Effects of MI-Guided Bedside ADL Training on Functional and Emotional Outcomes In Post-Stroke Depression: A Retrospective Cohort Study

Podsumowanie

This protocol describes a method integrating motivational interviewing with bedside activities of daily living training to support the rehabilitation of patients with post-stroke depression, with a focus on improving functional independence and psychological engagement.

Streszczenie

Post-stroke depression (PSD) impedes recovery and is often insufficiently addressed by conventional rehabilitation. This retrospective cohort study presents a structured protocol for integrating motivational interviewing (MI) with bedside activities of daily living (ADL) training, including standardized bedside rehabilitation procedures and repeated functional and psychological assessments in PSD patients. In a retrospective cohort of 174 patients, participants were assigned to either an MI-guided ADL training group or a conventional rehabilitation group. Functional independence, emotional status, and serum monoamine neurotransmitter levels were assessed at multiple time points using standardized scales and biochemical analysis. The results showed that the MI-ADL group was associated with improved functional and emotional outcomes compared with the conventional rehabilitation group, accompanied by increased levels of key monoamine neurotransmitters: 5-hydroxytryptamine (5-HT), norepinephrine (NE), and dopamine (DA). This protocol provides a structured and reproducible bedside rehabilitation approach for combining psychological motivation with functional rehabilitation. However, as this was a retrospective cohort study, these findings are hypothesis-generating, and further prospective studies are needed to confirm causal relationships.

Wprowadzenie

Post-stroke depression (PSD) is the most common neuropsychiatric complication among stroke patients, affecting approximately one-third of stroke survivors^1,2. Its clinical manifestations are complex. Besides typical depressive symptoms, it often involves cognitive decline, sleep disorders, and other complex presentations, which seriously affect patients' enthusiasm for recovery, delay neurological recovery, and increase family and societal burdens^3,4,5. To address these challenges, this protocol describes a method integrating motivational interviewing (MI) with bedside activities of daily living (ADL) training, with the overall goal of improving functional independence and emotional outcomes in PSD patients.

Multiple studies have suggested a statistically significant association between post-stroke depressive symptoms and limitations in basic or instrumental activities of daily living^6,7,8.

At present, clinical management of PSD mainly relies on drug therapy and conventional rehabilitation training⁹. However, antidepressant drugs have variable efficacy and potential side effects, while conventional rehabilitation can improve physical function but often provides limited support for psychological motivation. Compared with drug-only treatment, psychological therapy alone, or standard rehabilitation without integrated mental health support, this combined method targets both mood and daily function simultaneously^10,11.

MI is a patient-centered psychological counseling method that uses specific communication strategies to help patients resolve conflicting emotions during behavioral changes and enhance their intrinsic motivation¹². The main focus of this protocol is the method of MI‑guided bedside ADL training, delivered within a structured clinical rehabilitation setting. Combining it with bedside ADL training may yield a synergistic effect, improving physical function and enhancing psychological engagement. However, the effectiveness and mechanism of this integrated approach still need to be verified^13,14.

Based on the monoamine neurotransmitter hypothesis of depression, dysfunction of the 5‑HT, NE, and DA systems is a key physiological basis of depression^15,16. To explore whether MI‑guided ADL is associated with changes in these systems through psychological-neural pathways, this study compared outcomes between the MI‑guided protocol and conventional rehabilitation. The method integrates motivational interviewing into bedside ADL training and includes multi‑time‑point neurotransmitter monitoring to assess potential mechanisms.

This study employed a retrospective cohort design to compare the MI-guided ADL training protocol with conventional rehabilitation in patients with post-stroke depression (PSD). The primary hypothesis was that the MI-ADL group would be associated with greater improvements in functional independence (measured by the Modified Barthel Index), depressive symptoms (measured by the Hamilton Depression Rating Scale and Self-Rating Depression Scale), and serum levels of monoamine neurotransmitters (5-HT, NE, DA) compared with the conventional rehabilitation group, and that these differences would be sustained at 6‑month follow‑up. The secondary hypothesis was that the MI-ADL protocol would demonstrate acceptable safety and feasibility. This study is expected to provide clinical and mechanistic evidence for the integrated approach and to inform future prospective research.

This protocol incorporates multi‑time‑point assessment of functional performance, emotional status, and serum neurotransmitter levels to evaluate the effectiveness of the integrated approach. This method is designed for clinicians, rehabilitation specialists, and clinical researchers who manage patients with post‑stroke depression (PSD). It provides a structured and reproducible strategy that integrates psychological and functional rehabilitation.

The potential of this method includes improving patient motivation and adherence, enhancing activities of daily living, and enabling mechanism-based evaluation through neurotransmitter monitoring. By addressing both physical and psychological aspects of recovery, it supports more comprehensive and individualized patient care than conventional rehabilitation.

Protokół

Ethical Statement:
This study was approved by the Ethics Committee of the Fujian University of Traditional Chinese Medicine Affiliated Rehabilitation Hospital (Approval No.: 2023KY-046-002). All procedures adhered strictly to the principles of the Declaration of Helsinki. Because this study involved only retrospective analysis of de-identified data extracted from routine electronic medical records, the Ethics Committee granted a waiver of individual informed consent for research purposes. All patients had provided general written consent for the use of their medical records for clinical research at the time of hospital admission, as required by institutional policy. Patient privacy and data security were protected by storing all personal information using anonymous coding methods, and access to research data was granted only to authorized researchers. Research data will be retained for 5 years after study completion and then destroyed in accordance with institutional regulations.

1. Research Subjects and Study Design

1. Identify the eligible study population
   1. Conduct a retrospective cohort study.
      NOTE: This study was purely observational and retrospective. No prospective allocation or experimental assignment of rehabilitation modalities was performed. All rehabilitation procedures were conducted as part of routine clinical care, and treatment exposure was identified retrospectively from electronic medical records.
   2. Access the electronic medical record system of Fujian University of Traditional Chinese Medicine Affiliated Rehabilitation Hospital. Retrieve all medical records of patients diagnosed with post-stroke depression (PSD) who were hospitalized between July 2023 and December 2025.
   3. Apply the predefined inclusion and exclusion criteria to screen all retrieved records. Identify and select all cases that meet the eligibility criteria for further analysis.
   4. Review the rehabilitation methods documented in each patient’s medical record. 1.1.5. Assign patients who received motivational interviewing (MI) combined with bedside activities of daily living (ADL) training to the MI-ADL group.
   5. Assign patients who received only conventional rehabilitation treatment to the conventional rehabilitation group.
   6. Confirm sample size and grouping. Ensure that each group includes 87 patients. Confirm that a total of 174 eligible patients are included in the final analysis. Refer to Figure 1 for the study grouping and patient selection workflow.
2. Participant Selection and Group Formation
   1. Screen all electronic medical records (EMR) of patients diagnosed with post-stroke depression (PSD) who were hospitalized at Fujian University of Traditional Chinese Medicine Affiliated Rehabilitation Hospital between July 2023 and December 2025.
   2. Screen a total of 286 patient records. Apply the inclusion and exclusion criteria to all screened records. Exclude 112 records after eligibility assessment.
   3. Exclude 78 records that do not meet the inclusion criteria, including age outside 40–75 years, absence of neuroimaging confirmation, or hospitalization duration of less than 6 weeks.
   4. Exclude 24 patients who declined participation according to the clinical records. Exclude 10 records with incomplete medical records or missing key assessment data. Include the remaining 174 eligible patients for analysis.
   5. Review the rehabilitation exposure documented retrospectively in each patient’s electronic medical record.
      NOTE: Classify the eligible patients retrospectively into two naturally occurring cohorts based on the rehabilitation protocol documented in the electronic medical records during hospitalization.
   6. Assign patients who received motivational interviewing-guided bedside activities of daily living (ADL) training to the MI ADL group (n = 94).
   7. Assign patients who received conventional ADL training without any motivational interviewing component to the conventional rehabilitation group (n = 156).
   8. Perform 1:1 propensity score matching (PSM) using a caliper value of 0.02 to reduce confounding, minimize selection bias, and improve baseline comparability between the two retrospective cohorts.
      NOTE: The rehabilitation modality received by each patient was determined during routine clinical care and was not assigned by the investigators.
   9. Include age, sex, stroke type (ischemic/hemorrhagic), time from stroke onset to enrollment (days), baseline Hamilton Depression Rating Scale-17 (HAMD-17) score, and baseline Modified Barthel Index (MBI) score as matching covariates.
   10. Generate 87 matched pairs after propensity score matching.
       The final propensity score-matched cohort consisted of 87 patients in the MI ADL group and 87 patients in the conventional rehabilitation group (total N = 174).
   11. Include patients with a stroke diagnosis confirmed by neuroimaging. Include patients who meet diagnostic criteria for post-stroke depression (PSD). Select patients aged 40–75 years with a hospitalization period of at least 6 weeks and complete medical records^17,18.
       NOTE: Use the 40–75-year age range to support clinical representativeness while reducing confounding from uncommon stroke etiologies in younger patients and comorbidities, cognitive decline, or reduced communication ability in older patients.
   12. Exclude patients with severe cognitive impairment or aphasia that affects effective communication. Exclude patients with other severe physical diseases. Exclude patients with incomplete medical records or missing key data^19,20.
   13. Extract all basic clinical characteristics, intervention plans, and assessment data for the included cases from the electronic medical record system.
   14. Verify the completeness of all extracted data.
   15. Refer to the participant flowchart (Figure 1) for a visual summary of the screening, exclusion, matching, and final sample derivation.
3. Treatment: Conventional rehabilitation group
   1. Administer a standardized 6-week rehabilitation plan according to the hospital’s established clinical pathway for post-stroke depression (PSD). Provide physical therapy focused on motor function, balance, and transfer training²¹.
   2. Apply neurodevelopmental therapy techniques to regulate abnormal muscle tone. Conduct joint range-of-motion training to prevent contractures.
   3. Perform sitting-to-standing balance training and indoor walking training according to each patient’s functional level. Deliver physical therapy for 30 min per session, once daily, 5 times per week²².
   4. Provide occupational therapy to improve activities of daily living (ADL). Include training in personal self-care activities and simulated household and community activities.
   5. Deliver occupational therapy for 30 min per session, once daily, 5 times per week. Provide routine psychological support concurrently with physical and occupational therapy.
   6. Deliver psychological support through basic psychological counseling, rehabilitation encouragement, and health education. Cover disease explanation, confidence building, and emotional support during psychological support.
   7. Use a supportive and instructive communication style throughout routine psychological support. Do not use a structured psychotherapeutic model for this support component.
4. Treatment: MI-ADL group
   1. Provide motivational interviewing (MI)-guided personalized bedside ADL training in addition to conventional rehabilitation.
   2. Ensure that all therapists delivering the MI-ADL intervention have passed standardized assessments verifying accurate and consistent application of MI techniques.
   3. Administer the MI-ADL intervention for 6 weeks, with 3 sessions per week and 45 min per session. Structure each MI-ADL session into four consecutive stages.
   4. Establish a therapeutic alliance with the patient during the engagement stage for 5–10 min using empathic communication. Use the decisional balance technique during the focused exploration stage for 10–15 min to help the patient clarify specific and feasible ADL goals.
   5. Guide the patient during the focused exploration stage to explore ambivalent psychological aspects of behavior change. Use strategic questioning during the evocation stage for 10–15 min to evoke and strengthen the patient’s internal motivation for change.
   6. Reinforce the patient’s sense of self-efficacy during the evocation stage. Collaboratively formulate a step-by-step ADL training plan with the patient during the planning stage for 10–15 min.
   7. Immediately initiate practical implementation of the ADL training plan to convert motivation into concrete action^23,24,25.
5. Detection indicators
   1. Functional independence evaluation
      1. Use the Modified Barthel Index (MBI) as the standardized assessment tool for evaluating activities of daily living²⁶.
      2. Assess feeding, bathing, grooming, dressing, bowel control, bladder control, toilet use, chair/bed transfer, ambulation on a level surface, and stair climbing. Score each item according to the degree of assistance required to complete the task.
      3. Calculate the total MBI score from 0 to 100 points. Classify a score of 100 as complete self-care, 75–95 as mild functional impairment, 50–70 as moderate functional impairment, 25–45 as severe functional impairment, and 0–20 as total dependence.
      4. Assign trained rehabilitation therapists to conduct the assessment. Perform the assessment through patient and caregiver interviews combined with direct observation of patient performance.
   2. Emotional status assessment indicators: Hamilton Depression Scale (HAMD)^27:
      1. Use the 17-item Hamilton Depression Rating Scale (HAMD) to assess depressive symptom severity.
      2. Evaluate the following symptom domains: depressed mood, guilt feelings, suicide, initial insomnia, middle insomnia, late insomnia, work and interests, retardation, agitation, psychic anxiety, somatic anxiety, gastrointestinal symptoms, general somatic symptoms, genital symptoms, hypochondriasis, weight loss, and insight.
      3. Apply a 5-point scoring system (0–4) for most HAMD items. Assign a score of 0 for absent symptoms, 1 for mild symptoms, 2 for moderate symptoms, 3 for severe symptoms, and 4 for very severe symptoms.
      4. Apply a 3-point scoring system (0–2) for the HAMD items designed for 3-point evaluation. Assign a score of 0 for absent symptoms, 1 for mild-to-moderate symptoms, and 2 for severe symptoms for the 3-point items.
      5. Calculate the total HAMD score for each patient after completion of all item assessments.
      6. Interpret total HAMD scores according to the following criteria: interpret scores >35 as potentially indicating severe depression, scores >20 as indicating mild-to-moderate depression, and scores <8 as indicating absence of depressive symptoms.
      7. Assign psychiatrists or psychotherapists who have received standardized and consistent training to administer the HAMD assessment.
      8. Conduct all HAMD assessments using structured interviews to ensure assessment objectivity, consistency, and accuracy.
   3. Emotional status assessment indicators: Zung Self-rating Depression Scale (SDS)²⁸
      1. Use the Zung Self-Rating Depression Scale (SDS) to evaluate patients’ subjective depressive symptoms experienced during the previous week. Use the SDS to assess patients’ subjective emotional experience related to depression.
      2. Administer the 20-item SDS questionnaire covering four symptom domains: pervasive affective disturbances, physiological disturbances, psychomotor disturbances, and psychological disturbances.
      3. Score each SDS item using a 4-point scale ranging from 1 to 4. Reverse-score the 10 designated reverse-scored SDS items before calculating the total score.
      4. Calculate the raw SDS score by summing the scores of all 20 items. Multiply the raw SDS total score by 1.25 to obtain the standard score. Round the calculated standard score to the nearest whole number.
      5. Interpret the SDS standard score according to the Chinese norm criteria.
      6. Define the SDS cut-off value for depression screening as 53 points. Classify SDS standard scores between 53 and 62 as mild depression, scores between 63 and 72 as moderate depression, and scores above 72 as severe depression.
      7. Instruct patients to complete the SDS questionnaire independently in a quiet environment. Read each SDS item aloud when patients are unable to complete the questionnaire independently because of physical limitations.
      8. Record patients’ verbal responses accurately when assessor-assisted SDS administration is required.
   4. Neurochemical observation indicators
      1. Collect all blood samples between 7:00 and 9:00 in the morning after patients have fasted for 12 h. Use standardized fasting morning collection procedures to minimize potential interference from circadian rhythm variation and dietary factors.
      2. Draw a 5 mL venous blood sample from the patient’s antecubital vein. Transfer the collected blood sample into a serum-separating vacuum blood collection tube without anticoagulant.
      3. Allow the blood sample to stand at room temperature for 30 min to permit natural coagulation. Centrifuge the coagulated blood sample at 1510 × g for 15 min at 4 °C.
      4. Separate the upper serum layer immediately after centrifugation. Aliquot the separated serum into labelled 1.5 mL microcentrifuge tubes (generic descriptor; specific product information is provided in the Table of Materials).
      5. Store all serum aliquots in an ultra-low-temperature freezer at −80 °C until batch testing and analysis.
         Pause point: One can take a pause here during this process.
      6. Quantify serum levels of 5-hydroxytryptamine (5-HT), norepinephrine (NE), and dopamine (DA) using a High-Performance Liquid Chromatography coupled with Electrochemical Detection (HPLC-ECD) system. Perform all analytical procedures according to the laboratory’s established Standard Operating Procedures.
      7. Perform chromatographic separation using a C18 reversed-phase column (4.6 mm × 250 mm, 5 µm particle size).
      8. Maintain the chromatographic column temperature at 35 °C throughout the analysis.
      9. Prepare the mobile phase using 100 mmol·L-1 sodium acetate, 85 mmol·L-1 citric acid, 0.4 mmol·L^-1 di-n-butylamine, 1.5 mmol·L^-1 sodium octanesulfonate, 0.2 mmol·L^-1 ethylenediaminetetraacetic acid (EDTA), and 18% (v/v) methanol.
      10. Adjust the mobile phase pH to 4.5 using phosphoric acid. Filter the freshly prepared mobile phase through a 0.22 µm membrane before use.
      11. Degas the filtered mobile phase using ultrasonication before chromatographic analysis. Set the chromatographic flow rate to 0.9 mL·min^-1.
      12. Use an injection volume of 20 µL for each sample. Set the total chromatographic run time to 30 min per sample.
      13. Use an amperometric electrochemical detector (DECADE II, Antec Scientific, Zoeterwoude, Netherlands) equipped with a glassy carbon working electrode and an Ag/AgCl reference electrode.
      14. Set the detector potential to +0.65 V. Set the detector sensitivity to 1 µA full scale. Use 3,4-dihydroxybenzylamine (DHBA, 100 ng·mL^-1) as the internal standard. Spike each serum sample with a fixed concentration of DHBA before injection to correct for recovery and matrix effects.
      15. Include quality-control samples containing low, medium, and high concentrations of 5-HT, NE, and DA at the beginning, middle, and end of each assay run. Use the quality-control samples to ensure assay accuracy, precision, and inter-run comparability.
      16. Use limits of detection (LOD) of 0.5 nmol·L^-1 for 5-HT, 0.3 nmol·L^-1 for NE, and 0.3 nmol·L^-1 for DA. Use limits of quantification (LOQ) of 2.0 nmol·L^-1 for 5-HT, 1.0 nmol·L^-1 for NE, and 1.0 nmol·L^-1 for DA.
   5. Study Timeline and Blinding Procedure
      1. Conduct all scale assessments, including the Modified Barthel Index (MBI), Hamilton Depression Rating Scale (HAMD), and Zung Self-Rating Depression Scale (SDS), at four predetermined assessment time points.
      2. Complete the initial baseline assessment before the start of the intervention period.
      3. Conduct the first post-intervention assessment at 4 weeks after the start of the intervention.
      4. Conduct the second post-intervention assessment at 6 weeks after the start of the intervention and use this assessment as the endpoint evaluation for the intervention period.
      5. Conduct the long-term follow-up assessment at 6 months after the start of the intervention.
      6. Collect serum samples at three predetermined time points for neurochemical analysis.
      7. Obtain the first serum sample before the start of the intervention period as the baseline specimen.
      8. Collect the second serum sample 4 weeks after the start of the intervention.
      9. Collect the final serum sample 6 weeks after the start of the intervention and use this collection as the endpoint specimen assessment.
      10. Blind all assessors responsible for data extraction and outcome analysis to patient group allocation to minimize assessment bias. Remove all rehabilitation-group identifiers, including “MI-ADL” and “conventional rehabilitation,” from the electronic medical record dataset during data extraction.
      11. Replace all original group identifiers with coded labels, including “Group A” and “Group B,” before data analysis. Assign a separate researcher who is not involved in data extraction or statistical analysis to maintain the group-code linkage key.
      12. Provide the statistician only with the coded dataset for all statistical analyses, including repeated-measures analysis of variance (ANOVA).
      13. Perform all statistical analyses without disclosure of actual patient group identities to the statistician. Maintain the blinding procedure until completion of all statistical analyses.
6. Follow-up data collection
   1. Data sources
      1. Collect all follow-up data from the hospital’s electronic medical record system and post-discharge management files.
      2. Obtain follow-up information from assessment records completed during hospitalization, outpatient review appointments, and telephone follow-ups conducted after discharge.
   2. Follow-up time points and windows
      1. Collect follow-up data at four predetermined time points to assess the sustainability and safety of the interventions. Complete the baseline assessment (T0) within 1 week before the start of the intervention.
      2. Conduct the first short-term follow-up assessment (T1) at 4 weeks ± 3 days after the start of the intervention.
      3. Conduct the second short-term follow-up assessment and endpoint assessment (T2) at 6 weeks ± 3 days after the start of the intervention.
      4. Conduct the long-term follow-up assessment (T3) at 6 months ± 7 days after the start of the intervention.
   3. Follow-up indicators
      1. Record dynamic changes in functional independence, emotional state, and quality of life at each follow-up time point. Record adverse events and recurrence events throughout the follow-up period.
7. Sample size calculation
   1. Perform a post hoc power analysis using G*Power software to assess the statistical power of the observed sample size.
   2. Use an odds ratio (OR) of 3.5 for the association between depression and stroke outcomes based on a prior prospective epidemiological study²⁹.
   3. Apply a two-sided significance level (α) of 0.05 for the power analysis.
   4. Include the final matched sample consisting of 87 patients per group (total N = 174) in the analysis.
   5. Confirm that the post hoc power calculation provides > 95% power to detect an effect of this magnitude.
   6. Verify that the sample size is adequate for the primary outcome analyses.
8. Statistical methods
   1. Conduct all statistical analyses using SPSS software. Set the two-tailed significance level at α = 0.05. Consider differences statistically significant when p < 0.05.
   2. Test the normality of continuous variables, including MBI, HAMD, SDS scores, and neurotransmitter levels, using the Shapiro-Wilk test.
   3. Report normally distributed measurement data as mean ± standard deviation. Report count data as number (percentage).
   4. Use two-sample t-tests for between-group comparisons of normally distributed continuous variables, including age, baseline MBI score, and time from stroke onset to admission.
   5. Use the chi-square test or Fisher’s exact test, as appropriate, for categorical variables, including proportion of PSD onset, hypertension, diabetes, stroke type, lesion side, antidepressant use, and adverse reactions.
   6. Apply repeated-measures analysis of variance (ANOVA) to evaluate the time effect, group effect, and time × group interaction effect for the main outcome (MBI), serum neurotransmitters, HAMD, and SDS scores measured repeatedly at T0, T1, T2, and T3.
   7. Perform simple effect analysis when a significant group × time interaction effect is detected.
   8. Adjust P-values using the Bonferroni correction during simple effect analysis.
   9. Perform between-group comparisons at each time point using two-sample t-tests when normality and homogeneity of variance assumptions are met including T0–T3 for clinical scales and T0–T2 for serum neurotransmitters.
      NOTE: Perform between-group comparisons at T0–T3 for clinical scales and at T0–T2 for serum neurotransmitters.
   10. Categorize clinical efficacy according to the HAMD-17 score reduction rate from baseline to week 6.
   11. Define a significant effect as a HAMD-17 score reduction ≥ 50%.
   12. Define an effective outcome as a HAMD-17 score reduction of 25%–49%.
   13. Define an invalid outcome as a HAMD-17 score reduction < 25%.
   14. Use the chi-square test to compare the distribution of efficacy categories between groups.
   15. Report effect sizes for repeated-measures ANOVA as partial η².
   16. Interpret partial η² values ≥ 0.01 as small effects, ≥ 0.06 as medium effects, and ≥ 0.14 as large effects. 

Figure 1: Flowchart of patient selection, grouping, and assessment time points.Flowchart showing patient screening, exclusion, enrollment, group allocation, intervention period, and follow-up assessments. A total of 286 patients with post-stroke depression were screened, and 174 eligible patients were assigned to either the MI-guided activities of daily living (MI-ADL) rehabilitation group or the conventional rehabilitation group. Outcome assessments were performed at baseline (T0), 4 weeks (T1), 6 weeks (T2), and 6 months (T3). Please click here to view a larger version of this figure.

Wyniki

Participant Flow and Baseline Comparability
A total of 286 medical records of patients with PSD were screened. After applying the inclusion and exclusion criteria, 112 records were excluded (78 did not meet inclusion criteria, 24 declined participations according to clinical records, and 10 had incomplete data). The remaining 174 patients were enrolled and underwent 1:1 propensity score matching, resulting in 87 patients in the MI‑ADL group and 87 patients in the conventional rehabilitation group. All patients completed the 4‑week intervention period and the 6‑month follow‑up, with no dropouts and no missing data. The participant flowchart is shown in Figure 1. Baseline characteristics were well balanced between groups after matching (see Table 1), with no significant differences in age, sex, stroke type, baseline HAMD‑17, baseline MBI, or antidepressant use.

As shown in Table 1, in terms of demographics and basic health conditions, Age, gender, BMI, and educational level showed no differences between the two groups (p > 0.05), ruling out the possibility of bias in the rehabilitation effect due to differences in nutritional status or cognitive comprehension ability. There were no differences in stroke type, duration, lesion side, and the two groups' statistics of the National Institutes of Health Stroke Scale (p > 0.05), and the absence of differences in NIHSS scores proved that the severity of neurological deficits at the time of enrollment was comparable between the two groups. The distribution of lesion sides was balanced, ruling out differential effects on emotions and functional recovery due to factors such as the damaged dominant hemisphere. The proportion of PSD onset, hypertension, diabetes complications, and the proportion of patients taking antidepressants were crucial baseline data. This suggests that the baseline conditions of the two groups were comparable and supports the interpretation that subsequent outcome differences were associated with differences in the rehabilitation approaches.

Baseline		MI-ADL group (n = 87)	Conventional Rehabilitation Group (n = 87)	Test	95%CI		Effect size	t	P-value
					Lower	Upper
Age		62.51 ± 8.69	63.13 ± 9.19	T test	-3.298	2.056	0.01	-0.458	0.648
Gender (n, %)	Male	48 (55.17)	45 (51.72)	Chi-squared			0.208		0.648
	Female	39 (44.83)	42 (48.28)
Body Mass Index (kg/m², x̄ ± s)		23.82 ± 3.14	24.11 ± 2.94		-1.19	0.628	0.462	-0.61	0.543
NIHSS (score,  x̄ ± s)		8.52 ± 2.30	8.71 ± 2.14		-0.855	0.475	0.82	-0.564	0.574
The time from the onset of stroke to enrollment (days,  x̄ ± s)		35.21 ± 10.52	33.80 ± 11.10		-1.834	4.638	0.434	0.855	0.394
The affected side	Left side	38 (43.68)	36 (41.38)	Chi-squared			0.101		0.951
	Right side	42 (48.28)	44 (50.57)
	Bilateral	7 (8.05)	7 (8.05)
Educational level (n, %)	High school level or above	41 (47.13)	38 (43.68)	Chi-squared			0.209		0.648
	High school and below	46 (52.87)	49 (56.32)
Type of stroke (n, %)	Cerebral infarction	65 (74.71)	68 (78.16)	Chi-squared			0.287		0.592
	Cerebral hemorrhage	22 (25.29)	19 (21.84)
First patient diagnosed with PSD (n, %)	No	8 (9.20)	6 (6.90)	Chi-squared			0.311		0.577
	Yes	79 (90.80)	81 (93.10)
Combined with hypertension (n, %)	No	22 (25.29)	25 (28.74)	Chi-squared			0.262		0.609
	Yes	65 (74.71)	62 (71.26)
Diabetes mellitus management (n , %)	No	59 (67.82)	56 (64.37)	Chi-squared			0.231		0.631
	Yes	28 (32.18)	31 (35.63)
Taking antidepressant medication (n , %)	No	42 (48.28)	39 (44.83)	Chi-squared			0.208		0.648
	Yes	45 (51.72)	48 (55.17)

Table 1: Baseline characteristics of the two groups.
Baseline demographic and clinical characteristics of patients in the MI-guided activities of daily living (MI-ADL) rehabilitation group and the conventional rehabilitation group before intervention. Variables include age, sex, stroke type, disease duration, baseline functional status, and baseline depression scores. Data are presented as mean ± standard deviation (SD) or number (%). No statistically significant differences were observed between groups at baseline (p > 0.05).

At baseline, there was no significant difference in MBI scores between the MI-ADL and conventional rehabilitation groups (45.21 ± 10.11 vs 44.82 ± 9.81, p > 0.05), indicating comparable functional independence levels between the two groups. Both groups showed improvement over time, with greater improvement observed in the MI-ADL group. At the 4th week, the MI-ADL group (65.31 ± 9.52) had a significantly higher score than the conventional rehabilitation group (58.14 ± 10.25; p < 0.05).

The repeated-measures analysis of variance revealed a significant time × group interaction (F = 6.304, p < 0.001), indicating different improvement trajectories between the two groups. As shown in Table 2, the within-group η² values over time were 0.772 for the MI-ADL group and 0.666 for the conventional rehabilitation group. According to conventional benchmarks (η² ≥ 0.14 indicates a large effect), both represent large effect sizes for the improvement in functional independence within each group.

The 6-month follow-up showed that the MI-ADL group maintained a score of 75.83 ± 7.21, approaching the level of mild functional impairment, and remained significantly higher than that of the conventional rehabilitation group (68.41 ± 8.51, p < 0.05), suggesting sustained benefit associated with the intervention. Post-hoc tests confirmed that the improvement in the MI-ADL group at each time point was significantly greater than that in the conventional rehabilitation group. See Table 2.

Parameters		T0	T1	T2	T3	η2	Effect size	P-value
MBI	MI-ADL group (n = 87)	45.21 ±10.11	65.31 ± 9.52#	72.51 ± 5.63#	75.83 ± 7.21#	0.772	191.674	<.001
	Conventional Rehabilitation Group (n = 87)	44.82 ± 9.81	58.14 ± 10.25*#	65.32 ± 9.27*#	68.41 ± 8.51*#	0.666	112.842	<.001
	F	0.066	22.858	38.231	38.537
	P	0.797	<.001	<.001	<.001
Ftime = 312.164，Ptime = <.001,Fgroup = 72.823, Pgroup = <.001, Ftime*group = 6.304, Ptime*group = <.001.

Table 2: Modified Barthel Index (MBI) scores at each time point (± s).
Comparison of Modified Barthel Index (MBI) scores between the MI-guided activities of daily living (MI-ADL) rehabilitation group and the conventional rehabilitation group at baseline (T0), 4 weeks (T1), 6 weeks (T2), and 6 months (T3), * P < 0.05 vs conventional rehabilitation group at the same time point. T0: baseline; T1: 4 weeks; T2: 6 weeks; T3: 6 months. Data are presented as mean ± standard deviation (SD). Higher MBI scores indicate better activities of daily living performance.

Before the baseline period, the HAMD score of the MI-ADL group was 24.61 ± 4.23, while that of the conventional rehabilitation group was 25.10 ± 4.03. There was no statistical difference between the two groups (p > 0.05), indicating that the severity of depression before the intervention was comparable. At the 6th week after intervention, the MI-ADL group's score dropped to 12.40 ± 3.53 points, while the conventional rehabilitation group's score was 16.82 ± 4.13 points. The difference between the two groups was statistically significant (p < 0.01). At the follow-up assessment 6 months after intervention, the MI-ADL group's score remained at 10.85 ± 2.97 points, approaching the normal range, while the conventional rehabilitation group's score was 15.14 ± 3.69 points. There was still a significant difference between the two groups (p < 0.05). Repeated-measures analysis of variance showed a significant interaction between time and group (F = 26.034, p < 0.001, partial η² = 0.132), indicating that the trajectories of depressive symptom improvement differed between the two groups. According to conventional guidelines (partial η² ≥ 0.14 indicates a large effect), this represents a moderate-to-large effect size. Post-hoc tests showed that the HAMD score of the MI-ADL group was significantly lower than that of the conventional rehabilitation group at each follow-up time point (all P < 0.05), as shown in Table 3.

Parameters		T0	T1	T2	T3	η2	Effect size	P-value
HAMD	MI-ADL group (n = 87)	24.61 ± 4.23	16.52 ± 3.82#	12.40 ± 3.53#	10.85 ± 2.97#	0.791	213.932		<.001
	Conventional Rehabilitation Group (n = 87)	25.10 ± 4.03	19.21 ± 4.14*#	16.82 ± 4.13*#	15.14 ± 3.69*#	0.653	106.872		<.001
	F	0.629	19.793	57.503	71.318
	P	0.429	<.001	<.001	<.001
Ftime = 913.669，Ptime = <.001,Fgroup = 111.773, Pgroup = <.001, Ftime*group = 26.034, Ptime*group = <.001.

Table 3: Hamilton Depression Rating Scale (HAMD) scores at each time point (± s)
Comparison of Hamilton Depression Rating Scale (HAMD) scores between the MI-guided activities of daily living (MI-ADL) rehabilitation group and the conventional rehabilitation group at baseline (T0), 4 weeks (T1), 6 weeks (T2), and 6 months (T3). Data are presented as mean ± standard deviation (SD). Lower HAMD scores indicate reduced depressive symptom severity.* P < 0.05 vs. conventional rehabilitation group at the same time point. T0: baseline; T1: 4 weeks; T2: 6 weeks; T3: 6 months.

Before the intervention, the SDS score in the MI-ADL group was 58.71 ± 7.52, while that in the conventional rehabilitation group was 59.01 ± 7.12. There was no statistical difference between the two groups (P > 0.05), indicating that the self-assessment of the depression level of patients before the intervention was comparable. At the 6th week after intervention, the MI-ADL group's score further decreased to 45.60 ± 6.23 points, while the conventional rehabilitation group's score remained 52.30 ± 7.04 points. The difference between the two groups was statistically significant (P < 0.01). At the follow-up assessment 6 months after the end of the intervention, the MI-ADL group's score remained 43.09 ± 5.51 points, while the conventional rehabilitation group's score was 50.72 ± 6.28 points. There was still a significant difference between the two groups (P < 0.05). Repeated-measures analysis of variance showed a significant interaction between time and group (F = 10.142, P < 0.001), indicating that the improvement trend in self-assessed depressive symptoms differed between the two groups. The post-hoc test results confirmed that the SDS score of the MI-ADL group was significantly lower than that of the conventional rehabilitation group at each follow-up time point (all P < 0.05), suggesting that the MI-ADL group was associated with greater improvements in patients' subjective depressive feelings, an association that persisted to the 6‑month follow-up, as shown in Table 4. As presented in Table 4, the within-group η² values for the change in SDS scores over time were 0.628 for the MI-ADL group and 0.332 for the conventional rehabilitation group. According to conventional benchmarks (η² ≥ 0.14 indicates a large effect), both represent large effect sizes for the improvement in self‑rated depressive symptoms within each group.

Parameters		T0	T1	T2	T3	η2	Effect size	P-value
SDS	MI-ADL group (n = 87)	58.71 ± 7.52	49.83 ± 6.83#	45.60 ± 6.23#	43.09 ± 5.51#	0.628	95.849	<.001
	Conventional Rehabilitation Group (n = 87)	59.01 ± 7.12	54.19 ± 6.98*#	52.30 ± 7.04*#	50.72± 6.28*#	0.332	28.137	<.001
	F	0.283	17.349	44.153	72.467
	P	0.595	<.001	<.001	<.001
Ftime = 115.705，Ptime = <.001, Fgroup = 74.900, Pgroup = <.001, Ftime*group = 10.142, Ptime*group = <.001.

Table 4: Self-Rating Depression Scale (SDS) scores at each time point (± s).
Comparison of Self-Rating Depression Scale (SDS) scores between the MI-guided activities of daily living (MI-ADL) rehabilitation group and the conventional rehabilitation group at baseline (T0), 4 weeks (T1), 6 weeks (T2), and 6 months (T3). Data are presented as mean ± standard deviation (SD). Lower SDS scores indicate reduced self-reported depressive symptoms.* P < 0.05 vs. conventional rehabilitation group at the same time-point. T0: baseline; T1: 4 weeks; T2: 6 weeks; T3: 6 months.

Table 5 shows that the levels of the three neurotransmitters (5-HT, NE, DA) in the MI-ADL group increased gradually over time. At the 4th week after intervention, levels of various neurotransmitters in the MI-ADL group had significantly increased compared to before intervention and were significantly higher than those of the conventional rehabilitation group during the same period (P < 0.001). By the 6th week, this enhancing effect further expanded, and the gap between the MI-ADL group and the conventional rehabilitation group became more obvious (P < 0.001).

Parameters		T0	T1	T2	η2	Effect size	P-value
5-HT	MI-ADL group (n = 87)	125.63 ± 25.31	158.91 ± 28.43#	185.42 ± 30.72#	0.543	101.645	<.001
	Conventional Rehabilitation Group (n = 87)	128.13 ± 24.81	142.08 ± 26.50*#	155.23 ± 28.51*#	0.194	20.627	<.001
	F	0.431	16.318	45.148
	P	0.513	<.001	<.001
Ftime = 106.370, Ptime = <.001, Fgroup = 40.270, Pgroup = <.001, Ftime*group = 15.182, Ptime*group = <.001.
NE	MI-ADL group (n = 87)	285.35 ± 45.22	328.72 ± 48.53#	365.75 ± 50.12#	0.395	55.772	<.001
	Conventional Rehabilitation Group (n = 87)	288.72 ± 46.13	305.26 ± 47.03*#	315.63 ± 48.32*#	0.069	6.349	0.002
	F	0.236	10.484	45.096
	P	0.628	0.001	<.001
Ftime = 52.227, Ptime = <.001, Fgroup = 24.782, Pgroup = <.001, Ftime*group = 12.917, Ptime*group = <.001.
DA	MI-ADL group (n = 87)	35.24 ± 8.06	42.31 ± 8.91#	48.93 ± 9.51#	0.376	51.605	<.001
	Conventional Rehabilitation Group (n = 87)	34.82 ± 7.94	37.63 ± 8.31*#	39.51 ± 8.71*#	0.068	6.234	0.002
	F	0.119	12.812	46.346
	P	0.73	<.001	<.001
Ftime = 45.733, Ptime = <.001, Fgroup = 50.373, Pgroup = <.001, Ftime*group = 10.940, Ptime*group = <.001.

Table 5: Neurotransmitter levels (5‑HT, NE, DA) at each time point (± s). 
Comparison of serum neurotransmitter levels between the MI-guided activities of daily living (MI-ADL) rehabilitation group and the conventional rehabilitation group at baseline (T0), 4 weeks (T1), 6 weeks (T2), and 6 months (T3). Measured neurotransmitters included 5-hydroxytryptamine (5-HT), norepinephrine (NE), and dopamine (DA). Data are presented as mean ± standard deviation (SD).* P < 0.05 vs. conventional rehabilitation group at the same time-point. T0: baseline; T1: 4 weeks; T2: 6 weeks; T3: 6 months.

The MI-ADL group demonstrated a significantly higher overall clinical efficacy rate than the conventional rehabilitation group (p < 0.05; Table 6).

Parameters	Significant effect	Effective	Invalid	Overall efficiency	χ²	df	P-value
MI-ADL group (n=87)	42 (48.28)	38 (43.68)	7 (8.05)	80 (91.95)	8.39	2	0.015
Conventional Rehabilitation Group (n=87)	28 (32.18)	40 (45.98)	19 (21.84)	68 (78.16)

Table 6: Comparison of clinical efficacy between the two groups 6 weeks after intervention [n (%)].
Comparison of clinical efficacy outcomes between the MI-guided activities of daily living (MI-ADL) rehabilitation group and the conventional rehabilitation group 6 weeks after intervention. Clinical efficacy was evaluated according to the reduction rate of the Hamilton Depression Rating Scale (HAMD-17) score from baseline. Data are presented as number (%). Significant effect: ≥ 50% reduction; Effective: 25%–49% reduction; Invalid: < 25% reduction. Overall efficiency = Significant effect + Effective. χ² test with 2 degrees of freedom.

Table 7 shows that there was no statistically significant difference in the incidence of adverse events and treatment compliance between the two groups, and the overall incidence of adverse events was relatively low. The MI-ADL group showed a higher trend of compliance, but this did not reach statistical significance (p > 0.05).

Parameters	MI-ADL group (n=87)	Conventional Rehabilitation Group (n=87)	χ² / Fisher	P-value
A fall incident occurred	1 (1.15)	2 (2.30)	0.557 (Fisher)	0.757
Fatigue / Discomfort	2 (2.30)	3 (3.45)
Overall incidence of adverse events	3 (3.45)	5 (5.75)
Good treatment compliance			0.748 (χ²)	0.387
- No	5 (5.75)	8 (9.20)
- Yes	82 (94.25)	79 (90.80)

Table 7: Comparison of adverse events and compliance during the treatment of the two groups of patients [n (%)].
Comparison of adverse events and treatment compliance between the MI-guided activities of daily living (MI-ADL) rehabilitation group and the conventional rehabilitation group during the intervention period. Data are presented as number (%).

To further adjust for potential confounding factors, multivariate regression analyses were performed for outcomes at 6 weeks (T2). After controlling for age, sex, baseline outcome score, antidepressant use, and number of rehabilitation sessions, the MI-ADL group remained associated with significantly better outcomes compared with the conventional rehabilitation group (Table 8). The adjusted mean differences were 6.83 (95% CI: 4.21–9.45) for MBI, −4.52 (95% CI: −6.10 to −2.94) for HAMD-17, and −6.91 (95% CI: −8.83 to −4.99) for SDS (all P < 0.001). The adjusted odds ratio for overall clinical efficacy was 3.24 (95% CI: 1.52–6.91, P = 0.002).

Outcome	Adjusted measure	MI-ADL vs. Conventional Rehabilitation
		β / OR	95% CI	SE	P-value
MBI (linear regression)	Adjusted mean difference	6.83	(4.21, 9.45)	1.34	<0.001
HAMD-17 (linear regression)	Adjusted mean difference	-4.52	(-6.10, -2.94)	0.81	<0.001
SDS (linear regression)	Adjusted mean difference	-6.91	(-8.83, -4.99)	0.98	<0.001
Overall clinical efficacy (logistic regression)	Adjusted odds ratio	3.24	(1.52, 6.91)	—	0.002

Table 8: Multivariate regression analysis for outcomes at 6 weeks (T2) after intervention.
Multivariate regression analysis evaluating the association between intervention group and clinical outcomes at 6 weeks after intervention (T2). Outcomes included Modified Barthel Index (MBI), Hamilton Depression Rating Scale (HAMD-17), Self-Rating Depression Scale (SDS), and overall clinical efficacy. Models were adjusted for age, sex, baseline outcome score, antidepressant use, and number of rehabilitation sessions attended. p values were obtained using Wald tests or t tests as appropriate.

Dyskusja

In this retrospective cohort study, MI-guided bedside ADL training was associated with significantly greater improvements in functional independence (MBI), depressive symptoms (HAMD-17 and SDS), and serum levels of monoamine neurotransmitters (5‑HT, NE, DA) compared with conventional rehabilitation. These improvements were sustained at the 6‑month follow‑up. Consistent with previous reports describing the clinical burden of PSD and its negative impact on rehabilitation outcomes^30,31. Our findings suggest that adding MI to bedside ADL training was associated with improved functional independence and emotional outcomes. This condition not only manifests as core symptoms such as persistent low mood and reduced interest, but is often accompanied by a series of complex clinical manifestations such as cognitive decline and sleep disorders, forming a vicious cycle that hinders the recovery of neurological functions^32,33. Consistent with the limitations of conventional approaches, our findings suggest that adding MI to ADL training was associated with better functional and emotional outcomes. While antidepressants are widely used, their variable efficacy and side effects limit clinical utility^34,35,36. Meanwhile, although regular rehabilitation training can effectively improve patients' motor function and daily living skills, it often neglects the psychological aspects of patients, especially the enhancement of their intrinsic motivation. As a result, many patients lack the intrinsic drive to continue participating in rehabilitation, which affects the final rehabilitation outcome^11,37. This clinical predicament has prompted us to explore more comprehensive treatment strategies, integrating psychological therapy with functional training in an organic manner, so as to more comprehensively address the challenges brought about by PSD.

In this context, MI, as a psychological counseling method with a solid theoretical foundation and abundant empirical support, provides a new perspective for improving the rehabilitation participation of PSD patients. Combining MI with bedside ADL training may improve both rehabilitation participation and emotional engagement^38–40.

Although this integrated treatment is theoretically sound, there is a lack of systematic research evidence to support its actual effectiveness in the PSD population, especially in terms of its impact on neurobiological indicators^41-43. However, because this was a retrospective cohort study, causality cannot be established.

This study, using a rigorous retrospective cohort design, systematically evaluated the comprehensive effects of MI-guided bedside ADL training on functional independence, emotional state, and serum neurotransmitter levels in PSD patients. Critical steps for successful implementation of the protocol include standardized MI delivery, individualized bedside ADL goal setting, consistent timing of assessments, and accurate monitoring of follow-up outcomes. The results showed that before the intervention, there were no significant differences in MBI, HAMD, and SDS scores between the MI-ADL and conventional rehabilitation groups, ensuring comparability between the groups. As the intervention progressed, both groups improved over time, but the MI-ADL group demonstrated greater and more sustained improvements in functional independence and depressive symptoms, consistent with previous rehabilitation studies⁴⁴. This finding is consistent with the research of Ying-Tzu Tseng et al., who showed that integrated psychological support rehabilitation treatment can significantly increase stroke patients' daily living activity ability scores over time⁴⁴.

In terms of improvement in emotional status, the HAMD score of the MI-ADL group decreased significantly from 24.61 points at the baseline to 12.40 points at the 6th week after intervention, and further dropped to 10.85 points during the follow-up period, approaching the normal level; while the conventional rehabilitation group only decreased from 25.12 points to 16.82 points, and was 15.14 points at the follow-up. This result is in strong agreement with the findings of the study by Yingjie Fu et al. The article points out that applying MI in stroke rehabilitation can increase the rate of improvement of depressive symptoms⁴⁵. The consistency between self‑rated (SDS) and observer‑rated (HAMD) improvements supports the robustness of the findings. This consistency between self-assessment and clinician assessment supports the reliability of the observed emotional improvements and suggests that MI-guided rehabilitation was associated with enhanced subjective emotional well-being.

This study explored the association between MI-ADL training and dynamic changes in serum neurotransmitter levels. The results showed that the serum levels of 5-HT, NE, and DA in the MI-ADL group of patients all showed a significant upward trend after intervention, and the increase was significantly greater than that of the conventional rehabilitation group. This finding links MI-ADL training to neurotransmitter changes. According to the research by Qingyang Zhan et al., the recovery of neurological function after stroke is closely related to monoamine neurotransmitter activity⁴⁶. Our findings further suggest that psychological behavioral therapy may be associated with changes in neuroendocrine function and monoamine neurotransmitter levels. This mechanism links behavioral therapy with neurochemical changes, providing new evidence for the application of psychoneuroimmunology theory in stroke rehabilitation.

Integrating motivational interviewing with bedside ADL training offers a novel biopsychosocial rehabilitation strategy for PSD. While previous research has demonstrated the effectiveness of MI in chronic disease management (e.g., improving self‑management in diabetes⁴⁷ and enhancing treatment adherence in substance dependence^48,49), the application of MI to post‑stroke depression rehabilitation, particularly when combined with task‑specific functional training, has remained unexplored. The present study addresses this gap by proposing a structured MI‑ADL protocol that can be delivered at the bedside during inpatient rehabilitation. Our findings suggest that this integrated approach is associated with improvements in both functional independence and depressive symptoms, and they provide preliminary correlational evidence linking these improvements to changes in serum monoamine neurotransmitter levels. By explicitly combining psychological motivation with ADL practice and by monitoring neurochemical correlates, this study advances the field in three ways: (1) it offers a practical, protocol‑driven method for implementing MI within existing rehabilitation workflows; (2) it generates the hypothesis that MI‑ADL may exert its effects at least partly through monoaminergic pathways; and (3) it provides a foundation for future prospective trials to test efficacy and mechanism definitively. Particularly noteworthy is that the observed changes in neurotransmitter levels in this study were temporally correlated with improvements in clinical symptoms, offering preliminary correlational evidence consistent with the hypothesized pathway of psychological treatment → neurobiochemical changes → clinical symptom improvement. However, because this was a retrospective cohort study, causality cannot be inferred from these temporal associations; further studies using mediation analysis or prospective designs are needed to test the proposed pathway.

The MI-ADL model integrates psychological motivation into bedside functional training without disrupting routine care. The protocol may be adapted according to patient communication ability, cognitive status, and fatigue level while maintaining standardized assessment procedures. It is feasible, sustainable (6‑month benefit), and may offer cost‑effectiveness advantages for PSD rehabilitation.

Longitudinal analysis showed that dynamic changes in serotonin, NE, and DA levels were associated with clinical outcomes.

Alternative psychological interventions for PSD include cognitive‑behavioral therapy, problem‑solving therapy, and mindfulness‑based interventions, each with established but modest evidence in stroke populations. Pharmacologically, selective serotonin reuptake inhibitors remain first‑line but are limited by side effects and variable efficacy. Compared with these alternatives, the MI‑ADL protocol has the advantage of seamlessly integrating psychological motivation into routine ADL training without requiring additional specialized personnel. However, the observational design of this study cannot directly compare MI‑ADL with these alternatives. A prospective randomized controlled trial (RCT) with an active comparator (e.g., cognitive‑behavioral therapy combined with ADL training) would provide stronger evidence. Additionally, a factorial design could disentangle the independent effects of MI and ADL training, and a crossover design might assess individual response patterns. These alternative designs should be pursued in future research. Future studies should also evaluate therapist fidelity monitoring, intervention standardization, and implementation feasibility across different rehabilitation settings.

This study has several limitations. First, the retrospective cohort design, despite propensity score matching, cannot eliminate selection bias or establish causality. Second, serum neurotransmitter levels are peripheral surrogates and may not reflect central synaptic concentrations. Third, the single‑center sample limits generalizability to other populations and healthcare systems. Fourth, the age restriction (40–75 years) excludes younger and older stroke patients. Fifth, the sample size justification was based on a post hoc power analysis using an effect size derived from prior literature (OR = 3.5). A prospective priori power calculation would have provided stronger assurance that the study was adequately powered for its primary hypothesis. The post hoc nature limits the interpretation of statistical power relative to the study's primary question. Sixth, no structured fidelity monitoring instrument (e.g., the Motivational Interviewing Treatment Integrity code, MITI) was used to assess adherence to the MI protocol across therapists and sessions. Although all therapists had passed a standardized competency assessment before the study, we cannot verify the uniformity and quality of MI delivery throughout the intervention period. Seventh, we did not assess long‑term (> 6 months) durability or cost‑effectiveness. These limitations should be considered when interpreting the findings.

In conclusion, MI-guided bedside ADL training was associated with improved functional independence and emotional outcomes in patients with PSD and may represent a practical integrated rehabilitation strategy. Future prospective studies are needed to confirm efficacy, clarify mechanisms, optimize intervention parameters, and evaluate broader clinical applicability..

Materiały

Lista materiałów użytych w tym artykule

Nazwa	Firma	Numer katalogowy	Komentarze
1.5 mL microcentrifuge tube (labeled, sterile)	Eppendorf (Hamburg, Germany) / Sigma-Aldrich	EP022600028 (North America)	Generic descriptor “1.5 mL microcentrifuge tube” used in text; Eppendorf tube
3,4-Dihydroxybenzylamine (DHBA) internal standard	Sigma-Aldrich (St. Louis, MO, USA)	377679	Internal standard for HPLC-ECD
5-Hydroxytryptamine (5-HT) standard	Sigma-Aldrich (St. Louis, MO, USA)	H9523	Reference standard for HPLC-ECD
Dopamine (DA) standard	Sigma-Aldrich (St. Louis, MO, USA)	H8502	Reference standard for HPLC-ECD
Electrochemical Detection (HPLC-ECD) system	Agilent Technologies, Santa Clara, CA, USA	Agilent 1260 Infinity II
G*Power software (version 3.1.9.7)	Heinrich-Heine-Universität Düsseldorf, Germany	Software (no catalog number)	RRID:SCR_013726 (for G*Power v3.1)
Mobile phase components (sodium acetate, citric acid, di-n-butylamine, sodium octanesulfonate, EDTA, methanol, phosphoric acid)	Sigma-Aldrich / Merck / Sinopharm (various)	No single catalog number (standard laboratory reagents)	Reagents for HPLC-ECD mobile phase
Norepinephrine (NE) standard	Sigma-Aldrich (St. Louis, MO, USA)	A9512	Reference standard for HPLC-ECD
Serum-separating vacuum blood collection tube (5 mL)	BD (Becton, Dickinson and Company, Franklin Lakes, NJ, USA)	367986 (5 mL, PET plastic, gold Hemogard closure, SST™ gel separator)	Alternative cat. nos. 367983 (3.5 mL) or 367955 also suitable
SPSS software (version 25.0)	IBM Corp. (Armonk, NY, USA)	Software (no catalog number)	RRID:SCR_002865
ZORBAX SB-C18 reversed-phase column	Agilent Technologies		chromatographic separation column