Well-Being and Diabetes Management in Early Pregnant Women with Type 1 Diabetes Mellitus

Factors affecting the quality of life in pregnant women with diabetes: the mediating effect of illnesses acceptance

INTRODUCTION

Gestational diabetes, as a disorder of carbohydrate metabolism, is considered one of the most common metabolic complications in pregnancy. The diagnosis of diabetes in pregnancy leads to changes in lifestyle, and the treatments employed can affect various aspects of pregnant women's lives, including their quality of life. The present study aimed to investigate the relationship between self-efficacy and the mediating effect of illness acceptance on the quality of life in pregnant women diagnosed with diabetes during pregnancy.

MATERIALS AND METHODS

This cross-sectional study was conducted on 240 pregnant women diagnosed with diabetes who were selected by convenience sampling method. Quality of life tools (SF12), the Acceptance of Illness Scale (AIS), and the Sherer self-efficacy scale were used to collect data.

RESULTS

The mean (SD) of quality of life, self-efficacy, and disease acceptance were 57.36 (6.63), 51.75 (7.44), and 29.07 (7.69), respectively. In the single-variable regression analysis, self-efficacy and disease acceptance variables could predict 20.6% (β = 0.457, P < 0.001) and 14.4% (β = 0.385, P < 0.001) of the variations in quality of life, respectively. In the multiple regression model, by entering the two main variables (self-efficacy and Acceptance of Illness), demographic characteristics, three disease knowledge variables, health status from an individual perspective, and type of treatment, the variables could explain 25% of the changes of the quality of life (R2adj 0.25, P < 0.001=). Income status and self-efficacy had the highest impact among the variables. According to the results of path analysis, the total effect of self-efficacy on the quality of life of pregnant women with diabetes was 0.711.

CONCLUSION

The overall quality of life in women with diabetes was moderate, and self-efficacy, illness acceptance, and income status were predictors of overall quality of life. Self-efficacy can influence the quality of life by affecting disease acceptance. The findings highlight the importance of designing educational programs and providing midwifery services to increase self-efficacy and illness acceptance to improve the quality of life of pregnant women with diabetes.

The Examination and Exploration of Diabetes Distress in Pre-existing Diabetes in Pregnancy: A Mixed-methods Study

OBJECTIVES

Diabetes distress (DD) has been understudied in the pregnancy population. Pregnancy is known to be a complex, highly stressful time for women with diabetes because of medical risks and the high burden of diabetes management. Our aim in this study was to explain and understand DD in women with pre-existing diabetes in pregnancy.

METHODS

An explanatory, sequential mixed-methods study was undertaken. The first strand consisted of a cross-sectional study of 76 women with type 1 and type 2 diabetes. A nested sampling approach was used to re-recruit 18 women back into the second strand for qualitative interviews using an interpretive description approach.

RESULTS

DD was measured by the validated Problem Area in Diabetes (PAID) scale. A PAID score of ≥40 was positive for distress. DD prevalence was 22.4% in the cross-sectional cohort and the average PAID score was 27.75 (standard deviation 16.08). In the qualitative strand, women with a range of PAID scores (10.0 to 60.0) were sampled for interviews. The majority of these participants described themes of DD in their interviews. Of the 15 women who described DD thematically, only 6 had positive PAID scores.

CONCLUSIONS

Integration of the mixed-methods data underscores important meta-inferences about DD in pregnancy, namely that DD was present to a greater degree than the PAID tool is sensitive to. DD was present qualitatively in most of the qualitative sample, despite interviewing women with a range of PAID scores. Future research on a pregnancy-specific DD scale is needed.

Development and psychometric evaluation of the High-Risk Pregnancy Well-Being Index in Mashhad: a methodological study

BACKGROUND

Assessment of well-being in high-risk pregnancy (HRP) is the key to achieve positive maternal and fetal outcomes. Although there are a wide range of instruments for well-being assessment, none of them is comprehensive for well-being assessment in HRP. The present study aimed at the development and psychometric evaluation of the High-Risk Pregnancy Well-Being Index (HRPWBI).

METHODS

This methodological study was conducted using the Waltz's four-step method. The dimensions of well-being in HRP were determined based on a conceptual model and the blueprint and the item pool of HRPWBI were developed. Then, the face and the content validity were assessed and item analysis was performed. Construct validity was also assessed through exploratory factor analysis with principal component analysis on the data obtained from 376 women with HRP in Mashhad, Iran. Finally, internal consistency, test-retest stability, sensitivity, and interpretability of HRPWBI were assessed.

RESULTS

The scale- content validity index (SCVI) of HRPWBI was 0.91. In factor analysis, 33 items were loaded on seven factors which explained 53.77% of the total variance. Internal consistency, relative stability, absolute stability, sensitivity, and interpretability of HRPWBI were confirmed with a Cronbach's alpha of 0.84, a test-retest intraclass correlation coefficient of 0.97, a standard error of measurement of 0.92, a minimal detectable change of 8.09, and a minimal important change of 2.92, respectively.

CONCLUSION

HRPWBI is a valid and reliable instrument for well-being assessment among women with HRP. It can be used to assess well-being and the effects of well-being improvement interventions on well-being among women with HRP.

Behavioural interventions delivered through interactive social media for health behaviour change, health outcomes, and health equity in the adult population

BACKGROUND

Social networking platforms offer a wide reach for public health interventions allowing communication with broad audiences using tools that are generally free and straightforward to use and may be combined with other components, such as public health policies. We define interactive social media as activities, practices, or behaviours among communities of people who have gathered online to interactively share information, knowledge, and opinions.

OBJECTIVES

We aimed to assess the effectiveness of interactive social media interventions, in which adults are able to communicate directly with each other, on changing health behaviours, body functions, psychological health, well-being, and adverse effects. Our secondary objective was to assess the effects of these interventions on the health of populations who experience health inequity as defined by PROGRESS-Plus. We assessed whether there is evidence about PROGRESS-Plus populations being included in studies and whether results are analysed across any of these characteristics.

SEARCH METHODS

We searched CENTRAL, CINAHL, Embase, MEDLINE (including trial registries) and PsycINFO. We used Google, Web of Science, and relevant web sites to identify additional studies and searched reference lists of included studies. We searched for published and unpublished studies from 2001 until June 1, 2020. We did not limit results by language.

SELECTION CRITERIA

We included randomised controlled trials (RCTs), controlled before-and-after (CBAs) and interrupted time series studies (ITSs). We included studies in which the intervention website, app, or social media platform described a goal of changing a health behaviour, or included a behaviour change technique. The social media intervention had to be delivered to adults via a commonly-used social media platform or one that mimicked a commonly-used platform. We included studies comparing an interactive social media intervention alone or as a component of a multi-component intervention with either a non-interactive social media control or an active but less-interactive social media comparator (e.g. a moderated versus an unmoderated discussion group). Our main outcomes were health behaviours (e.g. physical activity), body function outcomes (e.g. blood glucose), psychological health outcomes (e.g. depression), well-being, and adverse events. Our secondary outcomes were process outcomes important for behaviour change and included knowledge, attitudes, intention and motivation, perceived susceptibility, self-efficacy, and social support.

DATA COLLECTION AND ANALYSIS

We used a pre-tested data extraction form and collected data independently, in duplicate. Because we aimed to assess broad outcomes, we extracted only one outcome per main and secondary outcome categories prioritised by those that were the primary outcome as reported by the study authors, used in a sample size calculation, and patient-important.

MAIN RESULTS

We included 88 studies (871,378 participants), of which 84 were RCTs, three were CBAs and one was an ITS. The majority of the studies were conducted in the USA (54%). In total, 86% were conducted in high-income countries and the remaining 14% in upper middle-income countries. The most commonly used social media platform was Facebook (39%) with few studies utilising other platforms such as WeChat, Twitter, WhatsApp, and Google Hangouts. Many studies (48%) used web-based communities or apps that mimic functions of these well-known social media platforms. We compared studies assessing interactive social media interventions with non-interactive social media interventions, which included paper-based or in-person interventions or no intervention. We only reported the RCT results in our 'Summary of findings' table. We found a range of effects on health behaviours, such as breastfeeding, condom use, diet quality, medication adherence, medical screening and testing, physical activity, tobacco use, and vaccination. For example, these interventions may increase physical activity and medical screening tests but there was little to no effect for other health behaviours, such as improved diet or reduced tobacco use (20,139 participants in 54 RCTs). For body function outcomes, interactive social media interventions may result in small but important positive effects, such as a small but important positive effect on weight loss and a small but important reduction in resting heart rate (4521 participants in 30 RCTs). Interactive social media may improve overall well-being (standardised mean difference (SMD) 0.46, 95% confidence interval (CI) 0.14 to 0.79, moderate effect, low-certainty evidence) demonstrated by an increase of 3.77 points on a general well-being scale (from 1.15 to 6.48 points higher) where scores range from 14 to 70 (3792 participants in 16 studies). We found no difference in effect on psychological outcomes (depression and distress) representing a difference of 0.1 points on a standard scale in which scores range from 0 to 63 points (SMD -0.01, 95% CI -0.14 to 0.12, low-certainty evidence, 2070 participants in 12 RCTs). We also compared studies assessing interactive social media interventions with those with an active but less interactive social media control (11 studies). Four RCTs (1523 participants) that reported on physical activity found an improvement demonstrated by an increase of 28 minutes of moderate-to-vigorous physical activity per week (from 10 to 47 minutes more, SMD 0.35, 95% CI 0.12 to 0.59, small effect, very low-certainty evidence). Two studies found little to no difference in well-being for those in the intervention and control groups (SMD 0.02, 95% CI -0.08 to 0.13, small effect, low-certainty evidence), demonstrated by a mean change of 0.4 points on a scale with a range of 0 to 100. Adverse events related to the social media component of the interventions, such as privacy issues, were not reported in any of our included studies. We were unable to conduct planned subgroup analyses related to health equity as only four studies reported relevant data.

AUTHORS' CONCLUSIONS

This review combined data for a variety of outcomes and found that social media interventions that aim to increase physical activity may be effective and social media interventions may improve well-being. While we assessed many other outcomes, there were too few studies to compare or, where there were studies, the evidence was uncertain. None of our included studies reported adverse effects related to the social media component of the intervention. Future studies should assess adverse events related to the interactive social media component and should report on population characteristics to increase our understanding of the potential effect of these interventions on reducing health inequities.

Relación entre sentido de coherencia y diabetes mellitus: una revisión sistemática

Resumen El objetivo fue sintetizar las mejores evidencias científicas sobre el efecto del sentido de coherencia en el desarrollo de la enfermedad, tratamiento e indicadores biomédicos de control metabólico y desarrollo de complicaciones de personas en riesgo de desarrollar diabetes y en diabéticos. El método utilizado fue la revisión sistemática. Búsqueda y selección por dos revisores independientes en las bases de datos Scopus, Web of Science, PubMed, Ebsco, Science Direct y manuales, disponibles hasta 2017, en español e inglés, en población con edad superior a 18 años. De un total de 154 estudios, 20 artículos fueron incluidos en la revisión sistemática. Más de la mitad de los estudios utilizaron la versión SOC-13 para la verificación del sentido de coherencia y el indicador de control metabólico más frecuente fue la hemoglobina glucosilada. Además, 14, de los 20 estudios, encontraron una relación estadísticamente significativa entre el sentido de coherencia y la diabetes. Se concluye que el sentido de coherencia tiene una fuerte correlación con la diabetes en las diferentes fases de la enfermedad y está relacionado con la reducción del riesgo para el desarrollo de la enfermedad, la reducción de los valores de hemoglobina glucosilada y la aparición de complicaciones de la diabetes mellitus.

Behavior Change Techniques Included in Reports of Social Media Interventions for Promoting Health Behaviors in Adults: Content Analysis Within a Systematic Review

BACKGROUND

Social media are an increasingly commonly used platform for delivering health promotion interventions. Although recent research has focused on the effectiveness of social media interventions for health promotion, very little is known about the optimal content within such interventions, and the active ingredients to promote health behavior change using social media are not clear. Identifying which behavior change techniques (BCTs) are reported may help to clarify the content of interventions using a generalizable terminology that may facilitate future intervention development.

OBJECTIVE

This study aimed to identify which BCTs are reported in social media interventions for promoting health behavior change in adults.

METHODS

We included 71 studies conducted with adult participants (aged ≥18 years) and for which social media intervention was considered interactive in a Cochrane review of the effectiveness of such interventions. We developed a coding manual informed by the Behavior Change Technique Taxonomy version 1 (BCTTv1) to identify BCTs in the included studies. We identified BCTs in all study arms (including control) and described BCTs in the group and self-directed components of studies. We characterized the dose of delivery for each BCT by low and high intensity. We used descriptive analyses to characterize the reported BCTs.

RESULTS

Our data consisted of 71 studies published from 2001 to 2017, mainly conducted in high-income countries (n=65). Most studies (n=31) used tailored, interactive websites to deliver the intervention; Facebook was the most used mainstream platform. In developing our coding manual, we adapted some BCTTv1 instructions to better capture unique nuances of how BCTs were operationalized in social media with respect to likes, retweets, smiles, congratulations, and badges. Social support (unspecified), instruction on how to perform the behavior, and credible source were most frequently identified BCTs in intervention arms of studies and group-delivery settings, whereas instruction on how to perform the behavior was most commonly applied in self-directed components of studies, control arms, and individual participant settings. Instruction on how to perform the behavior was also the most frequently reported BCT in both intervention and control arms simultaneously. Instruction on how to perform the behavior, social support (unspecified), self-monitoring of behavior, information about health consequences, and credible source were identified in the top 5 BCTs delivered with the highest intensity.

CONCLUSIONS

This study within a review provides a detailed description of the BCTs and their dose to promote behavior change in web-based, interactive social media interventions. Clarifying active ingredients in social media interventions and the intensity of their delivery may help to develop future interventions that can more clearly build upon the existing evidence.

Quality of Life, Social Support, Acceptance of Illness, and Self-Efficacy among Pregnant Women with Hyperglycemia

Carbohydrate metabolism disorders resulting in hyperglycemia are among the most common metabolic complications of pregnancy. According to 2017 data from the International Diabetes Federation (IDF), 16.2% of pregnancies are complicated with hyperglycemia, of which gestational diabetes mellitus (GDM) accounts for 86.4% of cases. Carbohydrate metabolism disorders developing during pregnancy require the patient to change her lifestyle or, in some cases, to undergo pharmaceutical treatment, which may affect various aspects of the patient's life, including her perceived quality of life (QoL). The purpose of the present study was to evaluate levels of QoL, social support, acceptance of illness, and self-efficacy among pregnant patients with hyperglycemia. The study was performed between July 2016 and September 2017 in a group of hyperglycemic pregnant women. The following instruments were used: the World Health Organization Quality of Life-BREF (WHOQOL-BREF), the Berlin Social Support Scales (BSSS), the Acceptance of Illness Scale (AIS), the Generalized Self-Efficacy Scale (GSES) and a standardized interview questionnaire. Participants rated their overall QoL (3.64 points) higher than their overall perceived health (3.43). In terms of social support, the highest scores were obtained in terms of actually received support (3.53) and perceived available instrumental support (3.52), while the lowest in terms of support seeking (2.99) and the need for support (2.95). The mean acceptance of illness score among the hyperglycemic pregnant women that were studied was 31.37, and the mean generalized self-efficacy score was 31.58. Participants' reported QoL in the various WHOQOL-BREF domains was associated with specific social support scales, acceptance of illness, and generalized self-efficacy.

INTER-ACT: prevention of pregnancy complications through an e-health driven interpregnancy lifestyle intervention - study protocol of a multicentre randomised controlled trial

Background

Excessive maternal pre-pregnancy and gestational weight gain are related to pregnancy- and birth outcomes. The interpregnancy time window offers a unique opportunity to intervene in order to acquire a healthy lifestyle before the start of a new pregnancy.

Methods

INTER-ACT is an e-health driven multicentre randomised controlled intervention trial targeting women at high risk of pregnancy- and birth related complications. Eligible women are recruited for the study at day 2 or 3 postpartum. At week 6 postpartum, participants are randomised into the intervention or control arm of the study. The intervention focuses on weight, diet, physical activity and mental well-being, and comprises face-to-face coaching, in which behavioural change techniques are central, and use of a mobile application, which is Bluetooth-connected to a weighing scale and activity tracker. The intervention is rolled out postpartum (4 coaching sessions between week 6 and month 6) and in a new pregnancy (3 coaching sessions, one in each trimester of pregnancy); the mobile app is used throughout the two intervention phases. Data collection includes data from the medical record of the participants (pregnancy outcomes and medical history), anthropometric data (height, weight, waist- and hip circumferences, skinfold thickness and body composition by bio-electrical impedance analysis), data from the mobile app (physical activity and weight; intervention group only) and questionnaires (socio-demographics, breastfeeding, food intake, physical activity, lifestyle, psychosocial factors and process evaluation). Medical record data are collected at inclusion and at delivery of the subsequent pregnancy. All other data are collected at week 6 and month 6 postpartum and every subsequent 6 months until a new pregnancy, and in every trimester in the new pregnancy. Primary outcome is the composite endpoint score of pregnancy-induced hypertension, gestational diabetes mellitus, caesarean section, and large-for-gestational-age infant in the subsequent pregnancy.

Discussion

INTER-ACT is a unique randomised controlled lifestyle intervention trial in its implementation between pregnancies and during the subsequent pregnancy, with an e-health driven approach.

Trial registration

ClinicalTrials.gov Identifier: NCT02989142. Registered August 2016.

Empowerment in the Treatment of Diabetes and Obesity

As the available therapies for diabetes and obesity are not effective enough, diabetologists and educators search for new methods to collaborate with patients in order to support their health behaviors. The aim of this review is to discuss perspectives for the development of new empowerment-type therapies in the treatment of diabetes/obesity. Empowerment is a process whereby patients gain the necessary knowledge to influence their own behavior to improve the quality of their lives. It is carried out in five stages: (1) identify the problem, (2) explain the feelings and meanings, (3) build a plan, (4) act, and (5) experience and assess the execution. Although many years have passed since the advent and popularization of the concept of empowerment, the area remains controversial, mainly with regard to the methodology of therapy. Some previous studies have confirmed the positive effect of empowerment on body weight, metabolic control, and quality of life of patients with type 2 diabetes; however, few studies have been conducted in patients with type 1 diabetes. There is still a need to confirm the effectiveness of empowerment in accordance with Evidence Based Medicine by performing long-term observational studies in a large group of patients. In future, empowerment may become part of the standard of care for patients with diabetes and/or obesity.