Supporting Pain Self-Management in Patients With Cancer: App Development Based on a Theoretical and Evidence-Driven Approach.

BACKGROUND: To inform the development of an intervention, it is essential to have a well-developed theoretical understanding of how an intervention causes change, as stated in the UK Medical Research Council guidelines for developing complex interventions. Theoretical foundations are often ignored in the development of mobile health apps intended to support pain self-management for patients with cancer. OBJECTIVE: This study aims to systematically set a theory- and evidence-driven design for a pain self-management app and specify the app's active features. METHODS: The Behavior Change Wheel (BCW) framework, a step-by-step theoretical approach to the development of interventions, was adopted to achieve the aim of this study. This started by understanding and identifying sources of behavior that could be targeted to support better pain management. Ultimately, the application of the BCW framework guided the identification of the active contents of the app, which were characterized using the Behavior Change Technique Taxonomy version 1. RESULTS: The theoretical analysis revealed that patients may have deficits in their capability, opportunity, and motivation that prevent them from performing pain self-management. The app needs to use education, persuasion, training, and enablement intervention functions because, based on the analysis, they were found the most likely to address the specified factors. Eighteen behavior change techniques were selected to describe precisely how the intervention functions can be presented to induce the desired change regarding the intervention context. In other words, they were selected to form the active contents of the app, potentially reducing barriers and serving to support patients in the self-management of pain while using the app. CONCLUSIONS: This study fully reports the design and development of a pain self-management app underpinned by theory and evidence and intended for patients with cancer. It provides a model example of the BCW framework application for health app development. The work presented in this study is the first systematic theory- and evidence-driven design for a pain app for patients with cancer. This systematic approach can support clarity in evaluating the intervention's underlying mechanisms and support future replication.

Preferences of Patients With Musculoskeletal Disorders Regarding the Timing and Channel of eHealth and Factors Influencing Its Use: Mixed Methods Study.

BACKGROUND: Implementation of eHealth is progressing slowly. In-depth insight into patients' preferences and needs regarding eHealth might improve its use. OBJECTIVE: This study aimed to describe when patients want to use eHealth, how patients want to communicate and receive information digitally, and what factors influence the use of eHealth in clinical practice. METHODS: A multimethod study was conducted. Two meetings of ~5.5 hours with plenary information sessions and focus groups were held with 22 patients from the rheumatology, orthopedics, and rehabilitation departments of a Dutch hospital specialized in musculoskeletal disorders. Assignments were performed during the focus groups in which qualitative (eg, semistructured interview questions) and quantitative (ie, voting and ranking factors) data were collected. RESULTS: The way patients want to use eHealth varies between patients and moments of a patient's care pathway. Patients' digital channel preferences depended on the need for interaction with a health care provider (HCP). The interaction need is in turn influenced by the degree to which information or communication is specific to an individual patient and leads to consequences for the patient. The 5 most important factors influencing the use of eHealth were access to medical information (eg, electronic health records), perceived control over disease management, correctness and completeness of information, data security, and access to information or an HCP at any time. The 5 least important factors influencing eHealth use were help with using digital devices, having internet or equipment, digital skills, attitude or emotions toward eHealth, and societal benefits. CONCLUSIONS: Patients identified opportunities for using eHealth during all moments of their care pathway. However, preferences for eHealth varied between patients and phases in the care pathway. As a consequence, eHealth should be tailored to fit individual patients' preferences but also the need for interaction regarding different topics by offering a variety of digital channels with a gradient of interaction possibilities. Furthermore, digital skills and access to the internet might become less important to focus on in the future. Improving eHealth use by patients may be achieved by providing patients access to correct and safe (medical) information and more control over their care.

Identification of factors associated with fear of hypoglycemia using the capability, opportunity, motivation and behavior model in people with type 2 diabetes mellitus: a cross-sectional study.

AIMS: To examined the relationship between fear of hypoglycemia and certain variables in people with type 2 diabetes mellitus (T2DM) based on the Capability, Opportunity, Motivation, and Behavior model, combined with the context unique to people with diabetes to provide a basis for developing targeted nursing interventions. METHODS: In this cross-sectional study, 212 people with T2DM were recruited from February 2021 to July 2021. Data were collected using the Hypoglycaemia Fear Survey, Gold score, Patient Assessment of Chronic Illness Care (PACIC) scale and Diabetic Self-Management Attitudes Scale. Multiple linear regression analysis was performed to determine the predictors of fear of hypoglycemia using SPSS 26.0. RESULTS: The mean fear of hypoglycemia score was 74.88 ± 18.28 (range: 37.00-132.00). In people with T2DM, the frequency of blood glucose monitoring, the frequency of hypoglycemia in the past half-year, degree of understanding of hypoglycemia, impaired awareness of hypoglycemia, PACIC, and self-management attitude of diabetes were the influencing factors of fear of hypoglycemia (adjusted R2 = 0.560, F[21,190] = 13.800, P < 0.001). These variables explained 56.0% of the variance in the fear of hypoglycemia. CONCLUSIONS: The level of fear of hypoglycemia in people with T2DM was relatively high. In addition to paying attention to the disease characteristics of people with T2DM, medical staff should also pay attention to patients' own perception and handling ability of disease and hypoglycemia, attitude toward self-management behavior and external environment support, all of which have a positive effect on improving the fear of hypoglycemia in people with T2DM, optimizing the self-management level and improving quality of life.