A scoping review of interventions tailored to the unique needs of care partners of persons with frontotemporal degeneration
Bibliographic record
Abstract
Abstract Background Care partners for family members with Frontotemporal Degeneration (FTD) face challenges that are complex and distinct from those faced by care partners persons with Alzheimer’s disease and related dementias (ADRD). However, while there are numerous studies addressing the negative impact of providing care to persons with ADRD, less attention is paid to the needs of care partners of persons with FTD. Understanding how interventions can be tailored to address the behavioral symptoms of FTD can inform future approaches to meeting the needs of FTD care partners. Method A scoping review was undertaken following Arksey and O’Malley’s systematic methodological framework. Articles were identified through a comprehensive search of PubMed, PsychINFO, and CINAHL. Peer‐reviewed, data‐based articles reporting results of interventions specifically designed to address the unique needs of care partners of persons with FTD were included in our sample. Reviews, scale development, and studies including ADRD care partners of were excluded. Result We identified 290 unique records and retained 42 for full text screening. One paper was added after manual search of reference lists, resulting in eight papers describing five unique interventions meeting inclusion criteria. All included studies had small sample sizes (total n ranged from 2‐30); three were randomized controlled trials. The studies were based in the US, Australia, Germany, Canada and The Netherlands, and the majority of participants were white, female spouses. Three interventions were group‐based, and two were one‐to‐one. Duration ranged from five weeks to six months. Lack of informal support, stigma, financial concerns, and coping with FTD‐associated behavioral symptoms such as apathy and disinhibition were especially salient topics for participants. Participants benefited from peer support, problem‐solving, and positive reframing activities. Statistically significant improvement in burden were reported in three of the eight papers. Conclusion All of the included papers suggested positive qualitative and quantitative results from the interventions, but the samples were small and homogenous. This review highlights an important gap in the science addressing the behavioral challenges FTD care partners face. These findings support the need for larger studies with more diverse populations to identify effective interventions to support families living with FTD.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.027 | 0.090 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.009 | 0.009 |
| Bibliometrics | 0.016 | 0.016 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.006 | 0.004 |
| Open science | 0.003 | 0.003 |
| Research integrity | 0.004 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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 source (direct Gemma or distilled Codex), 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".