anxiety, depression, and patient-physician communication. To identify latent trajectories of change after the program, we used growth-mixture modeling. Then, to find out which baseline factors were associated with trajectory-group membership, we used logistic regression. Results Growth-mixture modeling revealed two trajectories—two groups that were defined by distinct patterns of change after the program. One of those patterns was improvement followed by backsliding: decay of impact. On anxiety and depression the decay of impact was large enough to be clinically important, and its prevalence was as high as 50%. Next, logistic regression analysis revealed that being in the decay-of-impact group could be predicted from multimorbidity, low self-efficacy, and high scores on anxiety or depression at baseline. In addition, one unexpected finding was an association between multimorbidity and better patient-physician communication. Conclusions These results support the hypothesis that previous findings (i.e., apparently small effect sizes and apparently ineffective reinforcement) actually reflect “dilution” of large effects, which was caused by mixing of data from distinct groups. Specifically, there was one group with decay of impact and one without. Thus, evaluations of health education should include analyses of trajectory-defined groups. These results show how the group of people who are most likely to need reinforcement can be identified even before the educational program begins. Extra attention and reinforcement can then be tailored. They can be focused specifically to benefit the people with the greatest need.