Body processes that influence self-care: Validation of an instrument for long-term care

doi:10.21203/rs.3.rs-4808731/v1

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Body processes that influence self-care: Validation of an instrument for long-term care

https://doi.org/10.21203/rs.3.rs-4808731/v1

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Objectives

This study aimed to develop a multidimensional assessment instrument focused on bodily processes that influence self-care and validate an instrument in long-term care (BIP@self-care). Methods: A methodological study was conducted with 149 elderly people with functional impairment to develop self-care activities. Generalised Linear Models and cluster analysis were used to analyse the data. Results: Balance and muscular strength were crucial factors in the recovery of autonomy. Sitting balance, dynamic balance, lower limb muscle strength and upper limb muscle strength significantly discriminated between the two identified groups. Conclusion: The BIP@self-care proves to be a comprehensive tool for assessing self-care deficits after a health event within the context of long-term care. These findings have significant implications for nursing practice and the development of targeted interventions aimed at improving these individuals’ autonomy and quality of life.

self-care

assessment

bodily processes

The ageing population poses significant challenges for health systems. In Europe, demographic estimates indicate a continuous increase in the elderly population. The percentage of people aged 65 and over is predicted to nearly double in the coming decades, reaching approximately 30% of the total population in some countries by 2080 [1]. This scenario implies changes in the health needs of the elderly population; therefore, it is crucial to understand the interaction between health and functional autonomy to target effective interventions that promote healthy and independent ageing.

The functional capacity of older adults to perform self-care activities is dependent on several factors. These factors include age, health status, decision-making capacity, physical capacity, and cognitive and emotional abilities [2, 3, 4]. Moreover, life experience, motivation, beliefs, cultural values, habits, functional and cognitive skills [4, 5, 6, 7, 8, 9], confidence, self-efficacy [6, 10], and support systems and access to care [5, 8, 9] are key aspects.

After the onset of functional dependence and the impairment in performing self-care activities, assessing the individual's potential for recovery is essential. In this context, the term "potential" refers to a person's inherent ability and opportunities to develop new self-care skills, thus increasing their autonomy [11].

Several studies focused on the recovery of autonomy in individuals with functional dependence and the inability to perform self-care activities have demonstrated that the potential for improvement in bodily processes is primarily confined to self-orientation and psychological stimulation, muscle strength, balance, and joint range [4, 5, 12]. Nurses must gather and analyse data on how patients respond to specific health issues. This enables them to make diagnoses, formulate expected outcomes, plan and implement interventions, and assess the results of these interventions [4, 5, 13]. Utilizing measurement instruments helps nurses thoughtfully and systematically address factors influencing the autonomy of individuals with functional dependence, facilitating clinical decision-making focused on rehabilitation, empowerment, and recovery [5, 6]. Also, it allows for the assessment of health benefits; therefore, enhancing the visibility of nursing interventions [14, 15].

This underscores the necessity of employing a comprehensive and coherent measurement instrument capable of identifying impairments in bodily processes and characterising the individual's potential for improving self-care.

This study aimed to design and propose an assessment framework for long-term care for individuals recovering from an acute event that compromised their autonomy in self-care activities. The metric proprieties of the measures were analysed, and the relationships between orientation, muscle strength, balance, and joint range of motion in self-care activities were explored. This analysis aimed to identify which measures showed better explanatory capacity regarding the different types of impairments in self-care in long-term care settings.

A Delphi study [4] identified the concepts of bodily processes that should integrate the assessment and monitoring of care for people with self-care deficits after an acute event in long-term care situations. A group of experts with researchers of recognised merit in long-term care and self-care were invited, following the guidelines of Boateng et al. [16]. The main concepts identified were orientation, muscular strength, balance, and range of joint movement [4]. The authors selected items related to these dimensions and, through a consensus technique, established the experimental version of the measurement instrument, “The Body processes that influence self-care (BIP@selfcare)”. This methodological study was developed to examine the metric properties of the instrument.

A convenience sample of 149 participants was selected from two general hospital services (patients awaiting transfer to long-term care) and two long-term care units in northern Portugal. The following inclusion criteria were set: having a nursing diagnosis of self-care deficit, being at least 18 years old, having completed at least four years of schooling, being able to comprehend and respond to the questionnaire, and providing informed consent. Individuals who exhibited verbal behavioural responses indicating confusion or marked cognitive impairment were excluded from the study, with clinical staff responsible for assessing this criterion.

Material

The BIP@self-care is composed of four scales: orientation, muscle strength, balance, and joint range of motion.

Orientation Assessment Scale

Nine items were initially created to evaluate orientation. However, as an inclusion criterion, participants had to identify their name, date of birth, and the people around them, leading to invariance in these items. Therefore, orientation was evaluated through five questions: 1. Identifies the current day, 2. Identifies the year, 3. Identifies the season, 4. Identifies the city they live in, and 5. Identifies their profession. Exploratory factor analysis (EFA) suggested only 1 component explaining 61.22% of the variance. The Cronbach’s alpha coefficient value was 0.94.

The Muscle Strength Scale

The muscle strength scale assesses four segments (left upper limb, right upper limb, left lower limb, and right lower limb. These segments were computed into two components: muscle strength of the upper limbs and muscle strength of the lower limbs. Each item was assessed using a scale from 0 to 5: 0 - No movement is observed, 1 - Only a slight movement is observed or felt, or fasciculations are observed in the muscle 2 - Muscular strength and joint movement are present only if gravity resistance is removed, 3 - The joint can be moved only against gravity and without resistance from the examiner, 4 - Muscle strength is reduced, but there is muscle contraction against resistance, and 5 - Normal strength against total resistance. EFA suggested two components that explained 70.43% of the variance. The first component represented the muscle strength of the upper limbs, and the second component represented the muscle strength of the lower limbs. The Cronbach’s alpha coefficient for these four items was 0.60.

Balance Assessment in Long-Term Care

Thirteen variables were defined to assess balance. EFA suggested two components that explained 64.89% of the variance in balance. The analysis included sitting static and sitting dynamic balance (5 items) and orthostatic balance, orthodynamic balance, and dynamic balance (8 items). Dynamic balance was evaluated through gait, namely confidence versus hesitation at the start of gait, step width, step height, and the ability to walk 3 meters. Orthostatic balance and orthodynamic balance exhibited Cronbach’s alpha of 0.91 and 0.86 for the sitting balance.

Joint Range of Motion Assessment

Joint range of motion (19 items for the left side and 19 items for the right side) was assessed through extension, flexion, and rotation movements of the joints of the upper limbs (humerus, elbow, wrist, and hand) and the lower limbs (hip joint, knee, and ankle joint). EFA suggested five components that explained 75.51% of the variance. The first component included the wrist, hand, and finger joints; the second component included the knee and ankle joints; the third component included the humerus; the fourth component included the hip joint and the fifth component included the elbow joint.

Participants’ commitment to self-care activities such as transfer; turn around, stand up, use the toilet, feeding, grooming, dressing, bathing, and walking) were assessed by a scale ranging from 1-Requires total assistance and is unable to perform self-care activities independently, 2-Requires assistance from another person to perform self-care activities, 3-Requires equipment or aids to assist in self-care activities, and 4-Is independent and does not require any help to perform self-care activities [17].

Ethical considerations

The study received ethical approval from the Ethics Committee of the Portuguese National Health Service, with a favourable opinion granted under reference number (2019.059.051-DEFI/052-CE). Additional ethical clearances were also secured through the Boards of Directors of the participating healthcare institutions. Informed consent was obtained from all participants, who were provided with comprehensive explanations regarding the nature and objectives of the study. It was assured that all participant identification data would be kept strictly confidential, and their anonymity fully preserved. Furthermore, participants were informed of their right to withdraw from the study at any point, without incurring any penalties.

Procedures and data analysis

Participants were referred to the study by the nurse in charge of the inpatient service and were approached during their hospitalisation. EFA was utilised to examine the structure of the data matrix and determine the number and nature of the latent variables (factors) that best represented the observed variables. EFA analyses the inter-relationship structure of the observed variables and defines the factors that better explain their covariance [18]. According to Pestana and Gageiro [19], the Kaiser-Meyer-Olkin (KMO) test and Bartlett's test of sphericity were employed to assess the adequacy of the data and the strength of the correlations among variables before performing the factor analysis. KMO values greater than 0.7, and Bartlett's test values < 0.05 were used as a reference [19]. The confirmation of the number of factors considered the following criteria: (1) eigenvalues > 1, 2) exclusion of factorial loadings < 0.40, (3) each factor explaining at least 5% of the variance, and 4) use of Horn's parallel analysis criteria through graphical analysis of the variance curve and discontinuity principles. To determine the sample size, the study followed the recommendations for EFA, selecting at least five participants for each item under analysis [18].

The reliability of the measures was evaluated using Cronbach's alpha coefficient for the scale's internal consistency, calculated from the average of the inter-correlations between all items of the scale for good internal consistency. The alpha value should be higher than 0.80, but values above 0.60 are accepted [19].

Through Generalized Linear Models, a binary logistic regression was used to predict the extent to which the variables under investigation (orientation, balance, joint range of motion, and muscle strength) contributed to explaining autonomy in different self-care activities. Before conducting the logistic regression analysis, assumptions such as the independence of observations and the absence of perfect multicollinearity were verified [20]. The maximum likelihood method was employed, and the significance of individual coefficients in the logistic regression model was assessed using the Wald statistic. The goodness of fit of the statistical models was evaluated to determine how well the model aligns with the observed data and accurately describes the dependent variable. Additionally, the exponentiation of the B coefficient, known as the odds ratio, was utilised to assess the multiplicative increase in odds associated with a one-unit change in the independent variable.

The study aimed to identify distinct profiles of autonomy in various self-care activities by categorising them based on the similarity of assessed characteristics. The number of clusters was determined by an exploratory cluster analysis technique known as Ward's agglomerative hierarchical method. In logistic regression analysis, the scores for each self-care activity were recoded as binary variables, where the first two options indicated a condition of dependence, and the last two options represented a condition of autonomy for self-care. Subsequently, a confirmatory cluster analysis was conducted using the K-means method, which iteratively assigned cases to clusters until a final solution with two distinct groups was reached. Means and standard deviations were calculated to examine the differences between groups, and ANOVA tests were performed.

The participants had a mean age of 76 years (SD = ± 11.45), mostly women (61.73%). Table 1 details the sociodemographic variables. Most participants had experienced a stroke episode or lower limb fractures due to falls at home, while only a few had faced the decompensation of chronic diseases. All participants experienced a temporary loss of autonomy, with potential recovery possibilities identified. Help-seeking was predominantly required for bathing, dressing, and undressing due to limitations in self-care activities, whereas fewer impairments were observed in activities such as feeding, transferring, and turning.

Table 1

*Descriptive characteristics of the participants*
	N (%)	Mean ± SD
Gender Female Male	92 (61.70) 57 (38.30)
Age		76.0 (± 11.45)
Schooling		4.0 (± 3.49)
Marital status: Married Divorced Widowers Singles	40 (26.80) 21 (14.10) 67 (45.00) 21 (14.10)
Work status Working Not working	13 (8.70) 136 (91.30)
Situation that led to dependence on self-care Accident (falls) Dementia Neurologic disease (stroke) Osteoarticular disease Cardiac disease Other	32(21.50) 3(2.00) 75(50.30) 18(12.10) 7(4.70) 14(9.40)
Time of dependence (days)		90(± 824.75)
Self-Care Assessment Self-Transferring/Self- turning Walking Self-Toileting Self-Feeding Self-Grooming Self-Bathing Self-Dressing or Undressing		2.18 (± 0.65) 2.11 (± 0.88) 2.27 (± 0.71) 3.34 (± 0.94) 2.60 (± 0.94) 2.13 (± 0.41) 2.13 (± 0.55)

An endeavour was undertaken to examine whether orientation, balance, and range of motion of major joints served as predictors of autonomy in various self-care activities. The outcomes of the binary logistic regression analysis are presented in Table 2. The ability of an individual to transfer from one surface to another is primarily elucidated by orthostatic and dynamic balance. The capacity to move the body while lying down or sitting and transitioning between positions is primarily explained by the muscular strength of the upper limbs. Rising from the bed or a chair is predicted by the muscular strength of the upper limbs. Orthostatic and dynamic balance, in conjunction with the muscular strength of the upper limbs, were the best predictors of autonomy in using the toilet. Autonomy in self-feeding is primarily expounded by the range of motion of the hand and fingers, along with the muscular strength of the upper limbs. The self-care activity of feeding is explained by both orientation and muscular strength of the upper limbs. Orientation and muscular strength of the upper limbs are likely predictors of autonomy in grooming, which encompasses activities contributing to a presentable and orderly appearance for day-to-day interactions. Autonomy in dressing and undressing is predicted by sitting balance and range of motion of the humerus. Autonomy in walking exhibits predictors of orthostatic and dynamic balance, as well as muscular strength of the upper limbs.

Table 2

*Binary regression analysis of predictors of each self-care activi*
					95% CI
	Beta	SE	Wald	Exp(B)	Lower	Upper
Self-Transferring
(Intercepts)	14.05	6.38	4.85	12592.60	4.66	340002579.48
Orientation	-0.76	0.54	2.02	0.47	0.16	1.33
Sitting balance	-1.06	0.69	2.41	0.34	0.09	1.32
Orthostatic and dynamic balance	-0.22	0.08	6.90	0.80	0.68	0.95
JRM Humerus	0.11	0.19	0.32	1.12	0.76	1.63
JRM elbow	-0.14	0.66	0.04	0.87	0.24	3.16
JRM hand and fingers	-0.02	0.21	0.01	0.98	0.65	1.50
JRM hip	0.18	0.22	0.68	1.20	0.78	1.85
JRM Knee and tibiotarsus	0.05	0.16	0.08	1.05	0.76	1.44
Upper limb muscle strength	-0.27	0.23	1.43	0.76	0.49	1.19
Lower limb muscle strength	0.09	0.22	0.16	1.09	0.71	1.69
(Scale)	1
Self-Turning
(Intercepts)	5.39	2.18	6.14	219.52	3.09	15601.84
Orientation	-0.08	0.17	0.24	0.92	0.67	1.28
Sitting balance	-0.30	0.16	3.47	0.74	0.54	1.02
Orthostatic and dynamic balance	-0.05	0.06	0.53	0.96	0.84	1.08
JRM humerus	-0.14	0.14	1.08	0.87	0.66	1.14
JRM elbow	0.42	0.38	1.24	1.53	0.72	3.22
JRM hand and fingers	-0.07	0.14	0.24	0.93	0.70	1.24
JRM hip	0.06	0.16	0.14	1.06	0.78	1.44
JRM knee and tibiotarsus	0.05	0.11	0.23	1.05	0.86	1.29
Upper limb muscle strength	-0.48	0.14	11.42	0.62	0.47	0.82
Lower limb muscle strength	-0.021	0.1529	0.019	0.979	0.73	1.32
(Scale)	1
Standing
(Intercepts)	10.20	3.10	10.85	26834.64	62.19	11579920.35
Orientation	-0.42	0.22	3.47	0.66	0.43	1.02
Sitting balance	-0.35	0.22	2.47	0.71	0.46	1.09
Orthostatic and dynamic balance	-0.12	0.06	3.56	0.88	0.78	1.00
JRM humerus	0.25	0.16	2.57	1.29	0.95	1.75
JMR elbow	0.33	0.43	0.60	1.40	0.60	3.26
JRM hand and fingers	-0.08	0.18	0.22	0.92	0.64	1.31
JRM hip	-0.17	0.17	1.06	0.84	0.61	1.17
JRM Knee and tibiotarsus	0.24	0.12	4.15	1.27	1.01	1.61
Upper limb muscle strength	-0.66	0.18	13.37	0.52	0.36	0.74
Lower limb muscle strength	-0.28	0.17	2.66	0.76	0.54	1.06
(Scale)	1
Self-Toileting
(Intercepts)	17.57	6.44	7.45	42589409.75	141.64	1280609640301.13
Orientation	-0.39	0.34	1.32	0.68	0.35	1.31
Sitting balance	-1.32	0.73	3.28	0.27	0.06	1.12
Orthostatic and dynamic balance	-0.16	0.07	4.46	0.85	0.74	0.99
JRM humerus	0.24	0.18	1.89	1.28	0.90	1.81
JRM elbow	-0.42	0.73	0.33	0.66	0.16	2.75
JRM hand and fingers	0.03	0.22	0.02	1.03	0.67	1.58
JRM hip	-0.09	0.20	0.18	0.92	0.62	1.37
JRM Knee and tibiotarsus	0.01	0.15	0.01	1.01	0.75	1.36
Upper limb muscle strength	-0.58	0.23	6.10	0.56	0.35	0.89
Lower limb muscle strength	0.08	0.19	0.19	1.09	0.75	1.58
(Scale)	1
Self-Feeding
(Intercepts)	1.37	2.22	0.38	3.95	0.05	307.71
Orientation	0.15	0.19	0.58	1.16	0.80	1.68
Sitting balance	-0.14	0.14	1.00	0.87	0.65	1.15
Orthostatic and dynamic balance	-0.01	0.07	0.02	0.99	0.87	1.13
JRM humerus	0.02	0.15	0.01	1.02	0.76	1.37
JRM elbow	1.01	0.61	2.71	2.74	0.82	9.14
JRM hand and fingers	-0.34	0.16	4.33	0.71	0.51	0.98
JRM hip	0.28	0.18	2.28	1.32	0.92	1.89
JRM Knee and tibiotarsus	-0.02	0.12	0.04	0.98	0.78	1.23
Upper limb muscle strength	-0.49	0.14	12.02	0.61	0.46	0.81
Lower limb muscle strength	0.11	0.16	0.49	1.12	0.82	1.54
Self-Getting up
(Intercepts)	8.83	2.72	10.54	6814.45	33.02	1406152.63
Orientation	-0.56	0.28	3.97	0.57	0.33	0.99
Sitting balance	-0.14	0.19	0.59	0.87	0.60	1.25
Orthostatic and dynamic balance	-0.05	0.07	0.56	0.95	0.83	1.08
JRM humerus	0.24	0.15	2.37	1.27	0.94	1.71
JRM elbow	0.14	0.38	0.12	1.14	0.54	2.43
JRM hand and fingers	-0.05	0.14	0.10	0.96	0.72	1.26
JRM hip	0.16	0.16	1.02	1.17	0.86	1.60
JRM Knee and tibiotarsus	0.07	0.11	0.38	1.07	0.86	1.33
Upper limb muscle strength	-0.87	0.22	16.38	0.42	0.27	0.64
Lower limb muscle strength	0.11	0.16	0.49	1.12	0.82	1.51
(Scale)	1
Self-Dressing or Undressing
(Intercepts)	10.71	3.63	8.71	44727.45	36.43	54913424.38
Orientation	0.32	0.19	2.84	1.38	0.95	2.00
Sitting balance	-0.29	0.24	1.43	0.75	0.47	1.20
Orthostatic and dynamic balance	-0.28	0.07	15.19	0.75	0.65	0.87
JRM humerus	0.09	0.17	0.28	1.10	0.78	1.53
JRM elbow	-0.82	0.74	1.22	0.44	0.10	1.89
JRM hand and fingers	0.15	0.22	0.46	1.16	0.76	1.77
JRM hip	0.04	0.20	0.05	1.05	0.71	1.54
JRM Knee and tibiotarsus	-0.17	0.17	1.03	0.85	0.61	1.17
Upper limb muscle strength	-0.42	0.18	5.56	0.66	0.46	0.93
Lower limb muscle strength	-0.34	0.25	1.86	0.71	0.43	1.16
Scale)	1
Self-Bathing
(Intercepts)	13.90	6.05	5.28	10899.59	7.70	154341043.89
Orientation	-1.26	0.86	2.11	0.29	0.05	1.55
Sitting balance	-0.43	0.37	1.30	0.65	0.31	1.36
Orthostatic and dynamic balance	0.06	0.09	0.47	1.06	0.89	1.27
JRM humerus	0.14	0.24	0.35	1.15	0.72	1.84
JRM elbow	0.36	0.51	0.51	1.44	0.53	3.88
JRM hand and fingers	-0.16	0.25	0.42	0.85	0.52	1.38
JRM hip	-0.33	0.25	1.76	0.72	0.44	1.17
JRM Knee and tibiotarsus	0.18	0.16	1.17	1.19	0.87	1.64
Upper limb muscle strength	-0.31	0.23	1.79	0.73	0.46	1.16
Lower limb muscle strength	-0.08	0.20	0.14	0.93	0.62	1.38
Scale)	1
Walking
(Intercepts)	10.71	3.63	8.71	44727.45	36.43	54913424.38
Orientation	0.32	0.19	2.84	1.38	0.95	2.00
Sitting balance	-0.29	0.24	1.43	0.75	0.47	1.20
Orthostatic and dynamic balance	-0.28	0.07	15.19	0.75	0.65	0.87
JRM humerus	0.09	0.17	0.28	1.10	0.78	1.53
JRM elbow	-0.82	0.74	1.22	0.44	0.10	1.89
JRM hand and fingers	0.15	0.22	0.46	1.16	0.76	1.77
JRM hip	0.04	0.20	0.05	1.05	0.71	1.54
JMR Knee and tibiotarsus	-0.17	0.17	1.03	0.85	0.61	1.17
Upper limb muscle strength	-0.42	0.18	5.56	0.66	0.46	0.93
Lower limb muscle strength	-0.34	0.25	1.86	0.71	0.43	1.16
(Scale)	1

Two clusters were identified: the first cluster comprised 56 participants, and the second cluster included 93 participants, with the latter group exhibiting lower autonomy. Means and standard deviations of the variables studied for each group are exhibited in Table 3. Not all variables under study contributed statistically to discriminating the clusters. Notably, only sitting balance, dynamic balance, lower limb muscle strength, and upper limb muscle strength discriminated participants between cluster 1 and cluster 2 (Fig. 1).

In sum, balance and muscular strength were found to exert the greatest influence on restoring autonomy in self-care activities. Consequently, nurses’ interventions within these clinical contexts should consider these factors.

Table 3

*Means and standard deviations of the variables under study for each profile identified in the cluster analysi*
	Cluster 1(N = 56)		Cluster 2(N = 93)
	M(SD)		M(SD)		p
Orientation	4.59	(0.93)	4.43	(1.25)	0.41
Sitting balance	6.77	(0.69)	5.76	(2.01)	< 0.001
Orthostatic and dynamic balance	7.18	(2.05)	0.70	(1.01)	< 0.001
JRM humerus	5.25	(1.50)	5.00	(1.82)	0.38
JRM elbow	3.82	(0.51)	3.83	(0.69)	0.95
JRM hand and fingers	11.50	(1.57)	11.45	(1.61)	0.86
JRM hip	5.30	(1.19)	4.84	(1.76)	0.08
JRM Knee and tibiotarsus	9.11	(1.52)	8.38	(2.75)	0.07
Upper limb muscle strength	8.89	(1.29)	8.13	(1.67)	0.004
Lower limb muscle strength	8.68	(0.74)	7.01	(1.93)	< 0.001

Legend: Sit- sitting; Dyn – dynamic; JRM – joint range of motion; ULMS- upper limb muscle strength; LLMS - lower limb muscle strength

This study sought to develop and analyse a multidimensional assessment for long-term care for individuals recovering their functional capacity after an acute event impairing their autonomy in self-care activities. BIP@self-care can predict the potential for restoring autonomy in self-care activities in elderly individuals with reduced functional capacity following a sudden clinical situation or exacerbation of a chronic illness. Identifying these predictors enables nurses to develop effective intervention strategies, supporting older adults in regaining their independence and promoting the best possible quality of life [21].

Participants had an average age of 76 years and were mostly women. The primary causes of functional dependence among the participants were strokes and falls frequently leading to fractures of the lower limbs. Most of these cases necessitated orthopaedic surgery, such as hip arthroplasty or hemiarthroplasty [22]. Additionally, disuse syndrome, characterised by the loss of mobility following prolonged hospital stays with extended periods of immobility and bedridden [23], was prevalent and demanded long-term care. These study findings are mainly related to this population.

Binary logistic regression analysis revealed several significant predictors of autonomy in self-care activities. The influence of orthostatic and dynamic balance on transferring between surfaces and using the toilet underscores the necessity of maintaining stability and mobility for these activities. Similarly, upper limb muscle strength emerged as a significant predictor for transferring, mobilising in bed, and rising from bed or a chair, highlighting the importance of maintaining trunk balance for performing these self-care activities. This emphasises the potential benefits of incorporating mobility exercise training, such as rising and sitting down from a chair, flexing and extending the knees with the support of the bed rail, and alternately lifting the lower limbs with nurse assistance. These interventions, integrated into rehabilitation programmes for individuals with functional dependence, can positively impact the improvement of functional capacity for self-care activities and enhance their well-being [24, 25, 26].

Self-feeding ability was significantly influenced by the range of motion of the hand and fingers, underscoring the critical role of fine motor skills in initiating and completing this self-care task. Similarly, autonomy in dressing and undressing was associated with sitting balance and the range of motion of the shoulder joint, highlighting the importance of trunk stability and upper limb mobility. These findings stress the need for interventions that include balance training and active resistance exercises targeting muscle strength and joint mobility. Such interventions are crucial for enhancing autonomy in daily tasks among older adults [27]. This study also identified significant correlations between fine motor skills, balance, mobility, and autonomy in daily self-care activities. These findings are consistent with previous research. For example, Gorman et al. [28] demonstrated the impact of hand and finger range on feeding abilities in elderly individuals with various motor impairments. This association underscores the critical role of fine motor skills in handling utensils and ensuring the ability to independently and effectively feed oneself. Furthermore, autonomy in dressing and undressing is closely linked to maintaining sitting balance and sufficient range of motion in the upper limbs. These findings underscore the essential role of trunk stability and sufficient mobility in the upper limbs for performing basic daily tasks autonomously among the elderly. These insights emphasise the significance of interventions to enhance autonomy in this population. Therefore, comprehensive approaches should be planned, focusing on training in fine motor skills, engaging in active muscle exercises for joints, improving hip elevation, and practicing controlled hip rotation [12, 29].

Identifying distinct clusters of individuals with varying levels of autonomy in daily activities underscores the importance of personalised intervention strategies tailored to the individual characteristics of elderly individuals. This highlights the necessity for an integrated, multidisciplinary approach to delivering care for people with functional dependence. This approach should consider specific aspects of self-care and the person’s physical capacity, mobility, and emotional well-being. This comprehensive approach aims to foster sustainable recovery of autonomy in self-care activities and ultimately enhance quality of life following a period of functional dependence [6, 30].

The novelty of these study findings allowed the identification of two distinct clusters with different levels of autonomy, providing valuable insights into the heterogeneity of elderly populations regarding self-care capacities. Cluster 1, which evidenced higher autonomy, likely includes individuals who have maintained better physical functioning, possibly due to healthier lifestyle choices and proactive management of health conditions. Conversely, Cluster 2, demonstrating lower autonomy, may comprise individuals facing more complex health issues, mobility limitations, or inadequate access to healthcare. Understanding the variables that distinguish these clusters, such as sitting balance, dynamic balance, and strength in upper and lower limbs, enables targeted nursing interventions aimed at individuals with lower potential for restoring autonomy. This finding suggests that interventions focused on improving balance and muscle strength significantly enhance autonomy for self-care and basic activities of daily living among older people with functional dependence.

This study emphasises the importance of balance and muscle strength as key predictors of autonomy in self-care activities of individuals with functional impairments. This understanding enables healthcare professionals to develop focused and comprehensive intervention strategies aimed at enhancing the overall well-being and independence of these individuals. BIP@self-care has proved to be a useful multidimensional toolkit for monitoring individuals throughout the recovery process following health events that impact autonomy in self-care activities.

The findings strongly advocate for healthcare providers to prioritise preventive measures and early interventions aimed at maintaining or enhancing autonomy in self-care among the elderly population with functional dependence. This implies early referral to long-term care facilities for these individuals. Health professionals, particularly nurses who implement evidence-based interventions, play a crucial role in significantly improving the lives of older adults with functional dependence. By supporting older people in maintaining greater independence, nurses can substantially contribute to their overall quality of life and well-being.

These study findings hold substantial clinical implications, particularly for nurses and healthcare professionals involved in geriatric care. These findings call the attention for adopting a multidimensional approach that integrates mobility exercise programmes targeting balance, muscle strength, joint range, and fine motor function for older adults. Furthermore, proactive screening for early signs of mobility issues and functional decline is crucial. Early identification can facilitate prompt interventions aimed at preserving autonomy and preventing further dependence among elderly individuals.

Regarding methodology, the study followed a Delphi method to identify core concepts for evaluating BIP@self-care, which is adequate for achieving consensus among experts. Exploratory factor analysis (EFA) established construct validity for each scale within BIP@self-care. Generalised linear models and cluster analysis were employed to analyze predictors of autonomy and the discriminative capacity of the tool, offering a thorough examination of participant characteristics and outcomes.

Despite the existence of several scales to assess orientation, muscle strength, balance, and joint range of motion, the BIP@self-care novelty lies in its adaptation to the specific needs of older adults in long-term care facilities. This tool is particularly suited for residents with the potential to regain autonomy in self-care activities. BIP@self-care provides a more precise and effective evaluation of the potential for self-care autonomy recovery among the elderly, thus enhancing nurses' decision-making processes to better address this population’s real long-term care needs.

Author Contribution

M.L., T.M., and M.J.P. were responsible for the conceptualisation of the research concept. M.L., T.M., M.J.P, and P.E. were responsible for data collection. ML was responsible for data analysis and results. ML was responsible for the writing of the manuscript. All authors reviewed the manuscript

Acknowledgement

The authors wish to thank all the patients in the study. The authors wish to acknowledge the contribution of the professional translator Maria do Amparo Alves on the translation/editing of this article.

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Body processes that influence self-care: Validation of an instrument for long-term care

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Abstract

Objectives

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INTRODUCTION

METHODS

Material

Orientation Assessment Scale

The Muscle Strength Scale

Balance Assessment in Long-Term Care

Joint Range of Motion Assessment

Ethical considerations

Procedures and data analysis

RESULTS

DISCUSSION

CONCLUSION

Declarations

Author Contribution

Acknowledgement

References

Additional Declarations

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Version 1