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NCT03405103COMPLETEDanonymous

Efficacy of m-Health Self-Management Intervention

Sponsor

Source record

University of Wisconsin, Milwaukee

Phase

Source record

Completed (not classified in traditional phases such as Phase 1/2/3)

Modality

AI-normalized

behavioral intervention

Target

AI-normalized

m-Health self-management intervention focusing on osteoporosis prevention behaviors.

Indication / condition

AI-normalized

Osteoporosis

Intervention

Source record

Striving, Boning-Up, Personal Choice

Source & freshness

Source record

NCT ID

NCT03405103

Original source

ClinicalTrials.gov

Source last updated

Jan 26, 2018

Ingested at

Jun 18, 2026

Internal sync

Jun 18, 2026

Model version

trialsignal-ai-v1

Normalized confidence

96%

Validation status

validated

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NCT ID

NCT03405103

Title

Efficacy of m-Health Self-Management Intervention

Sponsor

University of Wisconsin, Milwaukee

Status

COMPLETED

Phase

Completed (not classified in traditional phases such as Phase 1/2/3)

Condition raw

Osteoporosis, Health Behavior

Condition normalized

Osteoporosis, Health Behavior

Modality raw

behavioral intervention

Modality normalized

behavioral intervention

Target raw

m-Health self-management intervention focusing on osteoporosis prevention behaviors.

Target normalized

m-Health self-management intervention focusing on osteoporosis prevention behaviors.

Interventions

Striving, Boning-Up, Personal Choice

Public preview

Source record

The study, sponsored by the University of Wisconsin, Milwaukee, investigates a novel m-Health intervention aimed at improving self-management behaviors in women at risk for osteoporosis. Given that over 35 million women in the U.S. are either affected by or at high risk for osteoporosis, and the projected healthcare costs associated with this condition are expected to exceed $25 billion by 2025, the market potential for effective interventions is significant. The competitive landscape includes traditional osteoporosis management strategies, but the integration of technology through a mobile application presents a unique value proposition. If successful, this intervention could be expanded to other health behaviors, enhancing its commercial viability. Diligence considerations should focus on the scalability of the app, user engagement metrics, and potential partnerships with healthcare providers or insurers.

AI-generated analysis supports research triage only. Verify source records, publications, sponsor disclosures and IP databases before making diligence decisions. Model: trialsignal-ai-v1.

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