Abstract. Chronic illnesses cause considerable burden in quality of life, often leading to physical, psychological, and social dysfunctioning of the sufferers and their family. There is a growing need for flexible provision of home-based psychological services to increase reach even for traditionally underserved chronic illness sufferer populations. Digital interventions can fulfill this role and provide a range of psychological services to improve functioning. Despite the potential of digital interventions, concerns remain regarding users’ engagement, as low engagement is associated with low adherence rates, high attrition, and suboptimal exposure to the intervention. Human–computer interaction (e.g., theoretical models of persuasive system design, gamification, tailoring, and supportive accountability) and user characteristics (e.g., gender, age, computer literacy) are the main identified culprits contributing to engagement and adherence difficulties. To date, there have not been any clear and concise recommendations for improved utilization and engagement in digital interventions. This paper provides an overview of user engagement factors and proposes research informed recommendations for engagement and adherence planning in digital intervention development. The recommendations were derived from the literature and consensualized by expert members of the European Federation of Psychology Associations, Psychology and Health Standing Committee, and e-Health Task Force. These recommendations serve as a starting point for researchers and clinicians interested in the digitalized health field and promote effective planning for engagement when developing digital interventions with the potential to maximize adherence and optimal exposure in the treatment of chronic health conditions.

The Chronic Pain Acceptance Questionnaire (CPAQ) is a measure of pain acceptance comprised of pain willingness (PW) and activity engagement (AE; McCracken et al., 2004). Concerns about the factorial structure of the CPAQ exist, as it is not yet clear whether PW and AE constitute 2 independent constructs or 1, pain acceptance. Concerns also exist about the internal and predictive validity of test score interpretations of this measure. This study also presents that the choice of predictor variables has contributed to theoretical confusion regarding the impact of pain acceptance on pain-related adjustment. The purpose of this study was: (a) to examine the psychometric properties of both the long (20 items) and short (8 items) versions of the Greek-Chronic Pain Acceptance Questionnaire (G-CPAQ); (b) to examine the utility of a 2-factor solution in predicting psychosocial adjustment to pain using confirmatory factor analysis; and (c) to explore the mediating effects of pain acceptance and cognitive defusion, comprising the "open" response style to pain, between pain interference and pain related outcomes. One hundred and sixty chronic pain patients completed a questionnaire packet including pain indexes, pain acceptance, cognitive fusion, avoidance, and emotional distress. Confirmatory factor analyses supported the 2-factor solution, though a general good model fit was achieved only for the short G-CPAQ version. Structural equation modeling showed that PW and AE coupled with cognitive defusion partially mediated the influence of pain interference on pain severity, emotional distress, and avoidance of pain. (PsycINFO Database Record

The findings indicate that EA is not a generalised negative response to highly aversive conditions, at least as far as the factors examined in this study are concerned. EA may rather reflect a coping reaction, the impact of which depends on its specific interactions with the other aspects of the self-regulation mechanism. At least in chronic pain, EA should become the focus of potential intervention only when its interaction with the illness-related self-regulation mechanism results in negative outcomes.

The success of acceptance and commitment therapy (ACT) in improving life functioning among chronic pain patients is followed by an interest in investigating mechanisms of action via which it unfolds and validating measures to assess its key constructs. The Psychological Inflexibility in Pain Scale (PIPS-II) assesses pain avoidance and fusion. This is the first study to examine the measurement models of this instrument’s Greek adaptation (G-PIPS-II) in patients with different pain localizations (i.e., chronic and headache). A community heterogeneous sample of chronic pain sufferers (N = 156) and two clinical samples comprising treatment-seeking chronic pain patients (N = 149) and treatment-seeking headache patients (N = 89) were recruited from nongovernmental chronic pain support organizations and primary care centers. Exploratory and confirmatory factor analyses demonstrated an acceptable model fit of the G-PIPS-II yielding a two-factor model: avoidance (8 items) and cognitive fusion (4 items). Moderate to high correlations with theoretically related measures supported its construct validity; reliability was high for the total scale and the Avoidance subscale and medium for the Cognitive Fusion subscale. Weak measurement invariance was established across the three pain groups, suggesting that regardless of pain localization, chronic pain and headache patients understand the two latent factors in a similar way. G-PIPS-II is a psychometrically sound instrument assessing two constructs targeted for change within ACT and is deemed a conceptually meaningful scale with items having similar meanings for patients with different pain localization.

Background Medication nonadherence of patients with chronic conditions is a complex phenomenon contributing to increased economic burden and decreased quality of life. Intervention development relies on accurately assessing adherence but no “gold standard” method currently exists. Purpose The present scoping review aimed to: (a) review and describe current methods of assessing medication adherence (MA) in patients with chronic conditions with the highest nonadherence rates (asthma, cancer, diabetes, epilepsy, HIV/AIDS, hypertension), (b) outline and compare the evidence on the quality indicators between assessment methods (e.g., sensitivity), and (c) provide evidence-based recommendations. Methods PubMed, PsycINFO and Scopus databases were screened, resulting in 62,592 studies of which 71 met criteria and were included. Results Twenty-seven self-report and 10 nonself-report measures were identified. The Medication Adherence Report Scale (MARS-5) was found to be the most accurate self-report, whereas electronic monitoring devices such as Medication Event Monitoring System (MEMS) corresponded to the most accurate nonself-report. Higher MA rates were reported when assessed using self-reports compared to nonself-reports, except from pill counts. Conclusions Professionals are advised to use a combination of self-report (like MARS-5) and nonself-report measures (like MEMS) as these were found to be the most accurate and reliable measures. This is the first review examining self and nonself-report methods for MA, across chronic conditions with the highest nonadherence rates and provides evidence-based recommendations. It highlights that MA assessment methods are understudied in certain conditions, like epilepsy. Before selecting a MA measure, professionals are advised to inspect its quality indicators. Feasibility of measures should be explored in future studies as there is presently a lack of evidence.