|
| Altazan et al. |
| Objective(s) |
| (i) To quantify changes in mental and physical quality of life and depressive symptoms across pregnancy and the postpartum period |
| (ii) To determine if gestational weight gain was associated with changes in mood and quality of life |
| (iii) To assess the effect of a behavioral intervention targeting excessive gestational weight gain on mood and quality of life |
| Inclusion/exclusion criteria |
| (i) Pregnant women |
| (ii) Age, 18–40 years |
| (iii) English speaking |
| (iv) With overweight or obesity |
| (v) Carrying viable singletons |
| (vi) No history or current psychotic disorder or major depressive episodes |
| Study sample |
| (i) N: 54 (initial), 43 (final) |
| (ii) Mean age = 29.2 years |
| (iii) Gestational age = 10.0 weeks |
| (iv) Mean weight = 83.3 kg |
| Intervention |
| Duration of approximately 18 weeks. SmartMoms®. Behavioral weight management counselling by interventionists either in a clinic-based setting (in-person) or remotely through a smartphone application (phone) |
| Mobile app features |
| Not described |
| Outcome measures |
| (i) Gestational weight gain |
| (ii) Quality of life/rand 12-item short form (SF-12) |
| (iii) Mood and depressive symptoms/Beck depression inventory II (BDI-II) |
| Main results |
| (i) No significant intervention effects |
| (ii) Women in the SmartMoms® intervention had less overall gestational weight gain as compared with the women in the usual care group |
| (iii) Higher gestational weight gain was associated with worsened mood and lower physical quality of life across pregnancy |
| (iv) Maternal depressive symptoms and physical health worsened significantly over time from early to late pregnancy in both the SmartMoms® and usual care group, but re-established at postpastum |
|
| Järvelä-reijonen et al. |
| Objective(s) |
| (i) To investigate the effects of acceptance and commitment therapy (ACT) intervention delivered in two different ways, i.e., via face-to-face group sessions and via mobile app, on reported eating behavior and diet quality among adults with psychological distress and overweight or obesity |
| Inclusion/exclusion criteria |
| (i) Age, 25–60 years |
| (ii) Psychologically distressed (≥3/12 points from the general health questionnaire, GHQ-12) |
| (iii) BMI, 27–34.9 kg/m2 |
| (iv) With computer and internet access |
| (v) No diagnosis of severe chronic illness including eating disorder |
| (vi) No pregnancy or breastfeeding within the past 6 months |
| (vii) Disabilities/illnesses affecting substantially physiological or mental health |
| (viii) No participation in other intervention studies during the ongoing study |
| (ix) No psychotherapy or other psychological or mental treatment at least twice a month |
| Study sample |
| (i) N: 219 |
| (ii) 85% female |
| (iii) Mean BMI = 31.3 kg/m2 |
| (iv) Mean age = 49.5 years |
| Intervention |
| Intensive 8-week intervention participants were assigned to one of the three parallel groups: (1) ACT-based face-to-face (six group sessions led by a psychologist), (2) ACT-based mobile (one group session and mobile app), and (3) control (no intervention). The face-to-face and mobile interventions provided the same ACT program, and only the delivery method of the intervention differed. Intervention did not include nutrition education. The mobile group received smartphones with the preinstalled oiva mobile app containing 46 exercises in text and audio formats and introduction videos about the ACT skills. |
| Mobile app features |
| The oiva mobile app contains 46 exercises in text and audio formats and introduction videos about the ACT skills |
| Outcome measures |
| (i) Eating behavior |
| (ii) Index of diet quality (IDQ) |
| (iii) Intuitive eating scales (IES-1) |
| (iv) Alcohol use disorders identification test consumption (AUDIT-C) |
| (v) Three-factor eating questionnaire (TFEQ-R18) |
| (vi) Perceived stress scale stress (PSS) |
| (vii) Health and taste attitude scales, (HTAS) |
| (viii) 48-h dietary recall |
| (ix) ecSatter inventory 2.0 (ecSI 2.0) |
| (x) Regulation of eating behavior scale (REBS) |
| Main results |
| (i) ACT-based interventions, delivered in group sessions or by mobile app, showed beneficial effects on reported eating behavior |
| (ii) Beneficial effects on eating behavior were, however, not accompanied by parallel changes in diet |
| (iii) No statistically significant effects were found for dietary measures |
|
| Levinson et al. |
| Objective(s) |
| (i) To test if cognitions which occur during, or briefly after, mealtime predict subsequent eating disorder behaviors |
| Inclusion/exclusion criteria |
| (i) Clinical diagnosis of eating disorder |
| (ii) Recruited from an eating disorder clinic after discharge either from a residential or partial hospitalization treatment program |
| Study sample |
| (i) N: 66 |
| (ii) Mean age, 24.9 years |
| (iii) 97.0% female |
| (iv) 86.2% European American |
| (v) Median BMI = 20.66 |
| (vi) 74.2% in treatment for an eating disorder (68.2% outpatient) |
| (vii) 60.6% with anorexia nervosa, 21.2% with atypical anorexia nervosa, and 1.5% with bulimia nervosa |
| (viii) Other mental health diagnoses: 62.1% anxiety disorder, 57.6% depressive disorder, 19.7% obsessive compulsive disorder, and 10.6% posttraumatic stress disorder |
| Intervention |
| Not applicable. All procedures of this descriptive study were completed either online or through a mobile application |
| Mobile app features |
| The application consisted in a questionnaire that assesses behaviors, cognitions, and emotions before, during, and after mealtimes. It notified participants four times a day for one week and asked questions about mealtime cognitions, as well as eating disorder behaviors and anxiety |
| Outcome measures |
| (i) Eating disorder diagnostic scale (EDDS) |
| (ii) Eating disorder inventory-2 (EDI-2) |
| (iii) Daily life daily habits questionnaire |
| Main results |
| Cognitions predict subsequent eating disorder behaviors and vice versa (e.g., having high standards during a meal predicted subsequent food intake restriction, worrying about weight gain during a meal and concerns about making mistakes during the meal predicted subsequent weighing oneself, feeling fat during the meal, and preoccupation with thinness predicted subsequent excessive exercise) |
|
| Ma et al. |
| Objective(s) |
| (i) To evaluate the clinical and cost effectiveness and implementation potential in primary care of I-CARE (integrated coaching for better mood and weight), an integrated, technology-enhanced, collaborative care model for treating comorbid obesity and depression |
| Inclusion/exclusion criteria |
| (i) Age, 18 years and older |
| (ii) BMI ≥30.0 kg/m2 for non-Asians, BMI ≥27.0 kg/m2 for Asians |
| (iii) Clinically significant depression (≥10 points from the patient health questionnaire-9, PHQ-9) |
| (iv) Patient of the Palo Alto Medical Foundation ≥1 year and seen in primary care at least once in the preceding 24 months |
| (v) No severe mental condition other than minor or major depressive disorder and/or dysthymia, with the exception of any comorbid anxiety disorder (active suicidal ideation, bulimia nervosa, and alcohol/substance use disorder) |
| (vi) Not ongoing psychiatric care with a provider outside of Palo Alto Medical Foundation |
| (vii) No bariatric surgery within the past 12 months |
| (viii) No pre-existing diabetes or cardiovascular disease, diagnosis of cancer, and/or severe medical comorbidities that require aggressive treatment |
| (ix) No diagnosis of a terminal illness and/or residence in a long-term care facility |
| (x) No cognitive impairment based on the callahan 6-item screener |
| (xi) Capable of speaking, reading, and understanding English |
| (xii) With reliable telephone service and/or regular internet access |
| (xiii) No plan to move out of the area or transfer care outside the Palo Alto Medical Foundation |
| (xiv) Not currently pregnant, lactating, or planning to become pregnant |
| (xv) Not enrolled, or planning to enroll, in another research study |
| (xvi) No family/household member of another participant or of a staff member |
| Study sample |
| N: target sample size of 404 participants |
| The gender and minority racial/ethnic composition of the target enrollment population is estimated to be 64% female, 10% non-Hispanic black, 18% Hispanic/Latino, and 44% Asian |
| Intervention |
| Duration of 12 months. Participants will be randomized to usual care enhanced with the provision of a pedometer and information about the health system’s services for mood or weight management (control) or with the I-CARE program (intervention). The I-CARE program integrates the diabetes prevention program-based group lifestyle balance™ (GLB) program for weight loss and cardiometabolic risk reduction with the PEARLS program for collaborative stepped depression care, which uses problem solving therapy combined with behavioral activation, intensified with stepwise increases in doses and number of antidepressant medications as needed |
| Mobile app features |
| Participants will wear a fitbit pedometer and log their weight on the fitbit website or mobile application; also, they will log their minutes of physical activity and dietary intake using MyFitnessPal website or app |
| Outcome measures |
| (i) BMI |
| (ii) Quality of life (short Form-8 health survey, euro-qol-5d-5 L) |
| (iii) Depression (depression symptom Checklist-20) |
| (iv) Impact of obesity on psychosocial functioning (obesity-related problem scale) |
| (v) Anxiety (generalized anxiety disorder scale (GAD-7), panic |
| (vi) Functional disability (Sheehan disability scale) |
| (vii) Disorder module of the mini-international neuropsychiatric interview) |
| (viii) Direct medical costs and direct nonmedical costs |
| Main results |
| Not applicable |
|
| Naslund, Aschbrenner, Barre et al. |
| Objective(s) |
| (i) To assess the feasibility of using popular mHealth technologies for activity tracking among overweight and obese individuals with severe mental illness |
| Inclusion/exclusion criteria |
| (i) Age, 21 years and older |
| (ii) BMI ≥ 25 kg/m2 |
| (iii) Impairment in multiple areas of functioning |
| (iv) Diagnosis of severe mental illness (schizophrenia spectrum disorder, bipolar disorder, or major depressive disorder) |
| Study sample |
| (i) N: 10 (initial), 9 (final) |
| (ii) Mean age = 47.7 |
| (iii) Mean BMI = 42.4 kg/m2 |
| (iv) 90% female |
| (v) 90% white |
| (vi) Diagnosis: 3 with schizophrenia, 1 with bipolar disorder, 6 with major depressive disorder |
| Intervention |
| The weight loss program was adapted from the in SHAPE intervention for people with severe mental illness and consisted of weekly peer-led group and individual exercise and nutrition education sessions, as well as individual meetings with a certified fitness trainer. The intervention lasted between 80 and 133 days |
| Activity tracking devices, smartphones, and mobile apps were provided |
| Mobile app features |
| Participants were provided with iPhone 4S smartphones and one of two commercially available devices: FitBit zip or nike inc. FuelBand. Both are small size accelerometers that track steps, distance, and calories burned. Each device syncs wirelessly with its own smartphone application that reward milestones, track activity over time, and allow users to compare steps and progress with others through a closed social network |
| Outcome measures |
| (i) Feasibility (frequency of device use) |
| (ii) Acceptability (follow-up semistructured interviews regarding behavior, experiences, and preferences) |
| Main results |
| Participants reported high satisfaction, stating the devices were easy to use, helpful for setting goals, motivational, and useful for self-monitoring. Several participants liked the social connectivity feature of the devices where they could see each other’s progress on the smartphone application, noting that “friendly” competition increased motivation to be more physically active |
|
| Naslund, Aschbrenner, Scherer et al. |
| Objective(s) |
| (i) To examine whether daily step count measured using fitbit wearable devices was associated with weight loss and improved fitness among individuals with serious mental illness enrolled in a 6-month lifestyle program |
| Inclusion/exclusion criteria |
| (i) Age, 21 years and older |
| (ii) BMI ≥ 30 kg/m2 |
| (iii) English speaker |
| (iv) Diagnosis of severe mental illness (schizophrenia, schizoaffective disorder, major depressive disorder, or bipolar disorder) |
| (v) Stable pharmacological treatment status defined (i.e., receiving the same psychiatric medications over the prior 2 months) |
| (vi) No medical contraindication to weight loss |
| (vii) Not pregnant or planning to become pregnant within the next 6 months |
| (viii) No current diagnosis of an active alcohol-use or substance-use disorder |
| Study sample |
| (i) N: 43 (initial), 34 (final) |
| (ii) Mean age = 50.2 |
| (iii) Mean BMI = 38.5 kg/m2 |
| (iv) 61.8% female |
| (v) 100% non-Hispanic white |
| (vi) Diagnosis: 8 with schizophrenia, 17 with major depressive disorder, and 9 with bipolar disorder |
| Intervention |
| Duration of 6 months. The group-based lifestyle behavioral program focused on achieving weight loss through healthy eating and increasing physical activity through weekly sessions led by lifestyle coaches |
| Mobile app features |
| The fitbit zip is a compact wearable accelerometer that tracks number of steps, and it synchs wirelessly with a free companion smartphone application. The fitbit rewards milestones such as reaching daily step goals with colourful trophies, and it allows users to compare steps and progress with other through the smarthphone application |
| Outcome measures |
| (i) Daily step count |
| (ii) Weight |
| (iii) Fitness (6-minute walk test) |
| (iv) Change in fitness (calculated as the change in feet on the 6-minute walk test from baseline to 6-months) |
| Main results |
| At 6 months, higher average daily step count was associated with greater weight loss but not improved fitness |
|
| Williams et al. |
| Objective(s) |
| (i) To identify assays that engage emotion, cognition, and self-reflection aspects of self-regulation within lab-based, VR, and naturalistic settings, to understand the relations between assays taken at different levels of measurement, and to evaluate the extent to which these assayed self-regulation targets predict and/or mediate adherence to the intervention and mood and weight outcome |
| Inclusion/exclusion criteria |
| (i) Adult patients receiving primary care at Palo Alto Medical Foundation |
| (ii) Weight <350 pounds |
| (iii) With comorbid depression and obesity |
| (iv) With no significant medical or psychiatric comorbidities |
| (v) No MRI contraindications |
| vi) No traumatic brain injuries |
| (vii) No tumor or any other known structural abnormality in brain |
| Study sample |
| N: minimum target sample size of 100 participants |
| Intervention |
| The ENGAGE (engaging self-regulation targets to understand the mechanisms of behavior change and improve mood and weight outcomes) study is embedded within and operationally linked to the RAINBOW (research aimed at improving both mood and weight) randomized controlled trial. See the description of the RAINBOW study by Ma and colleagues mentioned above |
| Mobile app features |
| A mobile application will be used exclusively for the naturalistic assays. The mindstrong data collection application will be installed on a participant’s smart phone and will provide continuous passive naturalistic sampling of 288 phone-use feature variables throughout the two-year study period. Mindstrong’s technology and algorithms have shown that a user’s day-to-day smartphone keyboard and swipe-tap interactions contained repeated psychometric challenges capable of approximating gold-standard neuropsychological tests across a battery of domains |
| Outcome measures |
| Assays of three self-regulation targets (emotion, cognition, and self-reflection) will be collected in multiple settings: neuroimaging and behavioral lab-based measures, virtual reality, and passive smartphone sampling. Through data analysis, researchers will identify which targets relate most to behavioral and health outcomes, which change together, and which predict who will achieve behavioral change following an intervention and why |
| The mindstrong app used for the passive smartphone sampling targeting regulation of emotion, cognition, and self-reflection will record word frequencies collected from input text in emails, text messages, or search terms as well as punctuation usage indicative of emotional states, and behavioral changes will be inferred from changes in social activity, such as incoming and outgoing calls and messages |
| Main results |
| Not applicable |
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