Evidence map›Paper›PMID 42756108›Full record

ArticleFrontiers in public health2026

Behavioral intention to use mental health chatbots in Saudi Arabia: a cross-sectional UTAUT-based study.

Zaenb Alsalman, Abdullah Almaqhawi, Abdullah Almulhim, Anwar Fawzi Alqadeep, Ghadeer Mohammed Almutawah, Fatemah Ali Al Khalifa, Fatima Ramzi Alghadeer, Hawra Adnan Aleid, Walaa Mohammed Alkhalifah, Zainab Abdrabulridha Alabdullah and 2 more

Abstract read
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Article in Frontiers in public health, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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1 · What the graph read from it

What it found

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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

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3 · Its place in the literature

Who cites it

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4 · The record

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5 · Who and what money

Authors and funding

12 authors.

Zaenb AlsalmanDepartment of Family and Community Medicine, College of Medicine, King Faisal University, Al-Ahsa, Saudi Arabia.
Abdullah AlmaqhawiDepartment of Family and Community Medicine, College of Medicine, King Faisal University, Al-Ahsa, Saudi Arabia.
Abdullah AlmulhimDepartment of Family and Community Medicine, College of Medicine, King Faisal University, Al-Ahsa, Saudi Arabia.
Anwar Fawzi AlqadeepCollege of Medicine, King Faisal University, Al-Ahsa, Saudi Arabia.
Ghadeer Mohammed AlmutawahCollege of Medicine, King Faisal University, Al-Ahsa, Saudi Arabia.
Fatemah Ali Al KhalifaCollege of Medicine, King Faisal University, Al-Ahsa, Saudi Arabia.
Fatima Ramzi AlghadeerCollege of Medicine, King Faisal University, Al-Ahsa, Saudi Arabia.
Hawra Adnan AleidCollege of Medicine, King Faisal University, Al-Ahsa, Saudi Arabia.
Walaa Mohammed AlkhalifahCollege of Medicine, King Faisal University, Al-Ahsa, Saudi Arabia.
Zainab Abdrabulridha AlabdullahFamily Medicine Academy, Al-Ahsa, Saudi Arabia.
Safiah Ahmed AlAmerCollege of Medicine, King Faisal University, Al-Ahsa, Saudi Arabia.
Marwa Mahmoud ShafeyDepartment of Family and Community Medicine, College of Medicine, Imam Abdulrahman bin Faisal University, Dammam, Saudi Arabia.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background and objectives: Despite the growing burden of mental health conditions in Saudi Arabia, sociocultural stigma, privacy concerns, and structural barriers leave a substantial proportion of the population with unmet psychological needs. Mental health chatbots offer an anonymous, accessible, and low-barrier alternative to traditional care, aligning with the Kingdom's digital health transformation goals. This study investigated factors associated with behavioral intention to use mental health chatbots among adults in Saudi Arabia. Materials and methods: A cross-sectional online survey was conducted among adults in Saudi Arabia. Data were collected using a questionnaire that assessed sociodemographic characteristics, mental health history, prior use of chatbots, technology acceptance based on a modified Unified Theory of Acceptance and Use of Technology (UTAUT) framework, and perceived barriers. Results: Among 533 participants (mean age 30.5 ± 11.7 years), 35.3% reported current psychological symptoms, and 51.6% reported needing psychological support during the previous year. Overall, 59.0% supported the integration of mental health chatbots into psychological services. In the primary multivariable linear regression analysis, perceived usefulness, perceived ease of use, social influence, and perceived need for psychological consultation were independently associated with higher behavioral intention. Conclusion: Behavioral intention to use mental health chatbots was primarily associated with perceived usefulness, perceived ease of use, and social influence. Perceived self-efficacy, perceived barriers, and most demographic characteristics were not independently associated with behavioral intention. These findings may inform the design and future evaluation of culturally appropriate mental health chatbot interventions in Saudi Arabia, although further research is needed to assess their real-world effectiveness and safety.

Indexed as

IntentionMental DisordersMental Health ServicesAdultCross-Sectional StudiesDigital HealthFemaleHumansMaleMental Health TeletherapyMiddle AgedSaudi ArabiaSurveys and QuestionnairesYoung Adultartificial intelligencemental health chatbotsprivacy riskSaudi Arabiastigmatechnology acceptancetreatment gapUTAUT model

Identifiers

PMID42756108
PMCPMC13582321

What Socratic holds

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the Socratic graph.