Applying a complexity lens to policy implementation: how feedback loops help to understand systems change in integrated healthcare

2025 · doi:10.22541/au.174166396.67458933/v1
preprint OA: closed
Full text JSON View at publisher
⚙ AI-generated summary by claude@2026-07, 2026-07-05 ⓘ

This paper uses a complexity lens to examine policy implementation in integrated healthcare, demonstrating how feedback loops can illuminate the mechanisms of systems change.

One-sentence paraphrase of the abstract; not a substitute for reading it. No clinical advice. How this works

⚙ AI-generated deep summary by claude@2026-07, 2026-07-05 · read from full text ⓘ

This preprint applies a complexity theory lens to policy implementation, using a UK case study of “Future in Mind” to improve children’s access to mental health services in a northern England municipality. The authors re-analysed interview data from 31 stakeholders across local government, the NHS, schools, and the voluntary/community sector, coding the transcripts in NVivo12 using sensitising constructs such as adaptation, feedback, emergence, and co-evolution. They identified five feedback loops—two positive (flexing the training offer; non-specialist staff gaining skills and changing behavior) and three negative (short termism, free rider behavior, and professional boundaries)—which together supported system-level emergence and cross-system co-evolution through shared values and language between schools and the NHS. A major caveat noted is that the work is a preprint without peer review and may involve preliminary data, and it focuses on integrated healthcare policy implementation rather than direct biomedical outcomes. The paper does not explicitly discuss endometriosis or adenomyosis; it was included in the corpus via a keyword match in the upstream search index.

Read from the paper's body, not the abstract. Not a substitute for reading the paper. No clinical advice. How this works

Abstract

Abstract Background: Although a complexity theory lens can help to understand national policy implementation at a local government level, application of this lens often remains metaphorical. We illustrate how complexity concepts (adaptation, feedback, emergence and co-evolution) can be used practically in research on policy implementation using a UK case study (Future in Mind; FiM), aimed at improving children’s access to mental health services in a municipality in northern England. Methods: We re-analysed interview data with staff from local government, the National Health Service, schools, and the voluntary and community sector (n=31) involved in implementing FiM and coded this data in NVivo12 using complexity concepts as sensitising constructs. Findings: We identified 5 feedback loops: two positives (1. flexing the training offer; 2. new skills, knowledge and behaviour by non-specialist staff) and three negatives (3. short termism, 4. free rider behaviour, 5. professional boundaries). These loops energised local adaptations of FiM by school and NHS staff, leading to system-level change (emergence), with the school system becoming more responsive to the mental wellbeing needs of children and young people, and shifts across systems (co-evolution), by developing joint values and language between schools and NHS. Conclusions: We demonstrate the importance of positive and negative feedback loops for evidencing system-level change and shifts across systems. Our findings provide new insights into unintended consequences of policy implementation and starting positions for implementers to utilise feedback for generating impact. We argue for blurring of boundaries between implementation and evaluation in policy research to optimise the use of feedback.
Full text 2,915 characters · extracted from oa-doi-fallback · 2 sections · click to expand

Abstract

Abstract Background Although a complexity theory lens can help to understand national policy implementation at a local government level, application of this lens often remains metaphorical. We illustrate how complexity concepts (adaptation, feedback, emergence and co-evolution) can be used practically in research on policy implementation using a UK case study (Future in Mind; FiM), aimed at improving children’s access to mental health services in a municipality in northern England. Methods We re-analysed interview data with staff from local government, the National Health Service, schools, and the voluntary and community sector (n=31) involved in implementing FiM and coded this data in NVivo12 using complexity concepts as sensitising constructs. Findings We identified 5 feedback loops: two positives (1. flexing the training offer; 2. new skills, knowledge and behaviour by non-specialist staff) and three negatives (3. short termism, 4. free rider behaviour, 5. professional boundaries). These loops energised local adaptations of FiM by school and NHS staff, leading to system-level change (emergence), with the school system becoming more responsive to the mental wellbeing needs of children and young people, and shifts across systems (co-evolution), by developing joint values and language between schools and NHS. Conclusions We demonstrate the importance of positive and negative feedback loops for evidencing system-level change and shifts across systems. Our findings provide new insights into unintended consequences of policy implementation and starting positions for implementers to utilise feedback for generating impact. We argue for blurring of boundaries between implementation and evaluation in policy research to optimise the use of feedback. Supplementary Material File (ijhpm - sdg 3 good health and wellbeing.docx) - Download - 86.52 KB Information & Authors Information Version history Copyright This work is licensed under a Non Exclusive No Reuse License.

Keywords

Authors Metrics & Citations Metrics Article Usage 248views 134downloads Citations Download citation Andrew Passey, Peter van der Graaf. Applying a complexity lens to policy implementation: how feedback loops help to understand systems change in integrated healthcare. Authorea. 11 March 2025. DOI: https://doi.org/10.22541/au.174166396.67458933/v1 DOI: https://doi.org/10.22541/au.174166396.67458933/v1 If you have the appropriate software installed, you can download article citation data to the citation manager of your choice. Simply select your manager software from the list below and click Download. For more information or tips please see 'Downloading to a citation manager' in the Help menu.

Text is read by the "Ask this paper" AI Q&A widget below. Extraction quality varies by source — PMC NXML preserves structure cleanly, OA-HTML may include some navigation residue, and OA-PDF can have broken hyphenation. The publisher copy (via DOI) is the canonical version.

My notes (saved in your browser only)

⚙ Ask this paper AI returns verbatim quotes from the full text · source: oa-doi-fallback ⓘ

Answers must be backed by verbatim quotes from this paper's full text. Hallucinated quotes are dropped automatically; if no verbatim passage answers the question, we say so. How this works

Citation neighborhood (no data yet)

We don't have any in-corpus citations linked to this paper yet. This is a recent paper (2025) — citers typically take a year or two to land, and the OpenAlex reference graph may still be filling in.

Source provenance

europepmc
last seen: 2026-05-20T01:45:00.602351+00:00