Self‐management interventions: Using an occupational lens to rethink and refocus
Bibliographic record
Abstract
‘Self-management relates to the tasks that an individual does to live well with one or more chronic conditions. These tasks include gaining confidence to deal with medical management role management and emotional management’ (Adams, Greiner, & Corrigan, 2004, p. 57, as cited in BC Ministry of Health, 2011). In most countries, provision of self-management programs (the interface between providers and clients) began with the adoption of the Chronic Disease Self-management Program (known in the UK as the Expert Patient Program, and in each Australian State with a different name), an eight week group program run by certified lay leaders. Policy makers adopted the program, usually targeting people with cardiovascular diseases, diabetes, chronic respiratory disease and asthma: conditions with high public burden and in which symptom monitoring and lifestyle management have the potential to change the course and trajectory of the condition. Evidence began to amass indicating positive impacts on quality of life, health utilisation and health outcomes. The understanding that ‘one size does not fit all’ led to proliferation of group programs and alternate format programs such as telephone coaching and online programs. Training programs emerged for lay leaders and health providers. More recently, it has become clear that supporting people to self-management is an ongoing process, not a one-time intervention. Health providers throughout the system are being expected to acquire self-management support competencies to work in partnership with clients and to support their active participation in care and management of their condition(s). Health-care provider education is also changing to embed these competencies in curricula (Pols et al., 2009). Today, chronic disease self-management interventions are increasingly being proposed and included in the care of people with conditions such as brain injury, stroke, mental health, HIV-Aids and cancer. With the course and trajectory of these conditions less significantly altered by lifestyle risk factor modification and/or day to day medication monitoring and management, practitioners are wise to ask whether current interventions will yield the same results. A critical look at the (i) content (ii) delivery and (iii) outcomes of self-management interventions using an occupation and client-centred lens suggests interventions for these new client groups may need to be refocused. Although confusion exists as to exactly what constitutes a self-management intervention and what self-management support competencies are, self-management viewed from a client perspective, is in fact, consistently defined across authors, settings and populations with almost all definitions directly or indirectly referring to the pivotal work of Corbin and Strauss (1988). Their qualitative studies described three forms of ‘work’ people undertaken when living with a chronic condition; these forms of work are now most often referred to as medical, role and emotional management. Most definitions also articulate that knowledge, skills and confidence are part of the self-management toolkit (Adams, Greiner & Corrigan, p. 57, as cited in BC Ministry of Health, 2011). Given this consensus, self-management interventions, then, are those that support individuals to develop knowledge, skills and confidence to manage some or all aspects of medical, role and/or emotional management. A critical review of self-management interventions is revealing; content of the vast majority of interventions focuses on assisting participants with medical management only (i.e. reducing lifestyle risk factors through exercise, diet, smoking cessation; self-monitoring of symptoms/medication; and/or treatment adherence). Less obvious and less numerous are interventions with content designed to assist people with role and/or emotional management; i.e. to maintain meaningful participation and occupational engagement. Outcomes measured are, not surprisingly, aligned with the content and focus on health outcomes (blood glucose levels, pain, number of asthma attacks), health utilisation (visits to emergency) and sometimes quality of life. While depression is often measured, almost never is participation in desired roles the expected or measured outcome (Augustine, Roberts & Packer, 2011). Some of the notable exceptions are interventions developed and tested by occupational therapists which focus on role and emotional management and measure participation (Ghahari & Packer, 2012; Girdler, Boldy, Dhaliwal, Crowley & Packer, 2010; Guidetti, Andersson, Andersson, Tham & Von Koch, 2010; O'Toole, Connolly & Smith, 2012). It is now clear that acquiring knowledge, skills and confidence to self-manage does not occur through education alone (Bodenheimer, Lorig, Holman & Grurnbach, 2002). Skills such as problem solving, decision making and action planning are useful tools. Features of interventions that assist people to embed these in everyday life are validation through sharing stories and experience with others, trial-and-error practice in a real life context and encouragement from knowledgeable health providers (Ghahari, Packer & Passmore, 2009). In other words, self-management is gained through conscious and planned engagement in specifically structured occupation. In summary, a client-centred and occupation-focused approach yields new insights about the services and interventions needed by people living with chronic conditions such as neurological conditions, mental health problems, cancer and HIV-Aids. Interventions and services must go beyond medical management to include a much greater focus on role and emotional management. Expected, planned and measured outcomes must move from a focus on behaviour change and health outcomes to the more distal and important measure of participation in everyday roles. Occupational therapy is beginning to make a unique and valued contribution to the research literature, chronic disease best practice and the health and wellbeing of the population. The author wishes to thank Jennifer Lochbihler, MScOT, OTReg(NS) for her assistance in preparing this editorial.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".