Concept
mHealth
mHealth uses mobile apps and phones to deliver assessment, coaching, or treatment support.
App claims are loud; trial and field evidence here separates usable tools from marketing.
Evidence
What the evidence shows
Drawn from 8 studies in this library. Each claim links to the studies behind it.
Multiple studies in this library examine mhealth with empirical patient or population outcomes rather than opinion alone.
Past-month use occasions, AUDIT-C, DAST-10, PHQ-8, and GAD-7 improved (all P<.05). In-app craving ratings fell roughly by half by weeks 8–9. Engagement averaged about 15.7 use days over 8 weeks. Authors call the approach feasible and acceptable but note the need for controlled efficacy trials.
3070 people were randomized. The intervention × time interaction was highly significant: adjusted WEMWBS differences favored MoodGYM by about 2.5 points at 6 weeks and 2.9 at 12 weeks (≈Cohen d 0.34). Attrition was much higher in the intervention arm (73.5%) than control (26.9%).
Audio coaching increased fruit intake by about three pieces per week versus text and control; vegetable intake had no significant main effect of condition (literacy interactions noted).
PeR improved self-efficacy and quality of life and eased symptoms; health improvement was 2.24× higher with high vs low Ex-SRES; dropout was 11.3%.
Intervention participants lost more weight than comparison participants (about 1.97 kg more; adjusted losses ~2.88 kg vs 0.91 kg).
Open questions
Where studies disagree
Open questions, not settled findings — worth knowing before you cite any one of these.
Effect sizes and settings differ across mhealth studies — digital vs clinic, trial vs observational — so results should not be pooled casually.
Common misconceptions
mHealth findings always generalise to every clinic.
These studies are context-bound; designs, populations, and endpoints limit transfer.
Exam-style questions
Short-answer questions that ask you to explain or compare, not recall.
What is mHealth and why do health students study it?
mHealth uses mobile apps and phones to deliver assessment, coaching, or treatment support. App claims are loud; trial and field evidence here separates usable tools from marketing.
Name one limit of the evidence base for mHealth in this library.
Single-setting trials, observational designs, or digital-only samples limit causal and external claims.
The studies
- SMS coaching for weight loss
Daily tailored text/MMS coaching produced about 2 kg more weight loss than print materials over 4 months in overweight adults.
- Woebot chatbot for substance use
An 8-week fully automated Woebot SUD program showed pre–post drops in substance use, cravings, depression, and anxiety in a single-group study.
- MoodGYM improves population wellbeing
In a large UK web RCT, automated MoodGYM raised mental well-being versus wait-list control despite high intervention attrition.
- Fitbit wear during an activity trial
Survivors wore Fitbits most days and roughly doubled ActiGraph MVPA over 12 weeks in the intervention arm.
- WeChat rehab helped COPD self-efficacy
A Chinese RCT used WeChat-supported personalized remote pulmonary rehab (PeR) to improve COPD patients’ self-efficacy, quality of life, and symptoms.
- Mobile Immediate Mood Scaler validation
A 22-item mobile Immediate Mood Scaler correlated strongly with standard PHQ-9 and GAD-7 scores in 110 participants.
- Tech parenting program cut postpartum distress
A Singapore RCT found a technology-based supportive educational parenting program improved bonding and satisfaction while reducing postnatal depression and anxiety.
- Audio vs text produce-app RCT
A tailored mobile app’s audio messages raised fruit intake more than text or control, while vegetable intake showed no overall main effect.
Learn alongside
Flashcards
Study mHealth properly
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