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1.
JMIR Mhealth Uhealth ; 5(12): e183, 2017 Dec 07.
Article in English | MEDLINE | ID: mdl-29217502

ABSTRACT

BACKGROUND: Diabetes is a complex, demanding disease that requires the constant attention of patients. The burden of self-management, including different medication regimens, routine self-care activities, and provider visits, has an impact on patients' emotional well-being. Diabetes distress and depression are two important components of emotional well-being that may negatively affect diabetes outcomes. OBJECTIVE: The aim was to determine the impact of the 1-year Mobile Diabetes Intervention Study cluster randomized clinical trial on emotional well-being measured by diabetes distress and depression among adults with type 2 diabetes (T2D). METHODS: A total of 163 adults with not-well-managed T2D were enrolled from community primary care practices. Primary care practices were cluster randomized into either a usual care control group or intervention group. Intervention participants were given a mobile phone with coaching software including a Web portal to communicate with providers. A priori established secondary outcomes included distress measured by the Diabetes Distress Scale (DDS), with subscales measuring emotional burden, interpersonal distress, physician-related distress, and regimen-related distress, as well as depression measured by the Patient Health Questionnaire (PHQ-9). Linear mixed models were used to calculate the effect of the intervention on diabetes distress levels over time, both overall and separately by sex, and to determine if the intervention affected distress or depression. The impact of total DDS on changes in HbA1c was also studied. RESULTS: There were no significant treatment group effects for DDS total (baseline: P=.07; differences over time: P=.38) or for depression (P=.06 over time). Significant declines in total DDS were observed over the 12-month intervention period (P=.01). Regimen-related distress significantly decreased for all study participants (P<.001), but no significant change over time was observed for emotional burden (P=.83), interpersonal distress (P=.64), or physician-related distress (P=.73). Women in both the usual care and intervention groups were more likely to have higher overall DDS, emotional burden, physician-related distress, and regimen-related distress, but not interpersonal distress. Women also reported higher baseline depression compared to men (P=.006). Overall, depression decreased over the treatment period (P=.007), but remained unaffected by group assignment (P=.06) or by sex (P=.97). Diabetes distress had no effect on the change in HbA1c (P=.91) over the treatment period. CONCLUSIONS: Although we found no definitive overall or sex-specific effect of the intervention on diabetes distress or depression, this study makes an important contribution to the understanding of mobile health interventions and the impact on emotional health. Our study verified previous work that although diabetes distress and depression are highly correlated, these measures are not evaluating the same construct. Design of future mobile technology provides an opportunity to personalize, contextualize, and intervene in the emotional well-being of persons with diabetes. TRIAL REGISTRATION: Clinicaltrials.gov NCT01107015; https://clinicaltrials.gov/ct2/show/NCT01107015 (Archived by WebCite at http://www.webcitation.org/6vVgRCLAF).

2.
Am J Public Health ; 105 Suppl 3: e64-70, 2015 Jul.
Article in English | MEDLINE | ID: mdl-25905822

ABSTRACT

OBJECTIVES: We considered changes in the geographic distribution of early stage breast cancer among White and non-White women while secular trends in lifestyle and health care were under way. METHODS: We aggregated tumor registry and census data by age, race, place of residence, and year of diagnosis to evaluate rate variation across Connecticut census tracts between 1985 and 2009. Global and local cluster detection tests were completed. RESULTS: Age-adjusted incidence rates increased by 2.71% and 0.44% per year for White and non-White women, respectively. Significant global clustering was identified during surveillance of these populations, but the elements of clustering differed between groups. Among White women, fewer local clusters were detected after 1985 to 1989, whereas clustering increased over time among non-White women. CONCLUSIONS: Small-area variation of breast cancer incidence rates across time periods proved to be dynamic and race-specific. Incidence rates might have been affected by secular trends in lifestyle or health care. Single cross-sectional analyses might have confused our understanding of disease occurrence by not accounting for the social context in which patient preferences or provider capacity influence the numbers and locations of diagnosed cases. Serial analyses are recommended to identify "hot spots" where persistent geographic disparities in incidence occur.


Subject(s)
Breast Neoplasms/ethnology , Breast Neoplasms/epidemiology , Adult , Aged , Aged, 80 and over , Breast Neoplasms/diagnostic imaging , Connecticut/epidemiology , Female , Geography , Humans , Incidence , Mammography/statistics & numerical data , Middle Aged , Population Surveillance , Prognosis , Racial Groups , Registries , Small-Area Analysis , Survival Analysis
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