Logic models are commonly used in evaluations to represent the causal processes through which interventions produce outcomes, yet significant debate is currently taking place over whether they can describe complex interventions which adapt to context. This paper assesses the logic models used in healthcare research from a complexity perspective. A typology of existing logic models is proposed, as well as a formal methodology for deriving more flexible and dynamic logic models. Various logic model types were tested as part of an evaluation of a complex Patient Experience Toolkit (PET) intervention, developed and implemented through action research across six hospital wards/departments in the English NHS. Three dominant types of logic model were identified, each with certain strengths but ultimately unable to accurately capture the dynamics of PET. Hence, a fourth logic model type was developed to express how success hinges on the adaption of PET to its delivery settings. Aspects of the Promoting Action on Research Implementation in Health Services (PARIHS) model were incorporated into a traditional logic model structure to create a dynamic “type 4” logic model that can accommodate complex interventions taking on a different form in different settings. Logic models can be used to model complex interventions that adapt to context but more flexible and dynamic models are required. An implication of this is that how logic models are used in healthcare research may have to change. Using logic models to forge consensus among stakeholders and/or provide precise guidance across different settings will be inappropriate in the case of complex interventions that adapt to context. Instead, logic models for complex interventions may be targeted at facilitators to enable them to prospectively assess the settings they will be working in and to develop context-sensitive facilitation strategies. Researchers should be clear as to why they are using a logic model and experiment with different models to ensure they have the correct type.

Background: In October 2022, it was estimated 2.3 million people in the United Kingdom have self‐reported Long Covid (LC). Many people have reported not receiving adequate healthcare support. There is a lack of research which provides an in‐depth exploration of the barriers faced by people with LC in accessing healthcare support. It is important to understand these barriers to provide better support, care and advice for those experiencing LC.Objective: To understand the barriers faced in accessing primary, secondary and specialist healthcare support for people with LC.Design and Participation: 40 interviews were conducted with people living with LC in Bradford alongside 12 interviews with healthcare professionals (HCPs) providing LC support in Bradford healthcare settings. Interviews were analysed using reflexive thematic analysis.Results: People living with LC had a large degree of difficulty in accessing healthcare services for LC support. We categorized the healthcare access experiences of participants into five main types: (1) being unable to access primary care, (2) accessing primary care but receiving (perceived) inadequate support, (3) extreme persistence, (4) alternatives to mainstream health care and (5) positive experiences. There was a severe lack of access to specialist LC services. Ethnic minority participants faced a further barrier of mistrust and fear of services deterring them from accessing support. HCPs discussed systemic barriers to delivering services. Experiences were embedded in macrostructural issues further exacerbated by the pandemic.Conclusion: To better support people with LC, the barriers faced in accessing healthcare support must be addressed. Of significance, improvements to general practitioner access are required; especially as GPs are the first line of support for people living with LC.Patient and Public Involvement: A patient and public involvement group is engaged at regular intervals in the project.

Patients are increasingly being asked for feedback about their healthcare experiences. However, healthcare staff often find it difficult to act on this feedback in order to make improvements to services. This paper draws upon notions of legitimacy and readiness to develop a conceptual framework (Patient Feedback Response Framework - PFRF) which outlines why staff may find it problematic to respond to patient feedback. A large qualitative study was conducted with 17 ward based teams between 2013 and 2014, across three hospital Trusts in the North of England. This was a process evaluation of a wider study where ward staff were encouraged to make action plans based on patient feedback. We focus on three methods here: i) examination of taped discussion between ward staff during action planning meetings ii) facilitators notes of these meetings iii) telephone interviews with staff focusing on whether action plans had been achieved six months later. Analysis employed an abductive approach. Through the development of the PFRF, we found that making changes based on patient feedback is a complex multi-tiered process and not something that ward staff can simply 'do'. First, staff must exhibit normative legitimacy - the belief that listening to patients is a worthwhile exercise. Second, structural legitimacy has to be in place - ward teams need adequate autonomy, ownership and resource to enact change. Some ward teams are able to make improvements within their immediate control and environment. Third, for those staff who require interdepartmental co-operation or high level assistance to achieve change, organisational readiness must exist at the level of the hospital otherwise improvement will rarely be enacted. Case studies drawn from our empirical data demonstrate the above. It is only when appropriate levels of individual and organisational capacity to change exist, that patient feedback is likely to be acted upon to improve services.

Background Teamwork and communication are recognised as key contributors to safe and high-quality patient care. Interventions targeting process and relational aspects of care may therefore provide patient safety solutions that reflect the complex nature of healthcare. Team reflexivity is one such approach with the potential to support improvements in communication and teamwork, where reflexivity is defined as the ability to pay critical attention to individual and team practices with reference to social and contextual information. Objective To systematically review articles that describe the use of team reflexivity in interprofessional hospital-based healthcare teams. Methods Following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines, six electronic databases were searched to identify literature investigating the use of team reflexivity in interprofessional hospital-based healthcare teams. The review includes articles investigating the use of team reflexivity to improve teamwork and communication in any naturally occurring hospital-based healthcare teams. Articles’ eligibility was validated by two second reviewers (5%). Results Fifteen empirical articles were included in the review. Simulation training and video-reflexive ethnography (VRE) were the most commonly used forms of team reflexivity. Included articles focused on the use of reflexive interventions to improve teamwork and communication within interprofessional healthcare teams. Communication during interprofessional teamworking was the most prominent focus of improvement methods. The nature of this review only allows assessment of team reflexivity as an activity embedded within specific methods. Poorly defined methodological information relating to reflexivity in the reviewed studies made it difficult to draw conclusive evidence about the impact of reflexivity alone. Conclusion The reviewed literature suggests that VRE is well placed to provide more locally appropriate solutions to contributory patient safety factors, ranging from individual and social learning to improvements in practices and systems. Trial registration number CRD42017055602.

Longitudinal qualitative research is starting to be used in applied health research, having been popular in social research for several decades. There is potential for a large volume of complex data to be captured, over a span of months or years across several different methods. How to analyse this volume of data – with its inherent complexity - represents a problem for health researchers. There is a previous dearth of methodological literature which describes an appropriate analytic process which can be readily employed. We document a worked example of the Pen Portrait analytic process, using the qualitative dataset for which the process was originally developed. Pen Portraits are recommended as a way in which longitudinal health research data can be concentrated into a focused account. The four stages of undertaking a pen portrait are: 1) understand and define what to focus on 2) design a basic structure 3) populate the content 4) interpretation. Instructive commentary and guidance is given throughout with consistent reference to the original study for which Pen Portraits were devised. The Pen Portrait analytic process was developed by the authors, borne out of a need to effectively integrate multiple qualitative methods collected over time. Pen Portraits are intended to be adaptable and flexible, in order to meet the differing analytic needs of qualitative longitudinal health studies. The Pen Portrait analytic process provides a useful framework to enable researchers to conduct a robust analysis of multiple sources of qualitative data collected over time.

Context: Collecting feedback from patients about their experiences of health care is an important activity. However, improvement based on this feedback rarely materializes. In this study, we focus on answering the question—“what is impeding the use of patient experience feedback?”Methods: We conducted a qualitative study in 2016 across three NHS hospital Trusts in the North of England. Focus groups were undertaken with ward‐based staff, and hospital managers were interviewed in‐depth (50 participants). We conducted a conceptual‐level analysis.Findings: On a macro level, we found that the intense focus on the collection of patient experience feedback has developed into its own self‐perpetuating industry with a significant allocation of resource, effort and time being expended on this task. This is often at the expense of pan‐organizational learning or improvements being made. On a micro level, ward staff struggled to interact with feedback due to its complexity with questions raised about the value, validity and timeliness of data sources.Conclusions: Macro and micro prohibiting factors come together in a perfect storm which provides a substantial impediment to improvements being made. Recommendations for policy change are put forward alongside recognition that high‐level organizational culture/systems are currently too sluggish to allow fruitful learning and action to occur from the feedback that patients give.