Venous leg ulcer recurrence : deciphering long term patient adherence to preventive treatments and activities

To better understand long term adherence to self-care activities to prevent the recurrence of venous leg ulcers, participants (n=80) were recruited to a prospective longitudinal study after experiencing healing of a venous leg ulcer. Data on demographics, health, psychosocial measures and adherence to prevention strategies (compression therapy, leg elevation and lower leg exercise) were collected every three months for one year after healing. Multivariable regression modelling was used to identify the factors that were independently associated with adherence. Over the year, a significant decline in adherence to all three strategies was observed, predominantly between 6–12 months after healing (p<0.01). Several factors were associated with adherence to more than one preventive activity. Regular follow-up care and a history of multiple previous ulcers were related to improved adherence (p<0.05), while scoring at higher risk for depression and restricted mobility were related to decreasing adherence over time (p<0.05). Patients with osteoarthritis had significantly reduced adherence to compression hosiery (p=0.026). These results provide information to assist care providers plan strategies for prevention of recurrent venous leg ulcers; and suggest a need for regular follow-up care which addresses both the physical and mental health of this population.

Suboptimal use of inhaled corticosteroids in children with persistent asthma : inadequate physician prescription, poor patient adherence or both ?

Mémoire numérisé par la Division de la gestion de documents et des archives de l'Université de Montréal

DOES THE MESSAGE MATTER? ENHANCING PATIENT ADHERENCE THROUGH PERSUASIVE MESSAGES

To improve health and reduce costs, we need to encourage patients to make better healthcare decisions. Many informatics interventions are aimed at improving health outcomes by influencing patient behavior. However, we know little about how the content of a message in these interventions can influence a health-related decision. In this research we formulate a conceptual model to help explain and guide the design of “persuasive messages”, those which can change and influence patient behavior. We apply the conceptual model to design persuasive appointment reminder messages using humancentered design principles. Finally, we empirically test our hypotheses in a randomized controlled trial in order to determine the effectiveness of persuasive appointment reminders to reduce the number of missed appointments in a sample of 1016 subjects in a community health center. The results of the study confirm that reminder messages are effective in reducing missed appointment compared with no reminders (p=0.028). Further, reminder messages that incorporate heuristic cues such as authority, commitment, liking, and scarcity are more effective than reminder messages without such cues (p=0.006). However, the addition of systematic arguments or reasons for attending appointments have no effect on appointment adherence (p=0.646). The results of this research suggest that the content of reminder messages may be an important factor in helping to reduce missed appointments.

Patient adherence to medication requirements for therapy of type 2 diabetes

Type 2 diabetes is a complex, progressive endocrine and metabolical disease that typically requires substantial lifestyle changes and multiple medications to lower blood glucose, reduce cardiovascular risk and address comorbidities. Despite an extensive range of available and effective treatments, <50% of patients achieve a glycaemical target of HbA <7.0% and about two-thirds die of premature cardiovascular disease. Adherence to prescribed therapies is an important factor in the management of type 2 diabetes that is often overlooked. Inadequate adherence to oral antidiabetes agents, defined as collecting <80% of prescribed medication, is variously estimated to apply to between 36% and 93% of patients. All studies affirm that a significant proportion of type 2 diabetes patients exhibit poor adherence that will contribute to less than desired control. Identified factors that impede adherence include complex dosing regimens, clinical inertia, safety concerns, socioeconomic issues, ethnicity, patient education and beliefs, social support and polypharmacy. This review explores these factors and potential strategies to improve adherence in patients with type 2 diabetes. © 2011 Blackwell Publishing Ltd.

Associations between patient factors and medication adherence: a Jordanian experience

Objective: To explore the effect of patient characteristics and health beliefs on their medication adherence. Methods: Patients (n=167) with chronic conditions (mean age 58.9; SD=13.54, 53% males) were recruited from March 2009- to March 2010 using a cross sectional study design. Data collected included patients’ demographics, medical conditions, medications therapeutic regimen, frequency of physician visits and health beliefs. Patient self-reported adherence to medications was assessed by the researcher using a validated and published scale. Treatment related problems (TRPs) were evaluated for each patient by competent clinical pharmacists. Associations between patient characteristics/health beliefs with adherence were explored. Results: About half of the patients (46.1%) were non-adherent. A significant association was found between lower adherence and higher number of disease states (p<0.001), higher number of medications (p=0.001), and higher number of identified TRPs (p = 0.003). Patient adherence was positively affected by older age, higher educational level, and higher number of physician visits per month, while it was negatively affected by reporting difficulties with getting prescription refills on time. Conclusion: This study identified different factors that may negatively affect adherence, including higher number of medications and disease states, higher number of identified TRPs and inability to getting prescription refills on time. Hence, more care needs to be provided to patients with complex therapeutic regimens in order to enhance adherence.

Treatment adherence and health outcomes in patients with bronchiectasis

Background: We aimed to determine adherence to inhaled antibiotics, other respiratory medicines and airway clearance and to determine the association between adherence to these treatments and health outcomes (pulmonary exacerbations, lung function and Quality of Life Questionnaire-Bronchiectasis [QOL-B]) in bronchiectasis after 12 months.

Methods: Patients with bronchiectasis prescribed inhaled antibiotics for Pseudomonas aeruginosa infection were recruited into a one-year study. Participants were categorised as " adherent" to medication (medication possession ratio ≥80% using prescription data) or airway clearance (score ≥80% in the Modified Self-Reported Medication-Taking Scale). Pulmonary exacerbations were defined as treatment with a new course of oral or intravenous antibiotics over the one-year study. Spirometry and QOL-B were completed at baseline and 12 months. Associations between adherence to treatment and pulmonary exacerbations, lung function and QOL-B were determined by regression analyses.

Results: Seventy-five participants were recruited. Thirty-five (53%), 39 (53%) and 31 (41%) participants were adherent to inhaled antibiotics, other respiratory medicines, and airway clearance, respectively. Twelve (16%) participants were adherent to all treatments. Participants who were adherent to inhaled antibiotics had significantly fewer exacerbations compared to non-adherent participants (2.6 vs 4, p = 0.00) and adherence to inhaled antibiotics was independently associated with having fewer pulmonary exacerbations (regression co-efficient = -0.51, 95% CI [-0.81,-0.21], p < 0.001). Adherence to airway clearance was associated with lower QOL-B Treatment Burden (regression co-efficient = -15.46, 95% CI [-26.54, -4.37], p < 0.01) and Respiratory Symptoms domain scores (regression co-efficient = -10.77, 95% CI [-21.45; -0.09], p < 0.05). There were no associations between adherence to other respiratory medicines and any of the outcomes tested. Adherence to treatment was not associated with FEV₁ % predicted.

Conclusions: Treatment adherence is low in bronchiectasis and affects important health outcomes including pulmonary exacerbations. Adherence should be measured as part of bronchiectasis management and future research should evaluate bronchiectasis-specific adherence strategies. 

Defining the content and delivery of an intervention to Change AdhereNce to treatment in BonchiEctasis (CAN-BE): a qualitative approach incorporating the Theoretical Domains Framework, behavioural change techniques and stakeholder expert panels

Background
Low patient adherence to treatment is associated with poorer health outcomes in bronchiectasis. We sought to use the Theoretical Domains Framework (TDF) (a framework derived from 33 psychological theories) and behavioural change techniques (BCTs) to define the content of an intervention to change patients’ adherence in bronchiectasis (Stage 1 and 2) and stakeholder expert panels to define its delivery (Stage 3).

Methods
We conducted semi-structured interviews with patients with bronchiectasis about barriers and motivators to adherence to treatment and focus groups or interviews with bronchiectasis healthcare professionals (HCPs) about their ability to change patients’ adherence to treatment. We coded these data to the 12 domain TDF to identify relevant domains for patients and HCPs (Stage 1). Three researchers independently mapped relevant domains for patients and HCPs to a list of 35 BCTs to identify two lists (patient and HCP) of potential BCTs for inclusion (Stage 2). We presented these lists to three expert panels (two with patients and one with HCPs/academics from across the UK). We asked panels who the intervention should target, who should deliver it, at what intensity, in what format and setting, and using which outcome measures (Stage 3).

Results
Eight TDF domains were perceived to influence patients’ and HCPs’ behaviours: Knowledge, Skills, Beliefs about capability, Beliefs about consequences, Motivation, Social influences, Behavioural regulation and Nature of behaviours (Stage 1). Twelve BCTs common to patients and HCPs were included in the intervention: Monitoring, Self-monitoring, Feedback, Action planning, Problem solving, Persuasive communication, Goal/target specified:behaviour/outcome, Information regarding behaviour/outcome, Role play, Social support and Cognitive restructuring (Stage 2). Participants thought that an individualised combination of these BCTs should be delivered to all patients, by a member of staff, over several one-to-one and/or group visits in secondary care. Efficacy should be measured using pulmonary exacerbations, hospital admissions and quality of life (Stage 3).

Conclusions
Twelve BCTs form the intervention content. An individualised selection from these 12 BCTs will be delivered to all patients over several face-to-face visits in secondary care. Future research should focus on developing physical materials to aid delivery of the intervention prior to feasibility and pilot testing. If effective, this intervention may improve adherence and health outcomes for those with bronchiectasis in the future.

Adherence: the journey of medication taking, are we there yet?

Patient adherence to medications has been an issue challenging healthcare professionals for decades. Adherence rates, causes of non-adherence, barriers and enablers to medication taking, interventions to promote adherence, and the impact of non-adherence on health outcomes, have been extensively studied. In light of this, the area of adherence research has progressed conceptually and practically. This special issue contains a range of articles which focus on different aspects of adherence, from standardising terminology and methods of measurement, to non-adherence in a broad range of patient populations, and to interventions to promote adherence.

Treatment non-adherence in teenage and young adult patients with cancer

Adhering to treatment can be a significant issue for many patients diagnosed with chronic health conditions and this has been reported to be greater during the adolescent years. However, little is known about treatment adherence in teenage and young adult (TYA) patients with cancer. To increase awareness of the adherence challenges faced by these patients, we have reviewed the published work. The available evidence suggests that a substantial proportion of TYA patients with cancer do have difficulties, with reports that up to 63% of patients do not adhere to their treatment regimens. However, with inconsistent findings across studies, the true extent of non-adherence for these young patients is still unclear. Furthermore, it is apparent that there are many components of the cancer treatment regimen that have yet to be assessed in relation to patient adherence. Factors that have been shown to affect treatment adherence in TYA patients include patient emotional functioning (depression and self-esteem), patient health beliefs (perceived illness severity and vulnerability), and family environment (parental support and parent–child concordance). Strategies that foster greater patient adherence are also identified. These strategies are multifactorial, targeting not only the patient, but the health professional, family, and treatment regimen. This review highlights the lack of interventional studies addressing treatment adherence in TYA patients with cancer, with only one such intervention being identified: a video game intervention focusing on behavioural issues related to cancer treatment and care. Methodological issues in measuring adherence are addressed and suggestions for improving the design of future adherence studies highlighted, of which there is a great need.

Low levels of adherence with proton pump inhibitor therapy contribute to therapeutic failure in gastroesophageal reflux disease

To assess adherence to proton pump inhibitor (PPI) treatment and associated variables in patients with gastroesophageal reflux disease (GERD). Cross-sectional and prospective comprising 240 consecutive adult patients, diagnosed with GERD for whom continuous use of standard or double dose of omeprazole had been prescribed. Patients were ranked as ne-GERD (162: 67.5%) or e-GERD classified according to the Los Angeles classification as A (48:20.0%), B (21:8.6%), C (1:0.5%), D (1:0.5%), and Barrett's esophagus (7:2.9%). The Morisky questionnaire was applied to assess adherence to therapy and a GERD questionnaire to assess symptoms and their impact. Adherence was correlated with demographics, cotherapies, comorbidities, treatment duration, symptoms scores, endoscopic findings, and patient awareness of their disease. 126 patients (52.5%) exhibited high level of adherence and 114 (47.5%) low level. Youngers (P= 0.002) or married (O.R. 2.41, P= 0.03 vs. widowers) patients had lower levels of adherence; symptomatic patients exhibited lower adherence (P= 0.02). All other variables studied had no influence on adherence. Patients with GERD attending a tertiary referral hospital in Sao Paulo exhibited a high rate of low adherence to the prescribed PPI therapy that may play a role in the therapy failure. Age <60 years, marital status and being symptomatic were risk factors for low adherence.

A comparison of adherence with minocycline treatment in Parkinson's disease and rheumatoid arthritis clinical trials

Background: Little is known about the effects on patient adherence when the same study drug is administered in the same dose in two populations with two different diseases in two different clinical trials. The Minocycline in Rheumatoid Arthritis (MIRA) trial and the NIH Exploratory Trials in Parkinson's disease (NET-PD) Futility Study I provide a unique opportunity to do the above and to compare methods measuring adherence. This study may increase understanding of the influence of disease and adverse events on patient adherence and will provide insights to investigators selecting adherence assessment methods in clinical trials of minocycline and other drugs in future.^ Methods: Minocycline adherence by pill count and the effect of adverse events was compared in the MIRA and NET-PD FS1 trials using multivariable linear regression. Within the MIRA trial, agreement between assay and pill count was compared. The association of adverse events with assay adherence was examined using multivariable logistic regression.^ Results: Adherence derived from pill count in the MIRA and NET-PD FS1 trials did not differ significantly. Adverse events potentially related to minocycline did not appear useful to predict minocycline adherence. In the MIRA trial, adherence measured by pill count appears higher than adherence measured by assay. Agreement between pill count and assay was poor (kappa statistic = 0.25).^ Limitations: Trial and disease are completely confounded and hence the independent effect of disease on adherence to minocycline treatment cannot be studied.^ Conclusion: Simple pill count may be preferred over assay in the minocycline clinical trials to measure adherence. Assays may be less sensitive in a clinical setting where appointments are not scheduled in relation to medication administration time, given assays depend on many pharmacokinetic and instrument-related factors. However, pill count can be manipulated by the patient. Another study suggested that self-report method is more sensitive than pill count method in differentiating adherence from non-adherence. An effect of medication-related adverse events on adherence could not be detected.^

A technological framework based on automatic messaging for improving adherence of diabetic patients

En todo el mundo se ha observado un crecimiento exponencial en la incidencia de enfermedades crónicas como la hipertensión y enfermedades cardiovasculares y respiratorias, así como la diabetes mellitus, que causa un número de muertes cada vez mayor en todo el mundo (Beaglehole et al., 2008). En concreto, la prevalencia de diabetes mellitus (DM) está aumentando de manera considerable en todas las edades y representa un serio problema de salud mundial. La diabetes fue la responsable directa de 1,5 millones de muertes en 2012 y 89 millones de años de vida ajustados por discapacidad (AVAD) (OMS, 2014). Uno de los principales dilemas que suelen asociarse a la gestión de EC es la adherencia de los pacientes a los tratamientos, que representa un aspecto multifactorial que necesita asistencia en lo relativo a: educación, autogestión, interacción entre los pacientes y cuidadores y compromiso de los pacientes. Medir la adherencia del tratamiento es complicado y, aunque se ha hablado ampliamente de ello, aún no hay soluciones “de oro” (Reviews, 2002). El compromiso de los pacientes, a través de la participación, colaboración, negociación y a veces del compromiso firme, aumentan las oportunidades para una terapia óptima en la que los pacientes se responsabilizan de su parte en la ecuación de adherencia. Comprometer e involucrar a los pacientes diabéticos en las decisiones de su tratamiento, junto con expertos profesionales, puede ayudar a favorecer un enfoque centrado en el paciente hacia la atención a la diabetes (Martin et al., 2005). La motivación y atribución de poder de los pacientes son quizás los dos factores interventores más relevantes que afectan directamente a la autogestión de la atención a la diabetes. Se ha demostrado que estos dos factores desempeñan un papel fundamental en la adherencia a la prescripción, así como en el fomento exitoso de un estilo de vida sana y otros cambios de conducta (Heneghan et al., 2013). Un plan de educación personalizada es indispensable para proporcionarle al paciente las herramientas adecuadas que necesita para la autogestión efectiva de la enfermedad (El-Gayar et al. 2013). La comunicación efectiva es fundamental para proporcionar una atención centrada en el paciente puesto que influye en las conductas y actitudes hacia un problema de salud ((Frampton et al. 2008). En este sentido, la interactividad, la frecuencia, la temporalización y la adaptación de los mensajes de texto pueden promover la adherencia a un régimen de medicación. Como consecuencia, adaptar los mensajes de texto a los pacientes puede resultar ser una manera de hacer que las sugerencias y la información sean más relevantes y efectivas (Nundy et al. 2013). En este contexto, las tecnologías móviles en el ámbito de la salud (mHealth) están desempeñando un papel importante al conectar con pacientes para mejorar la adherencia a medicamentos recetados (Krishna et al., 2009). La adaptación de los mensajes de texto específicos de diabetes sigue siendo un área de oportunidad para mejorar la adherencia a la medicación y ofrecer motivación a adultos con diabetes. Sin embargo, se necesita más investigación para entender totalmente su eficacia. Los consejos de texto personalizados han demostrado causar un impacto positivo en la atribución de poder a los pacientes, su autogestión y su adherencia a la prescripción (Gatwood et al., 2014). mHealth se puede utilizar para ofrecer programas de asistencia de autogestión a los pacientes con diabetes y, al mismo tiempo, superar las dificultades técnicas y financieras que supone el tratamiento de la diabetes (Free at al., 2013). El objetivo principal de este trabajo de investigación es demostrar que un marco tecnológico basado en las teorías de cambios de conducta, aplicado al campo de la mHealth, permite una mejora de la adherencia al tratamiento en pacientes diabéticos. Como método de definición de una solución tecnológica, se han adoptado un conjunto de diferentes técnicas de conducta validadas denominado marco de compromiso de retroacción conductual (EBF, por sus siglas en inglés) para formular los mensajes, guiar el contenido y evaluar los resultados. Los estudios incorporan elementos del modelo transteórico (TTM, por sus siglas en inglés), la teoría de la fijación de objetivos (GST, por sus siglas en inglés) y los principios de comunicación sanitaria persuasiva y eficaz. Como concepto general, el modelo TTM ayuda a los pacientes a progresar a su próxima fase de conducta a través de mensajes de texto motivados específicos y permite que el médico identifique la fase actual y adapte sus estrategias individualmente. Además, se adoptan las directrices del TTM para fijar objetivos personalizados a un nivel apropiado a la fase de cambio del paciente. La GST encierra normas que van a ponerse en práctica para promover la intervención educativa y objetivos de pérdida de peso. Finalmente, los principios de comunicación sanitaria persuasiva y eficaz aplicados a la aparición de los mensajes se han puesto en marcha para aumentar la efectividad. El EBF tiene como objetivo ayudar a los pacientes a mejorar su adherencia a la prescripción y encaminarlos a una mejora general en la autogestión de la diabetes mediante mensajes de texto personalizados denominados mensajes de retroacción automáticos (AFM, por sus siglas en inglés). Después de una primera revisión del perfil, consistente en identificar características significativas del paciente basadas en las necesidades de tratamiento, actitudes y conductas de atención sanitaria, el sistema elige los AFM personalizados, los aprueba el médico y al final se transfieren a la interfaz del paciente. Durante el tratamiento, el usuario recopila los datos en dispositivos de monitorización de pacientes (PMD, por sus siglas en inglés) de una serie de dispositivos médicos y registros manuales. Los registros consisten en la toma de medicación, dieta y actividad física y tareas de aprendizaje y control de la medida del metabolismo. El compromiso general del paciente se comprueba al estimar el uso del sistema y la adherencia del tratamiento y el estado de los objetivos del paciente a corto y largo plazo. El módulo de análisis conductual, que consiste en una serie de reglas y ecuaciones, calcula la conducta del paciente. Tras lograr el análisis conductual, el módulo de gestión de AFM actualiza la lista de AFM y la configuración de los envíos. Las actualizaciones incluyen el número, el tipo y la frecuencia de mensajes. Los AFM los revisa periódicamente el médico que también participa en el perfeccionamiento del tratamiento, adaptado a la fase transteórica actual. Los AFM se segmentan en distintas categorías y niveles y los pacientes pueden ajustar la entrega del mensaje de acuerdo con sus necesidades personales. El EBF se ha puesto en marcha integrado dentro del sistema METABO, diseñado para facilitar al paciente diabético que controle sus condiciones relevantes de una manera menos intrusiva. El dispositivo del paciente se vincula en una plataforma móvil, mientras que una interfaz de panel médico permite que los profesionales controlen la evolución del tratamiento. Herramientas específicas posibilitan que los profesionales comprueben la adherencia del paciente y actualicen la gestión de envíos de AFM. El EBF fue probado en un proyecto piloto controlado de manera aleatoria. El principal objetivo era examinar la viabilidad y aceptación del sistema. Los objetivos secundarios eran también la evaluación de la eficacia del sistema en lo referente a la mejora de la adherencia, el control glucémico y la calidad de vida. Se reclutaron participantes de cuatro centros clínicos distintos en Europa. La evaluación del punto de referencia incluía datos demográficos, estado de la diabetes, información del perfil, conocimiento de la diabetes en general, uso de las plataformas TIC, opinión y experiencia con dispositivos electrónicos y adopción de buenas prácticas con la diabetes. La aceptación y eficacia de los criterios de evaluación se aplicaron para valorar el funcionamiento del marco tecnológico. El principal objetivo era la valoración de la eficacia del sistema en lo referente a la mejora de la adherencia. En las pruebas participaron 54 pacientes. 26 fueron asignados al grupo de intervención y equipados con tecnología móvil donde estaba instalado el EBF: 14 pacientes tenían T1DM y 12 tenían T2DM. El grupo de control estaba compuesto por 25 pa cientes que fueron tratados con atención estándar, sin el empleo del EBF. La intervención profesional tanto de los grupos de control como de intervención corrió a cargo de 24 cuidadores, entre los que incluían diabetólogos, nutricionistas y enfermeras. Para evaluar la aceptabilidad del sistema y analizar la satisfacción de los usuarios, a través de LimeSurvey, se creó una encuesta multilingüe tanto para los pacientes como para los profesionales. Los resultados también se recopilaron de los archivos de registro generados en los PMD, el panel médico profesional y las entradas de la base de datos. Los mensajes enviados hacia y desde el EBF y los archivos de registro del sistema y los servicios de comunicación se grabaron durante las cinco semanas del estudio. Se entregaron un total de 2795 mensajes, lo que supuso una media de 107,50 mensajes por paciente. Como se muestra, los mensajes disminuyen con el tiempo, indicando una mejora global de la adherencia al plan de tratamiento. Como se esperaba, los pacientes con T1DM recibieron más consejos a corto plazo, en relación a su estado. Del mismo modo, al ser el centro de T2DM en cambios de estilo de vida sostenible a largo plazo, los pacientes con T2DM recibieron más consejos de recomendación, en cuanto a dietas y actividad física. También se ha llevado a cabo una comparación de la adherencia e índices de uso para pacientes con T1DM y T2DM, entre la primera y la segunda mitad de la prueba. Se han observado resultados favorables para el uso. En lo relativo a la adherencia, los resultados denotaron una mejora general en cada dimensión del plan de tratamiento, como la nutrición y las mediciones de inserción de glucosa en la sangre. Se han llevado a cabo más estudios acerca del cambio a nivel educativo antes y después de la prueba, medidos tanto para grupos de control como de intervención. Los resultados indicaron que el grupo de intervención había mejorado su nivel de conocimientos mientras que el grupo de control mostró una leve disminución. El análisis de correlación entre el nivel de adherencia y las AFM ha mostrado una mejora en la adherencia de uso para los pacientes que recibieron los mensajes de tipo alertas, y unos resultados no significativos aunque positivos relacionados con la adherencia tanto al tratamiento que al uso correlacionado con los recordatorios. Por otra parte, los AFM parecían ayudar a los pacientes que no tomaban suficientemente en serio su tratamiento en el principio y que sí estaban dispuestos a responder a los mensajes recibidos. Aun así, los pacientes que recibieron demasiadas advertencias, comenzaron a considerar el envío de mensajes un poco estresante. El trabajo de investigación llevado a cabo al desarrollar este proyecto ofrece respuestas a las cuatro hipótesis de investigación que fueron la motivación para el trabajo. • Hipótesis 1 : es posible definir una serie de criterios para medir la adherencia en pacientes diabéticos. • Hipótesis 2: es posible diseñar un marco tecnológico basado en los criterios y teorías de cambio de conducta mencionados con anterioridad para hacer que los pacientes diabéticos se comprometan a controlar su enfermedad y adherirse a planes de atención. • Hipótesis 3: es posible poner en marcha el marco tecnológico en el sector de la salud móvil. • Hipótesis 4: es posible utilizar el marco tecnológico como solución de salud móvil en un contexto real y tener efectos positivos en lo referente a indicadores de control de diabetes. La verificación de cada hipótesis permite ofrecer respuesta a la hipótesis principal: La hipótesis principal es: es posible mejorar la adherencia diabética a través de un marco tecnológico mHealth basado en teorías de cambio de conducta. El trabajo llevado a cabo para responder estas preguntas se explica en este trabajo de investigación. El marco fue desarrollado y puesto en práctica en el Proyecto METABO. METABO es un Proyecto I+D, cofinanciado por la Comisión Europea (METABO 2008) que integra infraestructura móvil para ayudar al control, gestión y tratamiento de los pacientes con diabetes mellitus de tipo 1 (T1DM) y los que padecen diabetes mellitus de tipo 2 (T2DM). ABSTRACT Worldwide there is an exponential growth in the incidence of Chronic Diseases (CDs), such as: hypertension, cardiovascular and respiratory diseases, as well as diabetes mellitus, leading to rising numbers of deaths worldwide (Beaglehole et al. 2008). In particular, the prevalence of diabetes mellitus (DM) is largely increasing among all ages and constitutes a major worldwide health problem. Diabetes was directly responsible for 1,5 million deaths in 2012 and 89 million Disability-adjusted life year (DALYs) (WHO 2014). One of the key dilemmas often associated to CD management is the patients’ adherence to treatments, representing a multi-factorial aspect that requires support in terms of: education, self-management, interaction between patients and caregivers, and patients’ engagement. Measuring adherence is complex and, even if widely discussed, there are still no “gold” standards ((Giardini et al. 2015), (Costa et al. 2015). Patient’s engagement, through participation, collaboration, negotiation, and sometimes compromise, enhance opportunities for optimal therapy in which patients take responsibility for their part of the adherence equation. Engaging and involving diabetic patients in treatment decisions, along with professional expertise, can help foster a patient-centered approach to diabetes care (Martin et al. 2005). Patients’ motivation and empowerment are perhaps the two most relevant intervening factors that directly affect self-management of diabetes care. It has been demonstrated that these two factors play an essential role in prescription adherence, as well as for the successful encouragement of a healthy life-style and other behavioural changes (Heneghan et al. 2013). A personalised education plan is indispensable in order to provide the patient with the appropriate tools needed for the effective self-management of the disease (El-Gayar et al. 2013). Effective communication is at the core of providing patient-centred care since it influences behaviours and attitudes towards a health problem (Frampton et al. 2008). In this regard, interactivity, frequency, timing, and tailoring of text messages may promote adherence to a medication regimen. As a consequence, tailoring text messages to patients can constitute a way of making suggestions and information more relevant and effective (Nundy et al. 2013). In this context, mobile health technologies (mHealth) are playing significant roles in improving adherence to prescribed medications (Krishna et al. 2009). The tailoring of diabetes-specific text messages remains an area of opportunity to improve medication adherence and provide motivation to adults with diabetes but further research is needed to fully understand their effectiveness. Personalized text advices have proven to produce a positive impact on patients’ empowerment, self-management, and adherence to prescriptions (Gatwood et al. 2014). mHealth can be used for offering self-management support programs to diabetes patients and at the same time surmounting the technical and financial difficulties involved in diabetes treatment (Free et al. 2013). The main objective of this research work is to demonstrate that a technological framework, based on behavioural change theories, applied to mHealth domain, allows improving adherence treatment in diabetic patients. The framework, named Engagement Behavioural Feedback Framework (EBF), is built on top of validated behavioural techniques to frame messages, guide the definition of contents and assess outcomes: elements from the Transtheoretical Model (TTM), the Goal-Setting Theory (GST), Effective Health Communication (EHC) guidelines and Principles of Persuasive Technology (PPT) were incorporated. The TTM helps patients to progress to a next behavioural stage, through specific motivated text messages, and allow clinician’s identifying the current stage and tailor its strategies individually. Moreover, TTM guidelines are adopted to set customised goals at a level appropriate to the patient’s stage of change. The GST was used to build rules to be applied for enhancing educational intervention and weight loss objectives. Finally, the EHC guidelines and the PPT were applied to increase the effectiveness of messages. The EBF aims to support patients on improving their prescription adherence and persuade them towards a general improvement in diabetes self-management, by means of personalised text messages, named Automatic Feedback Messages (AFM). After a first profile screening, consisting in identifying meaningful patient characteristics based on treatment needs, attitudes and health care behaviours, customised AFMs are selected by the system, approved by the professional, and finally transferred into the patient interface. During the treatment, the user collects the data into a Patient Monitoring Device (PMD) from a set of medical devices and from manual inputs. Inputs consist in medication intake, diet and physical activity, metabolic measurement monitoring and learning tasks. Patient general engagement is checked by estimating the usage of the system and the adherence of treatment and patient goals status in the short and the long term period. The Behavioural Analysis Module, consisting in a set of rules and equations, calculates the patient’s behaviour. After behavioural analysis is accomplished, the AFM library and the dispatch setting are updated by the AFM Manager module. Updates include the number, the type and the frequency of messages. The AFMs are periodically supervised by the professional who also participates to the refinement of the treatment, adapted to the current transtheoretical stage. The AFMs are segmented in different categories and levels and patients can adjust message delivery in accordance with their personal needs. The EBF was integrated to the METABO system, designed to facilitate diabetic patients in managing their disease in a less intrusive approach. Patient device corresponds in a mobile platform, while a medical panel interface allows professionals to monitoring the treatment evolution. Specific tools allow professional to check patient adherence and to update the AFMs dispatch management. The EBF was tested in a randomised controlled pilot. The main objective was to examine the feasibility and acceptance of the system. Secondary objectives were also the assessment of the effectiveness of system in terms of adherence improvement, glycaemic control, and quality of life. Participants were recruited from four different clinical centres in Europe. The baseline assessment included demographics, diabetes status, profile information, knowledge about diabetes in general, usage of ICT platforms, opinion and experience about electronic devices and adoption of good practices with diabetes. Acceptance and the effectiveness evaluation criteria were applied to evaluate the performance of the technological framework. The main objective was the assessment of the effectiveness of system in terms of adherence improvement. Fifty-four patients participated on the trials. Twenty-six patients were assigned in the intervention group and equipped with mobile where the EBF was installed: 14 patients were T1DM and 12 were T2DM. The control group was composed of 25 patients that were treated through a standard care, without the usage of the EBF. Professional’s intervention for both intervention and control groups was carried out by 24 care providers, including endocrinologists, nutritionists, and nurses. In order to evaluate the system acceptability and analyse the users’ satisfaction, an online multi-language survey, using LimeSurvey, was produced for both patients and professionals. Results were also collected from the log-files generated in the PMDs, the professional medical panel and the entries of the data base. The messages sent to and from the EBF and the log-files of the system and communication services were recorded over 5 weeks of the study. A total of 2795 messages were submitted, representing an average of 107,50 messages per patient. As demonstrated, messages decrease over time indicating an overall improvement of the care plan’s adherence. As expected, T1DM patients were more loaded with short-term advices, in accordance with their condition. Similarly, being the focus of T2DM on long-term sustainable lifestyle changes, T2DM received more reminders advices, as for diet and physical activity. Favourable outcomes were observed for treatment and usage adherences of the intervention group: for both the adherence indices, results denoted a general improvement on each care plan’s dimension, such as on nutrition and blood glucose input measurements. Further studies were conducted on the change on educational level before and after the trial, measured for both control and intervention groups. The outcomes indicated the intervention group has improved its level of knowledge, while the control group denoted a low decrease. The correlation analysis between the level of adherences and the AFMs showed an improvement in usage adherence for patients who received warnings message, while non-significantly yet even positive indicators related to both treatment and usage adherence correlated with the Reminders. Moreover, the AFMs seemed to help those patients who did not take their treatment seriously enough in the beginning and who were willing to respond to the messages they received. Even though, patients who received too many Warnings, started to consider the message dispatch to be a bit stressful. The research work carried out in developing this research work provides responses to the four research hypothesis that were the motivation for the work: •Hypothesis 1: It is possible to define a set of criteria to measure adherence in diabetic patients. •Hypothesis 2: It is possible to design a technological framework, based on the aforementioned criteria and behavioural change theories, to engage diabetic patients in managing their disease and adhere to care plans. •Hypothesis 3: It is possible to implement the technological framework in the mobile health domain. •Hypothesis 4: It is possible to use the technological framework as a mobile health solution in a real context and have positive effects in terms of diabetes management indicators. The verification of each hypothesis allowed us to provide a response to the main hypothesis: The Main Hypothesis is: It is possible to improve diabetic adherence through a mHealth technological framework based on behavioural change theories. The work carried out to answer these questions is explained in this research work. The framework was developed and applied in the METABO project. METABO is an R&D project, co-funded by the European Commission (METABO 2008) that integrates mobile infrastructure for supporting the monitoring, management, and treatment of type 1 diabetes mellitus (T1DM) and type 2 diabetes mellitus (T2DM) patients.

Therapeutic education, the premise of adherence to the type 2 diabetes therapeutic regimen

Background: type 2 diabetes mellitus includes changes in lifestyle in its etiology of prevention, but the evidence is clear —even when people know what to do and what they want to do, they simply do not adopt adherence behaviors. Structured education will allow improving not only metabolic control, but also the adjustment process to a new situation of disease, as well as to develop the patient’s skills in order to make him the key manager of his illness. Objectives: To determine patients’ adherence to prescribed therapeutic regimens. Material and methods: Quantitative, cross-sectional, non-experimental, descriptive, correlational study, with a sample of 102 people with type 2 diabetes, aged between 40 and 85 years old, mostly male (51.96%). The evaluation protocol included social-demographic and clinical questionnaire, Diabetes Self-care Scale and a questionnaire on Diabetes’ knowledge. We also used HbA1c in order to directly assess adherence. Results: It appears that there is no statistically signiicant correlation between socio-demographic variables such as gender and age and adherence. Variables, such as blood glucose monitoring, speciic diet compliance and knowledge, reveal a statistically signiicant effect on adherence (P < .05). Conclusion: The evidence is clear on the urgent need to recognize the importance of measuring patient adherence to a diabetes treatment plan for the maintenance of glycaemic control. We suggest the reinforcement of educational programs in people with type 2 diabetes so as to improve adherence to self-care.