| Literature DB >> 30352584 |
Tobias Braun1, Alina Rieckmann2, Franziska Weber2, Christian Grüneberg2.
Abstract
BACKGROUND: The use of measurement instruments in physiotherapy has been recommended in clinical practice guidelines to improve evidence-based practice. The aims of the study were (a) to describe the current use of measurement instruments by physiotherapists working in Germany and (b) to investigate the facilitators and barriers to use measurement instruments.Entities:
Keywords: Cross-sectional survey; Evidence-based practice; Measurement instrument; Outcome measurement; Physical therapy; Physiotherapy; Rehabilitation
Mesh:
Year: 2018 PMID: 30352584 PMCID: PMC6199696 DOI: 10.1186/s12913-018-3563-2
Source DB: PubMed Journal: BMC Health Serv Res ISSN: 1472-6963 Impact factor: 2.655
Determinants of responding physiotherapists (n = 522)
| Determinant | Value |
|---|---|
| Sex [male/female] | 194/328 (37%/63%) |
| Age in years, mean | 38.2 ± 11.5 (19–67) |
| 18–30 | 188 (36%) |
| 31–40 | 111 (21%) |
| 41–50 | 121 (23%) |
| 50+ | 102 (20%) |
| Highest degree of education | |
| Diploma (vocational school) | 368 (70%) |
| Bachelor/diploma (university) | 110 (21%) |
| Master | 38 (7%) |
| Higher academic degree | 6 (1%) |
| Further education/training, mediana | 2 (1–3) |
| None | 45 (9%) |
| Medical exercise training | 293 (56%) |
| Manual therapy | 333 (64%) |
| Manual lymphatic drainage | 314 (60%) |
| Vojta therapy | 19 (4%) |
| Proprioceptive neuromuscular facilitation (PNF) | 120 (23%) |
| Bobath/Neurodevelopmental Treatment (NDT) | 130(25%) |
| At least one other training | 149 (29%) |
| Work experience in years | |
| < 1 | 48 (9%) |
| 1–3 | 63 (12%) |
| 4–10 | 132 (25%) |
| 11–15 | 56 (10%) |
| > 15 | 223 (43%) |
| Primary setting of work | |
| Hospital or rehabilitation clinic (inpatient) | 97 (19%) |
| Outpatient clinic/(private) practice | 397 (76%) |
| No primary setting of work or “other” | 28 (5%) |
| Number of working hours per week, median | 38 (30–40) |
| 1–30 | 172 (33%) |
| 31–40 | 240 (46%) |
| 41+ | 110 (21%) |
| Number of patients per week | |
| 1–5 | 46 (9%) |
| 6–10 | 89 (17%) |
| 11–15 | 132 (25%) |
| 16–20 | 172 (33%) |
| 21–25 | 52 (10%) |
| > 25 | 31 (6%) |
| Main type of treated patients | |
| Musculoskeletal | 381 (73%) |
| Neurological or internal medicine | 53 (10%) |
| Mixed | 88 (17%) |
| Age group of patientsa | |
| Young children < 6 years | 63 (12%) |
| Children 6–13 years | 125 (24%) |
| Adolescents 14–17 years | 220 (42%) |
| Adults 18–65 years | 489 (94%) |
| Older adults > 65 years | 386 (74%) |
Values are the total numbers (percent) or indicated otherwise. Mean values are given with the standard deviation (range), and median values are given with the interquartile range. a Multiple answers possible
Fig. 1Usage frequency of measurement instruments
Fig. 2Frequency of statements concerning the measurement instruments (or methods/devices) that were applied most frequently by respondents and dictated most frequently by the employer. Abbreviations: BFS = body functions and structures; AAP = activities and participation; DASH = Disabilities of the Arm, Shoulder and Hand. (* described in one of the German-language textbooks on measurement instruments [37–39])
Fig. 3Frequency of the 5 most frequently used measurement instruments, described in one of the German-language textbooks on measurement instruments [37–39], by the complete sample of participants and according to the subgroups “work setting” and “main type of patients”
Fig. 4Facilitators and barriers to the use of measurement instruments in physiotherapy in the categories of “perspective of the therapist” and “skills and knowledge” (n = 522). Missing values (m) represent the “cannot assess” option
Fig. 5Facilitators and barriers to the use of measurement instruments in physiotherapy in the categories of “therapeutic setting” and “organisational structures” (n = 522). Missing values (m) represent the “cannot assess” option
Fig. 6Facilitators and barriers to the use of measurement instruments in physiotherapy in the categories of “clinical reasoning process” and “inter-professional approach” (n = 522). Missing values (m) represent the “cannot assess” option
Odds of frequent use of measurement instruments by participants and practice characteristics (results of the multivariate logistic regression analysisa)
| Factor | Use of measurement instruments in ≥80% of patients | Odds Ratio | 95% CI | ||
|---|---|---|---|---|---|
| Lower | Upper | ||||
| Professional degree | < 0.001 | ||||
| Non-academic (vocational school) | 45% (99/220) | Reference | |||
| Academic (Bachelor, Master or PhD degree) | 80% (64/80) | 4.81 | 2.49 | 9.29 | |
| Main setting of work | < 0.001 | ||||
| Outpatient clinic / private practice | 47% (106/226) | Reference | |||
| Inpatient (hospital or rehabilitation clinic) | 79% (45/57) | 3.96 | 1.90 | 8.27 | |
| Number of patients treated per week | |||||
| 1–5 patients | 79% (23/29) | 3.48 | 0.91 | 13.24 | 0.07 |
| 6–10 patients | 56% (30/53) | 1.40 | 0.46 | 4.21 | 0.56 |
| 11–15 patients | 51% (36/71) | 1.51 | 0.52 | 4.34 | 0.45 |
| 16–20 patients | 55% (52/94) | 2.05 | 0.74 | 5.69 | 0.17 |
| 21–25 patients | 40% (12/30) | 1.10 | 0.33 | 3.69 | 0.88 |
| 26+ patients | 43% (10/23) | Reference | |||
Abbreviations: CI confidence interval
aGoodness-of-fit statistics: chi2 = 2.508; p = 0.868; R2 = 0.230
Note that each factor is adjusted for the remaining variables in the model