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Research Article
Enhancing inhaler technique and asthma knowledge through a pharmacist-guided AI tool
expand article infoAbeer M. Kharshid‡
‡ Mutah University, Al Karak, Jordan

Corresponding author: Abeer M. Kharshid ( abeer.kharshid@mutah.edu.jo )

Academic editor: Petya Milushewa
© 2025 Abeer M. Kharshid.
This is an open access article distributed under the terms of the CC0 Public Domain Dedication.
Citation: Kharshid AM (2025) Enhancing inhaler technique and asthma knowledge through a pharmacist-guided AI tool. Pharmacia 72: 1-5. https://doi.org/10.3897/pharmacia.72.e164298
Open Access

Abstract

Background: Incorrect inhaler technique and insufficient patient education are commonly associated with poor asthma control. Community pharmacists are well positioned to deliver this counseling; however, verbal counseling alone may not always be effective or practical, particularly in busy pharmacy settings. AI-enabled tools provide interactive, personalized asthma self-management education.

Aim: This study aimed to assess the impact of pharmacist-led AI education on inhaler technique and asthma knowledge in Jordan.

Materials and methods: An interventional pre-post study was conducted at five community pharmacies in South Jordan. Adults (≥18 years) prescribed a metered-dose inhaler (MDI) or dry-powder inhaler (DPI) participated in 20–30 minute pharmacist-led sessions that combined verbal counseling with AI-assisted digital demonstrations. The primary outcomes were asthma knowledge (10-item questionnaire) and inhaler technique (10-step checklist), assessed at baseline and 1 week post-intervention.

Results: Four hundred participants (59% female; mean age 42.3 ± 14.8 years) were included in the study. Correct inhaler technique improved from 42% at baseline to 89% after the intervention (absolute difference 47%; 95% CI: 41–53; p < 0.001). Knowledge scores rose significantly from 4.3 ± 1.2 to 8.5 ± 1.0 (mean difference +4.2; 95% CI: 4.0–4.4; p < 0.001). Improvements were most notable among women and those with tertiary education. A strong correlation was observed between knowledge and inhaler technique (r = 0.71).

Conclusion: Pharmacist-led, AI-supported education significantly improved both inhaler technique and asthma knowledge. Adopting this scalable model could strengthen pharmaceutical care in community pharmacies and contribute to international efforts to enhance asthma self-management.

Keywords

artificial intelligence, asthma, community pharmacy services, education, inhalation technique, pharmacy

Introduction

Asthma, a major chronic inflammatory airway disease, affects more than 262 million people worldwide and results in approximately 455,000 deaths each year (Woolcock and Peat 2007). Because inhaled medications deliver drugs directly to the lungs, they provide a rapid onset of action and a favorable safety profile. As a result, they remain the cornerstone of asthma therapy. Metered-dose inhalers (MDIs) and dry-powder inhalers (DPIs) are the most commonly prescribed device types (Ramadan and Sarkis 2017).

Nevertheless, despite these advantages, inhalers are frequently misused. The most common errors include poor coordination between actuation and inhalation, inadequate inspiratory effort, and failure to exhale before inhaling (Chrystyn et al. 2017). These mistakes reduce pulmonary drug deposition and are associated with suboptimal asthma control, avoidable exacerbations, and increased healthcare utilization.

Patient education aimed at improving inhaler technique is therefore essential. As highly accessible healthcare professionals, community pharmacists are well positioned to assess inhaler technique and provide corrective training (Hussain and Paravattil 2020). Structured pharmaceutical care programs in Europe, particularly in Spain, the UK, and Bulgaria, demonstrate that pharmacist-led education can improve asthma management, and these approaches can be adapted to other global contexts (Mes et al. 2018; Macekova et al. 2025).

Even so, verbal counseling alone may be insufficient, especially in busy pharmacy environments. AI-enabled platforms that deliver interactive and adaptive education have been shown to enhance patient engagement, knowledge retention, and self-management behaviors (Rammal et al. 2024). However, little research has explored their use in routine pharmacy practice, particularly in low- and middle-income countries (Anisha et al. 2024).

Therefore, this study aimed to evaluate the impact of pharmacist-led, AI-assisted asthma education on inhaler technique and asthma knowledge in community pharmacies in Jordan.

Materials and methods

Study design and setting

A pre-post interventional study was conducted between January and March 2025 in five community pharmacies in South Jordan. Pharmacies were selected based on patient volume, the availability of private counseling space, and pharmacist willingness to participate.

Participants

Adults aged ≥ 18 years with a physician-confirmed diagnosis of asthma and currently prescribed a metered-dose inhaler (MDI) or dry-powder inhaler (DPI) were eligible. Patients with cognitive impairment, or communication barriers or who were unwilling to provide informed consent were excluded. Recruitment was carried out by pharmacists, who approached eligible patients during prescription refills and invited them to participate. All participants provided written informed consent.

Pharmacist training

Participating pharmacists attended a 2-day training workshop before study initiation. Training covered:

  • Standardized application of the Global Initiative for Asthma (GINA)-based 10-step inhaler technique checklist (Hoque and Nayak 2025).
  • Administration and scoring of the 10-item asthma knowledge questionnaire (Trebuchon et al. 2009; Hasan and Halabi 2021).
  • Operation of the AI-enabled digital tool, including troubleshooting, monitoring patient engagement, and supervising patient demonstrations.
  • Ethical considerations, including patient confidentiality and the responsible use of digital platforms in clinical settings.

Intervention

The intervention consisted of a pharmacist-led educational session supported by an AI-based interactive tool. Each session lasted approximately 20–30 minutes and included:

  • Baseline assessment: Participants demonstrated inhaler technique and completed the knowledge questionnaire.
  • AI-guided education: The tool provided personalized instruction through animations, voice guidance, and interactive feedback. Content was tailored to patient literacy, baseline knowledge, and performance.
  • Pharmacist reinforcement: Pharmacists supervised, corrected misconceptions, and ensured that patients practiced with their own inhalers or demonstration devices.
  • Follow-up support: Participants had access to an AI chatbot for frequently asked questions and reinforcement of inhaler technique during the study period.

Outcome measures

  • Asthma knowledge: Assessed using a validated 10-item multiple-choice questionnaire. Scores ranged from 0–10, with higher scores indicating greater knowledge.
  • Inhaler technique: Evaluated using a standardized 10-step checklist adapted from GINA guidelines. Correct performance of all steps was required for classification as “correct use.”

Follow-up

One week after the initial session, participants were reassessed using the same knowledge questionnaire and inhaler technique checklist.

Statistical analysis

Data were analyzed using SPSS version 26 (IBM Corp., Armonk, NY, USA). Continuous variables are presented as mean ± standard deviation (SD) with 95% confidence intervals (CIs). Categorical variables are expressed as frequencies and percentages. Paired t-tests were used to compare knowledge scores, while chi-square tests assessed improvements in inhaler technique. Logistic regression identified predictors of improvement (gender, age, and education level). Pearson’s correlation coefficient (r) was used to examine relationships between knowledge and inhaler technique. A p-value < 0.05 was considered statistically significant.

Ethical considerations

The study was approved by the Scientific Research Committee of the School of Pharmacy, Mutah University (Approval No. SERC 2024–2025/24; 1 December 2024) and conducted in accordance with the Declaration of Helsinki. Written informed consent was obtained from all participants.

Results

Participant characteristics

A total of 400 patients were enrolled (59% female; mean age 42.3 ± 14.8 years). The majority were aged 31–50 years (45%), and 42% had tertiary education (Table 1).

Table 1.
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Participant demographics.

Characteristic N (%)
Female 236 (59.0)
Male 164 (41.0)
Age 18–30 102 (25.5)
Age 31–50 180 (45.0)
Age > 50 118 (29.5)
Primary or less 88 (22.0)
Secondary 144 (36.0)
Tertiary 168 (42.0)

Primary outcomes

At baseline, 42% of participants (168/400) demonstrated correct inhaler technique. Following the intervention, this proportion increased to 89% (356/400), representing an absolute improvement of 47% (95% CI: 41–53; p < 0.001).

Asthma knowledge scores improved from 4.3 ± 1.2 at baseline to 8.5 ± 1.0 post-intervention, with a mean difference of +4.2 points (95% CI: 4.0–4.4; p < 0.001) (Table 2).

Table 2.
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Pre- and post-intervention outcomes.

Outcome Baseline Post-intervention Difference (95% CI) p-value
Correct inhaler use 42% (168/400) 89% (356/400) +47% (41–53) <0.001
Knowledge score 4.3 ± 1.2 8.5 ± 1.0 +4.2 (4.0–4.4) <0.001

Subgroup analyses

Improvements differed according to education level (Table 3). Patients with tertiary education achieved the greatest gains, although all groups showed significant improvements.

Table 3.
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Improvement by education level.

Education level Technique gain (%) Knowledge gain (Mean ± SD)
Primary or less +35% +3.1 ± 0.9
Secondary +48% +3.9 ± 1.1
Tertiary +61% +4.8 ± 1.0

Predictors of improvement

Logistic regression analysis indicated that female gender (OR 1.45, 95% CI: 1.06–1.98; p = 0.021) and tertiary education (OR 2.11, 95% CI: 1.52–2.91; p < 0.001) were significant predictors of greater improvement. Age was not a significant predictor (Table 4).

Table 4.
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Logistic regression results.

Variable OR 95% CI p-value
Female (vs. Male) 1.45 1.06–1.98 0.021
Tertiary education 2.11 1.52–2.91 <0.001
Age > 50 (vs. < 30) 0.88 0.63–1.22 0.446

Correlation analysis

There was a strong positive correlation between inhaler technique and knowledge (r = 0.71, p < 0.001), as well as between knowledge, skills, and confidence (r = 0.66, p < 0.001).

Discussion

This study demonstrated that pharmacist-led, AI-assisted education significantly improved both inhaler technique and asthma knowledge. The proportion of patients using the correct technique nearly doubled, while knowledge scores increased by more than 4 points. These findings underscore the effectiveness of combining pharmacist expertise with digital support in enhancing patient self-management.

Our results are consistent with previous studies highlighting the positive impact of pharmacist interventions on asthma outcomes (Basheti et al. 2007, 2019; García-Cárdenas et al. 2013). Moreover, the findings align with European pharmaceutical care programs and Bulgarian research that emphasize the pharmacist’s pivotal role in patient education and chronic disease management (Petkova et al. 2006; Petkova and Atkinson 2017).

The integration of AI further extends these efforts by providing interactive and personalized education. Comparable digital health applications have demonstrated benefits in chronic disease self-management (Aungst et al. 2021; Briggs et al. 2022). The strong correlations observed between knowledge, skills, and confidence in this study suggest that integrated pharmacist–AI interventions can simultaneously strengthen cognitive and behavioral dimensions of patient self-care.

Nevertheless, several challenges may hinder real-world implementation. Pharmacists require sufficient digital literacy and training, while workflow adjustments are necessary to allocate time for structured counseling. In addition, robust data privacy safeguards must be established. Cost-effectiveness analyses will also be critical to ensure sustainable adoption, particularly in resource-limited healthcare settings (Chatterjee and Gani 2024).

Conclusion

Pharmacist-guided education supported by AI significantly enhanced both inhaler technique and asthma knowledge in Jordanian community pharmacies. These results highlight the potential of combining professional expertise with digital tools to advance pharmaceutical care.

Future research should include randomized controlled trials, long-term follow-up to evaluate retention, and assessment of clinical outcomes such as symptom control and healthcare utilization. Expanding this model internationally—including within European and Bulgarian contexts—could meaningfully contribute to global strategies for optimizing asthma management.

Additional information

Conflict of interest

The author has declared that no competing interests exist.

Ethical statements

The author declared that this was an interventional pre–post study, not a randomized clinical trial.

The author declared that no experiments on humans or human tissues were performed for the present study.

The author declared that written informed consent was obtained from all participants.

The author declared that no experiments on human tissues were performed.

The author declared that no commercially available immortalised human and animal cell lines were used in the present study.

Use of AI

AI tools were used to generate tables. All content was reviewed and verified by the author.

Funding

No funding was reported.

Author contributions

The author solely contributed to this work.

Author ORCIDs

Abeer M. Kharshid https://orcid.org/0009-0008-5703-8057

Data availability

All of the data that support the findings of this study are available in the main text.

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