Embracing digital technology in chronic respiratory care: Surveying patients access and confidence

Jácome, Cristina; Marques, Fábio Ferreira; Paixão, Cátia; Rebelo, Patrícia; Oliveira, Ana; Cruz, Joana; Freitas, Célia; Rua, Marília; Loureiro, Helena Maria Almeida Macedo; Peguinho, Cristina; Simões, A.; Santos, Madalena; Valente, Carla; Simão, Paula; Marques, Alda

doi:10.1016/j.pulmoe.2019.05.001

Cited by 11 publications

(8 citation statements)

References 8 publications

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“…Overall, 16 participants (12 women), age range 48-86, accepted to participate in an individual face-to-face interview at 3 months after the intervention started. Follow-up interviews were done at 3 and 12 months, as both ranges of time are commonly used when investigating intervention-based effects in people with COPD [ 13 , 14 ]. At 3 months, 15 interviews were conducted in the participants’ homes and 1 at a university (the worksite of the interviewer), according to the participant’s wishes.…”

Section: Methodsmentioning

confidence: 99%

“…eHealth tools, such as mobile apps and web-based platforms, represent a promising way of delivering health services such as support for self-management strategies to people with COPD. eHealth solutions are becoming increasingly common and are found to be feasible and effective within the COPD population [ 9 , 13 - 20 ]. eHealth tools have, for example, been used for educating and keeping track of a person’s health and are thought to be a significant source of health-related information [ 14 , 15 , 19 , 20 ].…”

Section: Introductionmentioning

confidence: 99%

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Experiences and Factors Affecting Usage of an eHealth Tool for Self-Management Among People With Chronic Obstructive Pulmonary Disease: Qualitative Study

Marklund¹,

Tistad²,

Lundell³

et al. 2021

J Med Internet Res

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Tell me about how you have used the COPD Web (during this time) In what purpose/purposes have you visited the COPD Web? User experience What are your views on having the computer/this kind of computer based program as help/assistance? Have you missed anything particular on the COPD Web? Have you been able to identify yourself with the contents on the COPD Web, or in other ways feel that "the COPD Web is for me"? How do you perceive the COPD Web is to navigate/navigate to on the Internet? How have you perceived the [films/information/how information is presented/the amount of information]? How have/has [films/step registration/login/the COPD Web in general] worked/functioned for you? Accompanying parts/"Triggers"

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Section: Methodsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Experiences and Factors Affecting Usage of an eHealth Tool for Self-Management Among People With Chronic Obstructive Pulmonary Disease: Qualitative Study

Marklund¹,

Tistad²,

Lundell³

et al. 2021

J Med Internet Res

View full text Add to dashboard Cite

show abstract

“…The perceptron inputs a real number with magnitude and direction and then performs matrix operations on these vector values through the researched algorithm. Refer to the gate circuit programming logic [ 24 ]; if the output is greater than a certain value, the output result is 0; otherwise, the output is 1, as shown in Equation ( 3 ) of the sensor [ 25 ].

…”

Section: Respiratory Care Of Big Data Communication On the Nursing An...mentioning

confidence: 99%

Respiratory Care of Big Data Communication to Prevent Respiratory Tract Infection Nursing Analysis of Patients with Heart Failure

Lin

Feng

et al. 2022

BioMed Research International

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Heart failure is the final stage of the development of heart disease, with a high mortality and disability rate. It poses a serious threat to human health and brings tremendous pressure to human society. Preventing respiratory infections in patients with heart failure is also the first priority of care. This article is aimed at studying the nursing analysis of respiratory tract care based on big data exchanges to prevent respiratory tract infections in patients with heart failure. This article uses benchmark and sample collection. Studies have shown that for Pseudomonas aeruginosa, its resistance to ampicillin, amoxicillin/clavulanic acid, cefazolin, cefuroxime, ceftriaxone, cefotaxime, and cefoxitin has reached more than 80%. It is also suitable for piperacillin, ticarcillin/clavulanic acid, piperacillin/tazobactam, cefepime, aztreonam, gentamicin, tobramycin, ciprofloxacin, and levofloxacin. The resistance rate of stars is within 10%-30%. These antibiotics are effective and can be used for clinical treatment. The drug resistance rates of ceftazidime, imipenem, meropenem, and amikacin were all lower than 10%, and the drug resistance rates of ceftazidime and imipenem were much lower than those reported in the 2016 literature. These antibiotics have become the most effective drugs for the treatment of Pseudomonas aeruginosa infections. Basically, good communication of respiratory care data is realized, thereby preventing respiratory care analysis of patients with heart failure.

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“…mHealth allows the combination of computation, communication, and interactive display that makes it possible to use gamification and peer support tools with the potential to inspire behavior changes and offer treatment adherence quantification [ 11 , 12 ]. Moreover, patients with asthma have increasingly high smartphone ownership levels and are interested in using disease-specific apps [ 13 , 14 ].…”

Section: Introductionmentioning

confidence: 99%

Feasibility and Acceptability of an Asthma App to Monitor Medication Adherence: Mixed Methods Study

Jácome¹,

Almeida²,

Pereira³

et al. 2021

JMIR Mhealth Uhealth

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Background Poor medication adherence is a major challenge in asthma, and objective assessment of inhaler adherence is needed. The InspirerMundi app aims to monitor adherence while providing a positive experience through gamification and social support. Objective This study aimed to evaluate the feasibility and acceptability of the InspirerMundi app to monitor medication adherence in adolescents and adults with persistent asthma (treated with daily inhaled medication). Methods A 1-month mixed method multicenter observational study was conducted in 26 secondary care centers from Portugal and Spain. During an initial face-to-face visit, physicians reported patients’ asthma therapeutic plan in a structured questionnaire. During the visits, patients were invited to use the app daily to register their asthma medication intakes. A scheduled intake was considered taken when patients registered the intake (inhaler, blister, or other drug formulation) by using the image-based medication detection tool. At 1 month, patients were interviewed by phone, and app satisfaction was assessed on a 1 (low) to 5 (high) scale. Patients were also asked to point out the most and least preferred app features and make suggestions for future app improvements. Results A total of 107 patients (median 27 [P25-P75 14-40] years) were invited, 92.5% (99/107) installed the app, and 73.8% (79/107) completed the 1-month interview. Patients interacted with the app a median of 9 (P25-P75 1-24) days. At least one medication was registered in the app by 78% (77/99) of patients. A total of 53% (52/99) of participants registered all prescribed inhalers, and 34% (34/99) registered the complete asthma therapeutic plan. Median medication adherence was 75% (P25-P75 25%-90%) for inhalers and 82% (P25-P75 50%-94%) for other drug formulations. Patients were globally satisfied with the app, with 75% (59/79) scoring ≥4,; adherence monitoring, symptom monitoring, and gamification features being the most highly scored components; and the medication detection tool among the lowest scored. A total of 53% (42/79) of the patients stated that the app had motivated them to improve adherence to inhaled medication and 77% (61/79) would recommend the app to other patients. Patient feedback was reflected in 4 major themes: medication-related features (67/79, 85%), gamification and social network (33/79, 42%), symptom monitoring and physician communication (21/79, 27%), and other aspects (16/79, 20%). Conclusions The InspirerMundi app was feasible and acceptable to monitor medication adherence in patients with asthma. Based on patient feedback and to increase the registering of medications, the therapeutic plan registration and medication detection tool were redesigned. Our results highlight the importance of patient participation to produce a patient-centered and engaging mHealth asthma app.

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Embracing digital technology in chronic respiratory care: Surveying patients access and confidence

Cited by 11 publications

References 8 publications

Experiences and Factors Affecting Usage of an eHealth Tool for Self-Management Among People With Chronic Obstructive Pulmonary Disease: Qualitative Study

Experiences and Factors Affecting Usage of an eHealth Tool for Self-Management Among People With Chronic Obstructive Pulmonary Disease: Qualitative Study

Respiratory Care of Big Data Communication to Prevent Respiratory Tract Infection Nursing Analysis of Patients with Heart Failure

Feasibility and Acceptability of an Asthma App to Monitor Medication Adherence: Mixed Methods Study

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